Sustainable rural development: What is the role of the agri-food sector?

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Sustainable rural development:
What is the role of the agri-food sector?
Studies on the Agricultural and Food Sector
in Central and Eastern Europe
Edited by
Leibniz Institute of Agricultural Development
in Central and Eastern Europe
IAMO
Volume 39
Sustainable rural development:
What is the role of the agri-food sector?
Edited by
Martin Petrick and Gertrud Buchenrieder
IAMO
2007
Bibliografische Information Der Deutschen Bibliothek
Die Deutsche Bibliothek verzeichnet diese Publikation in der Deutschen
Nationalbibliografie; detaillierte bibliografische Daten sind im Internet über
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Die Deutsche Bibliothek lists the publication in the Deutsche Nationalbibliografie;
detailed bibliographic data are available in the internet at: http://dnb.ddb.de.
Diese Veröffentlichung kann kostenfrei im Internet unter
<www.iamo.de/dok/sr_vol39.pdf> heruntergeladen werden.
This publication can be downloaded free from the website
<www.iamo.de/dok/sr_vol39.pdf>.
¤ 2007
Leibniz-Institut für Agrarentwicklung in Mittel- und Osteuropa (IAMO)
Theodor-Lieser-Straße 2
06120 Halle (Saale)
Tel. 49 (345) 2928-0
Fax 49 (345) 2928-199
e-mail: [email protected]
http://www.iamo.de
ISSN 1436-221X
ISBN 3-938584-22-X
ACKNOWLEDGEMENTS
This volume of proceedings, available both as hard copy and pdf, is an edited
compilation of selected contributions to the IAMO Forum 2007, which will be
held in Halle (Saale), Germany, at the Leibniz Institute of Agricultural Development in Central and Eastern Europe from 27 to 29 June 2007.
We would like to thank all those persons and organisations who contributed to
the realisation of the IAMO Forum 2007 and the volume in hand. First of all, we
thank all lecturers, whose commitment and papers made both the conference and
the publication possible. Furthermore, we appreciate the financial support provided by the Federal Ministry of, Food, Agriculture, and Consumer Protection
and the Federal State of Saxony-Anhalt.
The conference would not be successful without the active engagement of such a
large number of colleagues from IAMO, that we cannot mention them here. We
wish to express our deepest gratitude to all of them.
For improving the book languagewise and supporting us in its technical production our thanks go to JAMES CURTISS and SILKE SCHARF.
Halle (Saale), June 2007
Martin Petrick and Gertrud Buchenrieder
Sustainable rural development: What is the role of the agri-food sector?
iii
CONTENTS
Acknowledgements .................................................................................................... i
Conceptual issues
Rural-urban interlinkages and regional development ............................................... 3
Flemming Just
Sustainability assessment of rural development: A review of methodologies .......... 18
Adinyira Emmanuel, Oteng-Seifah Samuel, Adjei-Kumi Theophilus
Post-soviet transition, rural development and the peasant problem:
The cultural and institutional economic dimension................................................. 28
Ernst-August Nuppenau
Rural land and labour markets
Economic impacts of land market development: Evidence from Moldova .............. 49
Dragoş Cimpoieş
Regional specificity of rural labour allocation and migration in Ukraine............... 67
Oleksandr V. Zhemoyda
Infrastructure as a determinant of rural non-farm employment:
The case of Ukraine ................................................................................................. 80
Mariya Portyanko
Rural financial markets
Informal loans – Alternatives or supplements to bank credit for Polish farms......... 97
Alina Danilowska
Development of innovative technologies in rural finance..................................... 113
Anna Bondarenko, Roman Kosodiy, Eugeniy Mishenin
Efficiency of index-based crop insurance in Russian agriculture ......................... 128
Raushan Bokusheva, Marina Sannikova, Olaf Heidelbach
Rural credit partnerships and their role in the development of agriculture
in Kazakhstan......................................................................................................... 148
Sholpan Gaisina
Taking the hands off the rural credit market: An evidence from China.................. 164
Xiangping Jia, Franz Heidhues, Manfred Zeller
Martin Petrick, Gertrud Buchenrieder
iv
Food industry
Rural development policy and food industry development:
Investigations of small firms in Denmark ............................................................. 183
Derek Baker, Jens Abildtrup, Anders Hedetoft
Dairy food chain restructuring in Poland – Causes and impacts........................... 200
Dominika Milczarek, Agata Malak-Rawlikowska, Jan Fałkowski
Policy design and effects
Strategies to face the socio-economic crisis in a rural territory:
The case of the Baronnies Provençales (Drôme, Southeast France)..................... 219
Ana Poletto, Richard Raymond, Emilien Barussaud
Empirical assessment of Fuzzy Intervention-Logics: The case of rural
development in East Germany............................................................................... 231
Anne Margarian
Comprehensive rural development in China: Strategy and implementation
challenges .............................................................................................................. 248
Achim Fock, Karin Fock
Who is benefiting from rural development policies? ............................................ 258
Andrea Pufahl, Regina Grajewski, Barbara Fährmann
Anticipated impacts of GMO introduction on farm profitability in Poland ............ 274
Mariusz Maciejczak, Adam Was
List of authors ........................................................................................................ 287
CONCEPTUAL ISSUES
Sustainable rural development: What is the role of the agri-food sector?
MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central and Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 3-17.
RURAL-URBAN INTERLINKAGES AND REGIONAL DEVELOPMENT
FLEMMING JUST∗
ABSTRACT
The paper discusses the need for broadening the approach in rural research from
a narrow endogenous and sectoral point of view to a broader regional approach
with an eye on exogenous factors and place-based or territorial strategies. With
Denmark as empirical case it is shown that the globalisation process and the
knowledge economy have created stronger regional disparities within the last
decade, and that this tendency seems to continue. An answer to refute the problems is a stronger emphasis on regional strengths and cross-sectoral collaboration.
Keywords: Endogenous, neo-endogenous, Denmark, rural and regional development.
1
INTRODUCTION
In the days of planning euphoria in the 1950s and ‘60s, there was a strong belief in
macro economics and its possibilities for developing peripheral areas and underdeveloped countries. W. W. ROSTOW and other development researchers were in
clover with their focus on investment rates and other exogenously given factors’
influence as developmental factors (ROSTOW, 1960).
Alongside macro economic stimuli, Western countries pursued a sectoral policy,
both economically and politically, giving strong segmented interests in agriculture, industry, shipbuilding and other industries’ easy access to legislation and
huge subsidies. Most extremely, the sectoral approach has dominated agriculture
and not least the Common Agricultural Policy in EEC/EU.
Since the middle of the 1980s this dominating top-down policy has been supplemented with a new approach putting focus on local resources. One the most prominent rural sociologists propagating an endogenous developmental strategy with
emphasis on internal resources, has been Professor JAN DOUWE VAN DER PLOEG
from Wageningen University in the Netherlands. He has defined it in this way:
∗
Danish Institute of Rural Research and Development (IFUL), University of Southern
Denmark, Esbjerg. Email: [email protected]
4
Flemming Just
‘Endogenous development patterns are founded mainly, though not exclusively,
on locally available resources, such as the potentialities of the local ecology,
labour force, knowledge, and local patterns for linking production to consumption.’ (LONG, VAN DER PLOEG, 1994, pp. 1-2).
Most rural research and practice in Europe focus on endogenous relations
(multi-functional agriculture, rural entrepreneurs, improved living conditions in
rural areas, local amenities etc.) as the way of securing development or just a
pleasant life for the actual inhabitants. The argument in this paper is that there is
a need for strengthening another pillar in rural research and action, a pillar that
to a higher degree considers rural economy in its close interrelationship with and
dependency of urban economy (knowledge production, industry, service, culture, institutions). Bringing matters to a head, the argument will be that one of
the most important ways of stimulating rural development will be through a
strengthening of regional towns and through regional development plans.
The argument is not that rural research should be identical with the regional
economics. This scientific area deals first and foremost with application of
macro-economics on a given sub-national, geographical unit. What I am in favour of is to develop a rural research agenda, which with rural set of problems –
i.e. how to develop rural and peripheral areas – logs on to exogenous factors such
as the knowledge economy, innovation systems, competence building, regional
specializations and the like. There is simply a need for a new approach or ’a new
rural policy’ as it is labelled by some Americans (DRABENSTOTT, WEILER and
NOVACK, 2004, pp. 97-104) or ’a new rural paradigm’ as it is called by the
OECD (OECD, 2006). A more precise term, but perhaps not that comprehensible
in a broader audience, has been phrased by professor Christopher Ray, Newcastle,
calling for a ’neo-endogenous’ approach (RAY, 2006). The core of all three labels is to claim a need for a closer interlinkage between rural and urban economy and to see rural development in a close interplay with regional development in general. The content of this approach will be presented below taking
departure in developments in OECD as such and in its member countries.
The empirical case will have Denmark as an example. This small country, only
43,000 km² and 5.3 mill. inhabitants – i.e. the size of Niedersachsen – has a tradition of a quite homogenous geographical distribution of economic activity.
However, in the recent decade regions have diversified, and population and economic activity are concentrating in a few areas. It will be shown how the general
development in urban economy and globalization contributes to create increased
regional inequality. It is not the intention to explain why those factors influence
rural districts. The aim is to underline with Denmark as example that it is not
sufficient to see rural areas as isolated regions, but to understand their developmental potentials both as a matter of own resources and strengths and as part of
Rural-urban interlinkages and regional development
5
their proximity to adjacent bigger towns and placement in the general regional
development.
2
ENDOGENOUS AND EXOGENOUS DEVELOPMENT STRATEGIES
We see the endogenous development strategy in policies in many countries aiming
at promoting for instance:
-
Local niche products;
Rural entrepreneurs;
Rural, social capital;
Local innovators, ’Feuergeister’;
Multi-functional farming.
This approach corresponds very well with the philosophy in both national and
EU’s rural policy and Leader-programme.
A communication from the Commission says about general objectives:
‘Drawing on the specific resources of rural areas as part of a development
strategy which is relevant and tailored to the local circumstances seems increasingly to be the only way of adapting them to an ever-changing socio-economic
context.….
The aim of Leader+ is thus to encourage rural actors to think about the longerterm potential of their area. The local actors implement the original strategy
that they themselves have designed, experimenting with new ways of:
Enhancing natural and cultural heritage;
Reinforcing the economic environment in order to create jobs;
Improving the organisational capabilities of their community.’
(EU COMMISSION, 2000).
-
Furthermore, the lessons learnt from the first Leader initiatives in the 1990s are
that the so-called Leader method bears some strengths:
‘The mobilising of local actors to take control of the future of their area; decentralised, integrated and bottom-up approach to territorial development; the exchange and transfer of experience through the creation of networks; the ability to
include small-scale projects and support small-scale promoters.’ (EU COMMISSION,
2000).
It will be fair to underline that the Commission is fully aware of the external
threats:
‘Changes in the agricultural sector as a result of the reform of the Common Agricultural Policy (CAP) and the increasing demands of consumers, environmental
pressure, the rapid spread of new technology, the ageing population and rural
6
Flemming Just
depopulation are all factors affecting the countryside today’ (EU COMMISSION,
2000).
Even more subsidization will not turn the tide with depopulation in rural areas
and continued concentration of economic activities in bigger towns and metropoles. The growing inequality between rural and urban regions is a result of the
globalization process and the knowledge economy. In this process, one of the
characteristic features has been that national borders have not been able to stem
the tide. Especially in Western Europe, national policies have aimed at securing
a degree of homogenous development. However, all countries, also outside
Europe, have experienced growing differences between regions, increased specialization, and concentration of settlement, employment, and activities around
bigger towns.
Through the Growth Project, the OECD has spearheaded quite a number of
cross-country studies in order to analyse why some nations and regions have
performed and developed much stronger than others. The conclusion is that five
distinctive growth factors may be identified in prosperous regions:
-
Macroeconomic stability and openness;
Human resources;
Entrepreneurship;
Innovation;
Information and communication technology (ICT) (OECD, 2001).
In a speech on ‘Globalising Cities and Regions – Rethinking the Urban and Regional Policy Agenda’ held on 22 January 2007, OECD Secretary-General
ANGEL GURRÍA has phrased it this way:
‘Regional development must be about wealth creation, and upgrading regional
assets, not just a redistribution policy. It is about building place-based assets
and potential that will attract business investment and strengthen local firms
already in the region. Where once we focussed on national systems of innovation, now we must focus on regional systems of innovation as well. This doesn't
mean a narrow approach based on so-called high-tech sectors. It means focusing
on innovation in all sectors and spheres of activity. Tourism, crafts and food can
all be successful activities which generate regional wealth. And they can all be
innovative, state of the art. To achieve regional innovation it is important to improve physical infrastructure, education and healthcare, the environment for
start-ups and growth of small and midsize businesses, the sharing and spreading
of knowledge, and the availability of support services…Universities and technical institutes can help companies, especially small and midsize enterprises,
solve technical, managerial or marketing problems, as well as helping to provide skilled people and access to lifelong learning. Moreover, local networks of
Rural-urban interlinkages and regional development
7
entrepreneurs and supporting service industries represent an important means
of knowledge-sharing in a community.’1
To sum up, it is possible to distinguish between two different development policies which both take their point of departure in a sectoral thinking, namely traditional development economics with emphasis on growth stimulation through
macro economic initiatives, and an endogenous approach focusing on the possibilities of single sectors to develop from within.
Another possibility is to base development on a territorial thinking. It does not
mean that rural development should be equated with regional economics, which
primarily deals with applying macro economics on a given sub-national, entity.
In stead it is an ambition to look at regions, rural and peripheral areas from a
combined territorial and endogenous angle. The territorial, endogenous policy
has invoked much attention in OECD-countries, where it has been labelled ’New
rural paradigm’ (OECD 2006). It may be illustrated in this way (Figure 1):
Figure 1:
Models of rural and regional development
Sectoral
Territorial
Exogenous
Traditional developmental policy
Regional economics
Endogenous
Traditional subsidization policy
’New rural paradigm’
Source: Author.
For regions it means that special attention is attached to regional innovation
systems. For rural districts and peripheral areas it means focus on a very close
relationship between the general development and policy in the region. The
point of departure is to see the rural economy in its close interlinkage with and
dependency of the urban economy and knowledge import from other regions. At
the same time attention is focused on regional positions of strength, cross sectoral collaboration, targeted investments (Figure 2).
Specifically, it means a gradual shift from sunset-sector subsidies to a policy
based on strategic investments aiming at improving the specific production assets and peculiarities in the area. Public policies and support schemes will have
more focus on comparative advantages, e.g. a specific nature, cultural environment, or business specialisations and clusters. The shift from a sectoral to a territorial policy also means an attempt to integrate the different sector policies at
local and regional level and integrate them with national policies. This results in
a more widespread use of partnerships between public, private and voluntary
sector.
1
<http://www.oecd.org/document/45/0,2340,en_2649_33735_37966061_1_1_1_1,00.html>.
Flemming Just
8
Figure 2:
Objectives
The new rural paradigm
‘Old’ policy
New policy
Create equality
Competitiveness of rural
areas
Generate income in farming
Valorisation of local assets
Create competitiveness in
farming
Exploitation of unused
resources
Key target
sector
Agriculture
Various sectors of rural
economies (tourism, manufacturing, ICT and others)
Main tools
Subsidies
Investments
Key actors
National governments
All levels of government
(supra-national, national,
regional, local)
Farmers
Various local stakeholders
(public, private, NGOs)
Source: OECD, Policy Brief. Reinventing Rural Policy, October 2006.
Many western governments have partly implemented the more integrated rural
policy (it should here be kept in mind that rural in the OECD definition means
regions with less than 100 inhabitants per square kilometre).
-
-
-
2
Finland has implemented a comprehensive rural development programme
emphasizing regional innovation systems since the beginning of the 1990s.
At the moment a strong debate takes place about a further concentration of
investments in only 4-6 internationally competitive centres/regions in different
parts of the country.2
Mexico has launched a so-called ‘strategy for micro-regions’, where 263
marginalised areas have formed Strategic Community Centres that mount
cross sectoral initiatives through a high degree of stakeholder involvement.
In the UK, the Government joined environment, food and rural areas in one
department (DEFRA, Department for Environment, Food, and Rural Affairs)
in 2001 in order to tackle rural policy from a broad perspective. A central
part is the formation of Local Strategic Partnerships (OECD, 2006a).
Presentation by director Sami Kurki, Ruralia Institute, Helsinki, OECD conference on rural
investments, Edinburgh, 11-12 October 2006.
Rural-urban interlinkages and regional development
9
In Australia, a strong focus is on local partnerships comprised by public
authorities, private sector and NGOs. All in all, 56 Area Consultative Committees have been established.3
- The Bush-administration has implemented the new rural policy. In stead of
the traditional product divided subsidies for agriculture, the many schemes
have been brought together in one single package. Additionally, the rural development part is emphasised with three central areas: Amenities (natural and
cultural), entrepreneurship (including the role of the creative class), and third,
a significant effort on bio energy.
- By the CAP reform in 2003 the EU has embarked on the same direction.
There are still many agricultural subsidy programmes, but they are grouped
in one single scheme. Much more profiled but with much less money a rural
policy programme for the period 2007-13 has been agreed upon. It contains
four pillars:
- Restructuring and modernisation of agriculture and forestry;
- Environment;
- Diversification of rural economy;
- LEADER method.
The positive stories being mentioned – according to the OECD – it should also
be stressed that the new rural paradigm has not swept across all countrysides.
Strong sectoral interests, difficulties in adjusting political and organisational institutions, and neglect of place-based approaches still remain a dominating policy
in many countries as it is documented in the latest review of German rural policies (OECD, 2007).
-
3
REGIONAL DEVELOPMENT IN DENMARK
A basic condition for future development is the demographic development. All
forecasts predict a concentration of people in the eastern part of the country in
the Copenhagen area plus in the eastern part of the peninsula Jutland around the
second largest town of Aarhus and the so-called triangular area between Jutland
and the island of Funen. Map 1 shows that southern, western and northern parts
of the monarchy with almost centrifugal power will experience a market decrease
in labour force, some areas by more than 10 per cent over the next decade. For
obvious reasons this will put pressure on the tax-financed heavy welfare system
in some regions.
A more recent forecast paints the same picture of growing regional disparity. In
the next ten years the Copenhagen metropolis will demand about 70,000 new
3
Presentation by executive director, CAROLYN MCNALLY, Department of Rural Development
and Transport, Australia, OECD conference on rural investments, Edinburgh, 11-12 October
2006.
10
Flemming Just
fulltime employed people and the Aarhus area about 11,000. The rest of the
country will lose about 37,000 fulltime workers (ARBEJDERBEVÆGELSENS
ERHVERVSRÅD, 2005).
Map 1:
Forecast until 2020 of labour force (20-65 years) in Denmark
Source: ERHVERVSREDEGØRELSE JYLLAND-FYN (2000), p. 41.
The employment driver is the service sector (ICT, transport, experience economy,
education, research, culture) which is especially strong in bigger towns. The
knowledge economy is a driver in itself as two-third of all private and public
research and development takes place in the Copenhagen area and 10 per cent in
the Aarhus area (see Map 2). At the moment private R&D makes out 1.85 per
cent of GDP and public research 0.75 per cent. As of 2010 it is expected that
private and public spending on research and development will count for 2 and 1 per
cent of GDP, respectively. This will push further in the direction of stimulating
knowledge-based activities in the metropolis. The Government has launched
Rural-urban interlinkages and regional development
11
some programmes in order to spread public research, but related to the overall
development it will only be drops in the ocean as public research is characterised
by the Matthew Principle: ‘For whosoever hath, to him shall be given, and he
shall have more abundance’ (MATTHEW, 13:12).4
Map 2:
Private R&D in Denmark 2003
Source: DANSK CENTER FOR FORSKNINGSANALYSE (2005), p. 26.
The growing regional disparity is emphasised in the latest GEM-analysis, i.e. the
annual international comparison of entrepreneurship, Global Entrepreneurship
Monitor. The Danish part shows how innovation and entrepreneurship has developed in the metropolis versus the provinces. The differences are substantial.
The probability of establishing a new firm is 50 per cent higher for a person in
Copenhagen than for a person in the provinces. The entrepreneur in the capital
region will most likely be more innovative, more export oriented, more ambitious and more growth oriented:
4
The Government has also introduced some special programmes aiming at stimulating rural
activities, in total about 7 mill. Euros per year. It is hard to estimate the effects as a major
part of funding goes to cultural activities, see THOMSEN (2007).
12
Flemming Just
‘…entrepreneurship is indeed more prevalent in the metropolis than in the
province. One reason is that the metropolis creates more networking, specifically with entrepreneurs, which in turn enhances the likelihood of being an entrepreneur. Furthermore, entrepreneurship in the metropolis is found to be more
ambitious in terms of export and growth-expectation, and perhaps also innovation’ (SCHØTT, 2006, p. 20).
This coheres with an important background variable, namely educational level
for a first-time entrepreneur. Persons with vocational qualifications and especially with long further educations have a much higher probability than others of
creating a start-up company (SCHØTT, 2006, p. 39).
‘Education has four indirect effects. Higher education raises odds of being competent, risk-willing, opportunity-recognizing and networking, and each of these
raises odds of being an entrepreneur’ (SCHØTT, 2006, p. 55).
As the educational level in the metropolis and in Aarhus is somewhat higher
than in the rest of the country, that factor will in itself contribute to create more
innovation and growth. Another dimension has been added through Richard
Florida’s work on the creative class (FLORIDA, 2002). He claims that competitiveness of companies will depend on their ability to attract and retain workforce
with innovative skills. This is not just about higher educations, but more about
innovative skills and readiness for change. In general one-third of the workforce
belongs to the creative class in the western world. The geographical distribution,
however, is very uneven. North American experience shows that talents stick
together in towns with special qualities, often characterised by open-mindedness
and tolerance.
As part of a big European project on ’Technology, Talent and Tolerance in
European Cities: A Comparative Analysis’, Vaarst Andersen & Mark Lorenzen
have investigated if Florida’s theses prove to be correct (VAARST ANDERSEN and
LORENZEN, 2005). Apparently this is the case. 40 per cent of the Danish population
belongs to the creative class, and it is primarily localised around Copenhagen
and Aarhus. Their study shows at the same time that there is a positive and significant correlation between localisation of the creative class and the number of
companies, but it does not tell about the causality: If the creative class creates
the technological and economic development or if the people is attracted by certain regions because of the economic situation there and existence of ‘tolerance’.
Probably, it is a dialectical relationship. Young people and the creative class are
attracted by towns because of like-minded people in towns and more offers.
Knowledge-based companies are localised in bigger towns because the needed
labour force is there, and because labour force in that type of companies will live
in big towns or in their vicinity. A consequence is that educational institutions in
rural communities have difficulties in attracting students, and companies need to
Rural-urban interlinkages and regional development
13
merge in order to have a volume, which is sufficiently inspiring for young candidates. With almost full employment it is even more important to amalgamate.
Thus, a higher educational level, job and cultural expectations, and the growing
adherence to the Matthew Principle among decision makers all point in the direction of hard times for peripheral areas. One major reason for that – and contributing to the choices made by private business and politicians – is the globalisation process that speeded up from the middle of the 1990s.
3.1 Globalisation and regional development
Globalisation is an external force that considerably influences conditions for rural
areas and contains an immanent strengthening of urban economy and weakening
of rural economy.
Part of the globalisation process is opening of food markets for exporters and
abolition of export subsidies. This has called for a thorough change of the Common
Agricultural Policy and hard times for many producers, for instance within
sugar, beef, milk, tobacco and wine production. Even though agriculture seems
to be hit in the first run, the bottom line is not necessarily negative. A substantial
portion of existing subsidies has been transferred to nature and environmental
purpose. Another part has been directed to rural development in general, and
lastly: We will see some dynamic effects. Some farmers will change the whole
production, e.g. to organic farming, or part of production either with niche products or with multi-functional agriculture, e.g. rural tourism. This value adding
process will mean a bigger share of the budget landing at the primary producer.
The most important decreasing employment effect in Danish agriculture was not
the reform of the CAP, but in stead significant increases in labour productivity –
for a long period about 6 per cent annually (MINISTRY OF FOOD, 1998). This rationalisation has been decisive for Danish agriculture’s strong position on international markets for foods, mink, malt, seed, starch, and seed.
Another perceptible consequence of globalisation is the outsourcing within traditional industry. It has been estimated that 5,000 workplaces annually move
from Denmark to low salary countries.5 As a whole, globalisation has evident
positive benefits for Danish society, but it has also many regional consequences.
Traditional jobs in the industry disappear, and these are almost always localised
outside the biggest towns. In return many jobs requiring high technical, mercantile
or communicative qualifications are established, but these are in general localised
in the biggest towns (ARBEJDERBEVÆGELSENS ERHVERVSRÅD, 2004: 69-80).
5
Professor PETER BIRCH SØRENSEN, Børsen, 7 January 2005.
Flemming Just
14
3.2 Differentiation
Empirical studies show that the challenges are rather different for rural areas. In
some parishes local initiators and voluntary associations make enormous efforts
to create a thriving and attracting village, but without much success measured in
increasing population if the parish is located a long way from a town with
growth. On the other hand, parishes without much activity experience growth if
located close to a prosperous town (SØGAARD, 1997).
This is not to say that action does not matter. A recent study shows that villages
in a remote area may experience quite different developmental paths. In this case
both villages had an active population. One was placed at the sea with a long
tradition for close contact with the outside world and hence an openness towards
new impulses and a slightly different composition of population. The other one
was placed in some distance from main roads and dominated by old farming traditions. The bottom line showed that the stock of social and human capital was
decisive for the positive development in the first village, whereas the second one
stagnated (SVENDSEN and SØRENSEN, 2007).
It shows that it is not enough to take a point of departure in a classical spatial
division of rural communities, e.g.:
A-rural areas
Close to bigger town centres;
B-rural areas
Close to towns in peripheral areas;
C-rural areas
Remote from towns in peripheral areas.
To get a full understanding of developmental potential, it is necessary to include
a content side, which looks at degree of participation in town and service economy
and the stock of human and social capital. The next step is to analyse the attractiveness and economic strength of the region in which the towns are situated.
4
DISCUSSION: CONSEQUENCES FOR RURAL RESEARCH
The changes brought about with the knowledge economy and globalisation call
for a stronger involvement of ’place-based assets’ where it is important to find
and commit ’stewards of place’ be it individuals, organisations or institutions
like universities (REINDL, 2005).
Much rural research has not followed this move. One exception is Centre for
Rural Economy, Newcastle University, headed by Professor Philip Lowe.
Already in the middle of the 1990s he and his colleagues pointed at the need for
examining the dividing line between an endogenous and an exogenous approach
in research (LOWE, MURDOCH and WARD, 1995). The latest contribution has
come from Christopher Ray from the same centre. He explicitly picks up the
thread and writes about the need for developing a ’neo-endogenous rural development’-approach (RAY, 2006).
Rural-urban interlinkages and regional development
15
‘Generally, a synonym for endogenous would be participative. The ’neo’ part,
whilst not challenging the integrity of bottom-up dynamics, identifies the roles
played by various manifestations of the extralocal. Actors in the politicoadministrative system (through the national up to the European level) as well as
in other localities are all seen as part of the extralocal environment of rural
development and as potentially recruitable by localities in support of their regeneration strategies’ (RAY, 2006: 278).
This leads him to define three levels in a ’neo-endogenous’ approach: An intraterritorial, i.e. internal resources in a given district; the political-administrative
context; and inter-territorial relations, i.e. relations between actors and structures
from both town and countryside in an area.
Ray’s approach could be programmatic for much rural research. We should still
analyse internal strengths, weaknesses, dynamics etc. Local initiatives are the
salt that creates engagement, local pride, and joy of countryside living. But these
conditions need to be seen in a closer context with exogenous politicaladministrative, economic, cultural and other factors influencing both town and
rural areas. Together these should be synthesised in analyses of inter-territorrial
conditions for two reasons: Because it reflects driving forces of reality and
because rural research in this way contributes to improved policy development.
A concrete example is the focus in many countries on growth drivers as innovation, entrepreneurship, human resources and ICT. However, can we conclude
that growth promoters in metropoles also are drivers in the rural economy? Or
do we need to develop a specific understanding of innovation processes and entrepreneurship in a rural context, for instance develop specific policies for creating
networks and linkages between SMEs and knowledge institutions in towns?
A first answer came from Bryden and Hall in a major international project on
dynamics in rural areas (DORA). They concluded that place-based and ‘soft’
variables or less-tangible factors are important for creating development, among
others vibrancy of civic community, cooperative behaviour, embeddedness, and
external linkages (BRYDEN and HALL, 2001). A comparative OECD study from
2003 about determinants for rural development shows that eight broad groups of
variables may be identified as important for business and settlement in rural
areas. The most important ones are amenities (natural and man-made), infrastructure, and cultural identity (CLARK, 2003).
The question about endogenous and exogenous factors’ importance for rural development cannot be settled with one or the other. There must be a mix of both if a
positive spiral should get going. In general, rural areas are more than ever dependent on the overall economic situation in the broader region. That is why rural
research needs a stronger focus on factors influencing rural communities and
instruments to make rural areas link to the knowledge economy. Rural research
must try to refine existing methodological and theoretical approaches, for instance
16
Flemming Just
innovation research, and empirically the domain must to a higher degree try to
analyse inter-territorial factors and be open for more comparative and nonEuropean experience. Classical development research may also offer new insights. In this way rural research may also deliver valuable contributions to
agenda setting and policy development.
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ARBEJDERBEVÆGELSENS ERHVERVSRÅD (2004): Økonomiske Tendenser 2004,
Copenhagen [Economic Council of the Labour Movement, Economic tendencies].
ARBEJDERBEVÆGELSENS ERHVERVSRÅD (2005): Nyhedsbrev, November, Copenhagen,
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BRYDEN, J., HALL, K. (2001): Dynamics of rural areas (DORA). The international comparison, The Arkleton Centre for Rural Development Research, University of Aberdeen.
CLARK, M. (2003): The future of rural policy. From sectoral to place-based policies in
rural areas, Paris, OECD.
DANSK CENTER FOR FORSKNINGSANALYSE (2005): Erhvervslivets forskning og udviklingsarbejde – Forskningsstatistik 2003, Aarhus [The Danish Centre for Studies in
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LONG, A., VAN DER PLOEG, J. D. (1994): Endogenous development: Practices and perspectives, in: VAN DER PLOEG, J. D., LONG, A. (eds.): Born from within. Practice
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LOWE, P., MURDOCH, J., WARD, N. (1995): Beyond models of endogeneous and exogenous development, in: VAN DER PLOEG, J. D., VAN DIJK, G. (eds.): Beyond
Modernization, Assen: van Gorcum.
MINISTRY OF FOOD, DANISH (1998): The structural development of agriculture, Commission Report No. 1381 (in Danish).
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Project, Paris.
OECD (2006): The new rural paradigm: Policies and governance, Paris.
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OECD (2006a): Policy brief. Reinventing rural policy, Paris.
RAY, C. (2000): Endogeneous socio-economic development in the European Union:
Issues of evaluation, Journal of Rural Studies, 16, pp. 447-458.
RAY, C. (2006): Neo-endogeneous rural development in the EU, in: CLOKE, P.,
MARSDEN, T., MOONEY, P. (eds.): Handbook of Rural Studies, London: Sage Publications, pp. 278-291.
REINDL, T. (2005): Stewardship of place: A U.S. perspective on higher education and regional development. OECD/IMHE/NUS/NUAS Seminar, 5 October 2005, Stockholm,
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ravisReindl.ppt#>.
ROSTOW, W. W. (1960): The stages of economic growth: A non-communist manifesto, Cambridge, Cambridge University Press.
SCHØTT, T. (2006): Entrepreneurship in Denmark 2005 – Studied via global entrepreneurship monitor, Odense: University of Southern Denmark.
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to settlement area], Esbjerg: Sydjysk Universitetscenter.
SVENDSEN, G. L. H., SØRENSEN, J. F. L. (2007): There’s more to the picture than meets
the eye: Measuring tangible and intangible capital in two marginal communities in
rural Denmark, Forthcoming in Journal of Rural Studies.
THOMSEN, L. (2007): Subsidy programs in rural Denmark: To whom and for which
purpose, Danish Institute of Rural Research and Development, Working Paper
No. 01/2007, Esbjerg.
VAARST ANDERSEN, K., LORENTZEN, M. (2005): The geography of the Danish creative class. A mapping and analysis, Copenhagen.
Sustainable rural development: What is the role of the agri-food sector?
MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central and Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 18-27.
SUSTAINABILITY ASSESSMENT OF RURAL DEVELOPMENT:
A REVIEW OF METHODOLOGIES
ADINYIRA EMMANUEL∗, OTENG-SEIFAH SAMUEL∗, ADJEI-KUMI THEOPHILUS∗
ABSTRACT
From its beginnings in economics and ecological thinking, sustainability has become a planning concept that has been widely applied in rural development.
Whether at the European or the state level, legislation, policy statements, and
even research programmes on the future of agriculture, regional development or
economic and social cohesion all increasingly refer to the need for sustainable
rural development. This paper thus presents a structured review of methodologies available for assessing the sustainability of rural development. Specific
recommendations regarding choice of sustainability measurement methods is not
the intent of the paper. The paper does, however, recommend a pragmatic shift
in the focus of sustainable rural development research away from theory development and towards more application and auditing.
Keywords: Assessment methods, rural development, sustainability.
1
INTRODUCTION
From its beginnings in economics and ecological thinking, sustainability has become a planning concept and has been widely applied in rural development.
It has been variously defined as the capacity to create, test, and maintain adaptive capabilities (HOLLING, 1973), the resilience of socio-ecological systems
(CARPENTER et al., 2001) or the ability to live within the regenerative capacity of
the biosphere, whilst maintaining natural capital (WACKERNAGEL et al., 2002).
Sustainability can simply be described as continuing to improve human wellbeing, whilst not undermining the natural resource base on which future generations will have to depend.
For the past decade, sustainability has been seen as the overriding developmental consideration and regarded as an inherently dynamic, indefinite and contested
concept (MOG 2004). Indeed, it can be argued that the goal of development is
essentially to enable its beneficiaries to gain a more effective form of control
∗
Department of Building Technology, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. Email: [email protected]
Sustainability assessment of rural development
19
over their environment. Thus, sustainable development must be seen as a neverending process defined not by fixed goals or the specific means of achieving
them, but by an approach for creating change through continuous learning and
adaptation (MOG, 2004). It is currently fashionable to say that the term ‘sustainable
development’ defies definition because it is too complex. In fact, there are rumoured to be well over 200 definitions of sustainable development in circulation
(PARKIN, 2000). However, the best-known definition is perhaps the one popularised by Brundtland (WCED, 1987), which arose from increasing global concern
about the plundering of resources to meet immediate needs at the expense of
long-term societal development.
The expression ‘rural development’ is currently used in various senses in a
number of public policy programmes and can be said to be a somewhat overworked expression. Simply put, rural development is about implementing a political, economic and social project attuned to a collective vision of the future of
rural regions (YVES, 2005). Whether at the European level or at that of existing
or new member states, legislation, policy statements, and even research programmes on the future of agriculture, regional development or economic and
social cohesion all increasingly refer to the need for rural development. This can
be attributed to the vital role that rural areas play in fulfilling functions that are
essential to the lifestyles of the urbanised population. Beyond the traditional
productive function of rural areas, i.e., supplying agricultural, agro-food and
forestry goods, goods from extractive industries and craft products, rural areas
have become an environment for living and leisure. In view of this, sustainable
development is paramount to maintaining its function of conserving nature and
protecting natural resources.
Rural sustainability is best attained through well-planned and properly implemented
initiatives that address the social, physical and economic facets of the environment
in an integrated and participatory approach (SANDHAM and VAN DER WALT, 2004).
This ensures that this generation’s activities leave future generations with a better
resource endowment than that which they inherited (YIRENKYI-BOATENG, 2001).
The concept of sustainable rural development embraces both the natural and
social environments. Since becoming a catchword in international policy discussions, several approaches to its assessment have been developed. According to
LAWRENCE (1997), sustainability assessment is simply applying the broad principles of sustainability to ascertain whether, and to what extent, various actions
might advance the cause of sustainability. The term "sustainability assessment"
is used in both literature and practice in two very different manners. Firstly, it is
used in the context of determining whether a community or organisation is progressing towards sustainability. Here, it serves as an auditing or performance
testing system. In the second context, the term serves more as an impact assessment process in that it attempts to assess the sustainability of proposed projects,
plans, policies or legislation before they are implemented (DEVUYST, 2000). In
20
Adinyira Emmanuel, Oteng-Seifah Samuel, Adjei-Kumi Theophilus
both contexts, much effort has been made to develop approaches to sustainability
assessment. These efforts have ranged from assessing change that pushes beyond an emphasis on economic signals, to a more complete treatment of both
human and ecosystem well-being (HODGE, 1997).
Much of the literature and theory surrounding sustainability assessment has argued that current assessment methods often fail to involve sufficient vision and
understanding of the interrelations and interdependencies of social, economic
and environmental considerations. This paper thus seeks to contribute to the
debate by reviewing the underlying methodologies for the existing assessment
methods and presenting their potentials and limitations. As part of the review,
some specific assessment methods found to be in extensive use are closely examined. In order to present a structured and focussed review, the paper relied on
a review framework that allowed for most issues relevant to sustainable rural
development to be covered. Specific recommendations regarding choice of a
particular sustainability measurement method is not the intent of this paper.
Rather, it presents basic methodologies for the assessment of sustainable rural
development and describes methods most commonly identified in practice.
2
REVIEW FRAMEWORK
As indicated earlier, "sustainability assessment" is used in literature and practice
in two very different contexts. Firstly, it refers to checking whether a community
or organisation is progressing towards sustainability, and secondly, it refers to
attempts to assess the sustainability of proposed projects, plans, policies or legislation before they are implemented. There are many methods for assessing sustainability in terms of the first context, but fewer for the second (DEVUYST, 2000).
This paper carries out a review of auditing or performance testing methods that
helps to determine if rural communities are progressing towards sustainability. It
also provides an overview of the current status of methods for assessing the sustainability of rural development. Due to the proliferation of well-established sustainability assessment methods, many such methods can be identified in practice. However, for the purposes of this paper, the identified assessment methods
are grouped based on their methodological foundation.
In carrying out this review, a framework allowing for the involvement of most
issues relevant to sustainable rural development was employed. For each group
of assessment methods identified, issues such as the origin and status of the
methodology, whether it ranged from well-established to experimental, its data
requirements and its applicability to rural developmental activities such as planning, construction and operation were all covered under the review. This allowed the strengths, limitations, potential applications, data inputs, outputs and
methodological problems for each group of assessment methods to be identified.
Sustainability assessment of rural development
3
21
ASSESSMENT METHODOLOGIES
Methods available for measuring the sustainability of rural development range
from sets of simple socio-economic and environmental indicators to complex,
holistically integrated models. A careful examination of the identified methods
revealed three common methodological foundations, namely, ‘environment in
general’, life cycle assessment, and sustainability indicator assessment.
3.1 ‘Environment in general’ methods
Sustainability assessment methods based on environmental assessment dates
back to the pre-Brundtland era, where sustainability mainly focused on environmental issues such as resource consumption, pollution and impacts on biodiversity. Across the range of rural activities, the environmental dimension of
sustainable development has the greatest coverage. Based on this methodology,
many sustainability assessment methods that focus on energy and material flow
and address both resource use and waste arising across a wide range of rural
activities have been developed. It is a methodology that prominently considers
resource consumption, pollution and environmental valuation.
A careful look at ‘environment in general’ methods of sustainability assessment
reveals rather significant limitations with respect to the range of sustainability
issues they are capable of addressing. These are mostly limited to applications at the
levels of policy planning and programme development (GUY and MARVIN, 1997).
‘Environment in general’ methods for sustainability assessment of rural development have lost their appeal due to their rather minimal coverage of sustainable
rural development activities. (BERGH et al., 1997; NIJKAMP and PEPPING 1998;
BIZARRO and NIJKAMP, 1997).
3.2 Life cycle assessment methods
The origin of life cycle assessment methods can be traced to Agenda 21’s call
for the integration of environment and other aspects of development such as social, economic and institutional issues (UNCED, 1992). This has resulted in a
shift of focus in method development away from environment evaluation to life
cycle assessment (LCA). LCA methods attempt to address broader sustainability
issues such as environmental limits, social equity concerns and stakeholder participation, and are based on a structured methodology that can be utilized to
evaluate the impact of various developments across their life cycles.
In comparison to ‘environment in general’ methods, LCA methods appear to
address a much broader range of rural developmental activities. This is due to its
focus on both social and economic issues of development. LCA methods capture
social, economic and environmental issues in their assessment of the sustainability
of rural development, but fail to integrate them. In spite of being based on a
22
Adinyira Emmanuel, Oteng-Seifah Samuel, Adjei-Kumi Theophilus
well-established and standardized methodology (SAHELY et al., 2005), LCA
methods still exhibit limitations with respect to the range of sustainability issues
they are able to address. They are seen not to perform well with respect to social
and institutional issues of development. Some major weaknesses of such methods
include the complex and time-consuming nature of analysis, and its large data
requirements. Nevertheless, LCA methods have contributed significantly to the
sustainability assessment of rural development by widening the coverage of developmental activities and spatial scales.
3.3 Sustainability indicator methods
How environmental, social and economic information is analysed, integrated
and presented to decision-makers is the most critical concern of sustainability
assessment. However, methods of assessment that were developed based on the
‘environment in general’ and LCA methodologies have all, in one way or another,
failed to achieve this requirement. Thus, a third methodology seeking to achieve
integration of all sustainable development issues has been developed. This
methodology employs a wide range of indicators to characterise the different
dimensions of sustainable development. With this methodology, the assessment
of rural development sustainability is actually an assessment of indicators by
which people in rural regions can track their progress towards sustainability.
Sustainability indicators are useful for monitoring and measuring the state of the
environment by considering a manageable number of variables or characteristics
(MCLAREN and SIMONOVIC, 1999). Several studies at the rural, urban, regional,
and national levels have compiled extensive lists of sustainability indicators
(FOXON et al., 2002; HELLSTRÖM et al., 2000; ALBERTI, 1996; MACLAREN, 1996).
Of these indicators, assessment methods have been developed which attempt to
simplify the holistic assessment of sustainable development. From a methodological standpoint, sustainability indicator methods are recognised as useful integration tools for evaluating a situation in several dimensions, as well as for
testing sustainability. However, the main problem with the use of sustainability
indicators is relating what the indicators measure to actual sustainability. Such
indicators are not useful when considered in isolation, but rather their usefulness
comes from monitoring relative changes in the state of the environment. The use
of sustainability indicator methods for assessing the sustainability of rural development has had mixed results in practice and, in some cases, minimal effects
on policy (LEVETT, 1998). These methods are unavoidably value-laden, and
sometimes present difficulties in interpreting whether or not any progress towards sustainability is actually being made.
Sustainability assessment of rural development
4
23
KEY ASSESSMENT METHODS
As shown in literature and in practice, some sustainability assessment methods
have received extensive use in rural sustainable development assessment due to
their strengths, potential applications, data inputs, outputs and applicability at
various spatial scales. This section of the paper takes a close look at examples of
such assessment methods, namely; Community Sustainability Assessment (CSA),
Material Flow Accounting (MFA), Ecological Footprinting (EF), and Integrated
Assessment (IA).
4.1 Community sustainability assessment
Community Sustainability Assessment (CSA) is a comprehensive checklist that
anyone can complete to get a basic idea of how sustainable their community is.
While CSA requires good knowledge of the lifestyles, practices and features of
the community, it does not require research, calculation or detailed quantification. With CSA, more people at the rural level are able to participate in and/or
learn about the sustainability assessment of their community develop-ment.
4.2 Material Flow Accounting (MFA)
Material Flow Accounting (MFA) is a sustainability assessment method that aims
to quantify the flow of resources, in terms of mass, within a defined geographical
area and over a set period of time. It does this by means of material input, output
and consumption indicators (HINTERBERGER, 2003; KRAUSMANN et al., 2004).
The various indicators used in MFA differ with respect to what stage of the material life cycle they measure, and cover all levels of aggregation (micro, macro,
input, output, consumption, trade). However, there are weak links between MFA
indicators and environmental impacts, and this is seen as a major weakness of
the MFA method of assessing rural development sustainability. Also, many of
the studies into MFA have, in most cases, focused on metho-dological issues
and the presentation of material balances to the detriment of policy-related uses
of its results.
4.3 Ecological footprinting
Ecological Footprinting (EF) is a land-based measure of a population’s demands
on natural capital, and is defined as the total area of productive land and water
required to produce all the resources consumed and to assimilate all the wastes
produced by a defined population, regardless of where that land is located (REES
and WACKERNAGEL, 1996). As a sustainability assessment method, ecological
footprint analysis (EFA) involves collecting data for a range of activities, including
food, materials, waste, direct residential and commercial services energy consumption, construction and land use in order to estimate both direct and indirect
24
Adinyira Emmanuel, Oteng-Seifah Samuel, Adjei-Kumi Theophilus
impacts on sustainable development. However, a major limitation of this method
is its lack of predictive capability.
4.4 Integrated assessment (IA)
Integrated Assessment (IA) of sustainable development is an interdisciplinary
process whereby knowledge from diverse scientific disciplines is combined, interpreted and communicated in such a way as to provide insights on issues of
sustainability to decision makers (ROTMANS et al., 2000). This approach to sustainability assessment of rural development allows for the integration of environmental, social and economic information in a single analysis of sustai-nable
rural development. However, this type of assessment is unavoidably valueladen, as it usually involves both qualitative and quantitative data from diverse
disciplines.
5
CONCLUSIONS AND RECOMMENDATIONS
The primary object of any sustainability assessment exercise is to provide the
opportunity for more inclusive and informed decision-making on issues of development. Thus, the ability to address economic, social and environmental interdependencies within policies, plans, legislations and projects at the rural level
has become a basic requirement of any sustainable rural development assessment
methodology. When examining the development of such sustainability assessment
methodologies, one sees steady progress toward achieving this requirement.
The evolution of methods that attempt to assess the impact of development
across most rural spatial scales can be traced to three underlying methodologies.
Most available methods fail to demonstrate sufficient understanding of the interrelations and interdependencies of social, economic and environmental considerations. Many reports on sustainable rural development assessment methods
point to the absence of truly integrated assessment methods. It is thus the view
of this paper that further improvement in assessment methods can only be
achieved when existing methodologies are critically reviewed and further research into methodological improvement is carried out.
One major shortfall of current developments in the area of sustainability assessment of rural development is the relative lack of implementing many of the developed methods. As demonstrated in this review, much progress has been made in
improving sustainable rural development assessment theories. However, a
wide gap still exists between assessment theories and assessment practices
(COOPER, 1997; 1999). New assessment methods remain largely experimental,
with relatively few applications in practice. An ample demonstration of this is
that most assessment methods currently in widespread use fail to make assessments that adequately address most issues underlying the sustainable rural development process.
Sustainability assessment of rural development
25
To improve upon the present situation, identifying those aspects of rural development which are poorly covered by available assessment techniques is necessary.
Based on the identified gaps, a cross-fertilisation of methodologies can then be
employed to develop methods which will be capable of addressing most if not
all rural development issues. The paper further recommends a pragmatic shift in
the focus of sustainable rural development research away from theory development towards more application and auditing. Methods must quickly move beyond
the experimental phase to practical application. In so doing, great steps will be
made in the learning process of assessing the sustainability of rural development, and these steps will help improve both theory and practice.
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MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central and Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 28-45.
POST-SOVIET TRANSITION, RURAL DEVELOPMENT AND THE
PEASANT PROBLEM: THE CULTURAL AND INSTITUTIONAL
ECONOMIC DIMENSION
ERNST-AUGUST NUPPENAU∗
ABSTRACT
This paper discusses transition-oriented problems stemming from the persistence
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distinct from pure profit maximisation. It further suggests the theory of reciprocity
as an explanatory approach. The paper illustrates how observations support the
hypothesis of the emergence of peasants. Finally, a discussion on policy responses
provides hints on how to cope with current problems to assure that transition
does not stagnate.
Keywords: Household subsidiary farming, peasant behaviour, land reform.
1
INTRODUCTION
Living in the 21st century does not mean that the problems regarding agriculture
that were prevalent in the 19th and 20th century are now obsolete. One of these
problems or issues is the question of which role peasants and peasantry play in
agriculture. With respect to rural development, rural livelihood, marketed surplus, commercialisation of agriculture, industrialisation, etc., peasants have always played a special role and have confused the proponents of agrarian change
(ELLIS, 2003). For some scholars, a peasant is a backward, shabby rural dweller,
an impediment to development, an ignorant farmer, etc., of whom we should rid
ourselves. For others, he is a land custodian, an efficient producer, a noncapitalist operator, etc., who is a committed tiller and has always been the backbone of the rural economy, thus guaranteeing ecological and economic stability,
as well as food security. In the beginning of transition, there existed in many
countries the idea of a rapidly developing middle-sized farmer class – let us also
call it a peasantry; but the idea was now distinct from rural labourers on large
enterprises. Unfortunately, this rapid expansion did not happen (as already suggested by SARRIS et al., 1999), perhaps due to the unwillingness of labouring
∗
Institute of Agricultural Policy and Market Analysis, Justus-Liebig-University, Giessen,
Germany. Email: [email protected]
Post-soviet transition, rural development and the peasant problem
29
‘peasants’ (rural proletariat) to become ‘real’ peasants (self-reliant, small-scale
owner class). Thus, the debate on farmer behaviour, rural and cultural identity,
rural organisation, etc., is back. This is not to say that the peasant is back.
Evidently, in the more eastern parts of transition countries, the phase of collectivisation, as well as the phase of large-scale collective and state-run farm operation (in Russia this ran from the late 1920s to the early 1990s; in other countries
it began post-World War II) started after governments initiated the dissolution of
a centuries-long prevailing agrarian institution: The peasant economy (as "labour
constitution"). However, it is difficult to say whether a "western" path would have
been inevitable had collective farming not occurred. The current phase of decollectivisation and emergence of new rural structures (small-scale household
subsidiary farming and partly-emerging large landholdings) should be seen in
light of this historical background; there is a path dependency at work. A major
hypothesis of this paper is that the current level of rural development (or lack of
development) in many transition countries has to be reviewed against this background. Problems with low labour and land productivity, economically "irrational" behaviour, and strategies to minimise work loads and commitments to
landlords seem to be deeply-rooted in rural cultures and impede new organisational schemes in transition countries. We thus must research "peasant
beha-viour" in transition to better understand rural development in the respective
countries, keeping in mind that peasant behaviour has a lengthy historical background.
Based on more and more qualitative findings from rural anthropology and empirical findings from economics, it has become evident that the strategies and
behaviour of rural populations suffering the severe problems of poverty and endangered livelihoods are correlated with what has been called peasant behaviour.
As observed, food insecurity, poverty, and missing markets in the countryside
drive the population to become less interested in exchange economies and to develop kinship or group-oriented solutions that are inward looking, resistant, subsistent, and even adversarial to outsiders. In more culturally-oriented institutional economics theories, as opposed to neoclassical economics, it makes a big
difference, with respect to motivation, whether somebody labours for wages or
is a free-holding farmer. Some of the older arguments on tenure, peasant farmers, freeholding, commercial small-scale farms versus big-estates as institutions and the corresponding behavioural and cultural background must be renewed and brought back into the discussion for understanding recent trends of
peculiar rural developments in transition countries (positive analysis). Further,
we need scenarios for better policies promoting progressive rural development
and interventions (normative analysis). As has been shown (below), even in economics culture matters. This contribution has to been seen in the light of
emerging questions of peasant behaviour or theories combining cultural and sociological aspects in rural development and transition studies.
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In the following, the paper presents a condensed analysis of arguments from the
theory of peasant behaviour, as well as theoretical suggestions from the new
socio-economic theory of reciprocity as a driver of change (no change). To support the theory, a literature overview explores current discussions on the reemerging problem of peasants (better peasant behaviour) and offers new findings,
especially for rural development. We will discuss how one can gain insight into
development analysis using knowledge from past and modern peasant literature.
Issues such as real and perceived ownership, uncertainty of contracts, power
struggles, migration strategies, urban-rural bias, and the necessity of social infrastructure are addressed. The objective here is to provide hints on what can be
done to make development more viable regarding peasant behaviour.
2
CLARIFICATION ON THE TERM "PEASANT"
2.1 Peasant behaviour definitions
As researchers have found in many areas of Eastern Europe, when the dissolution of collective and state-run farm operations took place, portions of rural
populations tended to distance themselves from labour and land markets and become self-sufficiency oriented small gardeners who prefer to work on household
plots and engage in petty trade rather than become modernised individual farmers. Though many labourers still work on large holdings, they retreat more and
more from official labour markets. Labour markets seem to be un-trustable and
unable to achieve food security and income. So how much of this is linked to
peasant behaviour? Apparently, the debate should be based on a wide range of
issues regarding the peculiarities of peasants; but it is nearly impossible to reflect
on even a few aspects in depth. We have to refer to given literature (ELLIS, 2003;
ELLIS and SWIFT, 1988; HOWE, 1991) and extract an essential, previously made
point when setting the agenda: How much does a peasant culture matter in transition (PAXSON, 2002)?
Let us start with what is meant by "peasant" and peasant institutions. Basically,
the term refers to a land use system containing parts of collective decisionmaking (MCCLOSKEY, 1991; BEKAR and REED, 2003) and is also reckoned to be
resistant to change. For those development planners who wanted to rapidly
modernise agriculture, peasant behaviour was always something suspect, and as
time went by, it became evident that it should undergo institutional reform towards smallholder tiller systems. This view is reiterated by history books about
the past living conditions of peasants (WEBER, 1979). Hence, it is understandable
that the word peasant creates negative emotions, but it creates positive ones as
well. However, if one tries to lay a foundation of peasant behaviour, which is
relevant for our further discussion, one finds seven building blocs of a peasant
Post-soviet transition, rural development and the peasant problem
31
economy and behaviour. Note that they are also divergent to conventional beliefs
on farmer behaviour:
-
An objective function that varies from profit and utility maximisation;
-
Collective elements of decision-making;
-
Collective land use and labouring, to various degrees (village, tribe, kin, family,
etc.);
-
Social connectivity, group-based risk mitigation, and cultural identification;
-
Lower degree of individualism (though difficult to perceive for economists);
-
Different mentality (paternalism, for instance);
-
Recognition of nature (soil fertility, but also forest and ecosystem wealth).
This basic list can be supplemented with many other aspects. For instance, an
anti-modernisation impetus, conservative attitudes, unwillingness to integrate into markets, etc.. To comprehend why peasant behaviour departs from "normal"
modern farm behaviour, many researchers have probed into peasant behaviour
and found explanations acceptable to economists (DE JANVRY et al., 1991). In
this context, there exists Eastern European and Russian literature that explores
such topics (TSCHAJANOV, 1923; GEORGESCU-ROEGEN, 1960). Some issues are:
-
Inferior natural conditions;
-
Preservation of natural resources and nutrient cycles;
-
Local risk-mitigation strategies;
-
Remoteness and high transaction cost;
-
Protection against exploitation of landlords and governments;
-
Limited expectations for prosperity.
So a major question is, are there "natural" conditions that impose a departure
from "capitalist" behaviour, and what creates a "peasant"? The authors would
answer, Yes, and respond that peasant behaviour is created by misery.
2.2 Questions regarding peasant behaviour
We could make things easy and ask ourselves, are the abovementioned types of
behaviour and issues prevalent in the rural areas of transition economies? But is
that sufficient? As will be shown, rural dwellers actually cope with misery. This
would imply a positive approach, as has already been initiated and conducted by
others (see below). In the following sections, information is provided on positive
research agendas, and we will see that there is already an illustrative form of literature arriving at the point that the ‘peasant’ has not disappeared.
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But further clarification on the normative aspects of research is needed. Dealing
with rural populations in transition, many researchers consider it self-evident
that transition should contribute to a "better livelihood" for the people and is
"good" for peasants. However, from the very beginning policy-makers anticipated that problems with the welfare of the rural population might occur
(WEGREN, 1993). However, statements on welfare require precision. An immediate
question is "who loses and who gains," (see below). This has a positive and a
normative component. For instance, while describing the winners and losers,
(WEGREN et al., 2002) we can find a wide spectrum of peasants. Social stratification in a peasantry can be narrow or wide, and it is necessary to clarify what stratum we are talking about (note: This also depends on ideology). The immediate
question is whether peasants are the only poor people without land. In the historical context of Eastern Europe (PAXSON, 2002), land rights per se define a
class. This is a particularly relevant problem in the current situation of weak
rights. Nowadays a duality (actually a triad: I. very small land occupations, gardening households; II. large farm operations; and III. medium-sized peasants)
prevails, where poor peasants are the majority. For the discussion of distribution,
this has strong implications. Currently, we are primarily dealing with the lowest
stratum of peasants. That is, the kulaks are missing, though any discussion of
behaviour has to be made with reference to social status as it matters in agrarian
societies. Status depends on the ability to command resources, that is, prominently land. However, in this respect the peasants who have emerged after decollectivisation may be more typical of manorial systems, eventually only owning
their cottage. These are not peasants exercising greater command and control, as
noticeable in history, of a viable or emerging better-off peasantry (in Western
Europe and the kulaks in Russian history). But kulaks are rare. Even managers
and powerful people (WEGREN, 1993) seem to behave differently from peasants.
The next question is, "Do we know the aims of the peasant?" From the point of
view of a research agenda, the (positive and normative) questions are interlinked. Any analysis on the absolute and relative position of a peasant needs to
delineate the aims of peasants. As will be shown (below) and as mentioned
above, peasants under harsh conditions may have developed hierarchies of objectives that aim to achieve different things than a culturally-biased agricultural
economist of the West may think. We have to go into an analysis of aims envisaged in whole life-cycles and of daily targets on an operational basis.
When it comes to explaining the limited involvement of peasants in labour markets, which is a prerequisite for the success of large-scale and medium-sized
farm enterprises in transition countries, the question of aims, objectives and
goals re-emerges. A major hypothesis is that aims such as a wish for reciprocity
and a will for self-governance are not addressed by the current design of transition policies. With respect to creating institutions, the current top-down approach
runs into the dangers that the addressed population is not willing to involve
Post-soviet transition, rural development and the peasant problem
33
themselves in ‘unfair’ institutions and that it pursues a strategy of hiding against
authority (HUMPHREY, 2002). This is a well-known feature of peasants, who
don’t like collaborating with governments and markets; they would prefer to
stay on their own. The question is, then: What are policy recommendations?
In traditional peasant societies, a fine-tuned relationship exists between peasant
communities, their representatives, the landlord and government authorities; this
builds a governance structure which includes land rights and regulations
(BARDHAN, 1989). In this context, some agricultural economists may have to reappreciate that not only private rights (tenure) exist, but that, especially under
harsh conditions, transition may result in some elements of common property
and informal regulations.
The behaviour of peasants towards a common (meadow and field) is one of the
most interesting topics in land use. Actually, some current land use practices in
Russia (PAXSON, 2002) already show features of a common property management system. Because the authority of the kolkhoz has collapsed, people use
meadows for hay and plant potatoes on grounds for which no exclusion mechanism exists. A majority of the rural population seem to live in an archaic world;
but it can also be a self-regulated world.
Though the objective of a government should be to regulate land use in the interest of society, a disconnection to government authority seems to have evolved. The question at hand is how to make peasant contributions productive and
efficient in the case of disconnection? Apparently, a ‘true commercialisation of
agriculture’ (in the sense of Western European institutions that include rural
labour markets and wage labour employment) has become wishful thinking. The
basics of policies are missing. Still, the issue is, can some peasants be integrated
in labour exchange and serve emerging big estates? The answer may be different
rights regimes and reciprocity beyond markets.
3
RECIPROCITY, EXCHANGE, AND IDENTITY
To further understand the interests of peasants and even to give provide hints on
how to better design transition policies (re-opening options), in this section we
refer to a more general, current debate on the fundamentals of exchange systems,
common interests, and mutual behaviour between agents. The idea is to create
more mutually acceptable and beneficial exchange systems. Here, we refer to
KAHAN, who has recently established the logic of reciprocity (KAHAN, 2005). In
light of KAHAN’s arguments and findings, a peasant might be rational in behaving
as he does, i.e., not providing labour to large estates or not giving up farming on
small plots to sell or lease land, but rather staying. A more fundamental misunderstanding may impede real transition.
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KAHAN argues that an agent looks at reciprocity thusly: "Most persons think of
themselves and want to be understood by others as cooperative and trustworthy
and are thus perfectly willing to contribute their fair share to securing collective
goods. By the same token, however, most individuals hate being taken advantage of. Accordingly, if they perceive that most other individuals are shirking, they
hold back to avoid feeling exploited." (KAHAN, 2005, p. 341). Also, "Individuals
prefer to contribute if they believe others are inclined to contribute, but to freeride if they believe others are inclined to free-ride." (KAHAN, 2005, p. 342). Further, KAHAN (2005, p. 344) writes: "An example is the power of higher-thanaverage wage to elicit higher-than-average productivity in the workplace. Workers naturally suspect their firms of being unwilling to share a fair portion of the
surplus generated by the workers’ labour…. They respond… by voluntarily
working more productively," (if they are offered a higher wage than marginal
productivity) "…, which inclines the firm to maintain or even raise their wage.
The result is a self-sustaining form of reciprocal cooperation that obviates the
need for costly performance monitoring regimes."
In this theory, one’s contribution is to be understood as a result of the contribution
of the other (KAHAN, 2005, p. 345): "Moreover, some reciprocators are relatively
intolerant: They bolt as soon as they observe anyone else free riding." Notably,
there are many issues surrounding cooperation and reciprocity, even if equity, intention, and potential to retaliate are concerned (FALK and FISCHBACHER, 2005);
especially intention plays a significant role. Humans infer intentions from rules
and regulations, as well as pay-off matrices imposed on them, and they can shy
away to cooperate with agencies which they consider to have the wrong intentions (FALK and FISCHBACHER, 2005, p. 206); peasants are no different.
What can be learnt from the literature on reciprocity for our problem on explaining peasant behaviour in light of transition must be seen in the assertion of
others’ intention and strategy in the ‘game’. Especially rural people, after decades
of collectivisation, which for most of them meant working in fields that produced food for urban people, should have a fine sentiment on the intentions of
their counterparts. This not only refers to relationships between labourers, firm
management and public authority. Even more pronounced is applying this to
money lenders, banks, crediting units and machinery and tool provision companies if they want business.
In contrast to outsiders, as will be explained below, peasants prefer to work with
those of a similar origin and who share common beliefs and intentions. Sometimes this phenomenon is simply portrayed as "trust". But it is also more, and
one cannot simply say "trust" must be created. For instance, peasants may have
developed a strong work ethic and they eventually, in terms of reciprocity, expect
similar behaviour from their managing counterparts (PAXSON, 2002, p. 169). To
generalise on ethics: One expects similar things from others as others expect
Post-soviet transition, rural development and the peasant problem
35
from you, i.e., expecting the same that (s)he expects of you. To a certain extent,
this relates to equity as well. But it does not mean that pure wealth equity is a
criterion. Rather, it reflects that efforts are to be put into reciprocity.
The concept of reciprocity can be supplemented with the concept of identity,
closeness, and agency as has been applied in rural anthropology and manifested
in culture (RANGERS, 1987, cited in LEONARD and KANEFF, 2002). This means
that exchange systems in peasant economies are both a means and ends of informal social contracts of people who live under harsh natural and social conditions, and who have a history and group feeling. A consequence is that the trading of goods and the exchange of labour and land become limited to specific
groups, and parallel cultures develop.
4
OBSERVATIONS
Any assessment of observations regarding success, problems and deficits of
agrarian reforms in light of the above peasant question must certainly first tackle
the issue of peasants’ objectives. Unfortunately, objectives are mostly and
merely broadly-given and not clearly-defined. For instance, title, tenure or even
individualisation (MACEY, 2002) can be goals of their own, but they can also be
a means of increasing productivity (WEGREN et al., 2002) or alleviating poverty
(O’BRIEN et al., 1993). Hidden objectives also exist, such as keeping agricultural
production under the control of the administration (AMELINA, 2002). Many officially-declared objectives, legal frameworks and property rights assignments are
vague, top-down, or overruled by local reality: "A growing body of literature on
property rights in the context of agrarian change in post-socialist countries suggests that under conditions similar to those in rural Russia, ownership categories
neither help us to understand the local realities of property relations nor necessarily determine particular economic outcomes," (ALLINA-PISANO, 2002). Similar observations apply in countries that have distributed land and titles. In these
countries, land markets as institutions seem not to function (GOGODZE et al.,
2007), even though land is redistributed; objectives, as well as the legal framework of new agrarian institutions, are also unclear, with the consequence that
farms are trapped in small, unproductive units.
Due to slight differences in conditions between a voucher and a land privatisation system, we firstly distinguish cases. The aim here is to refer to a more
general identification of peasant strategies and to make strategies conditional.
The underlying theme has been set by lacking formal reciprocity and the prevalence of informal reciprocity in communities. So there may be similarities, and
the contrasting cases may help to identify them. The subject of similarities in
peasant behaviour must be seen in light of reciprocity, identity and limited willingness to expose one’s self to formal exchange systems in a peasant environment.
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4.1 Voucher privatisation and peasants
This is not the place to discuss the strengths and weaknesses of voucher privatisation, for instance in Russia, in detail. Basically, however, a voucher system means
that employees and kolkhoz members receive a title, equivalent in value, but not
identified in hectares. Indeed, no straight parcelling of land occurs. The impacts
can be inferred from other publications (LERMAN, 2004; WEGREN et al., 2002).
Rather, here we will provide an excerpt dealing with the question of how much
this system has stabilised or contributed to peasant behaviour. Let us take the
above description of peasantry and look into the contribution of Margaret PAXSON
(2002) because it seems to be a representative case study. The case study was
done by an anthropologist, but it also delivers much insight for an institutional
economist dealing with peasant behaviour. A first introductory aspect is that
money plays a different role in Russian peasant communities than suggested by
neoclassical economists. As has been explained by other narratives (PAXSON, 2002,
p. 160-166), money is considered necessary as a medium of exchange for commodities, especially for purchased goods like sugar, gas and electricity, etc..
However, money should not do more. There is a fear that money destroys traditions in group exchange, which is built on mutuality in labouring and gift circles.
Money and cash payments cannot serve as a simple incentive scheme in peasant
communities. Also, we have to note that rural economies, as have been described,
never experienced a great surplus (MACEY, 2002). Thus, money may be of secondary importance, and eventually peasants feel that surplus money has to be shared
through purchased goods used in celebration of community identity and for developing trust. A second interesting feature is the relationship to land (PAXSON,
2002, p. 149-155). It may be surprising that a scanty concept of private land ownership exists. There are apparently household plots that are farmed as gardens and
considered private property, i.e., exclusive and protected. But these serve as a
medium of basic life support, not as an asset. Indeed, these "gardens" have
always been the backbone for food security. Beyond that, land seems to be considered common property. Especially the long description in the chapter by
PAXSON on family and community work in open fields and meadows, partly
abandoned by the kolkhoz, is an illustrative description of peasant living and
conditions not far from a traditional "mir" and "obshchina" (village and collective
farming) system. The decision-making of labour has not been completely individualised; rather, villagers follow traditional rules and the authority of the village headman plays a major role. Though land acquisition for "private farming"
is prevalent, there are apparently many social, moral, and economic impediments to land acquisition. It is likely that these impediments are not fully understood. In this respect, we have to acknowledge that it is more evident that private
farmers are winners (WEGREN et al., 2002), and that they expand their land
holdings (PATSIORKOVSKY et al., 2005). A question is, are peasants only a phenomenon of transition and will they disappear in favour of private farmers?
Post-soviet transition, rural development and the peasant problem
37
From the analysis of PAXSON (2002), one gets the impression that this will not be
the case: Unless those humans currently living in the countryside are completely
exchanged for a new species of dwellers (changing mindset) a peasantry will
remain. But to what extent will this happen?
As a fourth aspect, the mindset of peasants, who were previously labourers on
kolkhozes, plays a major role. Some people would argue that from their mentality,
they can only be labourers on large-scale private farms. Indeed, most of the emerging private farmers are highly-trained specialists. So one could dismiss the
majority of peasants as being ignorant and say that transition can only result in
large estates with low-quality labour. But is this true? It implies that there is a
path dependency of inherited low-skilled labour, and managers are needed to
assign labourers with tasks. A crucial question is, again, can this only be pursued
on large estates? We have to acknowledge, from the peasant theory, that labour
supervision imposes transaction costs or limited efforts result (BARDHAN, 1989).
A fifth aspect of peasant behaviour is given by the question of whether a hierarchical or command and control system exists in communities. It appears that in
villages, collective decision-making exists, which guarantees some leadership
(PAXSON, 2002, p. 166-170). This is important to know and is somehow also
self-evident, especially when one looks at the historical background. In Russian
peasant communities prior to 1917, the landlord and state authorities worked
with indirect governance to extract rents and recruits. This brought about a
countervailing internal communal structure resulting in the local leadership protecting the community against extraordinary exploitation. It did not, however,
create an individual will and feeling of responsibility (PAXSON, 2002, p. 171). In
contrast O’BRIEN et al., (2004, p. 485) still sees the existence of an ‘entrepreneurship’.
How to explain this contradiction? Personal initiative is very much related to
authority. A common statement is that the communist period (especially the time
under Stalin) created an extreme reluctance to interfere with authorities. Indeed,
breaking the peasants’ will was even policy. Hence, a sixth aspect is the mistrust
of power (PAXSON, 2002, p. 169). This is encapsulated by a quote given by
Smith in 1990: "Another deterrent to radical change in Soviet agriculture is the
brooding fear among peasants – a fear that the parasitic apparatus of officials
and Party workers shrewdly manipulates – that free-market economies will
cause thousands of state and collective farms to fail, throwing the mass of peasants into chaos and leaving them even in worse poverty than they are today
(SMITH, 1990, p. 215, cited in O’BRIEN et al., 1993). So there is suspicion on the
part of peasants.
Besides findings in the village, we have to appreciate the impact from the remaining large-scale farm operations and encounter its dynamics, apparently as
downscaling occurs in the process of privatisation. AMELIA (2002) and
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ALLINA-PISANO (2002) provide case studies in this area. Again, there are many
narratives and we can only highlight some aspects that contribute to reciprocity
and intention, the key issues in this paper. One main problem for new enterprises
is that they depend on local government positions towards their budget (soft
budgets) and the labourers know that. Soft budget constraints are typical, but: "If
the government changes, newly-elected administrators may decide not to invest
in preserving the redistribution scheme and instead let it collapse". Also, "…
money-making opportunities make the government periodically harden the
budget constraint," (AMELINA, 2002, p. 269). The question is, why do authorities
act or not act, and what can be expected? As a labourer, one has to know the
relationship of the manager to the authorities. Securing food provision is surely
one aspect; the other is taxing and reciprocity in oblast power struggles.
Surely there are managerial adaptations, but these can be harmful to both labourers and managers. "In Engels raion enterprises, the managers admitted that
they had too many workers, … However, they could not foresee firings, because
theft by fired workers would be even more difficult to control …" and "The
boundaries between the enterprise and the villages…continue to be ill-defined"
(AMELINA, 2002, p. 282). Regarding the social relationships in a reorganising
collective, ALLINA-PISANO (2002, p. 313) writes: "Both village intelligentsia
and…labourers concluded that the reorganisation process itself did not provide
for fundamental, equalising change it was intended to produce." Moreover, there
is the inherited enterprise and household tie: "In the years following reorganisation, access to garden inputs and trading relationships grew…important…"
(ALLINA-PISANO, 2002, p. 315), and "Both individual households and enterprises
produce not what they might most efficiently achieve in an ideal situation, but
what they need to survive in a climate of permanent scarcity and uncertainty
…members … remain tightly bound to the slowly disintegrating carcass of
Russia’s agroindustiral complex" (ALLINA-PISANO, 2002, p. 318). To interpret
this, there is a mentality or strategy to use resources, but reciprocity is differently reckoned.
4.2 Land and title distribution, parcelling and fragmentation
We briefly switch to the other type of privatisation, namely, land distribution by
parcelling and titles; this also can be taken to mean fragmentation. Below, we
touch on the case of Georgia. Again, objectives of reform matter, and our focus
is on the peculiarities of peasant behaviour. We must admit that parcelling is a
complex story that cannot be fully appreciated by this short review. Firstly, it is
noticeable that rural people have become poorer, and self-help systems have
been established (DERSHEM and GZIRISHVILIE, 1998). For the objectives and process of reform, it was expected that this privatisation would quickly result in
productivity and income growth; however, that did not happen. As a secondary
problem, the question of functioning land markets for peasants emerged
Post-soviet transition, rural development and the peasant problem
39
(LERMAN, 2004). GOGODZE et al., (2007, p. 12) state in their research on Georgia’s
rural reform in a chapter on policy implication that, "The progress of land reform
in Georgia was gradual and has not reached full coverage, mainly due to institutional complexity." Reasons given for this rank from problems in registration
(GOGODZE et al., 2007, p. 13) to credit availability (GOGODZE et al., 2007, p. 14).
Peasants, being less productive and efficient on their land, should eventually
lease to better farmers. However, they are not willing to participate in labour
markets. "First, increasing landholdings require …labour, and above a certain
threshold, family labour will not be sufficient and additional workers will have
to be hired. Second, if some farmers are to give up…rural labour market will be
the first choice. Without a well-functioning rural labour market, the response of
farm households to the land reform will be limited," (GOGODZE et al., 2007, p. 14).
In a second paper on Georgia, the same study group emphasises the issue of required farm equipment and increased sales as part of a commercialisation strategy
(KAN et al., 2006). They developed a farm-household model adapted to local
conditions and investigated the relationship between output market participation,
farm equipment and income. The results are not surprising; increased sales increase the propensity to buy inputs and foster commercialisation (KAN et al., 2006,
p. 4). In contrast, empirical evidence is that 28% of the farms investigated in the
survey did not participate in markets at all (KAN et al., 2006, p. 4), but are instead classified as subsistence farmers. A first explanation is that subsistence
farmers do not participate in labour and land markets due to a lack of trust
(KAN et al., 2006, p. 5).
At this point it must be mentioned that many subsistence farmers (household gardeners) in Russia do just the opposite and become commercial, i.e., lease land and
engage in output sales. This happens even though no formal land distribution program, such as the one in Georgia, has been introduced (O’BRIEN et al., 2004).
Some peasants who have expanded their household plots are capable of acquiring physical capital (machinery), and can be considered winners; that is, winners
for Russian conditions. But the question remains, why are such a large group of
Georgian farmers not willing to participate in the labour and food markets?
As a summary of the observations, one can conclude that peasants behave differently than a pure economic-rationality would imply, even in transition. In
transition, the abovementioned reasons for diverging from a simple economic
theory of profit and utility maximisation becomes more pronounced, and a retreat
to peasant behaviour becomes the strategy of individual rationality. Especially
risk and uncertainty, not only with respect to natural conditions, but also with
respect to authority and mutuality in transactions (lack of reciprocity), are obstacles for more fruitful involvement by peasants in exchange systems.
Ernst-August Nuppenau
40
5
CONCLUSIONS AND DISCUSSIONS ON ALTERNATIVES IN
TRANSITION
This brings the discussion back to the objectives of transition, its peculiarities,
the aim of peasants, their behaviour, and institutional change. A first conclusion
would be that peasant behaviour is an obstacle to farm development, at least, as
envisaged mostly by governments, which includes modernisation and rapid closure of the gap with Western farming. But managing transition as pure modernisation, as it is also seen by some international consultancies, is far from the
"best" strategy in the eyes of peasants. Further research is needed to address the
identified peasant behaviour characteristics in transition. As opposed to the simple
assigning of property rights, recommendations for more dynamic concepts of
institutional and evolutionary processes have to be found. These concepts should
not be purely planning concepts. Rather, they should include feedback and participation. As has been highlighted by SALETH, DINAR (2004), governing institutional amendments has to consider several layers and participation.
Regarding the request for participation of local communities, the emphasis
should be on community development, because not only individually-addressed
measures are needed in the reform. Governments have to risk a partial loss of
power to hand over power to communities and the local informal governance
structure of peasants. A second, better, conclusion is that power has to be redistributed. Although this statement relates to the objectives of reform and willingness to look for less "planned" reform paths, it does have a general feature. Its
findings are that most approaches are still very much top-down, and peasants are
really not willing to involve themselves. For some people it may, however, be a
question of whether they should be involved at all or only left to protest. Peasants no doubt create political problems such as uprises, self-empowerment and
uncontrollable games; but the alternative is that they shy away, and development
stops.
For independent researchers, especially for those who read peasant literature and
keep themselves independent from the delivered success stories, there is a feeling
that controlling peasants is indeed a hidden objective. For other researchers who
are strongly involved in power struggles, the opposite maybe true. We must
clarify the need for control. With unclear and under-determined objectives, even
in the presence of control and rules of conduct, it is evident that situations may
evolve which can be considered as being in a vacuum of authority. This is already envisaged as resulting in a large-scale farming system (combating theft:
KOESTER, 2005) which promotes newly-emerging landowners, advisers and authorities on the one side, and leaves out the peasants, who will be trapped in subsistence, on the other side. This is already happening (ALLINA-PISANO, 2004)
and it favours members of the rural elite.
Post-soviet transition, rural development and the peasant problem
41
In contrast, the class of potentially-emerging medium-scale farmers (from
peasants and subsistence farming) will have no chance to develop. As has been
said, it depends on the objectives whether more general aims in agricultural policy such as growth, productivity increases, employment aspects, etc., are a basis
of reform; or else peasant farming can become conducive. If this is not the case,
there will, perhaps, remain a sentiment of forgiven chances. Notably, however,
forgiven chances cannot design policy. But through will and support, upgrading
peasants to modernised peasants (or kulaks) or re-opening an evolutionary process of peasant integration is possible. Notice that historical examples do exist
(WEBER, 1979) and to look at their make-up, a proactive venture is needed.
A pro-active policy is not a harmonic thing. Crucial elements of a proactive policy
will be a (natural) selection of those peasants who have the potential to improve.
But peasant behaviour is a mixture of relational adjustments to a harsh natural
and social environment, and we have to appreciate that neither a voucher nor a
simple land distribution policy will initiate the comfortable process of peasants
engaging in modernisation strategies. Thus, a question: Will the process of modernisation stop with household labour as a constraint, or will communities offer
a platform for hired labour to increase operation and productivity?
Access to technology is an important facet of development. As subsistence
farming is known to be labour-intensive and medium-scale technologies are
lacking, it is of major importance to offer technologies that suit farmers. It has
been observed that parts of machineries and tools can be produced locally and
improved. This especially applies to simple technologies that may be, from a
Western point-of-view, outdated, but are still effective for peasants: A machine
supplied with horsepower can offer opportunities to specialise. As there are
records of community ownership of such machinery, a worthwhile question is,
How to expand?
On a social science level, one can think communities should become self-organising with a flat hierarchy. Recent research on nature-conserving communities (MCCARTHY et al., 2001) gives hints on how to start processes of mutual
responsibility that go beyond family and kinship. Cooperation is also not something based on an absolutely equal society. A major impetus may come from the
stratification of "peasants". In this respect, wealth accumulation plays a role. The
task will be to foster such local stratification and create a class of wealthier
peasants who can escape risk-aversion. This is not the same thing as market integration; it should not be seen as imposed, top-down market development. Cooperation and reciprocity are key issues, but cannot be imposed.
First of all, a differentiated analysis on the degree of peasant resistance to cooperation is needed; that is, cooperation which is not harmful to them. In the given
context of bad experiences both before and during transition, one could simply say
a "pro-peasant" policy is necessary, which means abolishing any discriminating
Ernst-August Nuppenau
42
policies and attempting to correct "wrong" cooperation, which is considered
exploitative. But more elaborate policies are also needed to regain trust and reciprocity. Apparently, one could put a pro-peasant policy into a slogan. But before we do so, an emphasis should be put on the aspect of reciprocity which lies
at the core. Reciprocity means that those who want peasants to become more
exposed to exchange systems must give up a minimum perspective on investing,
if negatively formulated. Or, if positively formulated, they should engage in activities that are in the indirect interest of peasants. These activities can be:
-
-
-
-
Providing service for public goods in rural areas such as health, infrastructure,
schools etc., though the services must be linked to community performance.
Taking the duality of peasant production and large farms into account, both
traders and local landowners should become engaged. Eventually, portions of
gains in trade should be used exclusively to refinance services for peasants.
Since land expansion is a major bottleneck both in pure-household-subsidiary
and full-land-tenure systems, schemes are needed that give investing farmers
scope, but also that allow the retired to secure jobs. In the first case, entitlements to more land could be built on labour and contracts with larger farms
that grant peasants ownership after a certain number of years of labour service:
Thus, land for labour.
Transparency is needed to reduce suspicion. A crucial element may be a
locally-negotiable tax system. Also, authorities have to understand that taxing
peasants should be moderate, transparent and include exemptions for emerging
farmers: Thus, suitable taxes.
Differentiation and stratification should be encouraged by wealth accumulation, which is conducive to peasant beliefs: Thus, animal accumulation.
Exhibition and extension of technologies and skill acquisition of (non-modernised) farm equipment appropriate for peasants can be a core element of a
new, yet-to-be-established extension system: Thus, local production of equipment.
A proactive peasant policy is not a self-run policy; it needs, at its core, motivated
policy-makers seeing reciprocity, identity and community development.
6
SUMMARY
This paper raised the topic of peasant behaviour in transition. It firstly provided
a brief introduction into elements of peasant behaviour which are typical and
could potentially shape the behaviour of the rural population in transition.
Secondly, aspects of reciprocity and identification as a basis of cooperation and
a need for accepted exchange systems were discussed from a theoretical point of
view. These two aspects were supplemented with observations made in the
literature on institutional deficits in transition. Two cases were presented: a) the
Post-soviet transition, rural development and the peasant problem
43
Russian voucher privatisation of land policy, and b) the land distribution, parcelling and title policy of Georgia. Based on the literature review, major findings
were that peasants do not respond as expected and maybe they are trapped in an
inferior rationality, from a societal point of view, but a superior rationality from
an individual and a community point of view. Emphasis was given to community-wise addressing of land and peasant behaviour issues.
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RURAL LAND AND LABOUR MARKETS
Sustainable rural development: What is the role of the agri-food sector?
MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central and Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 49-66.
ECONOMIC IMPACTS OF LAND MARKET DEVELOPMENT:
EVIDENCE FROM MOLDOVA
DRAGOŞ CIMPOIEŞ∗
ABSTRACT
Moldova has experienced striking changes in land tenure and land ownership
since its independence. The land reform, which was practically completed in
2000, created over 1 million landowners among the rural population. The creation of independent family farms was one of the primary goals of the land reform.
More than 280,000 peasant farms have been created, averaging 1.86 hectares in
size. The small size of the peasant farms, whose holdings are furthermore split
into 3-4 parcels, raises considerable concerns about their long-term viability and
has led to an intense public debate regarding the impacts of fragmentation. In
this context, land consolidation has been proclaimed as one of the major directions of the agricultural policy. Among the multiple methods of consolidation,
an important place belongs to the development of land market. In this paper, the
author considers the impacts of land reform on privatization and ownership
structure of agricultural land and analyzes the development of land market transactions. The analysis is based on official statistical sources, data and results of
several questionnaire-based surveys. The main idea of the paper – land market
register a steady development, plays an important role in reducing land fragmentation and there is no necessity in other mechanisms for land consolidation.
Keywords: Buy-and-sell, land lease, fragmentation, consolidation, farm size,
Moldova.
1
LAND REFORM OUTCOMES
Privatization of agricultural land and assets followed by restructuring of collective and state farms were among the primary goals of Moldova’s transition to a
market-oriented economy in the post-Soviet space (LERMAN et al., 1998).
The first attempts to reform the agrarian sector fall on 1992. This year can be
considered as "the beginning of all transformations" as the first post-Soviet Land
Code has been adopted, leading to effective privatization of land through the
∗
Department of Management, The State Agricultural University of Moldova, Chişinău,
Republic of Moldova. Email: [email protected]
50
Dragoş Cimpoieş
distribution of landownership certificates to more than one million individuals –
one third of Moldova’s population.
Despite an early start, the process of land reform in Moldova was not visible until
1996. Authorities had no sufficient political will for restructuring of old legal
entities and privatization of their land to rural residents, being a decisive factor
determining managers of the former collective farms be unwilling the forthcoming
changes. Therefore, during this period land reform in Moldova saw only minimum changes, agriculture not having got rid of the Soviet heritage.
In March 1998, the National Land Program (NLP) was initiated as a transition
from the pilot project to the privatisation of all existent collective farms and led
to a sweeping conversion of the paper certificates to physical plots, averaging
less than 1.5 hectares. The share of agricultural land in state ownership dropped
from 100% in 1990 to less than one-fourth in 2005. As of the end of 2005, over
670,000 holders of land shares, or about two-thirds of all beneficiaries, had
withdrawn nearly 900,000 hectares of agricultural land from large-scale collectives.
Table 1:
Progress with distribution of physical land to rural population
(cumulative data 1999-2005)
Number of people allocated physical plots against
land shares, ‘000
Total land allocated against land shares, ‘000 ha
Average allocated plot, ha
1998
2000
2002
2004
2005
241.1
502.7
617.0
655.8
677.3
317.5
1.32
701.8
1.40
836.6
1.36
862.6
1.32
881.7
1.30
Source: NATIONAL BUREAU OF STATISTICS.
Each landowner who decided to exercise his rights under the NLP received on
average 1.3-1.4 hectares of agricultural land. Combined with the original household plot of 0.3-0.4 hectares, the NLP distribution produced small holdings of
less than 2 hectares.
The fragmentation was further exacerbated by the equity-driven design of the
land privatization process in Moldova. To ensure that all peasants had equal
access to land of different types, each land share was divided into three separate
parts: A share of arable land, a share of orchards, and a share of vineyards. In
practice, however, many landowners received more than three parcels against
their land shares. In the 2003 World Bank survey of household plots, 53% of
respondents had more than three parcels. In the 2003 PFAP survey of peasant
farms, 55% reported 3-6 parcels and 19% reported more than 6 parcels
(MURAVSCHI and BUCATCA, 2005). The inherently small holdings are further
fragmented into still smaller parcels in scattered locations. Many parcels are located 3-5 or even kilometres away from the village, implying high production
costs. Land fragmentation in Moldova thus has two characteristics: Exceedingly
Economic impacts of land market development: Evidence from Moldova
51
small size of family farms and fragmentation of land ownership into multiple
parcels.
Less than half the landowners who received physical plots through the NLP
decided to farm their land independently (DSS, 2004a), creating the new category
of independent peasant farmers that did not exist prior to reform.1 The rest (57%)
leased their land to operators, including so-called "leaders" or "managers", i.e.,
enterprising individuals who founded new corporate farms by consolidating the
dispersed small plots of passive landowners. At present, these "leaders" manage
about 1,500 farms – limited liability companies, joint stock companies, agricultural production cooperatives – with an average size of 500-800 hectares depending on organizational form. The new corporate farms are substantially smaller
than the traditional collective and state farms, which averaged 2,000-3,000 hectares
in 1990.
Table 2:
Number and average size of corporate farms 1990-2004
1990
2004
Number of
units
Average size,
ha
Number of
units
Average
size, ha
State farms
432
1,600
72
2,200
Collectives
540
2,800
4
3,400
Interfarm cooperatives
71
1,500
4
50
Joint stock companies
112
440
Agricultural cooperatives
140
820
1,263
510
1,595
x
Traditional forms:
New organizational
forms:
Limited liability
companies
Total
1,043
x
Source: THE STATE CADASTRE AGENCY.
1
Unfortunately, official sources give widely conflicting information on the number of peasant
farms and the area of agricultural land they control. In DSS (2004b), one table (p. 120) gives
526,000 hectares in 283,200 registered peasant farms (implying an average of 1.86 hectares
per farm), while Cadastral data summarized in Table 2 correspond to 700,000 hectares in
558,000 peasant farms, which implies an average farm size of 1.3 hectares.
52
Dragoş Cimpoieş
As a result of all transformations occurred in agriculture, one positive shift
should be noticed: The share of land cultivated by large-scale corporate farms
declined from 90% in 1990 to 45% in 2004.
The distribution of land to the rural population led to dramatic changes in the
structure of land use by farms of various organizational forms (Table 2). Particularly notable is the shrinking share of former state and collective farms and a
corresponding increase in land used by the individual sector. Thus, in 1990,
about 30% of the 2.5 million hectares of agricultural land in Moldova was
managed by state farms and 60% by other corporate forms (collective farms and
interfarm cooperatives). The individual sector (household plots at that time) cultivated less than 9%. As of 2004, the individual sector (which now consists
of household plots and peasant farms) controls 40% of the agricultural land.
Approximately the same land area is operated by large-scale corporate farms,
mostly new organizational forms with private ownership of land and assets.
These new corporate farms – agricultural production cooperatives, joint stock
companies, limited liability companies – are basically corporate shareholder
structures with joint cultivation of land. The traditional collective farms practically disappeared during the last decade, as many of them have been privatized
or liquidated, while others registered in new legal forms. State farms still persist,
but they operate in highly specialized areas that can be legitimately regarded as a
public good (seed selection, livestock selection, experimental stations, agricultural education and research).
While corporate farms average 500-800 hectares, the individual farms (household plots and peasant farms) are much smaller. Thus, the average peasant farm
has 1.8 hectares and only 277 peasant farms (out of some 300,000 in total) are
larger than 50 hectares, compared to 342 similar farms in 2003 (DSS, 2004b).
Half the agricultural land in Moldova (excluding Transnistria) is in units smaller
than 10 hectares (WORLD BANK, 2005).
This category comprises over 1 million household plots and small peasant farms
with average holdings of 0.8 hectares. For comparison, the average farm size in
Greece is 4.4 hectares, in Italy 6.1 hectares, and in Portugal 9.3 hectares (in all
other EU-15 countries the average farm size is between 17 and 70 hectares).
These figures – the small average size and the huge number of small farming
units in a population of less than 4 million – clearly demonstrate the extent of
fragmentation produced by land reform processes in Moldova.
2
RATIONALE FOR LAND MARKET DEVELOPMENT
There is a voluminous literature on the farm size effect on efficiency and productivity both in transition countries. Thus, at the outset of transition some
argued the necessity of preserving large farm structures and following efforts to
hamper farm fragmentation on the basis that smaller farms are less efficient
Economic impacts of land market development: Evidence from Moldova
53
(KANCHEV and DOICHINOVA, 2000). In contrast, others argued that large farms in
Eastern Europe suffered from diseconomies of size so that land reform strategies
must include proposals to reduce the mean size of farms (KOESTER and STRIEWE,
1999). So far, the results are indecisive: There is no conclusive evidence that
large farms are more productive and more efficient than small farms or vice versa –
large farms are not inferior to small farms.
What are the criteria by which we can judge about the farm size? There has been
no generally accepted measure on firm size in the economic literature to guide
the choice in agricultural studies. Various measures of outputs, inputs and of incomes have been employed. However, the most commonly employed measure is
the total area of land managed by farm (LUND, 1983).
What do we mean by "large or small farms"? What is the optimum average
farm size for a given country? The optimality is largely an empirical issue
(SWINNEN, 2006). Several studies find that there is an inverse U-function between
size and efficiency (FEDER, 1985). Efficiency grows with size for the smallest
farms, but beyond a certain size, typically coinciding with larger family farms,
there is a declining relation between size and efficiency.
The most recent survey (2005, WB Survey) determined that size strongly affects
the standard of living of rural families, where a comfortable standard of living is
associated with a much larger farm size than lower standards of living.
Figure 1:
Probability of achieving a given standard of living as a
function of farm size for peasant farmers
1
probability
0.8
0.6
Poverty
Subsistence
Comfortable
0.4
0.2
0
0
10
20
30
40
50
land use, ha
Note:
Definition of standard of living levels: "Poverty" – family income not sufficient to
buy food; "subsistence" – family income just sufficient to buy food and daily necessities; "comfortable" – family income sufficient to buy food, daily necessities, and
durables.
Source: 2005 WB survey.
Peasant farmers reporting a comfortable standard of living in the 2005 WB survey
have 11 hectares on average, compared with less than 5 hectares for farms in the
Dragoş Cimpoieş
54
two lower categories – poverty, when family income is not sufficient to buy food,
and subsistence, when family income is sufficient to buy food and daily necessities. The standard of living of peasant farmers is thus an increasing function of
farm size, as is commonly observed in farm surveys in CIS and other transition
countries.
The probability of being in the highest standard of living (gray curve) increases
with farm size, while the probability of being on the lowest "poverty" level,
when family income is not sufficient to buy food (thick black curve), sharply
decreases with farm size.2 These results provide the ultimate support for land
consolidation policies and hence the need to encourage land market development.
Partial productivity measures versus number of parcels for
household plots in Moldova
lei/ha
lei/w ork day
7
1000
900
6
Farm income per ha
800
5
700
600
4
500
3
400
300
2
200
1
100
0
Farm income per work day
Figure 2:
0
1
2
3
4
5
6
7
8
9
10
Number of parcels
Farm income per ha
Farm income per work day
Source: 2003 WB survey of household plots.
Common wisdom argues that consolidation of small disjointed parcels into contiguous holdings is preferred by farmers and landowners. This kind of consolidation should reduce production costs and improve net income for a farm of given
size. Land consolidation that produces larger farms (keeping the number of parcels
fixed) is also believed to be beneficial, as it should reduce the ratio of fixed costs
per unit of land, allow more efficient use of technology, and ultimately increase
productivity and efficiency. These theoretical arguments, however, are difficult
to substantiate empirically and world experience does not unanimously support
either position.
2
The probabilities of achieving a given standard of living were obtained in a multinomial
logistic regression with the three-level standard of living as the discrete dependent variable
and farm size as the continuous covariate.
Economic impacts of land market development: Evidence from Moldova
55
Some evidence that supports the advisability of reducing the number of parcels
through land consolidation is provided by a 2003 World Bank survey of household plot operators in Moldova. This survey shows a clear negative relationship
between productivity and the number of parcels held by the operator.
The results presented in Figure 2 clearly show that both the productivity of land
(farm income per hectare) and the productivity of labor (farm income per work
day) decrease as fragmentation (i.e., the number of parcels) increases. The negative relationship between productivity and fragmentation is an ultimate argument
for the necessity of individual land consolidation, based on land market development.
3
EMERGENCE OF LAND MARKET IN MOLDOVA
In market economies, farms are usually privately run, and private ownership of
land and other farm assets is dominant in the agricultural sector. But owner and
farmer are not necessarily the same person; in fact, farmers may lease or rent
both land and other farm assets from natural and legal entities, or even from
public institutions. With the lease and sale of the land, historically established
farm boundaries may change, and farms can be expanded to reach their optimum
sizes (SCHULZE, 2000).
As a result of land reform held in Moldova, almost one million hectares of agricultural land has been distributed to over 600,000 people. Among this multitude
of smallholders, many of them remain inactive for different reasons (age, health,
etc.). Mass distribution of small plots to individuals requires development of
land market mechanisms to enable land to flow from less efficient to more efficient users, allowing farmers to adjust the size of their holdings. Land market is
the only effective way to satisfy the new demand for land from the direction of
those who desire to extend the size of their farms.
Land market is emerging in Moldova. The moratorium on buying and selling of
land and the imposition of high normative prices for land transactions and transfer
taxes was a major obstacle to the development of a viable land market in Moldova.
The "Law on Normative Price of Land and Procedure for Sale and Purchase of
Land", adopted in 1997 removed basic restrictions to the development of functioning land markets and this year can be considered by right as year of birth of land
market in Moldova.
The number of registered transactions is a general indicator of the land market
development.
Dragoş Cimpoieş
56
Figure 3:
160
Number and structure of transactions in agricultural land in
the Republic of Moldova
Thousands
100%
140
80%
120
100
Lease
Inherit+Gift
Sale
80
60
60%
Lease
Inherit+Gift
Sale
40%
40
20%
20
0
1999
2000
2001
2002
2003
2004
2005
0%
2000
2001
2002
2003
2004
2005
Note: Data for 2005 are extrapolated to a full year.
Source: First Cadastre Project.
Thus, transactions in agricultural land increased from virtually zero in 1999 to
about 150,000 in 2005. During the 6-year period 2000-2005, the cumulative number of transactions exceeds 550,000. Of the total number of recorded transactions, 51% are transactions involving inheritance and gifts, 36% involve buying
and selling of land, and the remaining 13% are leasing transactions.
It is necessary to note that the reported share of leasing transactions is much
smaller than in reality. According to recent studies, land lease is the most popular kind of land transactions, as it has important advantages with buying-selling
(GUDYM et al., 2003). According to the Cadastre Agency Data, about 30% of
total agricultural land is leased only by limited liability companies (the most
numerous corporate legal form) and peasant farms. If to take into account the
fact that many peasant farms lease land from their relatives, without concluding
an official land-lease agreement, this figure might be substantially higher.
This apparent discrepancy arises because only lease contracts for a term of 3 years
or longer are subject to registration in the regional cadastre office. Leases for
less than 3 years are registered at the village primaria (mayoralty), and no central record of these contracts exists. Local experts estimate that at least 70% of all
lease contracts in Moldova are for a term shorter than 3 years and are therefore
not reflected in State Cadastre records. A more detailed analysis of the place of
land lease in Moldavian agriculture will be discussed in the next section.
The increasing number of transactions led to a significant increase of the transacted area (Table 3). Over 300 thousands hectares of agricultural land changed
ownership during the investigated period. Taking into account that the overall
area of agricultural land amount about 2 million hectares, we conclude that during
such short period of time, about 19% of privately owned agricultural land
changed ownership.
Economic impacts of land market development: Evidence from Moldova
Table 3:
1999
2000
2001
2002
2003
2004
2005
19992005
57
Transacted area of agricultural land (excluding leasing)
Transacted area, ha
Percent of total
Other owOther
Sale
nership
Total
Sale ownership
transfers
transfers
74
28
102
73
27
1879
1364
3243
58
42
9,238
14,201
23,439
39
61
17,599
28,825
46,424
38
62
36,248
47,036
83,284
44
56
53,818
40,421
94,239
57
43
32,363
38,952
71,215
45
55
Average transaction, ha
Other
Sale ownership Total
transfers
0.68
0.48
0.57
0.61
0.61
0.61
0.62
0.74
0.65
0.63
0.59
0.61
0.66
0.68
0.67
1.15
0.58
0.73
1.62
0.89
1.06
151,121
0.88
170,825
321,946
47
53
0.68
0.72
Note: Data for 2005 are extrapolated to a full year.
Source: First Cadastre Project.
According to 2004 IAMO survey and 2006 survey of farm managers, conducted
by author, the development of buy-and-sell transactions dramatically changed
during a very short period of time. Farm managers began to understand the importance of having land in private property. If few years ago, most of them
owned several hectares of land, now the picture is changing dramatically.
Table 4:
2003
2006
Buying of land by farms of different legal forms
Average area bought per farm,
ha
35.4
160.6
Average price /
ha, lei*
4369
2605
Note: 1 Euro=14.5 MDL in 2003 and 16.5 MDL in 2006.
Source: Author.
During a relative short period of time they bought over one hundred hectares in
average per farm. Thus, the share of own land in used land increased substantially. According to the last survey, it already reaches about 17%. It is necessary
to note that CISR survey conducted in 2003 underlines that 98% of cultivated
land by farms is leased land (GUDYM et al., 2003).
One of the reasons may be that land became cheaper than even before. If in 2003
one hectare of agricultural land was estimated at about 300 Euros, now it
reaches only half (160 Euros).
Cadastre records show that some 150,000 hectares of agricultural land were sold
and bought in 160,000 transactions between 1999 and 2005 (see table 3). The
average land sale transaction was thus less than 1 hectare. The average transaction size remained fairly constant at 0.6-0.7 hectares between 1999-2003, and
then increased significantly to more than 1 hectare in 2004-2005. This is the
Dragoş Cimpoieş
58
average size of a parcel recorded as a cadastral object in the system, reflecting
the original fragmentation of the land shares in the process of privatization. The
increase in average transaction size between 1999-2003 and 2004-2005 may in
fact reflect certain parcel consolidation trends in Moldova.
Despite these positive developments, buy-and-sell transactions constitute only
one-third of all officially recorded land transactions in Moldova, and their role
in land consolidation so far seems to be marginal compared to the role of the
widespread leasing arrangements.
4
LAND LEASE DEVELOPMENT IN MOLDOVAN AGRICULTURE
In Moldova, lease relations in agriculture most probably arose because of the
small plots of agricultural land and of the incapacity of an important part of the
rural population to cultivate land individually (MURAVSCHI, 2002).
At the moment, the main approach to individual land consolidation is leasing.
According to the Center for Strategic Studies and Reforms (CISR), 50.6% of
agricultural land owned by individuals is leased out. Therefore, the problem of
the consolidation of land shares received by peasants as a result of the land reform is partly solved through leasing (GUDYM et al., 2003).
Lessees are represented by four legal entities: Joint stock companies, agricultural
cooperatives, limited liability companies and peasant farms. The area leased by
these enterprises constitutes over 94% of the total leased agricultural land. The
major lessees are limited liability companies, as 72% of their land is leased.
A general tendency for the above-mentioned farms was a transition to larger area
farming. Nevertheless, depending on the legal forms of enterprises, a specific
character is outlined.
Table 5:
Up to 50 ha
50 - 100 ha
100 - 500 ha
500 - 1000 ha
Over 1000 ha
Total
Structure of agricultural land depending on the legal forms of
enterprises, %
Joint stock
companies
0.0
0.0
33.3
33.3
33.4
100
Agricultural
cooperatives
0.0
7.2
21.4
14.3
57.1
100
Limited liability
companies
2.5
2.0
36.0
26.0
33.5
100
Source: Own calculations based on the CISR Survey, 2003.
Peasant farms
22.4
8.2
49.0
14.3
6.1
100
Economic impacts of land market development: Evidence from Moldova
59
Thus, joint stock companies and agricultural cooperatives operate only on large
areas, over 100 ha. Limited liability companies and peasant farms, based on
leases, cultivate both small and large areas. But even in this case, over 2/3 of the
lessees prefer to cultivate plots larger than 100 ha3.
Of particular interest for investigation is the distribution of leased areas according
to their size. Lease depends, to a great extent, on the plot size. Thus, plots
smaller than 1 ha are farmed by their owners independently. Large plots require
machinery for cultivation. Therefore, lack of machinery forces the owners of
such plots to lease them out.
Figure 4:
Structure of leased-out areas based on their size
8%
4%
3%
9%
76%
up to 1 ha
1-3 ha
3-4 ha
4-7 ha
over 7 ha
Source: CISR Survey, 2003.
Why do managers lease in land? In the 2004 IAMO survey of 104 corporate and
peasant farms in Moldova, more than 40% of respondents expressed the view that
they found it more profitable and more efficient to cultivate a larger plot. Nearly
30% indicated that they preferred to lease plots adjacent to the existing farm.
These two factors explain the strategy of leasing in additional land from individual
landowners to augment the farm. Farm managers seem to realize that land consolidation allows them to use land more efficiently (CIMPOIEŞ and SCHULZE,
2006).
What reasons do the households give for leasing out land? The main reason is
insufficiency of resources. In the 2003 CISR survey, 65% of lessors identify
lack of machinery and purchased inputs as the main cause for leasing out land.
Age is also one of the important reasons for leasing out one’s land – this was
indicated by every fourth landowner (GUDYM et al., 2003). In the 2005 WB survey, 40% of lessors put the blame on insufficient labor, while difficulties with
3
As to peasant farms, the results of the survey rise a big question on their reliability. According to official
statistics there are over 300.000 peasant farms and only 277 of them are larger than 50 hectares. However,
there is no information on how much land they operate.
Dragoş Cimpoieş
60
access to purchased inputs and credit (or money in general) rank next. In aggregate, reasons associated with the functioning of normal markets are cited by
78% of the households in the 2005 WB survey as responsible for their decision
to lease out land.
Table 6:
Reasons to lease out land and relationship with augmentation
factor for households
Percent of
lessors
Plot too far from house
Plot too small
Land of poor quality
Farming not profitable
Inputs not available
No money
Insufficient labor
No marketing channels
Obliged to lease as
member/shareholder
1
3
0
11
19
15
40
3
7
Grouped
reasons
Percent of Desired augmenlessors
tation, times
land used
Physical
15
1.0
Market
78
4.7
Institutional
7
50.0
Source: 2005 WB survey.
It may be argued that these individuals would tend to farm the land on their own
if the missing or distorted markets were corrected. This conjecture is supported
by the observation that respondents who attribute leasing to market imperfections express a desire to increase their plot size by a substantially greater factor
than respondents who lease out because of physical deficiencies of their land.
Health and age are important factors in the decision to lease out for pensioners
and elderly people. In the 2003 CISR survey, 80% of the pensioners and 70% of
landowners older than 60 cited health and age as main reasons for leasing out
their land. In the 2003 PFAP survey, the highest percentage of landowners who
intended to lease out their land (36%) were 60 or older (MURAVSCHI and BUCATCA,
2005).
The creation of new corporate farms by "leaders" is the most obvious manifestation
of land consolidation through leasing. In this way, farms with 500-1,000 hectares
of land are created by enterprising individuals who lease the dispersed and
fragmented plots of hundreds and even thousands of small inactive landowners.
Yet the results of various surveys in Moldova confirm that land leasing also
promotes consolidation in the individual sector, where the landowner is an active
farmer with an initial endowment of 2-3 hectares.
Survey results consistently show that land lease plays a huge role in land consolidation and its role with time is increasing. The share of leased land became
very significant in 2006: Only 12% of land of the total agricultural land belongs
Economic impacts of land market development: Evidence from Moldova
61
to farms. The rest of the cultivated land farms lease in from individual landowners.
About half of the surveyed farms had used leased land only.
Table 7:
Average size and structure of corporate farms in Moldova
according to different surveys
1999
Owned
Leased
Total
ha
621
780
1401
2003
%
44.3
55.7
100
ha
585
783
1368
2006
%
42.8
57.2
100
ha
171
1250
1421
%
12.0
88.0
100
Source: 2004 IAMO Survey of farm managers, 2006 Survey of corporate farms (unpublished).
A similar picture might be observed with peasant farms. Results of World Bank
surveys conducted in 1997, 2000 and 2005 show that peasant farms with leased
land are, on average, much larger than farms based only on privately owned
land. Markets for land leasing evolved strongly over time: Only 6% of peasant
farmers reported leasing land in the 1997 survey, and this percentage increased
to 28% in the 2005 survey (WORLD BANK, 2005).
Although no comprehensive official statistics on lease transactions are available
to this day, the number of lease transactions recorded in the State Cadastre increased from around 3,000 to more than 21,000 between the years 2000 and 2004
(this includes only contracts for a lease term of 3 years and longer). The land
lease market has definitely grown much stronger as leaders of the new corporate
farms join private farmers in competing for additional land among inactive landowners.
5
CONSTRAINTS ON LAND TRANSACTIONS
All the surveys mentioned in this study, as well as official statistical data on
sources of land used by agricultural producers reveal that farms of all types
heavily rely on leased land. However, among the latest trends we denote that
many of them began to purchase actively land from individuals and traditional
(old) forms of corporate farms. Thus, we may conclude that although to a short
history of the local land market, it has a perspective future. All the indicators
show that land fragmentation is reducing, while land consolidation is increasing.
In this context, an important role belongs to land transactions.
However, this does not mean that land market is developing cloudless. Although
to positive trends, some negative factors are triggering land market development.
The IAMO survey explored the difficulties that managers and farmers face in
their attempts to lease in land (Table 8). It is encouraging to note that nearly
30% of respondents did not report any difficulties in their lease transactions.
Among those who did mention difficulties, high transaction costs ranked highest
Dragoş Cimpoieş
62
(16% of respondents), followed by lack of cash to cover lease payments (14%),
and uncertainty about land prices in the absence of functioning markets (11%).
Table 8:
Main difficulties in leasing in agricultural land
2004
6.0
2.0
11.2
7.3
16.0
13.9
No supply
Farm administration does not know who wants to lease out land
Difficulties in determining the proper price
Land lease transactions are complex and are not cleared to farmers
High transaction costs
No money
Too many owners of very small parcels*
Land owners refuse to lease out their land because of low prices
Other reasons
No difficulties
Note:
Source:
*
11.9
3.3
28.4
2006
3.6
3.6
4.3
10.1
17.4
20.3
20.3
9.5
10.9
This option has not been provided by the 2004 IAMO Survey.
2004 IAMO Survey; 2006 Survey of corporate farms (unpublished).
Curiously, but 12% of farm mangers complained of insufficient supply of land,
and that despite the manifested tendency of small landowners to entrust their
land to operators. The recent survey of farm managers, conducted by author in
2006 underlined that about 20 percent of farm managers reported excessive
fragmentation (too many owners of very small parcels) as one of the biggest difficulty, followed by lack of cash to cover lease payments (20% of respondents)
and high transaction costs (17%). It seems that the state of land lease relations did
not take a turn for the better during this period. The number of respondents reporting no difficulties sharply dropped from 28.4% (IAMO Survey) to only 10.9%.
The situation is not better with buy-and-sell transactions. Again, about one quarter of respondents in 2004 IAMO Survey reports they do not face any problem, a
striking contrast to the results of the recent survey, reporting only 2% of farms
without problems in buy-and-sell transactions.
Table 9:
Main difficulties in buying agricultural land
2004
16.4
7.1
28.6
0.0
1.5
5.7
12.9
3.5
24.3
No supply
Difficulties in determining the proper price
No money
Too many owners of very small parcels*
Buyers do not know the average prices on land market
Land transactions are complex and are not cleared to farmers
Land transactions are too expensive
Other reasons
No difficulties
Note:
The 2004 IAMO Survey has not provided this option.
Source: 2004 IAMO Survey; 2006 Survey of corporate farms (unpublished).
2006
12.1
22.5
12.9
15.3
4.0
9.7
18.5
3.2
1.8
Economic impacts of land market development: Evidence from Moldova
63
Among those who face any difficulties, lack of money was on the top of difficulties two years ago. The last survey revealed that reluctance of landowners for
selling their land seems to be the biggest problem, especially in individual land
consolidation through buy-and-sell transactions. The first two difficulties correspond to this problem. Skeptical attitude of landowners towards buy-and-sell
transactions is caused by very low prices on the local land market (Table 4). One
of the major impediments for corporate farms is the excessive number of landowners possessing small and very small plots spread at a significant distance to
each other, making very difficult to buy contiguous plots in a single field. This is
one of the reasons of launching the National Land Consolidation Program.
No changes for better for excessive transaction costs. They are still high and the
registration procedures are very complex. Excessively high transaction costs and
complex administrative procedures constitute a serious obstacle to land consolidation through buying and selling. The costs associated with registration of
transfer of ownership are estimated at 277 lei per transaction (Table 10). This
figure underestimates the true transaction costs as it does not include the cost of
making two trips to the district cadastre office – one trip to submit the paperwork, another trip to collect the new title, which is estimated at about 35-40 lei,
raising the cost to over 300 lei per transaction. Nor does it include the cost of
surveying and mapping the plot: These activities were carried out with USAID
funding as part of the NLP and are free to the landowner.
Since the average sale transaction recorded in the State Cadastre is 0.9 hectares
(see table 3), purchasing one hectare of agricultural land involves practically one
cadastral transaction (one "parcel") and carries transaction costs of about 300 lei,
equivalent to 10% of the price of land.
Table 10:
Land transaction costs according to the standard and the
consolidation procedures
Extract from cadastre registry
Authentication of sales contract
by notary
State tax for authentication
New record of ownership
Certificate of land quality
Total
Standard procedure
Lei
%
24
9
180
15
42
16
277
65
5
15
6
100
Consolidated procedure
Lei
%
--25
-34
-59
42
-58
-100
Source: STATE CADASTRE AGENCY.
The main cost component is the notary fee for authentication of documents. It is
charged at 180 lei per transaction and thus accounts for 65% of the total transaction costs. In theory, notary fees are charged pro rata on a sliding downward scale.
However, the sliding scale starts at 1.3%, but not less than 180 lei. To reduce
Dragoş Cimpoieş
64
transaction costs under conditions of Moldova’s highly fragmented holdings, the
unrealistically high minimum fee should be abolished and notary fees should be
calculated pro rata.
High transaction costs in general, and high notary fees in particular, are damaging
for large agricultural investors even more than for small farmers. An entrepreneur buying 120 hectares of land would have to register 200 average transactions
to complete the transfer of ownership. The transaction cost would reach 60,000 lei,
or 10% of the 600,000 lei paid to landowners.
An even more radical solution to the problem of high transaction costs is to
charge all fees on the basis of a whole physical transaction, and not for each cadastral object ("parcel") separately. This, however, may involve considerable changes
in the configuration of the cadastral objects recorded in the system and thus
require additional costs for surveying and mapping. On the other hand, drastic
reduction of transaction costs will adversely affect the income of the territorial
cadastral offices, which by design cover their operating costs from fees and
taxes. The realization of radical cost-reducing measures therefore should be considered only in the whole context of costs and benefits of land consolidation
programs with proper external financing.
6
CONCLUSIONS AND RECOMMENDATIONS
Land fragmentation is considered as one of the major impediments for the successful development of Moldovan agriculture. In this context, the most common
approach to land consolidation in Moldova is individual or market-driven consolidation, which relies on encouraging the development of land market transactions – mainly leasing at the present stage. The prevalence of short-term lease
agreements is an obstacle to land consolidation as it discourages investment by
lessees in land improvement and infrastructure. Excessively high transaction
costs and complex procedures are two important obstacles to the development of
buy-and-sell transactions for land consolidation.
Agricultural policy therefore should encourage longer term leasing and simplify
the ownership-transfer procedures. Specifically, transaction costs can be reduced
by abolishing the minimum notary fee and allowing the buying and selling of
multiple parcels by one person to be treated as a single consolidated transaction.
ACKNOWLEDGEMENTS
The author would like to thank Zvi Lerman for able research assistance, valuable
comments and suggestions on an earlier version of this paper.
Economic impacts of land market development: Evidence from Moldova
65
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MURAVSCHI, A. (2002): Dezvoltarea rurală în Moldova (studiu de caz), Chişinău,
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Sustainable rural development: What is the role of the agri-food sector?
MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central and Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 67-79.
REGIONAL SPECIFICITY OF RURAL LABOUR ALLOCATION AND
MIGRATION IN UKRAINE
OLEKSANDR V. ZHEMOYDA∗
ABSTRACT
This paper analyses the determinants of rural labour allocation and migration in
Ukraine at the regional level. The Human Development Index in connection
with several socio-economic variables are used to explain the reasons of total
and foreign migration of rural population. Our findings suggest that such factors
as life expectancy, GDP per capita, social environment, unemployment level,
and housing conditions must be considered to provide sustainable development
of rural population.
Keywords: Rural labour, migration, Human Development Index, Ukraine.
1
INTRODUCTION
It is well known that the human potential is a basic strategic resource and one of
the main driving forces of the economic growth in any country. Among other
things, the specifics of able-bodied population’s allocation and migration can
significantly affect the sustainable development of regions that certainly differ in
patterns of socio-economic development. The Ukrainian regions make no exception in this respect reporting substantial changes in rural labour allocation and
migration in the transition period.
Generally, the regional differentiation of the level of human capital development
is determined by the differences in demographic tendencies, employment of
population, state of labour market, educational qualification, level of financial
well-being, development of social infrastructure, etc.
In this paper, we analyse the determinants of rural labour allocation and migration at the regional level using the human development index. The analysis takes
into account the following questions: Which factors influence rural labour migration and allocation in the Ukrainian regions? Which measures can be consequently taken for the sustainable rural development of the Ukrainian regions?
∗
Chair of State Management, National Agricultural University of Ukraine, Kyiv. Email:
[email protected]
68
2
Oleksandr V. Zhemoyda
THE DEVELOPMENT OF HUMAN POTENTIAL AND LABOUR
MIGRATION IN THE UKRAINIAN REGIONS
2.1 The development of human potential
Obviously, socio-economic processes in territorially and administratively coherent
regions coincide with general economic tendencies at the national level taking
some specific regional features. In the last 15 years, the socio-economic development in the Ukrainian regions can be divided into two basic stages: The period
of protracted economic crisis (1991-2000) and the period of economic recovery
(from 2001 till present time). Each of these stages is characterised by specific
aspects, tendencies and prevailing problems in socio-economic development of
regions (VARNALIY, 2005). Our focus is mostly on the second stage here.
Despite the economic recovery stage in Ukraine, the development of regional
human potential is still hampered by the difficult situation at the labour market
and high level of unemployment, depopulation, low availability and insufficient
quality of social services, decline in quality of education, etc. The combination
and degree of sharpness of these problems differ both between regions and in
every region between cities and rural territories.
Labour market. Even though the average official level of unemployment in
Ukraine (7.9 % of able-bodied population in 2005) is lower than in some developed EU countries, there is, however, an evidence of poor social support of an
unemployed population. Additionally, significant differences in unemployment
rates between regions occur ranging from 5 % in the West to 0.7 % in the East.
Official statistics also show that unemployment levels are more stable in industrially developed eastern regions while these tend to decrease in agriculturally
specialised western regions (STATE STATISTICS COMMITTEE OF UKRAINE –
DERZHKOMSTAT, 2005).
The average level of profits and personal consumption among rural population
remains low. In spite of substantial increase in real wages (about 25 % in 2006
compared to 2005) and high rate of wages growth in agriculture and related sectors
(129 % in 2006 compared to 2005; DERZHKOMSTAT, 2006), the consequences of
this improvement can hardly be observed in rural territories. As reported by the
Ministry of Labour and Social Policy of Ukraine, the lowest real wages are in
fisheries, agriculture and related sectors, and health and social services (MLSP,
2006) that can also result in increase of the regional development differences.
Regarding social services in the rural territories an important aspect is low and
lowering state support of the development of social infrastructure including poor
financing of rural developers crediting, arrangement of ambulance services and
provision of rural territories with gas. On account of this, more and more migration from villages to cities is being observed.
Regional specificity of rural labour allocation and migration in Ukraine
69
Education. Another driving force of urbanisation is education. In Ukraine, population with completed higher education increased in the transition period. The
number of urban population with higher education per 1000 inhabitants has risen
by 30.7 %, and rural population – by 68.8 % in 2001 compared to 1989. Such
development is the result of increased opportunities for population to enter higher
educational institutions. One of the possible explanations of this phenomenon is
that universities have increased their enrolment numbers in order to survive in
the newly established market conditions.
Social environment. Regarding social environment in Ukraine, its overall level
has essentially reduced over the last decade. Population’s psychotropic addictions are strongly exemplified in regions where other types of social problems
(criminality, suicides, diminishing of life-span and depopulation) are spread. In
this context, eastern regions prevail showing also a high level of poverty and
low level of education compared to other regions.
Health protection. Nowadays qualified medical services are mostly available in
the private sector of the national economy. However, due to high prices this type
of medical care is usually inaccessible for the majority of population. Adequate
medical care in the state sector is often hard to get because of outdated infrastructure. These tendencies are common for all regions of the country.
Terms of population dwelling. Though the living conditions remain low in rural
areas, today the level of housing corresponds to the number of population that
lives in rural areas. The main reasons for this are the demographic situation and
low housing costs compared to cities.
Population. Alongside with the above developments, a substantial reduction of
the population has occurred over the last decade. Between the Soviet census of
1989 and the Ukrainian census of 2001, Ukraine’s population declined from
51,271,996 to 48,077,020, with the loss of 3,194,976 people or 6.23% of the
1989 population. However, this loss has been quite unequal by regional aspect.
West-Ukrainian regions show slight average depopulation levels whereas the
population of eastern regions has dramatically decreased. Additionally, there is
an evidence of increase in population by some basis points in several western
regions. An overall pattern of population change from 1989 to 2001 is as follows:
Substantial growth in the capital – the city of Kyiv; slight decline in western
Ukraine; significant decline in eastern, central and southern regions; and catastrophic decline in Crimea.
2.2 Internal and foreign labour migration
In the context of low salaries and high unemployment within Ukraine, labour
migration became a mass phenomenon at the end of the 1990’s. The newfound
openness of borders has created opportunities for Ukrainians to improve their life
quality through labour migration. The adoption of the "Law on Entry and Exit" (1994),
Oleksandr V. Zhemoyda
70
alongside with the "Law on Employment of Population" safeguarded the right of
Ukrainian citizens to move to and work in areas that correspond to their preferences.
Map 1:
Total migration of rural population, 2006
8001 and >
6000 - 8000
< 5999
Source: Author’s calculations based on data of DERZHKOMSTAT.
The evidence suggests that rural areas, or impoverished urban regions, are
sending migrants to urban areas and big cities. Eastern oblasts of Kharkiv and
Dnipropetrovsk, and the cities of Kyiv and Sevastopol (Crimea) envisage the
largest inflows of internal migrants capturing more than 80 % of those. These
regions are large urbanised areas (more than 75 % of population live in towns
and cities). On the contrary, eastern Donetsk and Luhansk oblasts with about
90 % of urban population exhibit large outmigration. The main reason for this is
the worsening of living conditions caused by the closure of mines in these industrialised regions. In fact, Luhansk is one of the most depopulated oblasts. About
40 % and more of population live in rural areas of Kirovohrad (Centre), Kherson
(South), Chernihiv (North) oblasts, and western regions of Ukraine (Ternopil,
Vinnytsya, Rivne, Khmelnytskiy and Zhytomyr). These areas represent two thirds
of the internal migration.
Regarding foreign migration, Ukraine is the major source of migrants to many
of the European Union Member States. During the 1990’s and early 2000’s,
Ukraine’s sputtering economy and political instability contributed to rising emigration, especially to neighbouring Poland and Hungary, but also to other States
such as Portugal, Turkey, Israel, Russia and Canada. Although available estimates
vary, approximately two to five million Ukrainian citizens are currently working
abroad, most of them illegally, in construction, service, housekeeping, and agriculture industries (MALYNOVSKA, 2004).
Regional specificity of rural labour allocation and migration in Ukraine
Map 2:
71
Foreign migration of rural population, 2006
960 and >
450-960
< 450
Source: Author’s calculations based on data of DERZHKOMSTAT.
Official accounts of migration – that usually underestimate the real magnitude of
this phenomenon – indicate that, on average, more than 140 thousand Ukrainians
left the country each year between 1995 and 2001. In 2002 and 2003, the outmigration slowed down significantly to 34 and 24 thousand people, respectively.
In 2005, the number of outmigration accounted for about 20 thousand
(DERZHKOMSTAT, 2005). Ukrainian embassies report that 300,000 Ukrainian
citizens are working in Poland, 200,000 in Italy, approximately 200,000 in the
Czech Republic, 150,000 in Portugal, 100,000 in Spain, 35,000 in Turkey, and
20,000 in the US. The largest numbers of Ukrainian workers abroad, about one
million, are in the Russian Federation. Since 1992, 232,072 people born in
Ukraine have immigrated to the US. In the age-related context, migrants at the
age of 40 or above tend to migrate to the Russian Federation and other CIS
states, while younger migrants move to Europe and other Western countries. The
oblasts of Chernihiv (North), Rivne and Volyn (West) are the ones that send most
migrants abroad relative to their populations, whereas oblasts like Zakarpattya
(West) and Luhansk (East) have more than 28 % of the total amount of official
migrants (DERZHKOMSTAT, 2005).
The impact of emigrants on local economies is most frequently assessed by the
indicator of the volume of immigration as a proportion of the native population.
On account of this, Portugal and Czech Republic have the highest rate of
Ukrainian emigrants as a proportion of the native population.
Another economic result of foreign migration processes is the cash inflows into
the Ukrainian economy through remittances from Ukrainians abroad. They annually account for about $4-$6 billion. This income is predominantly used for
family consumption, housing, and children education. Considerably less amounts
Oleksandr V. Zhemoyda
72
of this money are invested in small family businesses, mainly because Ukraine
has few economic incentives for such enterprises.
One more important aspect in labour allocation is the shift that has occurred
between the public and the private sectors. In the period from 1999 to 2005
private employment has doubled, while public employment and, especially, collective employment has fallen. On the other hand, state owned organisations,
entities and institutions remain the single largest source of employment, still absorbing 47 % of all employment. Collective enterprises (mostly agricultural enterprises in rural areas) account for 10 %, while only one of five workers is
employed in a private company.
Generally, internal and external migration patterns suggest a strong correlation
between poverty and allocation of labour resources. In this case, migration
serves as household risk management behaviour since it provides alternative
sources of income. Thus, the difference in migration indicators is associated
with differences in labour markets opportunities that determine the level of earnings. Even so, possible "loading" of better income groups does not necessarily
reflect the incidence of migration. In fact, some specific surveys on migration indicate that while those in rural areas are more likely to migrate, a large
part of migrants is involved in seasonal migration on construction, and some in
agriculture and other works and services (LIBANOVA and POZNYAK, 2002).
We further discuss the determinants of rural labour migration in Ukraine. Additionally, we make suggestions about what can be done to deal better with rural
labour allocation and migration in Ukraine.
3
METHODOLOGY AND DATA
Human potential forms the social terms of the realisation of economic interests
at the regional level. One of the most important factors in the analysis of the determinants of regional economic interests’ formation is the standard of living
which predetermines a certain level of human potential. Obviously, achievement
of high population’s standard of living is the primary purpose of economic development in a region. On account of this, the standard of living has a substantial impact on both, formation and realisation of human potential and, consequently, of economic interests in a region. Undoubtedly, corresponding living
standards strongly correlate with average life expectancy as well as with level of
education.
3.1 Methodology
The integral measure of the state of human capital is the human development
index (HDI) developed by the United Nations. The HDI takes into account such
Regional specificity of rural labour allocation and migration in Ukraine
73
factors of human capital development as demography, labour market conditions,
social support, environmental conditions, educational quality, dwelling, etc.
As defined by the United Nations Development Program, the HDI is a summary
measure of human development. It provides measures of the average achievements in three basic dimensions of human development (UNDP, 2006):
-
A long and healthy life.
-
Knowledge.
-
A decent standard of living.
Corresponding weights are put on variables representing each of dimensions.
Before the HDI itself is calculated, an index needs to be created for each of these
dimensions. To calculate these dimension indices minimum and maximum values
(goalposts) are chosen for each underlying indicator.
Performance in each dimension is expressed as a value between 0 and 1 by applying the following general formula:
Dimension index = (actual value – minimum value) / (maximum value – minimum value). The HDI is then calculated as a simple average of the dimension
indices (UNDP, 2006).
In general to transform a raw variable, say x, into a unit-free index between 0
and 1 (which allows different indices to be added together), the following formula is used: x-index =
x − min( x)
max( x) − min( x)
where max (x) and min (x) are the lowest and highest values the variable x can
attain, respectively.
The Human Development Index (HDI) then represents the average of the following three general indices:
LE − 25
;
85 − 25
-
Life Expectancy Index =
-
Education Index =
-
Adult Literacy Index (ALI) =
-
Gross Enrollment Ratio (GER) =
-
GDP Index =
2
1
xALI + xGEI ;
3
3
ALR − 0
;
100 − 0
CGER − 0
;
100 − 0
log(GDPpc) − log(100)
,
log(46000) − log(100)
where LE denotes life expectancy; ALR – adult literacy rate; CGER – combined
gross enrollment ratio; GDPpc – GDP per capita at PPP in USD.
Oleksandr V. Zhemoyda
74
The gross enrolment ratio (GER) or gross enrolment index (GEI) is a statistical
measure used in the education sector. The GER gives a rough indication of the
level of education – primary, secondary, and/or tertiary – amongst residents in a
given jurisdiction. It is calculated by dividing the total number of students enrolled at each educational level (regardless of age) by the population of the age
group that should be enrolled at that level at the start of the academic year.
A combined gross enrolment ratio (CGER) incorporates all three levels of education. Amongst other measures used in the calculation, the CGER is given onethird weight in assessing the knowledge component while the adult literacy rate
for a given territory is assigned two-thirds weight.
At the second stage of empirical analysis we regress the indicators of total and
foreign migrations on HDI-based indexes and a number of variables described
below.
3.2 Data
The study employed the official information of the State Statistics Committee of
Ukraine – Derzhkomstat. Data on 25 regions (24 oblasts and Autonomous Republic of Crimea) of Ukraine for the year 2005 is extracted from the statistical
yearbooks Agriculture of Ukraine, Population of Ukraine, and Regional Human
Development in Ukraine. Statistical information used relates to rural population
only.
To elaborate on the index of labour market, we used the data on officially registered numbers of unemployed population. Terms of population dwelling are
given by the indicator of provision with dwelling according to the material wellbeing. The number of rural population undergoing medical treatment at hospitals
represents the health protection variable. Social environment is estimated by the
levels of alcohol and drug addictions as well as of psychological stability of rural
population. Ecological situation is given by the ratio of actually taken measures
and actually needed measures for the maintenance of ecological safety.
4
EMPIRICAL ANALYSIS
The results of the calculations are given in Table 1. We employ the HDI with
regard to rural labour on the regional level considering 9 exponents. These characterise the demographic development, development of labour market, financial
welfare, terms of population’s dwelling, health conditions and protection, educational level, social environment, financing of human development, and ecological
situation.
Regional specificity of rural labour allocation and migration in Ukraine
Table 1:
75
The HDI-based indexes for Ukrainian regions
LE Index
Region
Edu
Index
GDP
Index
LM
Index
TPD
HCaP
SE
ES
AR Crimea
0.32
0.95
0.59
0.14
0.16
0.22
0.21
0.65
Vinnytsia
0.41
0.95
0.59
0.18
0.40
0.17
0.16
0.55
Volyn'
0.30
0.92
0.57
0.25
0.09
0.15
0.43
0.63
Dnipropetrovs'k
0.38
0.95
0.67
0.26
0.25
0.23
0.48
0.33
Donets'k
0.40
0.96
0.67
0.04
0.15
0.24
0.65
0.28
Zhytomyr
0.39
0.94
0.56
0.22
0.29
0.19
0.44
0.57
Zakarpattya
0.25
0.93
0.56
0.11
0.13
0.18
0.22
0.61
Zaporizhia
0.37
0.96
0.65
0.38
0.14
0.23
0.69
0.41
Ivano-Frankivs'k
0.31
0.93
0.60
0.48
0.19
0.18
0.15
0.55
Kyiv
0.42
0.96
0.62
0.05
0.39
0.22
0.29
0.49
Kirovograd
0.39
0.95
0.58
3.15
0.20
0.17
0.86
0.55
Lugans'k
0.40
0.96
0.60
2.90
0.01
0.21
1.40
0.21
L'viv
0.33
0.94
0.60
0.18
0.22
0.24
0.11
0.47
Mykolaiv
0.33
0.95
0.61
5.29
0.07
0.19
0.45
0.56
Odessa
0.31
0.94
0.64
0.15
0.25
0.19
0.25
0.51
Poltava
0.42
0.96
0.65
0.23
0.32
0.16
0.40
0.76
Rivne
0.29
0.91
0.58
0.73
0.13
0.17
0.27
0.43
Sumy
0.45
0.96
0.59
3.00
0.20
0.20
0.75
0.51
Ternopl'
0.37
0.94
0.54
0.55
0.18
0.19
0.26
0.54
Kharkiv
0.40
0.96
0.64
0.14
0.21
0.22
0.47
0.43
Kherson
0.31
0.95
0.57
0.35
0.05
0.18
0.85
0.43
Khmel'nutskyi
0.43
0.95
0.57
0.17
0.30
0.15
0.40
0.54
Cherkasy
0.43
0.95
0.57
0.34
0.36
0.17
0.39
0.55
Chernivtsi
0.31
0.93
0.54
0.52
0.13
0.20
0.37
0.62
Chernigiv
0.51
0.95
0.59
0.02
0.39
0.16
0.84
0.46
Source: Author’s calculations based on data of DERZHKOMSTAT (2005).
Table 2:
Regression statistics on total and foreign migration
Regression statistics
Total migration
Foreign migration
Multiple R
0.760
0.807
R2
0.576
0.652
Fixed R2
0.302
0.478
139.331
49.374
25
25
Standard error
No. of observations
Source: Author’s calculations.
Oleksandr V. Zhemoyda
76
Due to the results of multiple regression (Table 2), total migration is strongly
correlated with the given factors. Precisely, the total migration dependence on
the factors of the model is 57.6 %. F-value of 4.19 % (see Appendix 1) suggests
that the model is statistically significant at 0.05 probability level. The dependence of foreign migration on considered variables is even more and accounts
for 65.17 % with F-value equal to 1.18 % at 0.05 probability level.
Table 3:
Main factors of total migration
Coefficient
Standard error
t-statistics
P-value
Y-Intercept
-7906.090
4293.465
-1.841
0.080
LE Index
13802.390
4781.243
2.887
0.009
GDP Index
18413.870
7219.579
2.551
0.019
Social environment
-3099.730
984.685
-3.148
0.005
Source: Author’s calculations.
Table 4:
Main factors of foreign migration
Coefficient
Standard error
t-statistics
P-value
Y-cross
-5315.166
1594.118
-3.334
0.003
LE Index
4506.678
2304.616
1.956
0.065
GDP Index
9505.731
2671.912
3.558
0.002
Labour Market
Index
-212.102
90.335
-2.348
0.029
Terms of PD
-5049.808
1397.776
-3.613
0,002
Source: Author’s calculations.
Resulting from multifactor simulation in regression analysis (Appendix 2), the
main determinants of total migration are Life Expectancy Index (LEI), GDP
Index and Social Environment Index (SEI). Each of these factors has significant
t-statistics (Table 3). In other words, the main reasons for migration in rural
areas are the level of family income; features of social environment, e.g. the
level of alcohol addiction or drug addiction of the population; and the level of
sustainable living.
In the case of foreign migration, multifactor simulation (Appendix 3) reveals
that the main factors are LEI, GDP Index, the ratio of employed and unemployed population, and terms of population dwelling (Table 4). As in the case
with total migration, foreign migration is strongly dependent on family income
and sustainability of livelihoods. Additionally, job availability and dwelling
conditions influence foreign migration.
Regional specificity of rural labour allocation and migration in Ukraine
5
77
CONCLUSIONS
Recent developments in most Ukrainian regions reveal an aggravation of inadequate standards of living of rural population. As our research findings suggest,
an increased attention must be paid to sustainable development of rural labour.
For this, such factors are of major importance as the level of family income, social
environment features, life expectancy, job availability and housing conditions.
In order to improve these indicators, efforts of the policymakers must concentrate
on the development of modern agricultural policy as it has always played an important social role in the Ukrainian rural areas.
REFERENCES
LIBANOVA, E., POZNYAK, O. (2002): Labour migration from Ukraine – A new migration potential from Eastern Countries, Paper presented at the Beyond Transition
Seminar organized by CASE.
MALYNOVSKA, O. (2004) International migration in contemporary Ukraine: Trends and
policy, Global Migration Perspectives No. 14 (October), Global Commission on
International Migration.
MINISTRY OF LABOUR AND SOCIAL POLICY OF UKRAINE (2006): Wages in Ukraine,
Report, <http://www.mlsp.gov.ua/document/48823/monitorung07.06.doc>.
STATE STATISTICS COMMITTEE OF UKRAINE (2005): Agriculture of Ukraine, Statistical
Yearbook, Kyiv.
STATE STATISTICS COMMITTEE OF UKRAINE (2005): Population of Ukraine, Statistical
Yearbook, Kyiv.
STATE STATISTICS COMMITTEE OF UKRAINE (2005): Regional human development in
Ukraine, Statistical Yearbook, Kyiv.
STATE STATISTICS COMMITTEE OF UKRAINE (2006): Statistical information on wages indices, <www.ukrastat.gov.ua/operativ/operativ2006/gdn/izp/izpu/izppr2006u.html>.
UNITED NATIONS DEVELOPMENT PROGRAM (2006): Human development reports,
<http://hdr.undp.Org/reports/global/2003/faq.html#21:
http://hdr.undp.org/reports/global/2003/pdf/hdr03backmatter 2.pdf>.
VARNALIY Z. (2005): Regions of Ukraine: Problems and priorities of socio-economic
development, Kyiv.
Oleksandr V. Zhemoyda
78
Appendix 1: Dispersion analysis of total and foreign migration
Total migration
df
SS
MS
F
Amount F
Regression
9
42233538.34
4692615.371
2.719387547
0.041962852
Remainder
16
31061066.22
1941316.639
Total
25
73294604.56
df
SS
MS
F
Amount F
Regression
8
7299140.528
912392.566
3.742624607
0.0118448
Remainder
16
3900546.432
243784.152
Total
24
11199686.96
Foreign migration
Appendix 2: Multifactor model simulation on total migration
Coefficient
Standard error
t-statistics
P-value
Y-Intercept
-54026.1489
37568.18855
-1.438082351
0.169682751
LE Index
4189.044796
12061.85756
0.347296822
0.732894593
Edu Index
62550.32475
47323.1899
1.321768987
0.204833073
GDP Index
9402.767128
10333.44245
0.909935597
0.376360768
Labour Market Index
-175.901434
275.7607931
-0.637876879
0.532577399
Terms of PD
1381.07064
7093.74176
0.194688598
0.848087341
Health conditions and
protection
-11094.96777
18189.85912
-0.609953475
0.550457999
Social environment
-3764.34977
2481.065274
-1.517231252
0.14871718
Ecological situation
-3692.767375
4208.242642
-0.877508188
0.393196698
Regional specificity of rural labour allocation and migration in Ukraine
Appendix 3: Multifactor model simulation on foreign migration
Coefficient
Standard error
t-statistics
P-value
-11621.10014
13312.96534
-0.872915977
0.395620798
LE Index
4217.78752
4274.33682
0.986770041
0.338443631
Edu Index
9438.889203
16769.82604
0.56284956
0.581339222
GDP Index
5620.462233
3661.841745
1.534873057
0.144351192
Labour Market Index
-189.4550087
97.72081173
-1.938737566
0.070380222
Terms of PD
-4962.922822
2513.795363
-1.974274794
0.065871441
Health condition and protection
3289.029377
6445.904721
0.510251007
0.616842411
Social environment
-515.2201025
879.2102377
-0.586003302
0.56604883
Ecological situation
-1243.788705
1491.266696
-0.834048469
0.416532572
Y-Intercept
79
Sustainable rural development: What is the role of the agri-food sector?
MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central and Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 80-93.
INFRASTRUCTURE AS A DETERMINANT OF RURAL NON-FARM
EMPLOYMENT: THE CASE OF UKRAINE
MARIYA PORTYANKO∗
ABSTRACT
The objective of my research is to empirically determine the role of infrastructure in Ukrainian rural non-farm employment (RNFE). Existing experience with
RNFE estimation is considered and the probability of RNFE estimation for
Ukraine is provided. Empirical evidence is taken from a household survey conducted in 2004. To find out what factors determine off-farm employment, a bivariable probit model is used. The paper also considers the issue of Ukraine accession into the World Trade Organization. The problem of subsidising agricultural activities is particularly discussed.
Keywords: Rural non-farm employment, infrastructure, Ukraine.
1
INTRODUCTION
The objective of my research is to empirically determine the role of infrastructure in Ukrainian rural non-farm employment (RNFE).
The spread of RNFE is important for the sustainable development of rural areas.
The key reason for this is diversifying rural employment opportunities and
sources of income. This permits avoiding or lowering agricultural risks, overcoming negative shocks and increasing incomes, thereby raising the standard of
living in rural areas.
As a substantial portion of the Ukrainian population lives in rural areas (more
than 30 %) sustainable rural development policy is very important for Ukraine.
Still, there is a sizable disparity between urban and rural areas in terms of
income, quality of life, job opportunities and physical and economic infrastructure. For a long time, rural areas were associated with farm activities, while
urban areas were associated with non-farm activities (REARDON,1998). And
indeed, traditionally, people who live in rural areas are engaged in farming.
However, the reformation and modernisation of agriculture releases labour
employed in farming. This is one of the reasons for rural unemployment.
∗
National University "Kyiv-Mohyla Academy", Ukraine. Email: [email protected]
Infrastructure as a determinant of rural non-farm employment
81
Therefore, promoting other types of employment, such as off-farm employment, is becoming more and more important. Moreover, RNFE is an important
source of income in rural areas. It was found that those involved in off-farm
activities usually have a higher living standard (DE JANVRY et al., 2005). Furthermore, for an efficient agricultural process, developing the agro-industrial sector is necessary. Overall, off-farm employment absorbs the excess labour supply,
proides rural people with an income source, improves the quality of life and
assists in efficient agricultural development. Therefore, RNFE promotion is
essential for the sustainable development of rural areas in Ukraine.
Considering the importance of RNFE in Ukraine, it is useful for the government
to know what factors determine off-farm participation and how they influence
the probability of participation. This research can provide the government with
proper information for conducting rural policies; for instance, one could expect a
positive influence of infrastructure on participating in off-farm activities. Moreover, it is obvious that investing in infrastructure would be beneficial not only
for the off-farm sector, but also for rural areas as a whole. The government
should consider this fact in their rural policies. Indeed, instead of subsidising
farms, the money could be better spent on improving infrastructure, education,
training and other developmental expenditures. This would have a positive effect
on both farm and off-farm activities.
RNFE is also of current importance for Ukraine in the context of WTO accession. One of the problems of the accession process is connected with agriculture:
Highly subsidising agricultural activities (which is a common practice) is restricted by the WTO, as such activities are considered to be trade-distorting
methods of support. Those activities belong to the so-called "amber box". Thus,
subsidising farms is considered to be a part of the "amber box".
As can be seen in Figure 1, "amber box" expenditures are increasing and are also
approaching the WTO restriction.
Mariya Portyanko
82
Figure 1:
Budget financing and the WTO "amber box" expenditure
restriction in Ukraine, 2006 and 2007
7.0
6.0
5.0
UAH
bn
4.0
3.0
2.0
1.0
0.0
2006
2007
"Amber box" expenditure
restriction in Ukraine
The WTO "amber box" expenditure
restriction (USD 1.14 billion)
Source: Author’s calculation based on the law, "On State Budget 2006", and the draft law
"On State Budget 2007", second reading.
At the same time, development expenditures are not forbidden by the WTO. In
Ukraine the share of "amber box" expenditures is still dominant; it accounts for
64.6% Table 1). Meanwhile, development expenditures remain extremely low –
about 35.4%. However, "green box" expenditures have positive long-run impacts
on rural development.
Table 1:
Budget expenditures in Ukraine according to WTO
classification, 2006 and 2007
2006
2007
Billion UAN
% of all
expenditures
Billion UAN
% of all
expenditures
"Amber box"
expenditures
4.2
57.8
5.8
64.6
"Green box"
expenditures
3.1
42.2
3.2
35.4
Total
7.3
100.0
9.0
100.0
Source: Author’s calculations based on the law, "On State Budget 2006", and draft law, "On
State Budget 2007", second reading.
Infrastructure as a determinant of rural non-farm employment
83
Therefore, it is necessary to re-direct budget expenditures towards the improvement of rural areas, since it will not only assist the sustainable development of
rural areas, but also allow Ukraine to enter the WTO. Thus, the results of this
research could be used by policy-makers in formulating rural development
policies, particularly for promoting RNFE.
2
LITERATURE REVIEW
Rural non-farm employment is defined as all economic activities conducted in
rural areas, aside from agriculture, livestock, fishing and hunting (LANJOUWA
and LANJOUW, 1995). Rural non-farm activities include agro-processing, small
businesses in rural areas, migration, switching from farming to commodity
trading, or selling household assets in response to negative circumstances
(DAVID and PEARCE, 2001).
The most discussed issues in the literature are those that describe:
-
Determinants of RNFE;
-
Factors of RNFE diversification;
-
Non-farm employment opportunities in countries with different levels of
economic development;
-
and methods of estimating RNFE participation.
I will shortly describe and summarise all of these issues in the literature review
section.
Most researchers agree that the main determinants of RNFE participation are
education, gender, credit, land and ethnicity (WANDSCHNEIDER, 2003). In his
article, DAVIS (2003) also considers physical infrastructure and information to
be determinants that influence the probability of participating in RNFE. Both
economists mention wider factors that determine participation in off-farm activities: Agricultural development, natural resource endowment, economic infrastructure, public services, investment, rural town development and businessenvironment (WANDSCHNEIDER, 2003; DAVIS, 2003).
Further, so-called peer1 effects were recognised to have a positive role on a
household’s decision to participate in off-farm activities. The distance to the
country capital also decreases the probability of participating in RNFE
(DE JANVRY et al., 2005). Similar results were found by LASS et al. (1992) in
their research; they included distance to the nearest town as an explanatory
variable and found that it has a negative effect on participating in off-farm activity. Another variable that they added was years of farming, which also decreases the probability of participating in RNFE. Additional important factors
1
Neighbours around the household on a certain area (DE JANVRY et al., 2005).
Mariya Portyanko
84
that determine RNFE participation are size of household, age and the presence
of livestock (BEZEMER and DAVIS, 2002).
The key point of the literature is to determine whether a person is engaged in
off-farm activities due to revenues and new opportunities, or is forced to conduct
off-farm activities due to factors that discourage the continuation of farming,
such as risky agriculture, bad soil, drought, land scarcity, etc. Thus, all factors
that determine participation in off-farm activities are defined as demand-pull or
distress-push (EFSTRATOGOLOU-TODOULO, 1990; ISLAM, 1997; BRIGHT 2000).
A more detailed description of the pull and push factors is presented in Table 2.
Table 2:
The pull and push factors of RNFE diversification
Pull Factors
Push Factors
Higher returns from off-farm
activities
Population growth
Higher returns on investment in
RNFE
Limited availability of quality land
Lower risk of non-farm activities
compared with farming
Decreasing farm productivity
A source of cash for households`
needs
Decreasing returns from farming
Economic opportunities: Social
advantages of urban centres
Insufficient access to farm input
markets
Urban life preferences of young
people
Exhausting of natural resources
Temporary circumstances and
shocks
Limited access to rural financial
markets
Source: DAVIS and PEARCE, 2001.
DAVIS and PEARCE (2001) suggest that in poor rural areas, people tend to switch
to non-farm activities due to its higher returns and lower risks. However, in spite
of having strong motivation to engage in non-farm employment, poor individuals often have limited access to RNFE due to a lack of resources
(REARDON, 1998). Therefore, participation in non-farm activities depends on a
household’s wealth. Less wealthy households prefer less risky activities, as it is
difficult for them to overcome shocks. The rate of RNFE also depends on rural
agro-climatic characteristics. Thus, households situated in areas with high-risk
Infrastructure as a determinant of rural non-farm employment
85
agriculture are "pushed" into RNFE to avoid negative shocks. On the other hand,
households situated in areas with low-risk agriculture are engaged in non-farm
activities due primarily to additional income opportunities.
Obviously, with an increase in returns to farming, RNFE will decline (DAVIS
and PEARCE, 2001). Moreover, demand-pull influence increases with the increase of incomes for poor or middle-income households, and for an increase in
demand of urban territories for rural products (ISLAM, 1997). Distinguishing between the reasons for participating in non-farm activities is important for authorities that conduct rural policies because it provides an understanding on whether a
given mode of livelihood provides prosperity or distress (DAVIS and PEARCE, 2001).
RNFE also differs across countries and the manner of promoting RNFE varies
with different levels of economic development. For developing countries, it is
necessary to increase poor households’ access to financial assets, improve the
quality of education and rural infrastructure, and take away land constraints
(REARDON, 1998). These measures, as well as experience in developed countries, can also be applied to countries in transition.
Agriculture in developed countries is characterised by increasing diversification.
Thus, some rural areas manage to specialise in tourism or rural products, for
example. And stress is placed on the peculiarities of a given region so that different policies are required and a multi-sectoral approach is needed (VON MEYER et al.,
2000).
To capture relationships between RNFE participation and explanatory variables,
most researches use a bi-variate probit model (LASS et al., 1992; LANJOUW, 1998;
ISGUT, 2002; DE JANVRY et al., 2005; HOYMAN and KIMHI, 2005). In addition to
a probit model, SERRA et al., (2003) estimate RNFE participation by a Tobit
model, as she supposes censoring of the samples due to the fact that most individuals are working on farm, but not off-farm.
A logit model produces results similar to probit estimation. The logit method was
applied in estimations carried out by BUCHENRIEDER (2003), while MDUMA (2003)
tried to estimate factors that determine the number of households in a cluster
(village) participating in wage employment. In order to do this, he employed a
Poisson regression.
In spite of the importance of the rural non-farm sector in agriculture and the
economy as a whole, little research has been done in this area for Ukraine; it is
thus of current interest for the Ukrainian economy. This paper determines the
factors that influence participation in off-farm activities, and particularly the role
of infrastructure in off-farm employment. Many studies on RNFE have been
conducted for other countries. But I want to conduct such research for Ukraine
in order to determine what factors influence RNFE participation and whether
estimates differ from those obtained for other countries.
86
Mariya Portyanko
An attempt to find the determinants of RNFE participation in Ukraine was carried out by NIVYEVSKIY (2005). However, that research does not convey much
information for policy-makers, as most of the variables used cannot be directly
influenced by the authorities. For example, such an important policy variable as
infrastructure is omitted from the model.
3
METHODOLOGY AND DATA DESCRIPTION
I employ research considering existing experience with RNFE estimation, but
apply it to the case of Ukraine. Considering previous studies on the RNFE issue
and my own suggestions, the following independent variables will be used in the
model: Age, gender, education, number of children, household size, land, geographical regions, infrastructure, and livestock.
Education consists of primary secondary education (8 years of studying at secondary school), high school secondary education (last 3 years of studying at seconddary school), basic higher education (4 years of education at a higher educational establishment), complete higher education (last 1-2 years of education at a
higher educational establishment) and basic technical education.
To account for a life-cycle effect, two variables, age and age squared, are introduced.
Under the variable "land", I consider land area per member of a household (in
0.01 hectares). To account for a change in probability of RNFE with an increase
of land per member, this variable will also be introduced in the power of 2.
Livestock means the presence of domestic animals, poultry or/and bees in a
household.
To capture the influence of geographical location on RNFE probability, I divided
the territory of Ukraine into five main geographical regions: Northern, Western,
Eastern, Southern, and Central2.
In the model, I added infrastructure as an important explanatory variable. This includes telecommunication, gasification, sewerage, and running water. This factor is
expected to be essential in determining RNFE participation (DAVIS, 2003).
Moreover, evidence of infrastructure impacting RNFE participation will allow
policy-makers to consider this fact in rural policy-targeting. As already mentioned, investment in Ukrainian rural development is currently of great impor-
2
Northern region: Zhytomyr, Kyiv, Rivne, Chernigiv, Sumy oblasts. Western region:
Zakarpattya, Lviv, Volyn, Ivano-Frankivsk, Ternopil, Chernivtsi oblasts. Eastern region:
Kharkiv, Donetsk, Lugansk oblasts. Southern region: Odesa, Mykolaiv, Kherson,
Zaporizhzhya oblasts and Crimea Autonomy.Central region: Vinnytsya, Khmelnitsky,
Cherkasy, Poltava, Kirovograd, Dnipropetrovsk oblasts.
Infrastructure as a determinant of rural non-farm employment
87
tance. This is even more evident when the process of Ukrainian WTO accession
is considered.
Aside from adding infrastructure as an explanatory variable, I also consider the
existence of livestock as a factor that contributes to the model specification.
Adding new explanatory variables will also allow to better specify the model
avoid omitted variable bias.
The dependant variable is the probability of RNFE. This either takes the value of
1 if a person is engaged in off-farming, or 0 otherwise3.
To find out what factors determine off-farm employment, bi-variable probit and
logit models will be used.
However, the problem of causality may arise in the estimation. Indeed, empirical
research shows a positive correlation between higher non-farm activity diversification and level of education, quality of infrastructure and other variables
(DAVIS and PEARCE, 2001). Nonetheless, the direction of causality is unclear.
It was found that panel data is more efficient in explaining causality, while
cross-sectional data sets fail to detect the direction of causality (ELLIS, 1998).
Data is available from State Committee of Statistics household survey, conducted
in 2004 in Ukraine, which gathered 10,059 total observations. Among these are
1,178 observations for rural areas covering all 25 regions, Kyiv and Sevastopol
cities.
After applying these methods of estimation, I expect the following results. Age
should have a positive influence on off-farm participation up to some point, and
then decrease the probability of RNFE participation (FERRIERA and LANJOUW,
2001). Gender should be significant and women are expected to have fewer
chances to be engaged in off-farm activities (WANDSCHNEIDER, 2003). Educated
people are expected to have more chances to start off-farm businesses
(WANDSCHNEIDER, 2003). However, the probability of non-farm employment
may change due to the level of education (NIVYEVSKIY, 2005). Results received
by NIVYEVSKIY (2005) show that a greater number of children decreases the
probability of RNFE participation. The larger the size of a household, the greater
is the probability of participation in non-farm activities (BEZEMER and DAVIS,
2002). Concerning the influence of land possession, NIVYEVSKIY (2005) found
that up to some point, land availability decreases the probability of RNFE participation, but then with an increase in land ownership, participation in non-farm
activities rises. Considering geographical regions, it was found (NIVYEVSKIY,
2005) that people who live in the Western region of Ukraine are the most likely
to participate in off-farm activities.
3
Only primary employment of the rural population is considered in my estimation.
Mariya Portyanko
88
As for the new factors added, I expect them to contribute to the model specification. Infrastructure quality is expected to increase the off-farm participation rate
(DAVIS, 2003). Using estimation results for Georgia, I expect that with the increase
in livestock, the probability of RNFE will fall (BEZEMER and DAVIS, 2002).
4
ESTIMATION RESULTS
The impact of each explanatory variable on the probability of RNFE is estimated
by marginal effects (elasticities). The marginal effects show how the probability
of non-farm employment changes when a particular explanatory variable changes
by one unit (or changes from 0 to 1 for the dummy variable) while keeping all
other explanatory variables constant. The elastisities are provided for a household
with optimal RNFE characteristics (according to probit and logit estimations).
Thus, this household is from the central region, with livestock and running water, and sewerage provided. The head of the household is a man with a high
school secondary education. All other explanatory variables are taken at their
average values. The probability of RNFE for this particular household is 58%
for the probit estimation, while for a household with all the characteristics taken
at the average values, the probability of RNFE is 38.7%.
The marginal effects of explanatory variables are presented in Table 3.
Table 3:
Estimated marginal effects (elasticities)
Household size
Number of children in a household
Age
Age squared
Gender*
Complete higher education*
Basic higher education*
Primary secondary education*
Probit
Logit
0.007
0.007
(0.016)
(0.016)
-0.013
-0.012
(0.023)
(0.022)
-0.001
-0.001
(0.011)
(0.010)
0.00001
0.00001
(0.0001)
(0.0001)
0.184***
0.186***
(0.049)
(0.058)
0.099**
0.097**
(0.043)
(0.045)
0.090**
0.082**
(0.038)
(0.039)
-0.089
-0.090
Infrastructure as a determinant of rural non-farm employment
(0.057)
(0.059)
0.015
0.013
(0.030)
(0.030)
0.013
0.008
(0.097)
(0.100)
-0.069
-0.063
(0.099)
(0.102)
0.041
0.042
(0.033)
(0.034)
0.086**
0.091**
(0.036)
(0.038)
-0.001***
-0.001***
(0.0002)
(0.0002)
1.5*10^-7***
1.5*10^-7**
(0.000)
(0.000)
-0.067
-0.070
(0.043)
(0.044)
0.086**
0.087**
(0.037)
(0.039)
0.118***
0.112**
(0.042)
(0.045)
0.099**
0.095**
(0.041)
(0.042)
0.267***
0.257***
(0.071)
(0.080)
0.145***
0.138***
(0.049)
(0.052)
Basic technical education*
Running water*
Sewerage*
Centralised gas*
Telephone*
Land per member of a household
Land per member of a household
Livestock*
Car*
Southern region*
Northern region*
Western region*
Eastern region*
Observations
1,178
Standard errors in parentheses
**
89
significant at 5%; *** significant at 1%
Note: (*) A dummy that takes values of either 0 or 1.
Source: Author’s calculations.
As mentioned previously, both models provided similar results.
90
Mariya Portyanko
As can be seen from the above table, coefficients such as household size, number
of children in a household, age, age squared, primary secondary education, basic
technical education, running water, livestock, centralised gas and sewerage appear
to be insignificant, even at a 10% level of significance.
For this particular household, ceteris paribus, a man is 18.4% more likely to be
engaged in RNFE than a woman. This result confirms the expectation that some
programs for females in rural areas are needed to encourage their participation in
non-farm activities. Somewhat unexpectedly, age appears to have a negative influence on off-farm participation up to some point, and then increases the probability of RNFE participation. This contradicts the results received by FERRIERA
and LANJOUW (2001) in their study. At the same time, this result is similar to
what NIVYEVSKIY (2005) found. However, the age coefficient in my estimation
is insignificant, even at a 10% level of significance. By taking into account the
negative impact of age on RNFE probability, it is obvious that programs aimed
at young rural people are important. Developing the rural financial market and
improving bank micro-crediting are crucial for this purpose.
The higher the level of education, the higher is the probability of RNFE. As can
be observed in Table 3, if the head of the household had a basic technical education, he or she would have 1.5% (1.4% in the logit model) more probability of
being non-farm employed, ceteris paribus. Basic higher education increases the
chances of RNFE by 9% (8.2% in the logit model) ceteris paribus. Receiving
complete higher education, ceteris paribus, increases RNFE probability even
further (9.9% for the probit estimation and 9.7% for the logit estimation). Thus,
we can conclude that, as was expected, receiving higher education raises the
chances of off-farm employment.
Issues that describe quality of infrastructure, such as running water and the provision of centralised gas – as was predicted – appeared to have a positive effect
on RNFE. Only the existence of sewerage decreases the chances of RNFE.
However, all these explanatory variables are insignificant, even at a 10% level
of significance. An exception is the availability of a telephone, which is significant at a 5% level and is positively correlated with RNFE participation. Thus,
having a telephone set increases the probability of RNFE by 8.6% (9.1% for the
logit estimation), controlling for all other explanatory variables. This result confirms our expectations about the positive impact of telecommunication on RNFE.
The probability of RNFE is also positively influenced by the number of cars in a
household. Each additional car in a household increases the probability of nonfarm employment by 8.6%, ceteris paribus.
It appears that the existence of livestock has no statistical influence on the probability of RNFE participation (at a 10% level of significance). However, as was
expected, an increase in livestock is negatively correlated with the probability of
RNFE.
Infrastructure as a determinant of rural non-farm employment
91
The availability of land per household member, as was expected, decreases the
probability of RNFE participation up to some point, but then with the increase in
land ownership, people tend to participate in off-farm activities. This result confirms the suggestion that it might be useful to remove land constraints.
Even though the coefficients of household size and number of children are statistically insignificant, they still show the direction of influence on RNFE participation. Thus, holding all other variables constant, the larger the size of a
household, the greater is the probability of participation in non-farm activities,
while each additional child, ceteris paribus, decreases the probability of nonfarm employment.
The probability of RNFE is influenced by the geographical location of a household. Thus, living in the Western region, ceteris paribus, increases the chances
of being non-farm employed by 26.5% (25.7% for the logit estimation) compared to the Central region. A household from the Eastern region also has a
greater probability of RNFE than those from the Central region – by 14.5%
(13.8% for the logit estimation). Compared to the Central region, living in the
Southern region increases the probability of RNFE by 11.8% (11.2% for the
logit estimation) and only by 9.9% (9.5% for the logit estimation) for the Northern
region. The reason for the high off-farm probability of participation in the Western
region may be the fact that by tradition, the Western region is less agrarian compared to other regions.
5
CONCLUSIONS AND SUGGESTIONS
Promoting RNFE is an important issue in the development of rural areas, and
includes increasing the quality of infrastructure, rural inhabitants’ education
level, removing land constraints, etc.
This is why RNFE should be carefully considered when the Ukrainian government addresses rural development policy; their main task is to switch from
trade-distorting measures and to developing budget expenditures that have positive long-run effects. This would not only guarantee the sustainable development of rural areas, but also accelerate the process of Ukrainian WTO accession.
Even if variables that constitute infrastructure, for example the availability of
running water and gasification, appeared to be insignificant, the direction of
their influence can still be taken into account. Thus, the availability of running
water, gasification and telecommunication has a positive effect on the probability
of RNFE. Therefore, infrastructure development is an important issue. Moreover, improving rural infrastructure will make the countryside an attractive region
for business. Therefore, the government should take steps to provide rural areas
with gas, electricity, roads, and telecommunication facilities. Furthermore, rural
educational programs should be undertaken, as they provide more chances for
92
Mariya Portyanko
the rural population to increase their incomes and standards of living. Also, it is
necessary to increase poor households’ access to financial assets. Considering
the fact that women are less active in RNFE participation, certain rural development policies should make their access to off-farm activities easier. All these
policies will increase RNFE opportunities and thus, permit the diversification of
income sources, raise rural inhabitants’ quality of life and make rural areas an
attractive place to live.
REFERENCES
BERDEGUE, J. A., REARDON, T., ESCOBAR, G. (2000): Policies to promote non-farm
rural employment in Latin America, Overseas Development Institute, London.
<http://www.odi.org.uk/nrp/55.pdf>.
BEZEMER, D., DAVIS, J. (2002): The rural non-farm economy in Georgia: Overview of
Findings, Report No 2729, Natural Resources Institute, UK, p. 24.
BRIGHT, H., DAVIS, J., JANOWSKI, M. et al. (2000): Rural non-farm livelihoods in
Central and Eastern Europe and Central Asia and the reform process: A literature
review, Report No 2633, Natural Resources Institute, UK.
BUCHENRIEDER, G. (2003): Poverty impacts and policy options of non-farm rural employment, paper presented at International Conference of Agricultural Economics
(IAAE) held in Durban, South Africa, 16.-22.08.2003.
CHOI, J.-S. (2004): Policies and measures for promoting rural non-farm employment,
report of the APO Seminar "Non-Farm Employment Opportunities in Rural Areas".
DAVIS, J. (2003): The rural non-farm economy, livelihoods and their diversification:
Issues and options, Report No 2753, Natural Resources Institute, UK.
DAVIS, J., PEARCE, D. (2001): The non-agricultural rural sector in Central and Eastern
Europe, Report No 2630, Natural Resources Institute, UK.
EFSTRATOGLOU-TODOULO, A. (1990): Pluriactivity in different socio-economic contexts: A test of the push-pull hypothesis in Greek farming, Journal of Rural Studies,
Vol. 6, pp. 407-413.
ELLIS, F. (1998): Rural livelihood diversification: Framework and categories, Unpublished paper prepared for the Natural Resources Institute, Chatham, UK.
FERREIRA, F., LANJOUW, P. (2001): Rural nonfarm activities and poverty in the Brazilian Northeast, World Development, Vol. 29, pp. 509-528.
ISGUT, A. E. (2002): Nonfarm income and employment in rural Honduras: Assessing the
role of location factors, Department of Economics, Wesleyan University, Middletown, CT.
ISLAM, N. (1997): The non-farm sector and rural development – Review of issues and
evidence. Food, Agriculture and Environment Discussion Paper No 22, Washington
DC, IFPRI.
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JANVRY, A., SADOULET, E., ZHU, N. (2005): The role of non-farm incomes in reducing
rural poverty and inequality in China, Department of Agricultural & Resource
Economics, UCB, CUDARE Working Paper No. 1001, <http://repositories.cdlib.
org/are_ucb/1001>.
LANJOUW, O. J., LANJOUW, P. (1995): Rural nonfarm employment. A survey, Background paper for World Development Report.
LANJOUW, P. (1998): The rural non-farm sector in Ecuador and its contribution to
poverty reduction and inequality, Policy Research Department, The World Bank.
LANJOUW, P. (1999): The rural non-farm sector: A note on policy options, Development Economics Research Group, The World Bank.
LASS, D., GEMPESAW II, A. C. M. (1992): The supply of off-farm labor: A random
coefficients approach, American Agricultural Economics Association.
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NIVYEVSKIY, O. (2005): Rural non-farm employment in Ukraine, Institute for Economic
Research and Policy Consulting in Ukraine, German Advisory Group on Economic
Reform, <http://ierpc.org/ierpc/papers/u13_en.pdf>.
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for FAO.
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and off-farm supply of labor, unpublished manuscript.
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ment dynamics in the EU: Key findings for policy consideration emerging from
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Hague, Netherlands.
WANDSCHNEIDER, T. (2003): Determinants of access to rural non-farm employment:
Evidence from Africa, South Asia and transition economies, Report No 2758, Natural
Resources Institute, UK.
RURAL FINANCIAL MARKETS
Sustainable rural development: What is the role of the agri-food sector?
MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central & Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 97-112.
INFORMAL LOANS – ALTERNATIVES OR SUPPLEMENTS TO
BANK CREDIT FOR POLISH FARMS
ALINA DANILOWSKA∗
ABSTRACT
The aim of the paper is to examine the different dimensions of informal loans in
Polish agriculture. The results of the investigation imply that informal lenders
were important sources of financing farmers’ activity in Polish agriculture during
the examined period. A significant percentage of borrowing farms took formal
and informal loans simultaneously, mainly for "productive purposes". The terms
of informal loans were considerably more advantageous than formal loans with
respect to form, interest and collateral.
Keywords: Credit, formal loans, informal loans, farmers, Poland.
1
INTRODUCTION
Among the various sources of financing the agricultural activity of farms and
consumption expenditure of farmers’ households, the role of bank credits is especially important. As a result, the creation and maintenance of a stable system of
rural financial institutions is one of the main aims of agricultural policy.
Researchers in this field focus on the barriers that constrain the development of
rural financial intermediaries (DESAI and MELLOR, 1993), intervention on credit
markets (BESLEY, 1998), the results of credit programs, or positive phenomena
such as the Grameen Bank of Bangladesh (ROBINSON, 1998). The problem of
informal sources of loans are often discussed in the context of the underdevelopment of formal financial institutions, which limits access to formal credits. Most
literature on this subject deals with informal loans in developing economies.
However, informal loans exist in developed and post-communist countries as
well. Polish agriculture provides a good example of the viability of the informal
loans phenomenon.
Considering the network of bank branch offices or terms of credits granted
mainly on preferential terms, Polish farmers have rather good access to bank
∗
Department of Economics and Economic Policy, Warsaw Agricultural University, Warsaw,
Poland. Email: [email protected]
Alina Danilowska
98
credits1 (DANILOWSKA, 2005)2. From 1995-2001, about 50 % of farms examined
by the Institute of Agricultural and Food Economics took bank credits every
year. However, the data shows that during that period, about 40% of the aforementioned farmers borrowed from individuals and various non-financial organisations. The aim of the paper is to examine the different dimensions of informal
loans in Polish agriculture. The analysis focuses on these questions: (i) how important is the informal sector as a source of loans for Polish farmers, (ii) what
are the formal and informal loans used for, (iii) what are the determinants of
taking formal and informal loans.
The paper is organised as follows. First, the classification of loans by sources is
presented. This is followed by analyses of the scope of informal loans in Polish
agriculture in comparison with bank credits. Next, characteristics of formal and
informal loans with respect to purposes and terms are given. Following that, an
econometric model is applied to identify the micro-determinants that lead farmers
to take formal and informal loans. Conclusions are drawn in the last section.
1.1 Materials and methods
The examined period covers 7 years, from 1995 to 2001, and the information
and data are taken from two main sources: (i) a survey by the author on the purposes of loans, terms of loans from different sources, and the implementation of
loan contracts, (ii) the Institute of Agricultural and Food Economics (IAFE).
The survey on terms of loans was carried out from January to March, 2004, and
involved a systematic study of farms by the Institute of Agricultural and Food
Economics. Specifically, it examined farms which were in debt due to informal
loans as of 31 December 2001. Because a portion of those farms were in debt
not only due to informal loans, but to bank credits as well, it was assumed that
they provided the information about terms of bank credits as well. Finally,
230 farms from all over Poland gave information about the purposes, terms and
implementation of 612 loan contracts: 362 bank credits, 108 loans granted by
individuals, and 142 loans extended by various non-financial organisations.
Additional information about the finances of the farms under investigation and
their borrowing activity from 1995-2001 was gathered from the Institute. Mixed
methods of analysis were then used. The descriptive method, with elements of
the comparative method, is used to characterise the loan market. Moreover, the
panel data analyses help to examine the microeconomic determinants of why
farmers take formal and informal loans.
1
2
In the examined period.
This does not mean they are not credit-rationed at all (see PETRICK, 2004).
Informal loans – Alternatives or supplements to bank credit for Polish farms
2
99
FORMAL AND INFORMAL LOANS: CLASSIFICATION
The existence of informal lending is derived from a lack of access to formal
financial institutions. The formal credit market does not develop smoothly in
poor rural areas because of the many barriers that formal intermediaries meet.
The lack of collateral, high transaction costs for small loans, enforcement problems, underdevelopment of complementary institutions, and imperfect information (BESLEY, 1998; ARYEETEY and UDRY, 1995) all create space for informal
lenders. These failures occur not only in the economies of developing countries,
but in post-communist and in developed countries as well. However, in developed
economies, their scope and scale are considerably smaller compared with developing ones.
MCKERNAN et al., (2005) presented a review of loan classifications by type of
sources. Three of the six presented classifications categorised the loans into
three groups: Formal, informal, and "others", while the three other classifications
considered loans as only formal or informal. Researchers who classify loans into
three groups consider loans granted by commercial and agricultural development
banks as formal loans, whereas loans granted by micro-credit government cooperative structures, NGOs, Grameen-type banks, and local groups are considered
"others". Other authors include these loans in the group of formal loans.
Informal loans is a very broad category. According to the motives for lending,
informal loans are often divided into two basic types: Commercial loans and
noncommercial loans (ROBINSON, 1994, p. 46; NISBET, 1967, p. 73). The first are
granted by moneylenders, landlords, traders, employers, commodity wholesalers,
and retailers, while the latter are given by relatives, neighbours, friends or some
form of rotating savings and credit associations. Commercial lenders are interested in profits and/or benefits from their lending activities. The benefits can be
in different forms, such as interest payments (BASU, 2004), borrowers’ defaults
(ROBINSON, 1994, p. 57) or labour at less than opportunity costs (SRINIVASAN,
2004). Non-commercial loans, on the other hand, are extended without financial
interest, but they often entail other types of social, political and economic obligation (ROBINSON, 1998, p. 394).
In this analysis, the sources of loans (as well as the loans themselves) are classified into two main groups: Formal and informal. Formal loans are granted by
two types of banks that operate in Polish rural areas: Commercial banks and cooperative banks. Informal loans involved all loans extended by no bank sources.
The group of informal sources is divided into two subgroups: Individuals and
non-financial organisations. This classification is derived from the motives to
lend. The reasons for lending in the case of individuals are not of an economic
character, while for non-financial organisations they are.
Alina Danilowska
100
Various dimensions of informal loans have been analysed, for example BRAND,
HOSIOS (2004) and BECKMANN, BOGER (2003) examined enforcement issues,
BELL (2005) and MCKERNAN et al., (2005), examined interactions between institutional and informal credit sectors, and BRAVERMAN, STIGLITZ (2004), ZELLER
(1994) investigated credit rationing by informal lenders. This paper provides
comparative analyses of formal and informal loans, as these are the alternatives
that Polish farmers faced.
3
THE SOURCES OF LOANS IN POLISH AGRICULTURE
From 1995-2001, the farms examined by the IAFE borrowed loans from different
sources – formal (banks) and informal (individuals and non-financial organisations. The scope and comparative role of each source can be evaluated by the
analysis of how many farmers borrowed from them.
Table 1:
Share of farms being examined by IAFE that borrowed from
different sources in 1995-2001 (%)
Specification
Banks
Individuals
Non-financial organisations
1995
34.7
22.8
34.7
1996
52.9
25.7
13.4
1997
53.4
24.0
14.5
1998
52.5
23.6
15.2
1999
54.0
26.1
17.3
2000
57.8
28.2
16.7
2001
51.9
25.6
14.4
Sources: Author’s calculation based on IAFE data.
Data in Table 1 indicates that banks were the most popular source of credit for
farmers. Since 1996, each year between 50-55% of farmers took bank credits. In
second place were individuals, with a 25% share. Non-financial organisations
extended loans year-by-year to about 15% of farms. In comparison, the results
of a World Bank survey indicate that in 1999, about 33% of investigated farms
took bank credits (REPORT, 2001, p. 76). That ratio is considerably lower than
that of the group of farmers reviewed by IAFE. This could have been influenced
by the fact that the group of farms that were examined by the Institute involved
larger and market-oriented farms. The report states that of the largest farms in
Poland, 12% borrowed from non-financial organisations (REPORT, 2001, p. 68).
The data suggests that informal loans were quite popular among Polish farmers.
As NIKOLOV (2004) reported, a similar situation occurred in another postcommunist country – Bulgaria. The percentage of Bulgarian rural households
that are served by informal lenders is estimated at 29%.
To obtain additional information about the role of each economic source in
farmers’ finances, research into the structure of total values of loans by type of
lenders was carried out (Table 2).
Informal loans – Alternatives or supplements to bank credit for Polish farms
Table 2:
101
The structure of the total value of loans taken by farms
examined by IAFE, by source (%)
Specification
Banks
Individuals
Non-financial organisations
Total
1995
68.1
15.9
16.0
100.0
1996
86.0
9.9
4.1
100.0
1997
88.9
8.2
2.9
100.0
1998
82.1
12.5
5.4
100.0
1999
84.5
10.9
4.6
100.0
2000
83.6
11.8
4.6
100.0
2001
80.9
15.6
3.5
100.0
Sources: Author’s calculation based on IAFE data.
Results of the data analysis from Table 2 support the tendency suggested by the
percentage of farms borrowing from formal and informal sources. That is, banks
extended the largest portion of the total value of loans. Every year their share
was high, but it decreased during the examined periods, so in the last examined
year it was 80%. In second place were informal loans, and in third were loans
from different non-financial organisations. The data from Tables 1 and 2 indicates that the value of bank credits was much higher than value of informal loans.
Data from the author’s survey showed that the average value of the examined bank
credits was about 2.8 times higher than of loans from individuals, and 3.2 times
more than loans from various non-financial organisations. In 1995, the share of
bank credits was considerably lower than in the following years. This was
probably due to the very high level of bank interest rates, which discouraged
farmers from taking credits, and the fact that the system of preferential credits
(very influential in the following years) was at the beginning stage of its operations.
The interesting question is whether farms are simultaneously active in both informal and formal markets. The answer can help to discover whether the farmers
who borrowed from informal sources used these sources because of a lack of
access to bank credits, or whether they were searching for another source of financial means, aside from bank credits.
Table 3:
Share of farms borrowing from given sources from 1995-2001 (%)
Specification
Farms that took loans
of which:
Only formal
Only informal
formal and informal
1995
100.0
1996
100.0
1997
100.0
1998
100.0
1999
100.0
2000
100.0
2001
100.0
40.5
36.2
23.3
45.6
17.8
36.6
49.2
17.7
33.1
48.0
18.4
33.6
42.3
17.3
40.4
44.9
16.2
38.9
46.4
18.9
34.7
Sources: Author’s calculation based on IAFE data.
Data (Table 3) showed that each year, more than 80% of borrowing farmers took
bank credits. This implies that they have quite good access to formal sources of
loans. Further, 30-40% of farms (researched by IAFE) that took loans in the
102
Alina Danilowska
examined period used formal and informal sources simultaneously. This indicates that many farmers were active in looking for financing possibilities for
their expenses. A quite high percentage of farmers borrowed only from informal
sources of loans; it is ambiguous whether they had limited access to formal loans
or whether they preferred informal sources. The internal structural analyses of
each source, in terms of informal and formal loans, that are contained in the next
part of the paper can clarify this problem.
4
GROUP STRUCTURE OF INFORMAL AND FORMAL LENDERS
In the Polish formal credit market, two types of banks operate: Commercial
banks and cooperative banks. Cooperative banks held a monopolistic position on
the rural credit market during the centrally-planned economy. However as data
indicates (Table 4) these banks are still the main formal source of credit for
farmers in the market economy. A comparison of the credit structure by number
with the credit structure by value shows that credits from cooperative banks
were of smaller value than from commercial ones.
The informal loan market in rural Poland is larger in number of participants than
the formal market, and much more heterogeneous. Two groups of lenders grant
loans to Polish farmers: Commercial lenders and noncommercial lenders like
relatives, neighbours and friends. However, the feature of the Polish lenders
which is lacking compared to similar groups in developing countries is the lack
of moneylenders3 or landlords, who are important sources of loans in these
countries. In the group of loans from individuals, loans from relatives are the
most important source when considering their share in number and value of
loans. A high number of loans from relatives indicates that farmers were afraid
of default. Were this to happen, the farmers have very limited possibilities to
make debtors repay debt. BECKMANN, BOGER (2003, p. 417) reported that only
38.5% of Polish farmers declared court as way of enforcing contracts. And
nearly 70% of farmers told the author that they do nothing to recoup loans.
3
Moneylenders were active in rural areas before the second war.
Informal loans – Alternatives or supplements to bank credit for Polish farms
Table 4:
103
The number and value structure of loans, grouped by source
of loans
Sources of loans
Structure (%)
by number
Bank credits
100.0
1
by value
100.01
of which:
- Cooperative banks
- Commercial banks
78.4
62.8
21.6
37.2
Loans from individuals
1001
1001
77.2
68.6
9.5
20.0
13.3
11.4
0.0
0.0
100.0
100.02
16.9
9.8
25.3
34.5
33.8
34.5
24.0
21.2
of which:
- Relatives
- Neighbors
- Friends
- Commercial lenders
Loans from non-financial organisations
of which:
- Employers
- Wholesaler and retailer of investment and working
capital
- Manufacturers
- Others
Only loans with answers. 2 The share of one loan in total value of loans from
non-financial organisations was 50%, so this loan was not taken into consideration.
Source: Author’s calculations based on the author’s survey of 612 loans.
Notes:
1
The group of non-financial organisations includes very different agents like
employers, wholesalers and retailers of investment goods and working capital,
shops with household equipment, farmers unions, processors, etc. The manufacturers that purchase agricultural products are the most important source of loans
in that group.
5
PURPOSE OF THE LOANS
Data reported in Table 5 indicates that most credits and loans from all investigated sources were taken for "productive purposes". However, the percentage of
consumption loans from informal sources was considerably higher than from
banks. It is remarkable that in each source, there was nearly the same percentage
of investment loans. Although the share of consumption loans in total number of
informal loans was quite high, it is worth indicating that it was lower than shares
of loans for working capital.
Alina Danilowska
104
Table 5:
Purpose of loans by the type of sources
Specification
Loans and credit total
of which:
- Agricultural investments and
residential building
- Working capital
- Consumption
Bank
Individuals
Number
100.0
100.0
Structure of (%)
NumValue
Number
ber
100.0
100.0
100.0
100.01
43.9
80.5
48.2
56.3
45.8
45.6
50.8
5.3
18.5
1.0
31.4
20.4
35.2
8.5
31.0
23.2
41.3
13.1
Value
Non-financial
organisations
Value
Source: Author’s calculations based on the author’s survey of 612 loans.
The results of loan value structure analyses by purpose are generally in line with
the tendency observed in number structure. The role of credits and loans taken
for financing production and investment is even higher than that which the
structure of loan numbers by purpose indicated. The shares of investment credits
from banks and loans from individuals in all loans’ total values exceeded 50%,
and in the case of bank credits, even 80%. The shares of consumption credits
and loans were much smaller in every examined group compared with the previous
classification, and especially low in bank credits. The very high share of investment credits in bank credits was due to the well-developed system of preferential credits that operated in Poland during the examined period. The bank consumption credits were not popular because of their high interest rate, so the borrowers preferred informal sources for financing consumption.
Results on the purpose of informal loans in Poland are not consistent with relevant findings concerning developing countries, where informal loans are taken
mainly for consumption. They are, however, in line with results regarding bank
credit purposes (BESLEY et al., 2001).
6
THE TERMS OF BANK CREDITS AND INFORMAL LOANS
Comparisons of the terms upon which formal and informal loans were granted
can help to understand the nature of each alternative and clarify the motives for
applying for all types of loan. Of course it is necessary to remember that poorer
borrowers, especially in developing countries, often do not face alternative
sources of loans; they have only limited choices, generally in the frame of informal loans. The terms of loans are evaluated by estimating the percentage of
loans that are characterised by the chosen features. It is worth noting that this
data can be treated as an indicator of the borrowing costs of each type of loan.
Informal loans – Alternatives or supplements to bank credit for Polish farms
Table 6:
105
Terms of formal and informal loans by sources
Specification
Banks
Individuals
Loan contracts in written form (%)
Loans with collateral (%)
Loans repaid by installments (%)]
Loans with interest of any kind (%)
100.0
91.2
60.5
100.0
5.6
0.9
55.3
17.1
Non-financial
organisations
91.5
49.3
83.8
35.7
Source: Author’s calculations based on the author’s survey of 612 loans.
Data in Table 6 shows that the terms of loans vary across the type of loan sources.
Bank credits are the most formalised, while nearly no loans from individuals are
formal. Collateral is generally required by banks and a portion of non-financial organisations. Only one loan from individuals was granted with collateral. Method of
repayment is the only aspect in which the differences between loans from the three
sources are not significant; most loans were repaid by installments. This method of
repayment is more advantageous for borrowers, especially when the loan is repaid
by product deliveries. The high percentage of loans being repaid in this way within
the group of non-financial organisations is an effect of many lenders, such as employers and manufacturers. In the literature concerning informal loans in developing countries, the problem of very high interest rates is discussed. Nevertheless,
that problem concerns loans granted by commercial informal lenders like moneylenders or landlords. Non-commercial loans are extended without any interest,
often with negative real interest rates (NISBET, 1967). In the investigated group of
farms, the repayment of loans from individuals were generally paid in kind (food,
sweets). Some lenders from the group of non-financial organisations were not interested in receiving financial interest payments. Instead, they achieved benefits
in other ways; for example, for manufacturers, high quality raw materials are very
important, so they granted loans to help farmers meet quality requirements
(DRIES and SWINNEN, 2005; DANILOWSKA, 2006).
7
THE DETERMINANTS OF TAKING INFORMAL LOANS AND BANK
CREDITS
Analysis of the scale of different loan source usage showed that quite a high proportion of farmers took formal or informal loans. The question is whether there is
a connection between taking loans from various sources and farm economics or
farmers’ characteristics. It is necessary to note that the act of a farmer taking a
loan is an effect of applying for a loan, and the willingness of a lender to lend.
Some variables exhibit their importance for lenders when they come to a decision
to lend. To clarify that problem, the probit estimation model was applied. From
the farms analysed by IAFE from 1995-2001, only those that were examined
every year during that period were qualified for analysis (balanced sub-panel).
There were 657 farms that met this condition.
106
Alina Danilowska
In the analysis, the two-way mixed probit model was chosen (DEMIDENKO,
2004).
7.1 The choice of variables to model
The fact of taking a loan is a dependent variable. It is of a dichotomous character
and takes the value of 1 if a farmer obtains the loan during a given year, or 0 if
not.
As determinants of taking loans, a set of independent variables (with expected
signs in parentheses) was chosen. These are related to: (i) farmer’s characteristics (ii) the economics of the farm. Among the determinants, 3 are dichotomous
in character: Level of education (1 – secondary and higher; 0 – less than secondary); gender (1 – man; 0 – woman); fact that farmer is a shareholder in a cooperative bank (1 – yes; 0 – no). Descriptive statistics of all variables used in the
model are displayed in Table 7.
To characterise the farmer, the following features were chosen: Age of farmer
(3-)4, gender (3?), level of education (+; ?, +), fact of being the shareholder of
cooperative bank (+; -; -).
The economics of the farm are represented by: Land area (owned and leased)
(+; -; +), the value of fixed assets (+; -; +), labour resources (3+), purchased
inputs (3+), consumption of chemical fertilisers kg/1 ha of agricultural land
(3+), value of market output/1 ha of agricultural land (3+), share of animal
output in final agricultural output (3+), investment value (3+), agricultural income (3+), income from nonagricultural activity (?; -; -), income from work
outside farm (?; ?; +), social benefits (3?), savings (3-).
4
This means that a negative influence is expected for each type of loan; for some other
signs, the following order was applied: Banks, individuals, non-financial organizations.
Informal loans – Alternatives or supplements to bank credit for Polish farms
Table 7:
107
Description of variables used in probit model
Variable
Age (year)
Gender
Level of education
Land area (own and leased)
Value of fixed assets (ths PLN)
Resources of labour (number)
Purchased inputs (ths PLN)
Consumption of chemical fertilisers
(kg/1 ha)
Value of market output (ths PLN/1 ha)
Share of animal output in final
agricultural output (%)
Investment value (ths PLN)
Agricultural income (ths PLN)
Income from nonagricultural activity
(ths PLN)
Income from work outside farm
(ths PLN)
Social benefits (ths PLN)
Savings (ths PLN)
Farmer is a shareholder of cooperatives
bank
Mean
Min.
45.6
0.88
0.37
17.11
182.42
2.9
18.80
123.4
Std.
Dev.
10.6
0.33
0.63
34.41
135.33
1.3
38.44
79.3
Max.
2.45
69.7
1.75
26.7
0.0
0.0
21.92
1.0
4599
4599
10.08
15.12
0.63
25.81
23.79
4.16
0.0
-38.06
-28.90
643.90
644.00
206.76
4599
4599
4599
3.48
6.72
0.0
69.14
4599
3.91
11.70
0.64
4.82
39.55
0.48
0.0
48.08
0 1130.39
0
10
4599
4599
4599
18
79
0
1
0
1
1.07
1203
7.35 1837.2
0.1
8
0.82 1168.29
0.0
408
Valid
obser.
4599
4599
4599
4599
4599
4599
4599
4599
Source: Author’s calculations based on IAFE data.
7.2 Results of model
Results of the applied model imply that the influence of chosen determinants for
obtaining bank credits was rather small. The level of R^2_LR is only 9%
(Table 8). From 17 modeled variables, only 11 are statistical significant. These
include: Age (-), level of education (+), labour resources (+), purchased inputs
(+), consumption of fertiliser per 1 ha of agricultural land (+), market output per
1 ha (-), investments (+), income from work outside the farm (-), social benefits
(-), value of savings (+), membership in a cooperative bank (+).
Alina Danilowska
108
Table 8:
The probit estimates of taking bank credit
(only significant variables)
Coefficient
Age
Level of education
Resources of labour (number)
Purchased inputs( ths PLN)
Consumption of chemical
fertilisers kg/1 ha
Value of market output
(ths PLN1 ha)
Investment value ( ths PLN)
Income from work outside
farm (ths PLN)
Social benefits (ths PLN)
Savings (ths PLN)
Farmer is a shareholder of
cooperatives bank
Model significance
R^2_LR
Notes
Source:
1
Std. Er- z-value
ror
-1.34E-02
1.86E-01
1.07E-01
8.77E-03
1.96E-03
3.86E-03
8.74E-02
3.06E-02
2.10E-03
5.01E-04
-3.4612
2.1242
3.4935
4.1716
3.9178
0.0005
0.0337
0.0005
3.0E-05
8.9E-05
Marginal
effect1
-0.522%
7.256%
4.183%
00%
0.08%
-8.3E-02
2.69E-02
-3.0831
0.0020
-3.0%
1.91E-02
-16.0
2.04E-03
5.83
9.3359 2.20E-16
-2.7525 0.005915
1.0%
-1.0%
-2.37E-02
-1.02E-02
6.85E-01
8.39
1.69E-03
8.90E-02
-2.8286 0.004676
-6.0506 1.44E-09
7.6975 1.39E-14
-1.0%
0,0%
26.76%
Pr(>|z|)
p-value= 3.705E-81
=0.091
Due to nonlinear dependencies, the marginal effect is calculated in percentage
points as sample mean. For the variables of dichotomy character, marginal effect
was calculated by changes from 0 to 1.
Author’s calculation based on author’s survey.
In most cases, the direction of influence is as it was assumed, except for market
output/ha. This indicates that the more efficient production is, the less willing a
farm is to take credit. The investigation settled doubts about gender (nonstatistically significant), and about the social benefits of income from work outside the farm. It is somewhat surprising that the influence of variables such as
land area, value of fixed assets or agricultural income are not statistically significant. Instead, they indicate the potential of farm and collateral for banks.
Informal loans – Alternatives or supplements to bank credit for Polish farms
Table 9:
109
Probit estimates of taking loans from individuals
(only significant variables)
Coefficient
Labour resources (number)
Purchased inputs (ths PLN)
Investment value (ths PLN)
Social benefits (ths PLN)
Savings (ths PLN)
Model significance
R^2_LR
Std. Er- z-value
ror
8.36E-02
28.2
2.960
2.99E-03
1.34E-03
2.236
5.22E-03
1.09E-03
4.796
-1.54E-02 7.27E-03
-2.117
-5.79E-03 1.39E-03
-4.177
p-value= 3.569E-14
=0.016
Pr(>|z|)
0.003
0.025
1.62E-06
0.034
2.96E-05
Marginal
effect1
2.259
0.08
0.14
-0.42
-0.16
Notes: 1 As in Table 8.
Source: Author’s calculation based on author survey.
In the case of loans from individuals, the level of R^2 is very small – about
0.016 (Table 9). Only 5 of the 17 variables were statistically significant. Among
these, there were no variables that represented the demographic characteristic of
farmers. The significant variables have the expected sign, but their influence on
the dependent variable were very small.
Table 10:
Probit estimates of taking loans from non-financial
institutions (only significant variables)
Gender
Level of education
Labour resources (number)
Purchased inputs (ths PLN)
Value of market output/1 ha
Investment value (ths PLN)
Agricultural income
(ths PLN)
Income from work outside
farm (ths PLN)
Savings (ths PLN)
Farmer is a shareholder of
cooperatives bank
(1 – yes, 0 – no)
Model significance
R^2_LR
Coefficient
-1.90E-01
1.22E-01
6.41E-02
2.98E-03
5.70E-02
2.21E-03
-3.32E-03
Std. Error
1.16E-01
8.06E-02
3.10E-02
1.57E-03
2.58E-02
1.15E-03
2.39E-03
z-value
Pr(>|z|)
1.23E-02
-1.638
1.514
2.064
1.904
-2.210
1.925
-1.389
0.101
0.130
3.90E-02
0.057
2.71E-02
5.43E-02
1.65E-01
5.32-03
2.316
0.021
0.00%
-5.35E-03 2.19E-03
1.49E-01 8.78E-02
-2.442
1.696
0.015
0.090
0.00%
2.50%
p-value=2.001E-10
=0.014
Notes: 1 As in Table 8.
Source: Author’s calculations based on author’s survey.
Marginal
effect1
-3.19%
2.05%
1.08%
0.00%
-1.00%
0.00%
0.00%
Alina Danilowska
110
The results of the probit model for loans from non-financial organisations
showed (Table 10) that 10 variables are statistically significant. Their signs are
as expected, except farm membership in a cooperative bank. What is more, in
the case of these loans, gender is statistically significant. Its influence is very
low, but it signals that this direction of investigation is worth examining.
8
CONCLUSIONS
The results of investigating the Polish loan market imply that informal lenders
were important sources of financing farmers’ activity in Polish agriculture during
the examined period. This is consistent with findings about other post-communist
countries and developing countries. However, the role of informal loans is very
different. In Poland, informal sources of lending play supplementary roles to
banks, while in developing countries they are the main source. It is expected that
informal loans will retain their importance in the future, as farms increasingly
integrate with their suppliers and buyers of their products.
The group of formal and informal lenders consists of the same type of lenders as
in developing countries, with one exception. There are no moneylenders or landlords in Poland nowadays, while in developing countries they are very important
sources of loans in rural areas.
The terms of formal and informal loans varied considerably. Moreover, the
terms varied across the main groups of informal loans. The terms of informal
loans were more advantageous for farmers compared with the terms of bank
credits. This implies that farmers would prefer informal loans (especially from
individuals) to formal loans. However, the informal sources offered loans of
rather small value, which could be a problem for large expenses, for example
investment projects. Thus, informal loans would not be sufficient.
Results on the level of influence that farm economics and farmers’ characteristics have on taking loans are somewhat surprising: They showed that neither
demographic features nor farm economics are important. Considering that loans
were taken mainly for investment and production, features of entrepreneurship
and creativity seem to be important.
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<www.econ.yale.edu/~cru2//papers>.
BASU, K. (2004): Rural credit markets: The structure of interest rates, Exploitation,
and Efficiency, in: BARDHAN, P. (ed.): The Economic Theory of Agrarian Institutions, Clarendon Press, Oxford University Press, pp. 203-220.
BECKMAN, V., BOGER, S. (2003): Courts and contract enforcement in transition agriculture: Theories and evidence from Poland, Proceedings of the 25th International
Informal loans – Alternatives or supplements to bank credit for Polish farms
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MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central & Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 113-127.
DEVELOPMENT OF INNOVATIVE TECHNOLOGIES IN RURAL FINANCE
ANNA BONDARENKO,* ROMAN KOSODIY,** EUGENIY MISHENIN***
ABSTRACT
Expanding financial service coverage for rural residents is determined by the
innovative potential of the financial sector. In this context, attention should be
paid to the obvious need for improvement of rural financial institutions. Indeed,
most rural residents do not have access to formal mechanisms of risk management; as a result, considerable credit risk is shifted to creditors. Therefore, special emphasis should be placed on strengthening the relevant institutional environment, including the development of rural finance, the creation of adequate
infrastructure, and a more enabling policy environment. In this context, applying
new financial technologies in Ukraine is critically important for reducing the
default risk for borrowers, which would simultaneously improve access to finance for many rural residents.
Keywords: Rural financial system, microloan, innovative technologies.
1
INTRODUCTION
There is a growing understanding that developing countries’ financial systems
should be more open to their rural populations, including those with low incomes. In general, providing financial services to rural residents is located in a
niche that is not sufficiently integrated into the main financial system. This isolation negatively affects both the coverage and efficiency of such services. High
transaction costs associated with the provision of financial services to rural
households (partly because they possess small amounts of money, live in
sparsely populated areas and rarely have a credit history), are the reason why
many representatives of the formal financial sector still view microfinance activities as non-profitable. Most rural residents do not have access to formal
mechanisms of risk management; as a result, considerable credit risk is shifted to
creditors.
*
Sumy National Agrarian University, Ukraine. Email: [email protected]
Sumy National Agrarian University, Ukraine. Email: [email protected]
***
Sumy National Agrarian University, Ukraine. Email: [email protected]
**
114
Anna Bondarenko, Roman Kosodiy, Eugeniy Mishenin
In this context, attention should be paid to the innovative potential of the financial sector, which determines the ability to expand financial service coverage for
rural residents. Twenty years ago, the main tasks for the financial sector when
dealing with the rural population were related to finding methods of providing
and repaying loans (not backed by collateral) for rural entrepreneurs and low
income households. Today, after major success in this area, a new systemic task
has emerged – the search for ways to integrate a full range of financial services
for the rural population into the traditional financial system.
Hence, the main task in rural development is the elimination of barriers between
the rural population and the formal financial sector. Since rural customers represent a huge potential market for retail financial services, more and more financial intermediaries all over the world are successfully entering this market.
However, it is obvious that financial intermediaries would not set the goal of
providing services to the rural population until they find ways of profitably providing services to these clients. This requires the availability of marketing channels for services that would not only be affordable for the majority of the rural
population, but would provide the opportunity to decrease transaction costs. Existing programs for providing loans to the rural population appear to be profitable,
but operating in this market requires changes in the personnel recruiting systems,
which is not easy to do for traditional financial intermediaries. In developed countries, the technological channels of low cost "direct financial services" (who
provide transactions at a price equal to just 1/5th of the cost of traditional services) are widely used (IVATURY, 2006). Thus, using modern financial technologies as a channel for providing services to the rural population may decrease
transaction costs to such a level that formal financial intermediaries would be
able to provide profitable services to very poor customers in remote areas.
However, we should not conclude that the rural population would turn to formal
financial services just because they have access to various technological channels.
In countries where financial intermediaries actively use these technological
channels for providing services to rural customers, a high percentage of rural
customers possess inactive accounts. In this context, it is important to determine
to what extent the manner of providing services limits the financial needs of the
rural population, and how it influences the profitability of the financial intermediaries providing these services. However, there are no studies in Ukraine that
analyse how convenient and reliable the existing channels of providing service are
for rural customers (according to their assessment). In this context, it is necessary
to conduct a survey to discover why some rural clients feel uncomfortable when
using technological channels: Do they not trust the operator? Do they feel that
the proposed products are not good for them? Or are they afraid of various technological innovations? Answers to these questions would allow financial intermediaries to expand their opportunities to use technological channels and products for providing services to rural customers.
Development of innovative technologies in rural finance
115
The need to study innovative approaches to rural finance is stressed by Fernando
(FERNANDO, 2003; 2004). Banks using technological channels to provide services
to the rural population are discussed in the works of Ivatury (IVATURY, 2006)
and Mainhart (MAINHART, 1999). These researchers analyse the strategy of creating policy and infrastructure, which is necessary for improving the rural population’s access to financial services, by means of technological channels, as well
as the peculiarities related to the poor using these technologies.
Concerning Ukraine, there is a lack of research dedicated to the interaction of
the banking sector and rural residents. Most studies analyse the needs of rural
residents, or develop recommendations for the governmental and financial sectors.
However, such recommendations often do not take into account the economic
interests of financial intermediaries, and that is why, as a rule, they do not look
attractive for participants in rural financial markets and are rather declarative by
their nature. Sedik (SEDIK, 2003) stresses the need to create a commercially
viable client base for the further development of rural finance. However, there
have been insufficient attempts to analyse the conditions under which providing
services to the rural population would be profitable for financial intermediaries.
2
METHODOLOGY
The main purpose of our paper is to explore financial technologies that would
facilitate the creation of viable financial products combining resource credit and
insurance, and simultaneously stimulate the development of a marketing infrastructure. We have explored alternatives for providing additional financial services through information and communication technologies. This survey was
conducted by interviewing various participants of the rural finance system:
Banks, which provide services to the rural population and to farms, the rural
population and managers of agricultural enterprises; also, experts in the field of
providing microfinance in rural regions. As a result of our research, we plan to
develop a strategy for creating efficient financial systems by means of technological channels.
The goal of our survey was to obtain answers to the following questions:
-
Will implementing various financial technologies in developing countries
result in the increased profitability of financial services provided to the rural
population by traditional financial institutions?
-
Will traditional financial institutions decrease costs to such a level that providing profitable services, even to the very poor or people who live in remote
areas (which are usually excluded by banks) is possible?
-
How will rural clients perceive the introduction of technological channels?
Will these channels be convenient for them?
Anna Bondarenko, Roman Kosodiy, Eugeniy Mishenin
116
-
Of what value is the use of technological channels for financial institutions?
In our research, we used materials from the Consultative Group to Assist the
Poor, as well as the Program of Providing Microloans in Ukraine, which is the
product of joint efforts by the European Bank for Reconstruction and Development and the German-Ukrainian Fund.
3
RESULTS
3.1 Analysis of the Ukrainian rural microfinance market
Today, the financial needs of Ukrainian rural territories, which are characterised
by a high percentage of agriculture, remain largely unsatisfied. Ukrainian banks
almost ignore small rural businesses. The percentage of loans extended to small
businesses in the total portfolio of loans of an average bank hardly exceeds 10%
(DEMENKOV, 2006). Obvious causes of this situation include underdeveloped
financial institutions, high risk, and the asymmetric distribution of information
between creditors and borrowers. Providing microfinance services to Ukrainian
rural households is associated with considerable costs – partly because they possess small amounts of money, live in sparsely-populated areas and rarely have a
credit history. Hence, high transaction costs associated with financial activities
in rural regions are the reason why many representatives of the formal financial
sector still see microfinance activities as non-profitable; they believe the rural
population is not able to pay the high interest rates that would offset these transaction costs.
Nevertheless, according to the results of our research, for most rural residents
banks are a very important source of borrowed funds (Fig. 1). Formal loans are
gradually replacing informal borrowing from relatives and other individuals.
The state as a source of loans has practically disappeared.
Figure 1:
Sources of credit for farmers and rural households in Ukraine,
2004
other
individuals
26%
relatives
33%
banks
32%
other
sources
9%
a) For households
Source: LERMAN et. al., 2006.
other
individuals
22%
relatives
23%
other
sources
8%
banks
47%
b) For farmers
Development of innovative technologies in rural finance
117
Figure 1 illustrates that, in contrast to general opinion, farmers and rural households (even with low incomes) need financial services, use them, and are ready to
pay even high interest rates. For example, in order to obtain a loan without collateral, a typical rural entrepreneur pays the bank a rate of 24-36% in annual interest.
Annual interest rates for collateralised loans are somewhat lower – 16-17%. So
interest rates for small rural entrepreneurs remain high in the financial market.
Comparisons with the United States, Western Europe and even Russia are not
beneficial for Ukraine (the cost of borrowed capital in developed countries usually
does not exceed 9%). Indeed, we have reason to say that domestic financial
institutions overstate interest rates – for all banks participating in our survey, the
percentage of overdue loans extended to small businesses did not exceed 1-2%
(DEMENKOV, 2006). However, banks oriented toward small businesses, especially in rural areas, add considerable risk premiums – hence, their loans are
quite expensive.
Despite quite expensive loans, the number of potential micro-borrowers is constantly increasing. For example, in 2005-2006, the number of loans extended
through the Program of Providing Microloans in Ukraine increased by 54%
(Fig. 2).
Loans, extended through the Program of Providing
Microloans in Ukraine
140000
16000
120000
14000
12000
loan amountnt
100000
10000
80000
8000
60000
6000
40000
number of loansn
Figure 2:
4000
20000
2000
Dec. 2006
Oct. 2006
Nov. 2006
Sept. 2006
July 2006
Aug. 2006
May 2006
June 2006
Apr. 2006
March 2006
Jan. 2006
Feb. 2006
Dec. 2005
Oct. 2005
loan amount
Nov. 2005
Sept. 2005
July 2005
Aug. 2005
May 2005
June 2005
Apr. 2005
March 2005
Jan. 2005
Feb. 2005
Dec. 2004
Oct. 2004
0
Nov. 2004
0
number of loans
Source: PROGRAM OF PROVIDING MICROLOANS IN UKRAINE: <http://microcredit.com.ua/>.
Thus, access to loans is more important for the poor than are interest expenses
(since small rural entrepreneurs have a larger income per hrivna of investments
compared with large businesses) and interest expenses appear more preferable
118
Anna Bondarenko, Roman Kosodiy, Eugeniy Mishenin
than other business expenses or costs associated with loans from informal
sources.
This explains recent positive trends in the area of providing microloans to
Ukrainian farms. For example, the average loan amount decreased considerably.
In 2000, the average loan amount equalled USD 12,000, while today it amounts
to just USD 6,700. This illustrates the improved access to loans for small market
segments. By the end of 2006, 84% of all outstanding loans were made up of
loans in the amount up to USD 10,000. Such a situation is the result of an increase in the banks’ interest in this group, as well as an increasing awareness
level inside the target group concerning the possible financing of small business
(PROGRAM OF PROVIDING MICROLOANS IN UKRAINE).
It should be mentioned that rural entrepreneurs’ access to banks’ resources was
opened by foreign financial intermediaries. The European Bank for Reconstruction and Development pioneered the field of providing loans to small businesses
in 1994. Today the number of banks that finance small rural enterprises (sometimes with the aid of foreign financial institutions) is constantly increasing.
The Program of Providing Microloans in Ukraine is a bright example of the interaction between Ukrainian banks and international financial intermediaries.
Participants of this program include the following banks: Raiffaisen Bank Aval,
Privatbank, Forum, ProCredit Bank, Nadra, Kreditprombank, and Kredo Bank.
These partner banks systematically obtain technical assistance that allows them
to develop loan products (which are acceptable for target groups), as well as to
determine the solvency level for potential borrowers and to assess possible risks,
thus controlling and expanding their loan portfolios.
In 2005, the focus of this program shifted to the expansion of activities directed
at the target group in rural towns, where most target customers are represented
by farmers who earlier did not have access to bank loans. The technologies for
providing loans used in this program were adapted to the peculiarities of agricultural business, and transferred to four partner banks – Privatbank, Nadra, Forum
and Kreditprombank. During the first year of using this technology, the partner
banks extended more than 4,000 loans amounting to USD 20 million to rural and
agricultural entrepreneurs. The average loan amount equalled USD 5,000, and in
most cases loan terms do not exceed one year (Table 1).
Development of innovative technologies in rural finance
Table 1:
Description of loan products of the Program on Providing
Microloans in Ukraine
Type of
Loan
Credit card
Maximum
Amount
Up to USD 1-2
thousand.
Overdraft
Up to
$25 thousand
Replenishment of
current assets
Credit line
Depends on
transaction
volume
USD 5-10
thousand
Replenishment of
current assets
Up to USD 30
thousand
Replenishment of
fixed and current
assets
Replenishment of
fixed and current
assets
Replenishment of Customised amortisation schedule
fixed and current
assets
Modernisation of
Project evaluation
existing operations
Express loans
Microloan
119
Loan in terms Up UAH 300
of the Agro+ thousand
Program
Small loan
Up to USD 100
thousand
Financing of USD 100-250
microprojects thousand
Source: Authors.
Purpose of Loan
Small purchases,
business travel
expenses
Replenishment of
current assets
Peculiarities
Target Group
No collateral,
flexibility in terms
of usage and
amortisation
Flexibility in terms
of usage and amortisation
Flexibility in terms
of usage and amortisation
No collateral, quick
application procedure
Collateral is necessary, interest rates
are lower.
Provided mostly in
UAH
Entrepreneurs,
legal entities,
etc.
Legal entities
Legal entities
Entrepreneurs
and legal entities
Entrepreneurs
and legal entities
Rural entrepreneurs
Small businesses
Small businesses
Ukrainian banks behave somewhat aggressively when providing microloans. An
increasing number of banks, being subject to severe competition in the traditional segment, are entering the market of providing loans for small businesses.
Thus, commercial banks play an important role in the market for microfinance
services. In view of the inactive microfinance organisations in Ukraine, commercial banks have a potential competitive advantage in many areas, such as
famous brands, infrastructure and access to capital.
As a result of our research, we found that many banks consider the possibility of
the rural population entering new financial markets; this is represented by absolutely new clients and assets. Commercial banks, encountering increasing competition in traditional retail markets, are showing interest in rural microfinance
because these new potential customers may increase the client base, but still allow
the banks to retain adequate profitability.
However, there are a lot of unsolved problems. For example, Ukrainian banks
provide almost no start-up capital and investments for modernising existing
Anna Bondarenko, Roman Kosodiy, Eugeniy Mishenin
120
capacities in agricultural enterprises. In view of the extreme shortage of investments in the modernisation of agricultural machinery and technologies, banks
usually provide loans for financing enterprises’ current operations. Indeed, the
share of investment loans for small businesses does not exceed 9% of the total
volume of extended loans. The high costs of investment loans restrict their
demand.
3.2 Organisational features of bank operation models in the field of
microfinance
It is necessary to understand that banks’ success in rural microfinance is not
guaranteed. Attempts by many Ukrainian banks to enter this market did not
bring them any success, since they did not understand this market’s dynamics
and tried to use standard approaches of providing services to new customers. We
can say for certain that there is no single prescription for entering the microfinance market. Each bank has its own business goal, its own competitive and
regulatory environments. Banks apply various approaches to the selection of the
microfinance market entry strategy. Isern and Porteous distinguish two microfinance market entry strategies, (depending on the way banks contact their clients)
either direct and indirect (ISERN and PORTEOUS, 2005). For example, banks may
enter the market directly, expand operations with individuals, or create a new
department or company. At the same time, other banks may apply indirect
approaches by cooperating with existing microfinance organisations.
The Consultative Group to Assist the Poor (CGAP) determined six different
approaches employed by banks for entering the microfinance market (Fig. 3).
Figure 3:
Decision tree for commercial banks in the field of microfinance
Internal unit
RATIONALE
Business
decision
Mandated by
government
STUDY OF THE NEW MARKET
Business goals
Competition
Provide services
directly
Regulatory
environment
Specialised financial
institution
Service company
Market size
Existing
infrastructure and
systems
Other factors
Source: ISERN and PORTEOUS (2005, p. 3).
Outsource retail
operations
Work through
existing providers
Commercial loans to
MFIs
Provide infrastructure
and systems
Development of innovative technologies in rural finance
121
Creating an internal department leads to the provision of microfinance services
in terms of existing organisational structure, as well as the improvement of personnel’s skills. Such a unit requires adapting the bank’s systems and procedures
to the microfinance requirements. Banks may extend more independence to their
units by creating separate systems, loan procedures, personnel policies and governance. Internal units may be linked to various bank departments, such as retail or
consumer finance departments.
On the other hand, rather than setting up an internal unit, banks may decide to
create a legal entity, for example a specialised financial institution (SFI), which is
licensed and regulated by local banking authorities. Such an institution (a finance
company or other non-bank institutions) may provide retail microfinance services
including loan origination, disbursement, collection, etc. SFI is characterised by
separate corporate identity, governance, management and personnel, as well as
the usage of parent bank infrastructure (offices, information technologies, accounting, etc.) (ISERN and PORTEOUS, 2005).
In terms of the service company pattern, banks create non-financial legal entities (service companies) that are expected to provide microloans and portfolio
management services. Unlike specialised financial institutions, service companies
usually undertake a rather restricted range of operations, and they are not regulated by banking authorities. Loans and other financial products (savings, transfers, payment services, etc.) are registered with the parent bank, while the service
company usually maintains separate corporate identity, governance, management,
personnel and information systems (though they tend to be linked directly with
the parent bank’s informational systems). Service companies may be owned by
the bank, but the structure of the service company allows the bank to use various
experienced providers of technical service and other interested investors as equity
partners, which would be impossible in terms of an internal unit. Further, service
companies may operate in designated areas within bank branches or in separate
offices located nearby the bank.
In terms of this model, the bank originates microfinance loans, which are registered in the bank’s books, in order to make loan decisions and to maintain the
loan portfolio. They do this in return for a share of the interest income or fees.
This arrangement is similar to how banks outsource transaction processing to
ATM network operators. Microfinance products, including loans, insurance, and
money transfers, may be branded by the bank or the MFI, or may be a joint
brand. However, this model requires the bank and MFI to share risks and incentives, thereby maintaining the quality of the portfolio. Hence, the bank may ask
the MFI to finance a portion of the microfinance loan portfolio or to provide a
first loss guarantee on a portion of it (ISERN and PORTEOUS, 2005).
Banks can provide loans to an MFI for various terms or lines of credit. This is
one of the most common models, since it is very close to standard commercial
122
Anna Bondarenko, Roman Kosodiy, Eugeniy Mishenin
bank lending. The loan may be unsecured, secured by collateral or be a third-party
guarantee. Further, the bank may stipulate the submission of regular financial statements, rights to inspection, and other financial covenants. In some cases, banks
provide access to their branches or ATM networks, front office functions (including
cashier services), or back-office functions such as IT services and transactions
processing, to a microfinance institution and its clients. In return, the bank receives
fees, commissions, and rents from the MFI and its clients depending on the terms
of the agreement. Transaction processing is the most basic and common form of
this link between banks and MFIs, and it is generally the lowest-risk approach.
MFIs can use their own personnel in the bank branch in order to serve MFI customers, or they can rely on the bank’s infrastructure (ATMs and cashiers) for loan
disbursements and repayments, domestic and international transfers, and foreign
exchange transactions. Clients can have accounts with the bank directly or receive
loan disbursements and repay loans to the MFI’s account at the bank.
Commercial banks oriented towards taking advantage of microfinance opportunities should carefully evaluate the considerations listed in the decision tree (Fig. 3);
specifically, they should consider their own goals, potential market size and competition, regulatory environment, current infrastructure and systems. Given the
differences between classic banking and microfinance, commercial banks should
view microfiance as a new business and conduct the same kind of research as any
company entering a new market (ISERN and PORTEOUS, 2005).
The abovementioned models present a certain risk for banks and their system of
management. Any bank will need to consider its own interests and institutional
capacity, competition and other market factors. Second, banks involved in microfinance will need to develop new products to satisfy their target customers. In
order to deliver their products effectively, banks often need to adapt their systems
and procedures, providing specialised staff with training and incentives regarding
new customers and products.
3.3 Use of technologies in financial system development
Considering the system for financing the rural population, we should remember that banks would not set the goal of providing services to the rural population until they find a way to do it profitably. This requires certain marketing
channels to be accessible to a larger number of rural clients, as well as possibilities to process transactions with moderate costs. Programs for providing
loans to the rural population have proven their profitability, but operating in
this market requires changes in the system of selecting personnel, which is not
easy to do for traditional banks. Despite this, developing ways to cut costs is
critically important for the successful provision of financial services to rural
customers (accounts and operations of rural clients with low incomes are quite
small, which makes decreasing transaction costs the primary task).
Development of innovative technologies in rural finance
123
Therefore, banks considering the possibility of financing rural clients and hoping
to obtain profits from this segment should study alternative ways of providing
additional financial services by means of information and communication technologies. Using modern banking technologies as a channel for providing services to the rural population may decrease transaction costs to such a level that
banks would be able to provide profitable services to very poor rural clients and
customers in remote areas. Hence, banks should search for ways of profitably providing loans. Since the majority of the rural population is paid in cash, in order
to process operations with cash outside banks, they should at least have access to
informational and communicational technologies.
Technology promises to reduce the costs of and improve transparency in delive
ring financial services, both of which can translate into increased access for large
numbers of rural clients. Streamlined and automated processes allow financial institutions to extend services to harder-to-reach and more costly clientele by replacing people and branches with point-of-sale (POS) devices and the like. At the
same time, reducing the "hassle factor" makes banking relationships attractive to
more people. Finally, technology underpins the information and reporting systems
that are essential for efficient financial service delivery (HELMS, 2006).
Figure 4 shows technologies that can be used to support financial services for
rural residents. These technologies range from software that supports the internal
systems of financial institutions to debit or credit cards and linkages with clients’
mobile phones.
Figure 4:
Technology map
Connectivity
Personal digital
assistants
Credit
scoring
ATMs
Point of
sales
PC kiosks in
villages
Cards
Mobile
phones
Biometrics
Internet
banking
Note: PC – Personal computer.
Source: Modified from HELMS (2006, p. 114).
CLIENTS
FINANCIAL INSTITUTIONS
Information
systems
124
Anna Bondarenko, Roman Kosodiy, Eugeniy Mishenin
These technologies are becoming increasingly available because of falling
hardware costs and growing support infrastructure. At one time, the poor supply
of telecommunications and electricity could not support ATMs or POS devices,
particularly in rural areas. Now, however, telecommunications and electricity are
more widespread and reliable.
Below we examine some of the technologies that may be used in rural microfinance.
Information Systems include custom-built or commercially-available software
that allows financial institutions to record transactions and create reliable financial
reports. Obtaining this right is a critical building block for all other technology
applications.
Connectivity refers to network connections (for example, dial-up, broadband, or
satellite) that link staff and branches for real-time information exchange, transaction processing, and distance learning.
Personal Digital Assistants (PDAs) refers to small handheld computers that help
staff in the field collect data more efficiently, manage client records and process
loans (HELMS, 2006).
Credit Scoring includes digitising or enhancing the loan approval process by the
computerised analysis of customer characteristics and behaviour in order to predict willingness and ability to repay.
Automatic Teller Machines (ATMs) refer to machines that dispense cash or provide a wider range of services to cardholders. ATMs are relatively expensive to
own and operate. Most of them require network connectivity and reliable power.
However, ATMs are intended for customers in urban and semi-urban areas.
These locations are more likely to have reliable electricity and "always-on" telecommunications connections that most ATMs require to connect to a bank’s
central server. In addition, because ATMs must regularly be manually refilled or
emptied of cash, it is most cost effective to place them in densely-populated areas.
POS devices are typically used to handle payment transactions. The device can
be a card reader, mobile phone, personal computer (PC), barcode scanner, or any
hardware that can identify customers and receive instructions for the transfer of
value. Where transaction volume is expected to be high, or where wireless Internet access is available, PCs may be used, although most POS devices are cardreading terminals. Each POS device uses a telephone line, mobile phone connection, or the Internet to send instructions for transferring value from one account
to another. For example, after swiping a card through the POS device, the merchant presses a button on the terminal authorising payment from the customer’s
line of credit (credit card) or funds available in the customer’s current account
(debit card). If the POS device is a mobile phone, the customer uses his or her
mobile phone to send a text message authorising payment from her bank account,
or from her account with the mobile phone company, to the merchant’s phone.
Development of innovative technologies in rural finance
125
A POS device is not a banking channel on its own. A human attendant must be
available to count and store cash and to use the POS device to identify the customer (such as by having the customer swipe a debit card and input a personal
identification number – PIN). The bank also relies on this person to answer customer queries, explain product features, and do other tasks. Supermarkets, drugstores, post offices, and other retail outlets are ideal locations for a POS device
because they have cash on hand and have staff to operate the device. In return
for "hosting" the POS device and offering banking services, the retail outlet
expects to increase sales by attracting customers as well as to earn a share of
bank fees (IVATURY, 2006).
Internet Banking is the ability to conduct banking transactions over the Internet
from any location, such as from the home or Internet kiosks. This service is
probably more relevant for higher-income clients.
Magstripe and Smart Cards include debit (or sometimes credit) cards that store
customer information and account balances. These cards allow customers to
access their accounts online via ATMs and POS devices. Smart cards have an
embedded chip that stores information, thereby allowing customers to complete
transactions using remote devices that do not have an online real-time connection with the central server (HELMS, 2006).
Biometrics is a technology that measures an individual’s unique physical characteristics, such as fingerprints, to recognise and confirm identity for security purposes.
Mobile Phones employs technology that offers an opportunity to operate virtual
bank accounts with minimal infrastructure. Millions of poor and low-income
people in rural regions have access to mobile phones, and increasingly use text
messaging. Mobile phones can also be used as a POS device by merchants, market
vendors, and others.
Financial institutions can employ some combination of these technologies to
reach clients directly, or use them in partnership with others. The large volume
of transactions required to ensure a return on technology investments (especially
ATMs) drive financial institutions to leverage each other’s networks. Also, by
working with agents like local merchants and smaller MFIs, financial institutions can reach poorer or more remote rural clients without building expensive
branch networks. Nevertheless, several challenges remain, including the high
cost and limited availability of existing technological solutions, consumer acceptance of technology, the lack of basic communications infrastructure, and inadequate government policies.
It is difficult to say whether using technological channels is profitable enough to
make providing bank services to rural clients possible. There is no analysis of
the profitability of substituting banks with cellular phones or cash terminals.
Though the use of ATMs or terminals for obtaining cash decreases costs, this
126
Anna Bondarenko, Roman Kosodiy, Eugeniy Mishenin
approach would not help banks to attract clients in remote areas. In general, using
technologies becomes profitable only if there is a critical mass of clients and if a
wide range of services is provided.
We believe that the most appropriate technological channel for Ukrainian financial institutions is related to the use of points of sales. As a result of the survey,
we came to the conclusion that many rural residents are unfamiliar with bank
branch procedures or feel uncomfortable dealing with tellers and other branch
staff. In contrast, retail and postal outlets often enjoy substantial brand value and
are trusted by rural residents. Instead of branch banking, customers may use
POS devices located at a nearby post office or retail outlet, which has longer
hours than the bank branch. Banks that did not participate in the survey are also
interested in using this technological channel, since it is much cheaper compared
to traditional methods of providing services. Indeed, bank branches are expensive because they require considerable investments in staffing, infrastructure,
equipment, and security for cash and valuables storage and transportation.
The ATM is a convenient technological channel for the cities’ suburbs. The
ATM channel is generally less expensive than the use of branch tellers, because
ATMs fully automate cash disbursements and collections. However, cash still
needs to be transported to and from the machine. The use of POS devices is
probably the least expensive of these channels, because these devices are placed
at retail or other outlets, which already have cash on hand.
4
CONCLUSION
Developing financial infrastructure in rural areas is vitally important for economic growth and poverty alleviation. The rural population needs deposit and
loan facilities, as well as other financial services that provide opportunities for
opening businesses, improving living conditions and the level of social and economic security. Efficient financial markets facilitate the accumulation of assets,
diversify and increase incomes, as well as decrease vulnerability to economic
perturbations. Hence, the rural population demands bank deposits and loans, and
is ready to pay a high price for services delivered by formal intermediaries.
Nevertheless, rural clients are still viewed as unprofitable by most banks. High
transaction costs associated with microfinance activities are the reason why
many commercial banks still view microfinance activities as unprofitable.
In many developing countries, state agricultural banks, development banks and
savings banks provide services to poor clients, but their goals are more social
than commercial in nature. Thus, rural finance has been seen as a specialised
niche for development programs, incompatible with financial markets and systems.
It is widely believed that the provision of loans to farmers and households is an
area for socially-oriented non-government organisations, and not for banks and
other participants of the financial market.
Development of innovative technologies in rural finance
127
In this context, attention should be paid to the obvious need for improvement in
rural financial institutions, since most rural residents do not have access to formal mechanisms of risk management; as a result, considerable credit risk is
shifted to creditors. The application of new financial technologies in Ukraine is
critically important for reducing the default risk for borrowers, which would
simultaneously improve access to finance for many rural residents. These
technologies would facilitate the creation of viable financial products combining resource credit and insurance, and simultaneously stimulate the development of marketing infrastructure. In other words, expanding financial service
coverage for rural residents is determined by the innovative potential of the financial sector.
REFERENCES
DEMENKOV, А. (2006): Loans for small businesses – Virgin soil for banks, ProstoBankConsulting, <http://www.prostobiz.com.ua/kredity/pressa/kredity_dlya_malogo_
biznesa_nepahanoe_pole_dlya_bankov>.
FERNANDO, N. (2003): ASA: The Ford motor model of microfinance – An update,
Finance for the Poor, Vol. 4(4), pp. 6-8.
FERNANDO, N. (2004): Microfinance outreach to the poorest: A realistic objective?,
Finance for the Poor, Vol. 5 (1).
HELMS, B. (2006): Access for all: Building inclusive financial systems, CGAP, The
International Bank for Reconstruction and Development.
ISERN, J., PORTEOUS, D. (2005): Commercial banks and microfinance: Evolving models
of success, CGAP: Creation of Efficient Financial System for Poor, Focus Note
№ 28.
IVATURY, G. (2006): Using technology to build inclusive financial systems. CGAP:
Creation of Efficient Financial System for Poor <http://www.cgap.org/portal/binary/
com.epicentric.contentmanagement.servlet.ContentDeliveryServlet/Documents/
FocusNote_32.pdf>.
LERMAN, Z., SEDIK, D., PUGACHEV, N., GONCHARUK, A. (2006): Ukraine after 2000:
A fundamental change in land and farm policy?, FAO, <http://www.fao.org/world/
regional/reu/resources_files/Rethinking_Ukrainian_agreform_summary_en.pdf>.
MAINHART, A. (1999): Management information systems for microfinance: An
evaluation framework, Development Alternatives, Inc.
SEDIK D. (2003): Rural Finance without markets in Ukraine, 1991-2000, FAO, ESA
Working Paper No. 03-01.
THE
PROGRAM
ON
PROVIDING
<http://microcredit.com.ua/info/>.
MICROLOANS
IN
UKRAINE,
Sustainable rural development: What is the role of the agri-food sector?
MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central & Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 128-147.
EFFICIENCY OF INDEX-BASED CROP INSURANCE
IN RUSSIAN AGRICULTURE
RAUSHAN BOKUSHEVA,∗ MARINA SANNIKOVA,** OLAF HEIDELBACH***
ABSTRACT
The paper evaluates two main types of index-based insurance – area yield insurance and weather-based index insurance – regarding their efficiency in reducing
the production risks of Russian farms in the steppe climatic zone. The analysis
considers area yield insurance at two levels of aggregation – oblast and rayon
(county) level. Weather-based index insurance products are drawn up by combining two weather parameters – daily precipitation and average daily air temperature. We employ yield and weather data from an experimental station in
Central Volga Russia from 1979 to 2000. In addition, expert assessments are
used to specify alternative levels of production technology and respective yield
distributions for the considered region. To assess the utility-efficiency of the
defined insurance products, a programming model was formulated for 22 states
of nature and 3 levels of the decision-maker’s risk aversion. The model estimation results show that area yield insurance, based on oblast and rayon yields, is
most efficient in stabilising farm income. The weather-based index insurance
follows immediately thereafter. Both index-based insurance types provide the
considered farm with a higher utility than farm yield insurance with deductibles.
This result implies the high potential of index-based insurance for Russian farms
situated in the steppe zone.
Keywords: Risk-management, index-based crop insurance, Russia.
1
INTRODUCTION
Production risk is an important determinant of production development in Russian
agriculture. Production risk caused by unfavourable weather conditions not only
seriously affects Russian farm income, but also significantly defines national
∗
Leibniz Institute of Agricultural Development in Central and Eastern Europe (IAMO),
Halle (Saale), Germany. Email: [email protected]
**
Saratov State Agrarian University, Saratov, Russia. Email: [email protected]
***
Delegation of the European Commission to the Republic of Kyrgyzstan. Email:
[email protected]
Efficiency of index-based crop insurance
129
agricultural output during individual years (LIEFERT, 2002). In this context, assessing production risk and determining effective risk-coping instruments play
an important role in terms of both the stabilisation of farm incomes and the consequent reduction of Russian agricultural output volatility. While assessing the
effect of production risk on the development of agricultural production has been
the subject of several investigations (BOKUSHEVA, 2002; BOKUSHEVA and
HOCKMANN, 2006), so far there has been no study analysing suitable risk management instruments for Russian agricultural enterprises.
Production risk is especially prevalent in crop production. Appendixes A and B
illustrate grain and sunflower yields and coefficients of variation in the main
Russian agricultural regions from 1985-2005. As can be seen, the grain yield
coefficient of variation in the individual oblasts of two main grain-producing
regions – the Southern and Volga Federal Districts – exceeds 20 per cent; in
several oblasts it accounts for more than 30 per cent. A similar picture is observable regarding sunflower yield variation: Its coefficient of variation is over 20
per cent in almost all main production regions.
The high level of production risk in Russian agriculture is primarily explained
by unfavourable climatic conditions in vast areas of the country. A significant
part of the country’s agricultural area is defined as either an area of risky agriculture, or as an area of increased production risk (SHELTIKOV et al., 2001). Indeed, the most important agricultural regions in Russia are situated in the steppe
climatic zone (LOSEV and ZHURINA, 2001). The steppe zone covers the Low and
Central Volga region, Northern Caucasus, Southern Ural as well as southern areas
of Western and Eastern Siberia. A main feature of the steppe zone is that annual
evaporation typically exceeds annual rainfall, which varies between 250mm and
450mm. The average daily temperature in July ranges from 20-25°C, and while
snow coverage in winter is rather moderate, the air temperature can get down to
-45°C (LOSEV and ZHURINA, 2001). With drought and dry winds as the main
natural hazards, such climatic conditions seriously affect agricultural production
and render the application of risk management instruments indispensable.
Agricultural commodity producers have many alternatives for coping with risks.
Risk management instruments can be classified into two basic groups: (1) onfarm instruments, and (2) risk-sharing tools (FLEISCHER, 1990). The first group
includes such risk management instruments as diversifying one’s production
portfolio, holding sufficient liquidity, creating reserves, choosing less risky
products and production practices, reducing production cycles, progressive investments, etc. Moreover, contracting production, hedging on the futures and options
markets, vertical integration, insurance, and availability of additional sources of
incomes belong to risk-sharing strategies (MEUWISSEN et al., 2004). While onfarm risk management instruments can be employed by farmers independently,
130
Raushan Bokusheva, Marina Sannikova, Olaf Heidelbach
risk-sharing strategies assume the availability of a corresponding institutional
environment and market infrastructure.
At the current stage of economic development, technological instruments and
crop insurance present the most accessible risk-reducing tools in Russian agriculture. Technological solutions include maintaining soil humidity, correctly
timing the implementation of technological operations, adopting new plant sorts,
etc. Crop insurance has a long tradition in Russia, but currently, it is provided in
the form of farm yield insurance (FYI) only. Historical experience shows that
this type of insurance is strongly prone to asymmetric information problems.
In fact, Russian agricultural insurers emphasise the increasing occurrence of
moral hazard (INTERFAX, 2007). A traditional way of preventing moral hazard is
to provide crop insurance at lower loss coverage levels. This, however, may
seriously affect insurance effectiveness from the farmers’ point of view, and thus
may reduce demand for this risk management instrument. The introduction of
index-based insurance presents a new approach for solving moral hazard problems
on the insurance market. However, to the best of the authors’ knowledge, the
applicability of such insurance products to Russian agriculture has not yet been
evaluated in the literature. Thus, the objective of the study is to determine appropriate index-based insurance products for Russian agriculture and to analyse
their efficiency in comparison to traditional FYI. Therefore, based on the
weather and yield time series from a study farm in Saratov oblast, we first draw
up alternative index-based insurance products. In a further step, by applying a
utility-efficient programming model, we comparatively evaluate their efficiency
by taking into account the decision-maker’s risk attitude and different levels of
farms’ risk exposure subject to production technology choice.
The paper proceeds as follows. In the next section, we describe the methodology
and data applied. Section 3 presents and discusses the empirical results of the
study. Section 4 concludes.
2
METHODOLOGY AND DATA
In the first step of the analysis, alternative schemes of index-based crop insurance
products were drawn up by taking into account climatic conditions and structural
characteristics of the Central Volga region. Area-yield insurance (AYI) was
formulated at oblast and rayon (county) levels. Weather-based index insurance
(WBII) was designed by employing different hydro-meteorological indices. In
the second step, the efficiency of the considered insurance products was analysed comparatively by applying a utility-efficient programming model and taking into account differences in farm’s risk exposure subject to choice of production technology.
Efficiency of index-based crop insurance
131
2.1 Insurance products design
Index-based insurance contracts applied in crop production are built on either a
weather index or an area-yield index for pricing insurance contracts. For AYI
contracts, average area yield triggers an indemnity payment equal to the difference, if positive, between actual area yield in an individual year and some predetermined critical yield (MIRANDA, 1991). In WBII contracts, insurance payoffs
are subject to the occurrence of a special weather event, which can be described
by a meteorological index (SKEES, 1999). Index-based insurance enables the
solving of problems caused by information asymmetries on the insurance market. This index-based insurance advantage exists due to the objective nature of
the parameters it is based on. At the same time, the risk-reducing potential of
index-based insurance contracts depends strongly on the extent to which individual farmers are affected by systemic risk related to AYI or an individual natural
hazard (drought, for example) concerning WBII. Consequently, the level of basis
risk which cannot be insured through index-based insurance will determine the
effectiveness and hence the demand for such insurance contracts. In this regard,
a particular task of insurance design is to find parameters of insurance contracts
that allow the maximum reduction of a farm’s basis risk.
Area yield insurance
According to MAHUL (1999) an individual farmer’s stochastic yield can be related
to a corresponding area yield as follows:
~
yi − μ i = β i ( ~
y − μ ) + ε~i ,
(1)
with
β = cov( ~y , ~y ) / var( ~y ) ,
(2)
Eε~i = 0; cov(ε~i , ~
y) = 0 ,
(3)
E~
y i = μ i ; E~
y=μ,
(4)
i
i
where ~y is the farmer’s stochastic individual yield, and ~y is the stochastic area
yield. The coefficient β measures the sensitivity of farm yield to changes in area
yield. Formula (1) divides a farm’s total yield risk into a component that perfectly correlates with the area yield, i.e., systemic risk, and a component ε~ that
does not correlate with the area yield, i.e., a farm’s idiosyncratic risk. Consequently, an AYI contract covers only involved systemic risk, while the farm’s
idiosyncratic risk remains uninsured in this case. The optimal coverage of the
AYI contract is equal to the farmer’s individual β -coefficient. Accordingly,
indemnity payments are defined by the following rule:
i
i
i
i
Raushan Bokusheva, Marina Sannikova, Olaf Heidelbach
132
if y t ≥ μ ⎤
⎡0,
indemnity t = ⎢
⎥,
⎣ β i ( μ − y t ), if y t < μ ⎦
(5)
where y is the actual realisation of the area yield in year t.
t
Weather-based index insurance
For WBII, the farmer’s individual yield ~y can be decomposed into a component
y w that depends on realisation of a weather parameter (or index) in year t and a
component ε~ that is determined by other factors:
i
i
~
yt = ytw + ε~t ,
(6)
with
y tw = const + α I t ,
(7)
Eε~t = 0; cov(ε~t , ~
y tw ) = 0 ,
(8)
E~
y tw = μ w ,
(9)
where the component y is defined by regressing the farm’s yield on a selected
weather-based index It.
w
t
Indemnity payments are defined, respectively, as follows:
if y tw ≥ μ w ⎤
⎡0,
indemnity t = ⎢ w
⎥.
w
w
w
⎣⎢ μ − y t , if y t < μ ⎦⎥
(10)
Farm yield insurance
In this study we evaluate the efficiency of index-based insurance products by
comparing them with traditional FYI, which is defined based on the farm’s historical yields. In this case, indemnity payments are described according to the
following:
if y t ≥ μ i ⎤
⎡0,
indemnity t = ⎢
⎥,
−
<
c
(
μ
y
),
if
y
μ
t
t
i ⎦
⎣ i
(11)
where y is the realised farm yield in year t and c is the coverage level.
t
An important disadvantage of FYI is its limited potential to prevent moral hazard.
Moral hazard is defined as the result of those hidden actions of the insured
which increase the risk of the insurer. The effect of moral hazard can be described
in the following way: Assume that a farmer demonstrates opportunistic behaviour by switching to a less intensive technology than he practiced in the past.
Then, the farmer’s indemnity gain due to moral hazard Imh can be defined as follows:
Efficiency of index-based crop insurance
I
mh
if y t ≥ y strike ⎤
⎥* p ,
if y t < y strike ⎦
⎡0
=⎢
APH
ext
⎣E( y ) − E( y )
133
(12)
with
y strike = E ( y APH ) > E ( y ext ) ,
(13)
where ystrike is the strike yield estimated on the basis of the farmer’s actual production history and typically equals its expected value E(yAPH); yt is the farmer’s
yield under the less intensive technology in production year t; E(yext) is the expected yield under this technology, respectively; and p is the price of the insured
crop as stated in the insurance contract.
2.2 Utility-efficient modelling framework
Comparing the efficiency of different insurance products was done by estimating
their utility-efficiency for the decision-maker. The Expected Utility approach
provides a convenient way to represent a decision-maker’s risk preferences: Its
basic idea is that a decision-maker maximises his expected utility. When income
increases, utility increases less than proportionately for risk-averse decisionmakers (the more risk-averse a person is, the more he will be prepared to pay to
eliminate risk). Hence, utility is an increasing but downward-bending function
of income. Expected utility estimates can be transformed into certainty equivalents (CE), which is the inverse of the utility function and which represents a
certain monetary value. This provides a decision-maker with the same utility as
a risky alternative, thus making him indifferent to facing the risk or accepting
the sure sum (HARDAKER et al., 2004). An important advantage of CE is that it
allows a quantitative comparison of different risky alternatives. Knowing certainty equivalent outcomes not only permits the ranking of risky alternatives, but
also facilitates estimating risk premiums. CE simultaneously accounts for the
probabilities of risky prospects and the preferences of the decision-maker
(ANDERSON et al., 1977). Each production activity and risk management instrument may influence a decision-maker’s expected utility. Examining CE is an
approach for investigating the magnitude of this influence.
The utility efficient programming model (HARDAKER et al., 2004) is formulated
as follows:
max CE = [(1 − r ) E (U )]
1 /(1− r )
,
(14)
where CE is the certainty equivalent, r is the absolute risk aversion coefficient,
and U a utility function defined in this study as a negative exponential function:
U = 1 − exp(1 − r ) z
subject to
(15)
Raushan Bokusheva, Marina Sannikova, Olaf Heidelbach
134
Ax ≤ b ,
(16)
Cx − Iz = uf ,
(17)
and
x ≥ 0,
(18)
where A is a matrix of technical coefficients for all activities, b is a vector of
capacities, x is a vector of activity levels, C is a matrix of activity net revenues
by state of nature, I is an identity matrix, z is the annual net income in each
state, u is a vector of ones, and f is fixed or overhead costs.
The absolute risk aversion range for the model was derived from the plausible
range of relative risk aversion coefficients – r , defined as the marginal utility of
wealth. ARROW (1965) has shown that
r
ra =
rr
,
w
(19)
where w is wealth. HARDAKER et al., (2004) suggest that r should be a number
close to 2. In our study, we employ three levels of relative risk aversion – 0.5
(hardly risk averse at all), 2 (rather risk averse) and 4 (extremely risk averse).
r
The model includes 4 different types of insurance products – FYI with coverage level 0.75, AYI based on oblast yield (OYI), AYI based on rayon yield
(RYI) and WBII – and considers three levels of production technology related
to the degree of intensity – intensive, medium, and extensive. Formulating
technologies was done through expert assessments, with one of the regarded
technologies being based on the historical yields of the study farm1. We consider 22 states of nature that correspond to the individual years in our data set.
The basic descriptive statistics of the considered technologies are presented in
Appendix C.
To rate the utility efficiency of index-based insurance products and assess their
effect on the farm’s production decisions, income certainty equivalent was estimated for different scenarios as described in Table 1.
1
Farm yields were de-trended by employing linear and second-degree polynomial functional
forms.
Efficiency of index-based crop insurance
Table 1:
Model scenarios
Scenario
135
Description
R
Reference scenario: No access to insurance, rr = 2
1
Access to all insurance products
2 (FYI-AYI)
Access to farm yield and area yield insurance
3 (FYI-WBII)
Access to farm yield and weather based index insurance
4 (AYI-WBII)
Access to area yield and weather based index insurance
Source: Authors’ estimates.
2.3 Data
In our empirical analysis we employ yield and weather data from an experimental
station, situated in Saratov oblast (the Central Volga region), from 1979 to 2000.
The weather data includes daily precipitation (mm) and average daily temperature (°C). Additionally, the study used official statistics on oblast and rayon
yields for the same period.
The study farm produces winter wheat and spring wheat, winter rye, barley, sunflower seeds, and has a typical Saratov oblast production structure. The farm’s
crop area is 4,193 ha. The study farm primarily applies intensive technology and
for the region has a relatively low yield variation2; nevertheless, coefficients of
variation of the farm’s main crops are higher than 30 per cent. The average level
of winter crop yields on the study farm is slightly higher than average yields
formulated by experts for intensive technology. On the other hand, spring crops’
yield is somewhat lower compared to expert assessments for this level of technology. The average sunflower yield corresponds to yields under medium technology.
Twenty two considered states of nature are combined in 5 aggregated states; this
allows a more convenient discussion of the model results:
S1 – Strong drought (1984, 1987, 1995, 1998);
S2 – Average drought (1979, 1981);
S3 – Weak drought (1985, 1988, 1991, 1992, 1994, 1996, 1999);
S4 – Favourable weather conditions (1980, 1982, 1986, 1990, 1993);
S5 – Very favourable weather conditions (1983, 1989, 1997, 2000).
2
As can be seen from Appendix C, yield variability is strongly connected to the technology
applied on farms in the considered region: Yield variation decreases with an increasing
level of production intensity.
Raushan Bokusheva, Marina Sannikova, Olaf Heidelbach
136
3
ESTIMATION AND EMPIRICAL RESULTS
3.1 Area-yield index insurance
The high correlation between farm yields and oblast and rayon yields (Appendix D) point to a relatively high level of systemic risk in Saratov oblast, which is
an important precondition for the introduction of AYI. Correlation coefficients
between farm and area yields at the rayon and oblast levels vary from 0.85-0.95,
with a higher correlation being observed with oblast yields. This means that the
study farm’s systemic risk component is better represented by yields of a higher
than rayon level of aggregation and supposedly illustrates a relatively low level
of idiosyncratic risks on the investigated farm compared to other farms in the
respective rayon. Table 2 presents critical β -coefficients, which reflect the optimum insurance coverage for individual crops.
Table 2:
β -coefficients estimated for AYI at oblast and rayon level
Oblast-yield index crop
insurance (OYI)
Rayon-yield index crop
insurance (RYI)
Winter rye
1.08
0.71
Winter wheat
1.14
0.83
Spring wheat
1.18
0.69
Barley
1.30
0.85
Sunflower
0.97
0.82
Crops
Source: Authors’ estimates.
3.2 Weather-based index insurance
In the literature, a weather index is usually built either from one or several
weather parameters (BOKUSHEVA et al., 2006; KARUAIHE et al., 2006). In our
study we tested different weather indices by employing various combinations of
two weather parameters – cumulative precipitation and average daily temperature. To determine the weights of individual weather parameters considered for a
weather index, the (de-trended) farm’s yields were regressed on selected weather
parameters. On the whole, we regarded two critical periods of plant vegetation:
1) from April to September for all crops, and 2) from December to February for
winter crops.3 Composition of the individual weather indices, which significantly determine the farm’s crop yields, is presented in Table 3.
3
We could not find any dependence between the weather parameters considered for the winter
period and winter crop yields.
Efficiency of index-based crop insurance
Table 3:
Crops
Winter rye
Winter wheat
Spring wheat
Barley
Sunflower
137
Weather index composition by crops
(assessed for the study farm, 1979-2000)
Weather parameter
Coefficient
estimates a)
Sum of rainfall from April 6 - June 4,
mm ( R )
0.05**
Sum of average daily temperatures from
May 11 - June 29, degrees ( T )
-0.04***
Sum of rainfall from April 16 - June 4,
mm ( R )
0.10***
Sum of average daily temperatures from
May 6 - June 29, degrees ( T )
-0.03***
Sum of rainfall from May 1-June 4, mm
(R)
0.05**
Sum of average daily temperatures from
May 1 - July 29, degrees ( T )
-0.01***
Sum of rainfall from April 26 - May 30,
mm ( R )
0.05**
Sum of average daily temperatures from
May 21 - July 29, degrees ( T )
-0.03***
Sum of rainfall from May 4 - May 20,
mm ( R )
0.07***
Sum of average daily temperatures from
May 4 - June 9, degrees ( T )
-0.01*
R-squared
0.80
0.78
0.66
0.69
0.70
Notes: a) ***, **, * - significant at 0.01-level, 0.05-level, and 0.10-level, respectively.
Source: Authors’ estimates.
3.3 Farm yield insurance
Farm yield insurance was constructed by employing the coverage level of 0.75,
which is typically used in crop insurance practice. Introducing deductibles aims
to prevent moral hazard; however, it can seriously affect the effectiveness of
FYI. Thus, there is a certain trade-off between the FYI risk-reducing efficiency,
which determines insurance demand, and losses that an insurer can experience in
the face of moral hazard. Figure 1 shows that the effect of moral hazard can be
very large under Russian conditions.
Raushan Bokusheva, Marina Sannikova, Olaf Heidelbach
138
Figure 1:
Expected indemnity values with and without moral hazard
Sunflower
Crops
Barley
Spring wheat
Winter wheat
Winter rye
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
Expected net indemnities with moral hazard, 0.1t per ha
Expected net indemnities without moral hazard, 0.1t per ha
Additional value of indemnities with moral hazard, 0.1t per ha
Source: Authors’ estimates.
For almost all crops, expected indemnity payments with moral hazard are at
least twice as high as those without moral hazard. The potential insurance losses
caused by moral hazard were calculated for a coverage level of 1.0, assuming
that an insured farmer would switch from the medium technology to the extensive technology4.
3.4 Utility-efficiency of index-based insurance products
Model estimation results for the reference scenario R (without access to insurance)
are presented in Table 4. According to the model estimates, the farm uses its
whole crop area, i.e., 4,193 ha with 497 ha being occupied by winter wheat,
2,909 ha by barley and 786 ha by sunflowers. Winter wheat production is more
profitable, but at the same time more risky than barley production – this prevents
the farm from producing more winter wheat in the reference scenario. All crops
are produced under intensive production technology. This result shows that this
technology guarantees the farm the highest income utility.
4
We estimate the moral hazard effect for switching from the medium to the extensive technology because only a limited number of farms in the Saratov oblast apply intensive technology.
Efficiency of index-based crop insurance
Table 4:
139
Technology choices, scenario R
Intensive
technology
Medium intensive
technology
Extensive
technology
Total
0
0
0
0
Winter wheat
497
0
0
497
Spring wheat
0
0
0
0
Barley
2909
0
0
2909
Sunflower
786
0
0
786
Total
4193
0
0
4193
Crops
Winter rye
Source: Authors’ estimates.
The integration of insurance products into the model seriously alters the optimal
production plan of the investigated farm (Table 5). The provision of insurance
allows the farm to switch from barley to winter wheat production, the outcome
of which is more uncertain. Demand for insurance strongly depends on the decision-maker’s level of risk aversion. A less risk averse decision-maker would insure only a part of his winter wheat crop area, while a more risk averse or extremely risk averse farmer would prefer to insure all crops except sunflower. At the
same time, it can be seen that preferences concerning crops and technologies are
quite stable over all considered levels of risk-aversion.
Moreover, the purchase of insurance contracts allows for considerable increases
in the farm’s expected income and certainty equivalent. In the reference scenario,
the expected income and certainty equivalent given a less risk averse decisionmaker are 5,741 and 5,584 thousand Rubles, respectively. In scenario 1 (access to
all insurance products) these values amount to 6,295 and 6,146 thousand Rubles.
These differences increase with increasing risk aversion.
Among analysed insurance products, the farm prefers AYI to WBII and FYI.
This result shows the prevalence of systemic risk on the considered farm. Additionally, we can observe that the farm uses a combination of OYI and RYI. This
supposes that the farm’s yield risk is well-captured by yields at both oblast and
rayon aggregation levels. An examination of the annual indemnity payments
shows that in some years, OYI ensures better indemnification of the farm’s actual
losses; however, in several years RYI performs better.
Optimal plans for all considered levels of risk aversion include sunflower production at the maximum rate of 786 ha (20 per cent of the total crop area). This
can be explained primarily by its high profitability, but also by the relatively low
yield variability of sunflowers. The latter fact indicates that sunflower production allows the farm to use the diversification effect. However, since traditional
cultivating practices in Russia do not permit the farm to increase the sunflower
crop area, this crop’s diversification effect can be used only to a limited extent.
140
Table 5:
Level of risk
aversion
Raushan Bokusheva, Marina Sannikova, Olaf Heidelbach
Technology and insurance product choices,
scenario 1 – All insurance products
Crop
Winter rye
–
–
–
Without insurance
718
Intensive
RYI
798
Intensive
OYI
57
Intensive
Spring wheat
–
–
–
Barley
Without insurance
1834
Intensive
Sunflower
Without insurance
786
Intensive
Winter rye
–
–
–
Without insurance
19
Intensive
RYI
870
Intensive
OYI
683
Intensive
Spring wheat
–
–
–
Barley
OYI
1834
Intensive
Sunflower
Without insurance
786
Intensive
Winter rye
–
–
–
RYI
1100
Intensive
OYI
473
Intensive
Spring wheat
–
–
–
Barley
OYI
1834
Intensive
Sunflower
Without insurance
786
Intensive
Winter wheat
Hardly risk
averse at all
( rr = 0.5 )
Rather risk
averse
( rr = 2 )
Extremely risk
averse
( rr = 4 )
Expected
Certainty
Area,
Technology income, '000 equivalent,
ha
Rub
'000 Rub
Insurance
product
Winter wheat
Winter wheat
6295
6146
6111
5831
6108
5581
Source: Authors’ estimates.
The income stabilising effect of crop insurance can be illustrated by means of
Figure 2, which shows the distribution of the farm’s income according to the 5
aggregated states of nature and its risk-aversion levels (for scenario 1). As can
be expected, the demand for crop insurance depends on a decision-maker’s risk
aversion – a more risk averse decision-maker has higher demands for crop
Efficiency of index-based crop insurance
141
insurance. At the same time, the decision maker’s preferences do not change for
the risk aversion coefficients in the range of 2.0 to 4.0.
Figure 2:
Income distribution among aggregated states of nature for
three levels of risk aversion ( r = 0.5 , r = 2 , r = 4 ),
scenario 1 – All insurance products
r
r
r
14000
Income, '000 rubles
12000
10000
8000
6000
4000
2000
0
1
2
3
4
5
States of nature
hardly risk averse at all
rather risk averse
extremely risk averse
Source: Authors’ estimates.
Subsequent elimination of one of the regarded insurance products from the
model (scenarios 2-4) was conducted to rate its individual utility-efficiency. The
results show that though WBII is less efficient than OYI and RYI, it provides
the farmer with a higher income utility than FYI, with a coverage level of 0.75.
4
CONCLUSIONS
The paper evaluates two main types of index-based insurance: Area yield insurance and weather-based index insurance regarding their efficiency in reducing
the production risks of Russian farms in the steppe climatic zone. The analysis
considers area yield insurance at two levels of aggregation – oblast and rayon
(county) level. Weather-based index insurance products are drawn up by combining two weather parameters – daily precipitation and average daily air temperature. To assess the utility-efficiency of the defined insurance products, a
programming model was formulated for 22 states of nature and 3 levels of decision-maker risk aversion. We employ yield and weather data from an experimental station in Central Volga Russia from 1979 to 2000. In addition, expert
142
Raushan Bokusheva, Marina Sannikova, Olaf Heidelbach
assessments are used to specify alternative levels of production technology and
respective yield distributions for the considered region.
The estimation results show that area yield insurance based on oblast and rayon
yields are most efficient in stabilising farm income. Weather-based index insurance follows immediately thereafter. Both index-based insurance types provide
the considered farm with a higher utility than farm yield insurance, with a coverage level of 0.75. Additionally, the analysis shows that Russian agricultural
insurance companies can experience serious losses related to moral hazard. Thus,
in the face of moral hazard, there is a certain trade-off between the demand for
FYI and the insurers’ willingness to provide this type of crop insurance. In this
context, index-based insurance substantially limits the scope of moral hazard
and presents a realistic alternative for Russian farms situated in the steppe zone.
Moreover, our investigations show that Russian farms, similar to farms in other
post-Soviet countries, have only limited options for coping with risks on-farm
(HEIDELBACH, 2006; BOKUSHEVA anD HOCKMANN, 2006). Most available technologies and production practices used on Russian farms are not adjusted to the
prevailing climatic conditions; this seriously limits the farms’ perspectives for
reducing high yield variability, as well as adopting higher levels of crop diversification.
REFERENCES
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2004-2005, Moscow.
ANDERSON, J. R., DILLON, J. L., HARDAKER, J. B. (1977): Agricultural decision analysis, The Iowa State University Press, Ames.
ARROW, K. J. (1965): Aspects of the theory of risk-bearing, Yrjö Jahnssonin Säätiö,
Academic Bookstore, Helsinki/Finland.
BOEHLJE, M. D., TREDE,. L. D. (1977): Risk management in agriculture, J. Am. Soc.
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BOKUSHEVA, R., BREUSTEDT, G., HEIDELBACH, O. (2006): Measurement and comparison of risk reduction by means of farm yield, area yield, and weather index
crop insurance schemes – The case of Kazakhstani wheat farms, Poster paper for
the International Association of Agricultural Economists Conference, Gold Coast,
Australia, August 12-18, 2006.
BOKUSHEVA, R., HOCKMANN, H. (2006): Production risk and technical inefficiency
in Russian agriculture, European Review of Agricultural Economics, Vol. 33,
pp. 93-118.
Efficiency of index-based crop insurance
143
BOKUSHEVA, R., HEIDELBACH O. (2004): Insurance in Agriculture: State of the art,
IAMO Discussion Paper No. 57, Halle (Saale), <http://www.iamo.de/no57.pdf>.
FLEISCHER, B. (1990): Agricultural risk management, Boulder & London, Lynne
Rienner Publishers.
HARDAKER, J. B., HUIRNE, R .B. M., ANDERSON, J. R., LIEN, G. (2004): Coping with
risk in agriculture, Second edition, CABI Publishing, Wallingford.
HEIDELBACH, O. (2006): Efficiency of selected risk management instruments – An
empirical analysis of risk reduction in Kazakhstani crop production, PhD-Thesis,
Halle (Germany).
INTERFAX (2007): Food and Agriculture weekly, Vol. XVI, Issue 5, Moscow.
KARUAIHE, R. N., WANG, H. W., YOUNG, D. L. (2006): Weather-based crop insurance
contracts for African countries, Contributed Paper for the International Association
of Agricultural Economists Conference, Gold Coast, Australia, August 12-18, 2006.
LITTLE, I. M. D., MIRRLLEES, J. A. (1974): Project appraisal and planning for developing countries, Heinemann, London.
LOSEV, A. P., ZHURINA, L. L. (2001): Agrometeorologiya (Agro meteorology), Moscow,
Russia.
MAHUL, O. (1999): Optimal area yield crop insurance, American Journal of Agricultural Economists, Vol. 81, pp. 75-82.
MEUWISSEN, M. P. M., HUIRNE, R. B. M., HARDAKER, J. B. (1999): Income insurance
in European agriculture, European Economy, 2, European Commission, DirectorateGeneral for Economic and Financial Affairs.
MIRANDA, M. J. (1991): Area-yield crop insurance reconsidered, American Journal of
Agricultural Economists, Vol. 73, pp. 233-242.
PATTEN, L. H., HARDAKER, J. B., PANNEL, D. J. (1988): Utility-efficient programming
for whole-farm planning, Australian Journal of Agricultural Economics 32, pp. 8897.
SHELTIKOV, V., KUZNETZOV, N., TEGLOV, S. (2001): Economicheskaya geographiya
(Economic Geography), Rostov-na-Donu, Russia.
SKEES, J. R., HAZELL, P., MIRANDA M. (1999): New approaches to crop yield insurance in developing countries, EPTD Discussion Paper No. 55, Environment and
Production Technology Division, International Food Policy Research Institute,
Washington, D.C.
144
Raushan Bokusheva, Marina Sannikova, Olaf Heidelbach
Appendix А: Descriptive statistics of grain crop yields in main agricultural
regions of Russian Federation (1985-2005)
Average
Structure of
Coefficient of
yield,
grain production
variation, %
0.1t/ha
in 2005, %
RUSSIAN
FEDERATION
16.5
12.4
100.0
Central Federal District
18.7
19.7
18.8
Belgorod Oblast
24.4
19.3
2.6
Voronezh Oblast
20.4
18.7
3.1
Kursk Oblast
21.5
16.2
2.4
Lipetsk Oblast
21.8
23.3
2.4
Southern Federal
District
24.0
20.8
34.2
Krasnodar Territory
36.5
16.0
10.6
Stavropol Territory
28.1
21.8
8.6
Volgograd Oblast
14.5
26.9
4.6
Rostov Oblast
21.9
21.6
8.0
Volga Federal District
15.0
18.7
24.5
Republic of Bashkortostan
16.7
31.5
3.7
Republic of Tatarstan
23.3
34.2
5.3
Orenburg Oblast
10.3
26.8
2.3
Saratov Oblast
12.2
25.9
4.5
Ural Federal District
14.0
15.0
6.3
Kupgan Oblast
12.3
27.3
1.7
Chelyabinsk Oblast
11.5
32.6
1.9
Siberian Federal District
13.1
12.1
14.9
Altay Territory
11.2
22.0
3.8
Novosibirsk Oblast
13.4
17.9
2.3
Omsk Oblast
13.4
20.8
3.7
Source: Authors’ estimates based on official statistics.
Efficiency of index-based crop insurance
145
Appendix B: Descriptive statistics of sunflower yields in main agricultural
regions of Russian Federation (1985-2005)
Average
Structure of sunCoefficient of
yield,
flower producvariation, %
0.1t/ha
tion in 2005, %
RUSSIAN
FEDERATION
10.4
18.7
100.0
Central Federal District
10.5
12.5
15.5
Belgorod Oblast
13.8
18.5
2.5
Voronezh Oblast
11.4
20.5
8.3
Tambov Oblast
9.0
30.9
3.8
Southern Federal
District
11.6
22.5
61.6
Krasnodar Territory
17.2
20.1
17.9
Stavropol Territory
12.2
20.7
6.6
Volgograd Oblast
8.3
23.1
10.5
Rostov Oblast
12.4
24.2
24.6
Volga Federal District
7.0
17.0
19.4
Orenburg Oblast
6.4
24.8
4.2
Samara Oblast
8.8
23.1
3.9
Saratov Oblast
6.3
29.1
8.2
Siberian Federal District
4.9
22.3
3.2
Altay Territory
5.1
18.9
2.5
Source: Authors’ estimates based on official statistics.
Raushan Bokusheva, Marina Sannikova, Olaf Heidelbach
146
Appendix C: Yield and yield variability of study farm’s main crops by
different levels of technology
Variation
Mean yield, Standard deviaCrops
Technology
coefficient,
0.1t per ha tion, 0.1t per ha
%
Winter rye
Winter wheat
Spring wheat
Barley
Sunflower
Intensive
18.71
5.61
30.01
Medium
intensive
16.28
6.91
42.48
Extensive
11.10
6.97
62.75
Intensive
19.31
6.52
33.77
Medium
intensive
16.52
7.77
47.05
Extensive
11.69
7.86
67.29
Intensive
13.49
3.57
26.43
Medium
intensive
7.37
3.63
49.29
Extensive
5.35
3.66
68.35
Intensive
16.78
4.80
28.60
Medium
intensive
10.44
4.89
46.83
Extensive
7.38
4.94
66.92
Intensive
9.37
2.56
27.28
Medium
intensive
6.12
2.90
47.38
Extensive
4.71
2.90
61.48
Source: Authors’ estimates.
Efficiency of index-based crop insurance
147
Appendix D: Correlation coefficients of study farm’s yields with respective
oblast and rayon yields (1979-2000)a)
Correlation coefficient
Correlation coefficient
Crops
between farm level and
between farm level and
oblast level yield
rayon level yield
Winter rye
0.93
0.87
Winter wheat
0.93
0.92
Spring wheat
0.91
0.85
Barley
0.95
0.92
Sunflower
0.76
0.85
Note: a) Correlation coefficients were calculated for de-trended yields.
Source: Authors’ estimates.
Sustainable rural development: What is the role of the agri-food sector?
MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central & Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 148-163.
RURAL CREDIT PARTNERSHIPS AND THEIR ROLE IN THE
DEVELOPMENT OF AGRICULTURE IN KAZAKHSTAN
SHOLPAN GAISINA∗
ABSTRACT
Transition from a planned to a market economy is neither an easy nor a fast
process, particularly regarding the agricultural sector. Even in more developed
countries, agriculture continues to be partially dependent on state support, and
the rural financial market is included in this trend. However, a country’s level of
agriculture development is, in most cases, determined by the extent of this dependency. When agricultural producers are less dependent on state support, their
position in the free market is more firm and stable. Hence, well-developed and
organised private institutions, including financial institutions, that function in
the agricultural market can significantly contribute to the strengthening of an
agricultural producer’s market position. There is relatively little work that investigates the performance of institutions operating in Kazakhstan’s rural financial
market. This article therefore attempts to describe steps which could be undertaken for the successful development of rural credit partnerships in Kazakhstan,
i.e., the first cooperative type of financial institution in Kazakhstani agriculture.
Keywords: Rural financial market, credit partnerships, Kazakhstan.
1
INTRODUCTION
The rural financial market in Kazakhstan is represented by two very important
groups of participants: Rural borrowers and rural lenders. The former include
different types of agricultural enterprises, individual (peasant) farms, and subsidiary small holdings. The latter include formal and informal financial institutions serving the rural producers. The development of the rural financial market,
which is the key element of successful transformation in the agricultural sector
(BEZEMER, 2002), assumes the creation and development of rural financial institutions.
During transition, a centrally-planned system has been replaced by new market
relations; however, this process has not always been accompanied by the creation of new market institutions. That is, some economic sectors, including
∗
Innovation University of Eurasia, Pavlodar, Kazakhstan. Email: [email protected]
Rural credit partnerships
149
agriculture, are forced to operate using market rules without having an appropriate market infrastructure. Nowadays, the financial agricultural market in
Kazakhstan is characterised by the dominating presence of governmental agencies and by the low participation of private financial institutions. This has been,
and in many cases remains, a perennial problem in transition countries’ rural
credit markets, where governmental financial agencies offer subsidised credit
(THE WORLD BANK, 2005).
Undoubtedly, credit plays an important role in the restructuring, competitiveness, recovery and growth of agriculture in transitions countries. Therefore,
issues related to developing rural credit institutions are crucial and require the
attention of both policy-makers and scientists.
2
THE AGRICULTURAL SECTOR OF KAZAKHSTAN
Agriculture has traditionally played a significant role in the Kazakhstani economy.
During the Soviet period, Kazakhstan was a major agricultural producer, supplying other republics with its surpluses of crop and livestock products (OECD,
1998). Agricultural production made up a considerable share of GDP in that
period, accounting for about 30%. However, as a result of the severe economic
crisis of the mid-1990s, along with the sharp reduction of agricultural production, the share of agriculture in GDP declined to 11% by the end of 1997, and in
recent years this level has been stable at 7%. Between 1992 and 2003, the cultivated area of rural enterprises decreased by 50%, including the area producing
cereals, which decreased by 39%, and the area growing feed crop, which decreased by 78.6% (Figure 1).
Figure 1:
Cultivated area (million hectares)
40
30
20
10
0
1992
1995 1998
In total
wheat
2000
2003
Cereals
2005
Feed crops
Source: AGENCY ON STATISTICS OF THE REPUBLIC OF KAZAKHSTAN, <www.stat.kz>.
Consequently, grain production also declined, from about 30 million tons per
year before the crisis, to 6.4 million tons in 1998. However, despite the marked
decline of both the area sown and production levels, Kazakhstan has remained a
150
Sholpan Gaisina
net-exporter of grain. During the recovery period, from 1998-2003, grain production increased to 14.8 thousand tons in 2003.
The value of livestock production from 1992 to 1998 also substantially decreased, from 9 million heads to 3.9 million heads. However, the recovery process
in this area was much slower than in grain production. Since 1999, the annual
rate of growth was approximately 4%.
The major goal of Kazakhstan’s first agricultural reforms was to undergo a significant structural transformation that required broad institutional changes. The
latter, in turn, included establishing a new legal form of farming and a new type
of land relations. The gradual structural transformation of Kazakhstan’s agricultural enterprises began in 1991 (after the collapse of the Soviet Union). At that
point, the former state (sovkoz) and collective (kolkoz) farms were dissolved as
legal entities, and collective farms, which were further converted into production
co-operatives, were created. This stage of restructuring, in most cases, led to
formal rather than substantive changes, with little practical effect on ownership
and management. The majority of farm entities continued to function as they did
under the Soviet system, however, the environment and conditions had been
changed. As a result, the production cooperatives faced financial difficulties and
the ever-deepening crisis of indebtedness. During 1998, the government undertook new steps towards farm restructuring: All collective farming enterprises
had to undergo re-registration as individual (peasant) farms, join-stock companies, or limited partnerships, so as to conform to the Kazakh Civil Code (OECD,
1998). Consequently, the number of agricultural producers increased markedly.
Currently in Kazakhstan, there are two main types of farming: Legally-recognised
forms and non-registered family farms, so-called subsidiary small holdings. The
latter, by their nature, have to provide exclusively for personal consumption, but
in fact most of those entities function as conventional commercial farms. Thus,
the following types of farming exist: State agricultural enterprises, production
co-operatives, joint stock companies, partnerships, individual (peasant) farms
and subsidiary small holdings. In 2004 the agricultural sector was comprised of
0.06% state enterprises, 1.4% production co-operatives, 2.7% partnerships, 0.1%
joint stock companies, and 95% individual (peasant) farms. The precise number
of subsidiary small holdings is not known, but according to approximate calculations, their number accounts for about 2 million farms (Table 1).
Rural credit partnerships
Table 1:
151
Number of agricultural enterprises and farms
1992
1998
2000
2002
State enterprises
(including kolkoz)
2004
2095
88
82
126
125
Production cooperatives
–
2909
1710
2866
2609
Partnerships
–
2140
3342
4822
5174
Joint-stock companies
–
509
293
269
222
9262
78949
105174
141328
177883
Other
–
1078
1298
1285
1141
Total
11769
85673
111899
150696
187139
Individual (peasant) farms
Source: AGENCY ON STATISTICS OF THE REPUBLIC OF KAZAKHSTAN, <www.stat.kz>.
Land reform measures and the restructuring of agricultural enterprises have
changed the distribution of agricultural land across farming structures. In 2002,
individual (peasant) farms operated on 32% of the total arable land (in 1997 this
number was 19%). Of these, small individual (peasant) farms (between 8-28
hectares) hold 81.4% of arable land and only 2.8 % of them are considered
large-scale farms with land plots of a minimum 1,150 hectares per farm. The
average hectares of arable land per agricultural enterprise have changed as well:
Small agricultural enterprises (75-200 hectares) operate 47.8% of the arable land,
medium-sized (1,300-3,200 hectares) operate 43.7% of arable land, and large
agricultural enterprises (13,000-18,000 hectares) operate only 8.5% of the total
arable land. That is, about 680 large-scale agricultural enterprises operate about
47% of the arable land.
Livestock production has become, by far, the most common specialisation
among subsidiary small holdings, accounting for 87% of total production. Agricultural enterprises and individual (peasant) farms held 8% and 5% of livestock,
respectively (Table 2). The same is true of dairy, vegetables and fruit production.
152
Sholpan Gaisina
Table 2:
Agricultural output by producer (%)
Type of agricultural producers
1995
1999
2002
Plant growing
Agricultural enterprises
69.0
46.0
33.0
Individual farms
3.0
26.0
42.0
Subsidiary small-holdings
28.0
29.0
26.0
Agricultural enterprises
32.0
10.0
8.0
Individual farms
2.0
5.0
5.0
Subsidiary small-holdings
66.0
85.0
87.0
Livestock
Source: AGENCY ON STATISTICS OF THE REPUBLIC OF KAZAKHSTAN, <www.stat.kz>.
In spite of the growth of productivity for individual (peasant) farms (between
1997-2000 this index doubled), large-scale agricultural producers earn the bulk
of net profits (72%). The level of profitability in small rural structures accounts
for only 2.9%, which is approximately one-fourth of the profit of large- and
middle-scale agricultural producers. Small farms and subsidiary small holdings
do not have the same access to know-how, new technologies, markets and credit
resources as the large- and middle-scale producers. The lack of working capital
is also a constraint for them.
It is well-known that capital comes in two basic forms: Equity capital and debt
capital. The use of credit is the second largest source of capital for farmers
(KENT, 2004). However, Kazakhstani farmers have faced difficulties with using
both sources. The low profitability of agricultural production, as well as hyperinflation in the early 1990s, complicated the use of their own financial resources.
In turn, reforms of the banking sector have dramatically changed the situation in
the rural financial market.
Prior to these reforms, credit for agricultural producers was distributed through
the state-controlled banking system in accordance to a state central plan
(SWINNEN et al., 2003). The interest rates for short-terms loans were 2%, and for
long-term loans 75 %. Producers operating at "a planned loss," i.e., having an
anticipated loss given the prices and commodity mix fixed in their production
plans, received special 2-year grants for the "replenishment" of working capital.
The ratio of loan repayment was very poor, which regularly led to restructuring and
writing-off of the debts (YANBYKH, 2000). This explains agricultural producers’
strong insistence on preferential credits. From 1992 to 1994, Kazakhstan’s government provided farmers with soft credits, which were very easy to obtain. However, farmers often considered these credits as a subsidy and did not wish to pay
Rural credit partnerships
153
off the debt. That is, it was not only an economical problem, but also a psychological/educational one (SWINNEN et al., 1999). As a result, by 1994, access to
soft state credit had become rare.
The new formal financial institutions that have arisen in the financial market of
Kazakhstan are reluctant to lend to agricultural producers for a number of reasons: (1) lack of collateral, low profitability, (2) outstanding debts, (3) lack of
credit history, and (4) high transaction costs.
Currently, large- and middle-scale farms, in particular grain producers, obtain
credit from two main sources: Subsidised credit provided by the government,
and through credit programs offered by international financial institutions. However, for the overwhelming majority of Kazakhstani farmers, informal credit has
become the single source of replenishing financial resources.
Today, the Kazakh rural financial sector is represented by three main players:
The government, international financial institutions and informal lenders. Financial institutions such as leasing companies, credit partnerships, credit unions,
and micro-credit organisations still play a very insignificant role for agricultural
producers.
3
THE ROLE OF CREDIT CO-OPERATION IN THE DEVELOPMENT
OF THE RURAL FINANCIAL MARKET
It is widely recognised that non-bank financing plays a significant role for rural
producers in developing countries and transition countries (BANERJEE et al., 1994).
Cooperative financial institutions are typically seen as filling a market niche that
consists of low-income entrepreneurs, small business people, or farmers who
need credit but who have essentially no collateral. In other words, cooperative
financial institutions may be particularly well-suited to bringing banking services to the otherwise "unbankable" (EMMONS et al., 1997).
By its nature, the credit cooperative is not opposed to traditional banks, but
rather supplements them. The credit cooperative system can better respond to
the specific interests of low-income rural producers than can formal financial
institutions, allowing them to periodically carry out innovative activity and investment projects (PHILIPPOVA, 2000). Cooperative financial services differ from
commercial bank services by their availability, cheapness, and simplicity. The
specific feature of the agricultural sector is the small scale of potential borrowers: Even the largest farms cannot be compared with industrial enterprises. In
addition, most agricultural entities are usually geographically removed from
financial centres.
Due to economies of scale in the provision of credit, credit cooperatives can
enhance competitiveness and facilitate the dissemination and adoption of innovations, particularly when markets are incomplete and farmers’ technical knowledge
154
Sholpan Gaisina
is deficient. This would enhance farmers’ economic well-being and facilitate the
successful competition of co-operatives in the private sector (KOWALSKI, 1995).
There are some important advantages of rural credit cooperatives that enable
them to be much better operators in the rural area than conventional commercial
banks are.
First is the role of the rural community. The community controls the cooperative
and can ensure whether its own objectives are met. Social sanctions, which can
be provided by community residents who are also the members of the cooperative, are typically not available to the commercial banks. In addition, the sustainability of credit cooperatives lies in the long-term and repeated interactions
of the participants (BANERJEE et al., 1994). Cooperative financial institutions
effectively substitute "reputation capital" for traditional physical or financial
capital (EMMONS et al., 1997).
The second advantage of credit cooperatives lies in their goals. Cooperatives are
interested in generating high profits for stockholders. Their objectives therefore
focus on providing services for members rather than on maximising overall
profit.
The third advantage is the level of transaction costs. Lenders’ typical transaction
costs include collecting and protecting information, reporting on transactions,
and decision-making costs as well. According to Adams and Nehman, borrowers’
transaction costs may include: (1) loan charges collected by the lender beyond
interest payments, such as application fees, and forced purchases of other lender
services, (2) costs due to negotiations with someone outside of the formal lending
agency, such as extension staff, local officials, or co-signers, and finally (3) travel
and time expenses, which may be substantial in rural areas and at certain times,
e.g. during planting or harvesting periods (ADAMS et al., 1979). Since transaction costs are independent of loan size (fixed costs), their percentage of the total
loan volume is especially high for small loans, which are demanded by small
farms. In addition, transaction costs are not allocated in a fixed proportion
among applicants, and as a result, the high transaction costs lead to the credit
rationing of small farms (CUEVAS et al., 1986). Rural credit cooperative staff
members are closer to their clients; in most cases they are a part of the rural
community, and they have greater special knowledge of relevant agricultural
activities. This can allow credit cooperatives to reduce asymmetric information
problems, and along with it, adverse selection and moral hazard problems, thereby
reducing rationing and stimulating agricultural lending (SWINNEN et al., 1997). In
addition, rural credit cooperatives have more opportunities to analyse the creditworthiness of clients, and can estimate the profitability and viability of a proposed project using untraditional methods to enforce the contracts. These all allow
cooperatives to reduce their transaction costs.
Rural credit partnerships
4
155
RURAL CREDIT PARTNERSHIPS IN KAZAKHSTAN
Currently, the rural financial market in Kazakhstan is characterised by the government reluctantly withdrawing from this market; the private sector, in turn, is reluctant to enter because of high risks and insufficient information, and also because
of the threat of constant governmental presence. Rural financial institutions in
Kazakhstan are the least developed institutions compared with other market institutions. The financing of agriculture is carried out through a number of channels, but not all of these channels are equally effective from the point of view of
both accessibility for rural producers and their influence on agricultural development. There are three main players (and a number of other players who make
up a very small part) in the rural financial market. The major players include the
government, international financial organisations and informal lenders. The minor
players are commercial banks, rural credit partnerships, leasing companies, insurance companies, and local public financial funds (Figure 2).
Figure 2:
The structure of rural financial system in Kazakhstan
Government
International financial Institutions
Subsidised Credit
Commercial
Banks and Private Financial
Organisations
State-owned Financial Organisations
Local Authorities
Informal
Lenders
Private
financial
organisations
Rural Credit
Partnerships
Farms and Agricultural Enterprises
Source: Author.
Most rural producers have limited access to credit programs initiated by both
government and international financial organisations. Furthermore, property
such as agricultural land, machinery and houses are not considered to be proper
collateral by commercial banks. Moreover, group guarantees are applicable only
for rural producers with small credit demands.
Sholpan Gaisina
156
The Kazakhstani government recognised this problem and initiated the creation
of financial institutions which could coexist both with state financial programs
and with the private sector. It did this by resolving what were seen to be market
failures and by operating on a more commercial basis than government.
One of these initiatives was the establishment of a rural credit partnership network
(RCP), which were new (for Kazakhstan) financial institutions operating in rural
areas. That is, RCP is a new program for Kazakhstani agriculture that began in
2001 as a pilot project initiated by World Bank.
According to the project goals, RCPs were established to extend access to shortand middle-term credits for rural producers. It is still too early to make a strong
comparison between RCPs and rural credit cooperatives in their classic form.
This is because of the great amount of state participation in the RCPs’ activity,
which is evidenced by its 30% share in the RCP’s authorised capital (the state’s
share is represented by the state-owned Agro Credit Corporation).
Established RCPs have a number of essential positive distinctions from other
lenders, including:
–
Short-term (up to 3 years) and middle-term (over 3 years) loans;
–
Simplified requirements for the collateral;
–
Low interest rate.
Since 2001, 130 RCPs have been established in Kazakhstan, and 4,300 farms
became members of RCPs (2.2% of the total number), of which, 78% are individual (peasant) farms. RCPs’ members operate about 2.9 million hectares of
arable land (about 19.3% of the total arable land in Kazakhstan) and hold about
928,000 head of livestock (about 26.5% of the total number of livestock in
Kazakhstan). From these figures, one can conclude that large-scale farms and
agricultural enterprises are the main members of RCPs. In addition, most RCPs
are located in Kazakhstan’s northern grain regions.
Though the scope of RCP’s network is still insignificant for satisfying all rural
producers’ requirements, RCPs have proved their viability. The main problem in
this stage of RCP development is trying to find the most effective way to further
it.
5
THE MAIN CHALLENGES OF THE RCPS’ DEVELOPMENT IN
KAZAKHSTAN
Obviously, RCPs should be able to provide as many rural producers as possible
with stable access to low interest rate credits. This means that RCPs must have
the capacity to grow over time on a sustainable basis in order to form an appropriate governance structure, and to be competitive on the rural financial market.
Rural credit partnerships
157
The following methods could support and accelerate the further development of
RCPs in Kazakhstan:
1. To continue expanding state participation in RCP activity.
2. To expand RCP activity by including additional financial services.
3. To establish an agricultural bank based on the Agro Credit Corporation.
Continuing state participation. Given that Kazakhstani farms are still financially
unsustainable and the RCP network covers only about 2% of total farms, it is
impossible to count on the independent development of RCPs. In addition, there
are essential distinctions between different regions of Kazakhstan. Large-scale
grain farms in northern and eastern Kazakhstan need significant credit sums to
replenish working capital (for fuel, fertilisers, seeds and so on) and also to replace
obsolete machinery and equipment. RCPs can grant such sums only by using
state sources. In turn, small-scale farms in southern Kazakhstan have small
financial demands, but require flexible timing and are associated with high risks.
They also need state support, but in their case it is possible to gradually reduce it.
State participation in the RCP’s activity is viewed, in some aspects, negatively.
Namely, this system does not create regular financial intermediation between
savings and investments; rather, it is wholly dependent on state financial sources.
This is a reason why RCPs are excluded from decision-making regarding the
granting of credit; it is the business of Agro Credit Corporation to approve credit
applications. However, it is necessary to note that Agro Credit Corporation staff
members are removed from local RCPs and hence, cannot take into account any
local particularities. In addition, RCP managers, being excluding from the process
of decision-making, cannot develop their managerial skills in what is for them a
new area of activity. As a result, RCP, as the credit organisation which should
join the rural producers, does not in fact have a significant influence on rural
society due to insignificant financial power and because very few rural dwellers
benefit from membership in RCPs (GAISINA, 2006).
Obviously, the government policy concerning RCPs has to be viewed as stimulating and strengthening RCPs’ market position, rather than as direct financial
participation. The government should not engage in strong control of the interest
rate, allocation of credits and operational subsidies or the direct provision of
financial services.
Thus, a more important role for the government should be to undertake complementary investment in rural and agricultural development such as infrastructure
development, education, and improving returns on rural finance investments.
Undoubtedly, state resources may be necessary to support new financial institutions; However, subsidies should assist primarily with capacity-building that aims
to increase the skills of staff and management workers in the new institutions.
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Sholpan Gaisina
State subsidies should not try to fill gaps in income and interest rates of any
institutions.
Expansion of activity. Another way of making RCPs more sustainable is by expanding their functions and attracting new members. The former could be realised
by two means: Expanding the types of available financial operations and expanding the types of activity.
The experience of some developing countries with well-organised credit cooperative systems shows that low-income rural producers may have greater savings
capacities than is sometimes estimated by policy-makers.
There are obvious advantages for agricultural producers and rural dwellers to
place their savings in credit cooperatives rather than in commercial banks (or
other formal credit institutions):
–
–
–
Cooperatives use these savings only for lending to cooperative members
under certain conditions, and so the lending is the responsibility of all
members. Commercial banks, on the other hand, may place the savings in
any direction on behalf of and under the responsibility of the bank. As a
result, the default risk in cooperatives is much less.
Savings regulations in cooperatives are based on conditions that are determined and accepted by a general meeting of the members. In contrast,
contracts on bank deposits are recognised as a public contract and regulated
by the Law on Banking, that is, without the direct participation of depositors
and borrowers.
Those who place their savings in cooperatives have many more incentives
and opportunities to keep their cooperatives financially sound than do
commercial bank savers regard their own banks (GAISINA, 2006).
In turn, RCPs also have obvious advantages by offering saving services. Currently, RCPs are strongly-regulated by and dependent on a state agency, and
government loans directed to farmers make up the main part of the loanable
funds handled by RCPs. Thus, RCPs are not flexible enough to meet members’
diverse credit needs, and offer very limited variations of loan products. In this
case, small savings accounts could become a stable and relatively low-cost funding source, and in due course make up a majority of loanable funds. Obviously,
some necessary conditions have to be created in agriculture to attract savings. As
T.Y. Lee, Dong Hi Kim and Dale W. Adams emphasise, first of all, agricultural
production has to be profitable enough to allow rural producers to devote extra
money towards their savings. In successful years, even the smallest farms and
subsidiary small holdings are able to save significant amounts of money. Second,
credit institutions based on the cooperative model should provide rural savers
with secure and inexpensive ways to save financially. In other words, most rural
producers cannot afford long-distance travel and must lose days of work in order
Rural credit partnerships
159
to make a financial deposit in the commercial banks located in the cities. Therefore, savings opportunities offered by RCPs could facilitate access to this financial operation for rural producers.
Third, and probably most importantly, is the expectation that the savings will
bring some financial benefits to savers; in other words, savers have to have an incentive to save (LEE et al., 1977). Thus, well-organised rural credit cooperatives
can play a major role in mobilising financial savings in rural areas (for example,
the well-known credit cooperative systems of Germany, Japan, and the USA).
The expansion of activities could be done by setting up multi-purpose cooperatives based on existing RCPs, which deal with credit, input supply, marketing,
and even provide some municipal requirements of the inhabitants. RCPs can
forge much needed backward and forward linkages among agricultural production, agricultural input distribution, and agro-marketing and processing subsystems. Multi-purpose rural financial institutions will also accelerate the consumption linkages of technological change because they have a larger impact on
rural incomes as a result of stronger and non-inflationary production and saving
linkages (MELLOR, 1995).
Attracting new members to RCPs is at present limited for two main reasons:
1. Although the law on Rural Credit Partnerships stipulates the opportunity of
resource expansion due to the additional payments of participants, RCP fixed
capital is not in this case increased, and investors do not receive additional
votes. This additional payment mechanism does not initially encourage sufficient motivation.
2. According to the law, only legally-registered farms and enterprises can be
members of an RCP. However, as mentioned above, subsidiary small holdings
in Kazakhstan make up a significant part of the agricultural market, in particular in the livestock, dairy, vegetable and fruit production areas. Some
such entities have already reached the size of small farms. The problem is
their unwillingness to be legally-registered, because their expectations of being registration are not very promising.
This means that the existing regulations concerning membership issues should
be revised to expand the RCPs’ opportunity to attract participants from various
levels of farm structure. The main conditions should only be the financial sustainability of a member. Despite a subsidiary small holding not being registered
as a legal entity, this does not mean that the head of the holding is not a legal
person. He (she) could participate as a physical person, and it should be the
responsibility and interest of RCP staff to elaborate on or to accept some known
specific financial tools to collect information on the potential member and to
control how this non-legally-registered member acts as a borrower.
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Sholpan Gaisina
Creating an agricultural bank. Presently in Kazakhstan, some economists have
offered to create an agricultural bank based on the state-owned Agro Credit
Corporation. The idea of the creation – or reanimation – of a specialised agricultural bank has many shortcomings that should be taken into consideration.
Experience in some developing and transition countries shows that such banks
inevitably become dependent on budgetary injections, excessively burden the
national budget and, finally, may go bankrupt. If such a bank is completely
state-owned, then according to its agricultural essence, it would be forced to
provide credits on low interest rates (otherwise there is no reason for its creation). In this case, such a bank has no source of liquidity maintenance except
state budget funds (SEROVA, 2000).
In this case, the established agricultural bank would be independent from state
bodies regarding the allocation of subsidised resources, and would instead be
guided by commercial interests; its shares could gradually be sold to borrowers,
who in due course could become its proprietors. Then the bank could transform
from being state property and into a cooperative form like the Farm Credit System
in the USA. Moreover, in due course, it could return the national budget resources
invested in its fixed capital during the initial stages of development. But if such
a bank is just a distributor of budget resources, then it could lead to a decrease in
the credit amount received by farmers, because the bank takes a certain percentage
of its activity. On the other hand, such a bank would control the intended usage
of budget funds. In other words, they would have to carry out the functions of
ministries and local authorities, which also increases transaction costs.
The agricultural banking systems in most OECD countries originated as rural
cooperative systems, for example, Norinchukin Bank (Japan), Rabobank (The
Netherlands), Credit Agricole (France), and Farm Credit System (USA). Many of
these bank organisations started with strong participation of state capital and under
special state policy. As they grew, these banks were more and more involved in the
crediting of agri-business and other sectors of the economy. Simultaneously
continuing to maintain special relations with agricultural producers, they have
expanded their client base. For example, Rabobank originated as a bank focused
on farms, now it is both the major internal lender in the Netherlands and a large
lender for agribusiness all over the world. Similarly, Credit Agricole, the French
cooperative bank, provides credits to agricultural producers not only in France,
but also in other countries. Moreover, cooperative banks were often created as a
result of local initiatives with partial state support, as in the cases of Germany
and Poland.
Cooperative banks usually have a wide network of branches and offer certain
advantages in their services, such as:
–
More simplified scheme of mutual relations with clientele;
Rural credit partnerships
–
–
161
Estimation of a credit application not only includes economic indexes, but
also such factors as the experience of the farmer and qualitative condition
of the farm;
Savings services for even very small amounts, and farmers are often involved
in management.
To support a cooperative agricultural banking network, it is necessary to provide
significant outlays. However, this type of bank considerably minimises the risk
of default and has an opportunity to cover a very broad array of clients. These
networks are also developed in tandem with members of various farms, which
helps to quickly address changes in the agricultural sector (DUNKAN, 1999).
6
CONCLUSIONS
The agricultural financial system in Kazakhstan today is arranged in such a way
that the largest part of credit resources are received by large-scale farms and agricultural enterprises, while small-scale farms and subsidiary small holdings suffer
from inaccessibility to credit sources. Rural credit cooperation structures (in
Kazakhstan’s case, the RCPs) could be an effective means of solving that problem.
Rural credit cooperation has usually appeared in regions where expanding local
businesses experienced a shortage of adequate financial sources. Credit cooperatives may supplement the bank system, but they are no substitute for it.
Despite improvements for farmers in market and legal conditions that began in
2001 Kazakhstan, the current farm income forecasts reflect uncertainty concerning accessibility to credit resources. Improvements in rural financial markets
can be a key stimulus for accelerating agricultural productivity and rural growth.
Financial services are instrumental in assisting rural producers in maintaining
food security and smooth consumption levels, thus safeguarding and improving
labour productivity.
Thus, the successful development of RCPs in Kazakhstan requires undertaking
the following activities:
–
–
To revise the existing legal status of RCPs, to widen the number of financial operations, and to gradually transform RCPs into multi-purpose cooperative structures. According to the existing law, only registered entities can
participate in RCP activities. However, there are a lot of effectivelyfunctioning rural producers suffering from a lack of access to credit sources
that have the financial potential and wish to participate in RCPs.
To allow RCPs to collect savings. The law does not allow deposit operations to be conducted by RCPs. Thus, RCPs have the only stable and sufficient crediting source represented by state-subsidised credit programs. At
the same time, the rural population does not have an opportunity to allocate
Sholpan Gaisina
162
its free money in these financial organisations; commercial banks do not
have sufficient networks in rural areas and RCPs have no right to collect
savings.
–
–
–
To promote cooperative concepts among rural producers. For the conditions in Kazakhstan, it would be impossible to force farmers into membership in agricultural cooperatives. This is because of seventy severe years of
kolkhoz and sovkhoz membership. But at the same time, it is necessary to
conduct an educational campaign to explain the principles of pure cooperation, as seen in developed western countries.
To continue governmental financial support of RCPs. Under the current
conditions of agriculture in Kazakhstan, it is impossible to count upon the
independent development of RCPs. Obviously, it is more reasonable to
maintain state financial support of RCPs, simultaneously strengthening the
managerial and professional skills of RCP’s staff.
To study and use the best international practices in rural credit cooperation
development.
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BEZEMER, D. J. (2002): Credit markets for agriculture in the Czech Republic, EuropeAsia Studies, Vol. 54, No 8, pp. 1301-1317.
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EMMONS, W. R., MUELLER, W. (1997): Conflict of interests between borrowers and
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SWINNEN, J. F. M., GOW, H. R. (1999): Agricultural credit problems and policies during
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Sustainable rural development: What is the role of the agri-food sector?
MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central & Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 164-180.
TAKING THE HANDS OFF THE RURAL CREDIT MARKET:
AN EVIDENCE FROM CHINA
XIANGPING JIA*, FRANZ HEIDHUES**, MANFRED ZELLER***
ABSTRACT
Previous research on rural credit market explored credit rationing with exclusion
of the non-borrowers. Formal and informal credits were estimated independently. By jointly estimating the credit rationing in both the formal and informal
sector, this paper elaborates on the existence of pervasive credit rationing in rural
China and the poor strata can hardly benefit from the subsidized but highly regulated credit policies. Due to a lack of a formal insurance system, the rural poor
divert to informal credit to pool risks. Reciprocal loans, however, do not fully
substitute for the institutional lenders. We therefore observe a highly fragmented
rural credit market in China.
Keywords: Rural China, credit rationing, partial observability, bivariate probit,
Asia.
1
INTRODUCTION
The rural financial market in China carries the traditional paradigm that is similar
to what has been found in many other developing countries: Institutional credit
is subsidized; formal credit programs are highly centralized and heavily depend on
governmental budget; "cheap" credits with earmarked utilization are extended to
stimulate investments in agricultural production; private lending is highly regulated
and often considered illegal (CHENG and XU, 2004; PIOTROWSKI and JIA, 2006).
Due to the increasing awareness of the importance of agriculture and the striking
inequality between urban and rural region, policy markers in China wage a
national "New Rural China Campaign" from 2006 onwards to spur the rural
economy and ease tensions in rural areas. Credit policies, believed often as efficient and guided tools to deliver money to groups of interest, gain a great deal of
*
Institute for Agricultural Economics and Social Sciences in the Tropics and Subtropics
(490), University of Hohenheim, Stuttgart, Germany. Email: [email protected]
**
Institute for Agricultural Economics and Social Sciences in the Tropics and Subtropics
(490), University of Hohenheim, Stuttgart, Germany. Email: [email protected]
***
Institute for Agricultural Economics and Social Sciences in the Tropics and Subtropics (490),
University of Hohenheim, Stuttgart, Germany. Email: [email protected]
Taking the hands off the rural credit market
165
appeal. Given the widely existing failure of government-driven rural credit programs in other developing countries: What are the outcomes of the current intervention? Can the rural poor benefit? Is credit policy a candidate to serve agricultural development? This paper assesses the current state of the intervention on
rural credit markets in China.
Three major sets of views have dominated the literature on rural credit markets.
Development economists during the 1950s-1970s viewed the lack of physical
capital as a primary constraint on both agricultural and industrial growth. The contribution of technology to agricultural production, especially the "Green Revolution", reinforced the belief that subsidized credits to small farmers played a crucial
role in the increase of agricultural production, poverty alleviation and rural development (EICHER and STAATZ, 1998). Ample evidence in the 1980s presented that
the government-oriented "cheap" credit policies, implemented in numerous developing countries, failed to live up to the expectations. The concessionary rate of
interest discouraged savings, distorted factor price and failed in the substitution of
labor for land and capital, paralyzed the institutional lenders and dampened the
poor and smaller farmers (VON PISCHKE et al., 1983; ADAMS et al., 1984). The
counterintuitive opinions on subsidized credit policy shed light on the failure of
the intervention of government and quickly appealed to many free-market fundamentalists. The theory of intervention-free rural financial market was thereby
oversold in the 1980s. In the following years, focusing on imperfect market and
information asymmetries, development economists started to explain the reasons
for the failure of rural credit markets in developing countries and redefined the
role of government in the presence of imperfect information (STIGLITZ and
WEISS, 1981; HOFF and STIGLITZ, 1990; STIGLITZ, 1990; BESLEY, 1994). Notwithstanding the progress in economic theory, there was little micro-level evidence on that. Therefore, in the subsequent years, empirical research, based on
rural surveys in various geographical and economic scenarios, have been mounting up.
This paper addresses four main questions. First, in the presence of subsidized
credit policies, to which degree are rural households credit rationed? Second,
which factors determine credit rationing? Third, can the rural poor benefit from
the subsidized credit programs? Forth, how fragmented are rural credit markets
in China?1
This analysis is organized as follows. Section 2 reviews the applied measurement of credit rationing in a variety of empirical analyses, primarily using survey
data. Section 3 presents the data collection and describes the participation in
1
Rural financial markets have often been described as fragmented in the sense that different
segments of borrowers are observed to be systematically sorted across different loan types
and lending intermediaries according to the characteristics of the borrowers and lenders
(CONNING and UDRY, 2005).
166
Xiangping Jia, Franz Heidhues, Manfred Zeller
credit markets. Starting with the econometric framework, section 4 presents
results in single sectors, and subsequently compares between estimates of partial
observability and full observability. An interlinked credit system is jointly estimated afterwards. Related conclusions are drawn in section 5.
2
MEASUREMENT OF CREDIT RATIONING IN EMPIRICAL ANALYSIS
Since the formal credit market is highly regulated with capped rates of interest
and earmarked loans in favor of agricultural investment, institutional lenders
always prefer the more creditworthy and wealthy farmers. It is consequently believed that formal credit rationing in rural areas is widespread. Informal credit
market fills a gap in the presence of spillover of credit demand from the formal
sector (BELL, 1990). By using the evidence from Malawi, however, DIAGNE and
ZELLER observed that informal sector’s function is more than just serving as a
substitute to the formal sector; the formal and the informal sector are by no
means perfect substitutes (DIAGNE and ZELLER, 2001).
Concerning informal credit market itself, ALEEM (1990) observed that in a less
monopolistic informal credit market in Pakistan, interest rates charged by private
money lenders are close to average costs and slightly above marginal costs. In
comparison, BELL claimed that, though the conventional views on private lenders
overstate the exploitative high interest rates, a free-entry informal credit market
is impossible because the contract of informal credit is exclusive and there are
entry costs for new private lenders (BELL, 1990). In addition, BELL et al. (1997)
observed that active informal credit systems are often tied with other transaction
(85 percent of informal loans are shown to have tied transaction). Another important branch of literature found a striking prevalence of reciprocal credits
without explicit interest rates and collaterals, for example, UDRY in rural Northern
Nigeria (1994), and La Ferrara in Ghana (2003).
Though various approaches are available measuring credit rationing in empirical
analysis, collecting credit information in surveys has been widely used.2 The
earliest empirical evidence of measuring credit constraints directly through interview can be backdated to JAPPELLI (1990) and FEDER et al (1990). Credit rationing
is defined as the presence of demand for loans in excess of binding borrowing,
by asking farmers whether they are willing to borrow more at the prevailing interest rate. The household with a positive answer is labelled as "credit-constrained". This practice, however, has been questioned for its reliability because
the presumable extent of credit rationing is likely to be overstated, especially
when subsidized credit policies are used to gain political patronage or give priority to a specific population.
2
A thorough review of different approaches exploring credit rationing in empirical analysis
is available in PETRICK (2005).
Taking the hands off the rural credit market
167
Rather than asking respondents about their extra credit demand, ZELLER (1994)
refined the approach by obtaining information about the credit application of
households in Madagascar. Those who applied were asked whether the credit
was fully granted, partially granted or rejected. Those who did not apply for
credits were questioned their particular reasons; according to their answer they
were then grouped into no-demand and discouraged households. Furthermore,
the author conceptualized a sequential decision process where borrowers first
decided whether to apply or not, and lenders then decided whether to grant.
Two-stage Probit was used to handle potential selection bias in the sequential
decision making framework.
While there has been by now a number of studies measuring rural credit rationing
through the direct survey method, few studies explore the relationship between
formal and informal credit markets. The path-breaking theoretical work has been
carried out by BELL (1990) and BELL et al. (1997), with the gap of empirical evidence filled by KOCHAR (1997) who estimated the probability of demand and
access to both formal and informal sources and thereby observed the overstated
credit rationing as assumed in conventional research. But as KOCHAR (1997,
p. 344) stated "the extent of effective formal sector rationing … requires knowledge of the households who demand formal credit but do not have access to
it…and such an analysis is clearly necessary for the design of effective credit
policy".
In this paper, we jointly estimate the credit rationing in formal and informal
markets, by including the information of the non-borrowers. This is a unique
study, because there is an increasing consensus that, in developing countries,
formal and informal credit markets are of different nature, providing different
types of loans at varying transaction costs and interest rates as well as collateral
requirements. In this analysis, we focus on the credit rationing in formal credit
markets and its spillover of demand in informal sectors in the presence of a
regulated formal system.
3
DATA AND DESCRIPTION OF PARTICIPATION IN CREDIT
MARKETS
The data are based on a multi-topic survey which was conducted by the authors
in Spring 2005 in the North China Plain. The survey covers such topics as land
tenures, farm resource management and production, and rural credit access, and
thereby is of a production-oriented nature. 337 rural households out of 5 counties were randomly selected in 20 villages.3 In the survey, households were
3
The villages were purposively selected to ensure its dominant farming activities and to
meet various needs in the survey team. Though meriting some advantages in the multitopic survey, the sampling technique still limit the generalization of the derived results.
168
Xiangping Jia, Franz Heidhues, Manfred Zeller
asked if they had applied formal and informal credit respectively from 2003 to
2004. Those who had applied for credit were further asked whether they were
fully granted, partially granted or rejected were furthered. The non-applicants
were questioned for the reasons and accordingly were grouped into no-demand
and discouraged households. The certain household is defined as credit rationed
when the application was partially rejected, fully rejected or discouraged.
Table 1 presents the participation in both formal and informal markets by the
sample households from 2001 to 2004. The sources of formal and informal credits are strikingly similar for all. As the Agricultural Bank of China (ABC) is
more urban oriented, Rural Credit Cooperatives (RCCs) casts the main role and
88 percent of institutional credits are from RCCs. Due to the fragile insurance
and public educational system in rural China,4 credits for medical and tuition
outlay carry substantial shares in the stated credit utilization, even though the
institutional loans are earmarked for agricultural production. In addition, institutional loans are mostly in short term (less than 1 year) and of medium size.
Informal credits, as shown in Table 1, feature the predominance of reciprocal
lendings within kinship or social networks. While a majority of the formal credits are in short term and demand a third-party cosigner as guarantor, informal
credits are more flexible and 50 percent of them even explicitly set no repayment dates. Few informal loans require mortgage and 92 percent of informal
loans carry no interest. The difference in the collateral requirements suggests the
advantages of information and enforcement mechanisms in informal sectors.
The distinct utilization of credits suggests a highly fragmented credit market.
While 70 percent of formal credit is stated for productive utilization, 61 percent
informal credits are for consumption; more than half of which are for medical
service and education. The reciprocal mechanism is more of the nature of risk
pooling rather than standard credit transaction.
The capped rate of interest is similar to the findings in other studies by various
researchers in other developing countries. The interest rate for institutional loans
in rural China is capped and allows less flexibility. The mean rate is around
10 percent, which is comparable to the interest rates of 12-14 percent in Thailand
in 1984, 10-12 percent in India in 1981 and 12 percent in Pakistan in 1980
(HOFF and STIGLITZ, 1990). If we take the inflation into consideration, however,
the real interest rates for institutional loans in rural China are even lower. The
concessionary rate of interest distorts the relative price of labor and capital, resulting in overcapitalization and a distorted resource allocation in the rural
4
Though education expenditure is reported to be 3.4 percent of its GDP, one report from UN
exposed that the real number was 2 percent, far lower than the UN recommended 6 percent
(ECONOMIST, 2003).
Taking the hands off the rural credit market
169
economy because institutional lenders are in favor of established large-scale
firms instead of small farmers.
4
ECONOMETRIC SPECIFICATION AND RESULTS
Univariate probit and censored regression models are widely used in this field,
although non-borrowers are treated with in different ways. While ZELLER (1994)
employed a two-stage probit to conceptualize the sequential decision process of
borrowing and lending, MUSHINSKI (1999), by applying a univariate probit,
estimates notional demand offer probabilities which are higher than the results
using merely observed outcome of formal credit access. In this analysis, we select
the univariate probit for two reasons. First, by grouping the partially granted,
fully rejected and discouraged household into credit rationed households, the
information on the demand side, de facto, has been incorporated into the estimation. In Table 3, the bivariate probit, which is used to capture the sequential decision process as Zeller did, does not produce significant differences compared
with the parameters of the univariate probit estimation.
Secondly, a two-stage probit undermines the full observability because the usage
of the Mills ratio leads to sample selection bias and thereby the estimation in the
second-stage is based on the partial observability, i.e. the outcome of credit access
is conditioned on the probability of credit application. If non-applicants are
taken into consideration, the estimation is in full observability. In this case,
two-stage approach is redundant and leads to large standard errors because it
introduces severe collinearity among regressors (WOOLDRIDGE, 2002, p. 564).
Xiangping Jia, Franz Heidhues, Manfred Zeller
170
Table 1:
Formal and informal credit market participation (2001-2004)1
Formal Credit
Freq.
Informal Credit
Pct.
Sources
Agr. Bank of China
RCCs
Proposed Amount
4000
6000
10500
50000
Proposed Utilization
Agri. Production
Consumption
Medical and educational expenditure
8
11.76
60
88.24
Percentile
25%
50%
75%
90%
32
23
44.44
31.94
14
19.45
Social activity
Non-agriculture
Maturities2
Short term
Medium & long term
3
17
4.17
23.61
58
9
86.58
13.43
Annual Interest Rate
<=9.6
(9.6-10.56]
(10.56-12]
12+
19
15
28
5
28.37
22.39
41.78
7.46
13
45
10
19.12
66.18
14.7
34
21
38.18
61.82
Mortagage
Personal guarantee
Consigner & bail
Others
Repayment
Yes
No
Sources
Friends&relatives in the same
village
Friends&relatives in different
villages
Other resources
Proposed Amount
≤1500 (25% percentile)
(1500, 5000],75%percentile
(5000,10000], 90% percentile
(10000+)
Proposed Utilization
Agri. Production
Consumption
Medical and educational expenditure
Social activity
Non-agriculture
Maturities
Short term
Medium & long term
Without limiting maturities
Annual Interest Rate
No interest rate
Charging interest rate
<=9.6
(9.6, 12]
12+
Mortagage
Personal guarantee
Written pledge
Others
Repayment
Yes
No
Freq.
Pct.
112
57.73
77
39.69
5
2.58
53
108
25.59
52.16
28
18
13.53
8.7
59
130
27.83
61.32
70
33.02
20
23
9.34
10.85
77
15
105
37.20
7.25
50.72
184
17
5
9
3
91.54
8.46
163
22
.
44
75
36.97
63.03
Notes: 1. This table presents both formal and informal credit participation from 2001-2004.
Since respondents failed in recalling some information, especially informal credits,
the observations are unmatched from items.
2. Short term is defined for credit with maturity less than or equal to 12 months;
medium & long term is defined for credit with maturity more than 12 months.
Source: Authors’ calculations.
Taking the hands off the rural credit market
Table 2:
Name
171
Description of variables
Explanatory Description
Obs
Median
IQR1
15500.00
6000
5000
28155.8
2
Mean
SD
Dependent Variables
ration_04
apply_fm
infration_04
gramnt_0
4
grant_04
willing
Formal credit rationed in 2004
(1=rationed; 0=not rationed)
Applied formal credit in 2004
(1=applied; 0=otherwise)
Informal credit rationing in 2004
(1=rationed; 0=not rationed)
The amount of formal credit granted by
institutional lenders
Granted formal credit (1=granted;
0=otherwise)
Willing to borrow from institutional
lenders at the prevailing rate of interest
(1=willing; 2=otherwise)
337
(129)
337
(41)
337
(57)
39
337
(39)
337
(127)
Explanatory Variables
land_own
agehead
deprt
ini
Owning area of land (mu2)
Age of household head
Dependency ratio
Observable initial assets (yuan3)
337
337
337
337
7.71
47.06
0.30
17329.66
7
48
0.33
10110
5
15
0.43
21000
aginc_rt
Ratio of farming revenue to sum of offfarm income and farming revenue
Medical and tuitional expenditure
(yuan)
Dummy of educational level of head:
Elementary school
Dummy of educational level: Middle
school
Dummy of educational level: Secondary school or higher
Household member has social responsibility in the village
(1=has; 0=has no)
Has self-run business
(1=has; 0=has no)
Knows the number of financial institutions in the dwelling area
(1=knows; 0=does not know)
Had formal credit in the past 3 years
(1=had, 0=otherwise)
Had informal credit in the past 3 years
(1=had, 0=otherwise)
337
0.75
0.86
0.47
3.90
11.29
0.25
18694.9
4
0.28
337
3160.61
1100
2600
6511.74
med_tui
edu1
edu2
edu3
social
selfrun
knowbank
grant01_0
3
infgrant0
1_03
336
(29)
336
(255)
336
(52)
337
(41)
337
(28)
337
(227)
337
(24)
337
(54)
Notes
Figures in parentheses are frequencies if the boolean variable is True. 1. IQR means
interquartile range (75% percentile minus 25% percentile) 2. 1 hectare = 15 mu. 3. 1
US$ = 8.2645 yuan, from Sep. 2003 to Oct. 2004.
Source: Authors’ calculations.
4.1 A single sector model
The variables used in different regression models are listed in Table 2. Different
models with distinct definition of the credit constraint which have been employed
172
Xiangping Jia, Franz Heidhues, Manfred Zeller
in various empirical analyses are presented and compared below. We start with a
specification including the non-borrowers, and we then estimate a model with
partial observability by excluding non-borrowers. By comparing the results, we
are able to find how biased the results are if non-borrowers are excluded from
the survey.
4.1.1 Model specification with full observability
3 presents the results of the determination of credit rationing with the different
regression specifications. While model I applies a univariate probit, model II
uses a seemingly unrelated bivariate probit to conceptualize the sequential decision process of credit access proposed by ZELLER (1994). We see no significant
difference in the parameters between these two specifications. The results show
that households whose family members take on social responsibility in dwelling
village are less likely to be formal credit rationed. The result leads to the interesting question: Whether the local elites have sufficient liquidity or have no
demand for credit? In the application estimation of Model II and Model IV, the
coefficients of social links are positive, indicating the local elites are more likely
to apply for and to be granted meanwhile. The "cheap" credits are rarely in favor
of the poor strata.
Moreover, the households who rely more on agricultural revenue are less likely
to be formal credit rationed (aginc_rt). Rather than benefiting from the subsidized credit programs, the households with higher dependencies on agriculture
are less active in borrowing, as shown by the less significant parameters in the
application estimation in Model II and Model V.
Furthermore, the significance of lgmed_tui in model I and II, together with
the insignificance in the application equation in model II, shows that the rural
poor are highly rationed in credit for medical and educational expenditures. This
figure also suggests that in the absence of an efficient insurance system the informal credit can not fully pool the risks and that there exists potential demand
for consumption credits.
In addition, as the area of family-owned land is used as a proxy of household
size,5 the bigger households are more likely to be formal credit rationed, notwithstanding that they did not apply to formal lenders (significantly negative
parameters of land_own in Model II and Model V).
Lastly, in Table 3, we find that the older household heads are less likely to be
formal credit rationed because they are risk-averse and have inactive demand
5
In China, the rural land is owned by village collective and land is contracted to farmers.
Consequently, we employ the owning area of land as the proxy of the size of household.
Taking the hands off the rural credit market
173
(in the application estimation of model II, the coefficient of age_head is negative, though not significant).6
Besides the categorization of households into rationed and non-rationed, some
other definition of credit constraint are used in model IV and V. While model IV
explores who was granted institutional loans, model V, which was used by
FEDER et al. (1990) to identify the extent of credit constraint, measures who is
willing to borrow in formal credit markets. Households who are active in selfrun businesses are more likely to borrow formal credits. The earmarked credit
programs in favor of agricultural production can hardly be effective because of
either the depressed demand for agricultural loans or the fungibility of credits.7
The spillover of demand for medical and educational credit, as shown in model I
and II, proves the tremendously unmet demand for smoothing liquidity in the
absence of institutional insurance.
4.1.2 Specification with partial observability
In some targeted surveys, only borrowers are questioned and the information of
non-borrowers is rarely covered. In this case, the sample is truncated and we observe neither the dependent nor the explanatory variables for the truncated population. But the more common type is incidental truncation in which only the dependent variables are truncated, though the sample is representative of the entire
population (WOOLDRIDGE, 2002, p. 522). In an example of credit survey, if we
ask whether they applied and then only those applicants are furthered, we do not
observe the additional information for the non-applicants. But we still have other
variables for non-applicants (demographic characteristics, farming activities etc.).
Incidental truncation involves a self-selection component and HECKMAN (1979)
suggested a two-step procedure, in which a probability model is estimated at the
first step based on the full observability to correct the error of sample selection.
Compared with other specification in Table 3, Model III employs a Heckman
two-stage estimation with sample selection. At the first stage, whether household applied credit is estimated in full observability and afterward the amount of
formal credit access is regressed in partial observability. While the amount of
credit granted depends on the demographic variables and other observable characteristics which influence the decision making of the institutional lenders, whether
to apply is expected to depend more on financial resources. Though few variables
of interest are significant, the results are in no way trivial. Households with social
6
7
Actually, the impact of age on regression is different among individuals and it is interacted
with other factors, i.e. education and dependency ratio. By using a square term of age and
an interaction term of age and education, however, we find no nonlinear characteristic.
Fungibility means the interchangeability, substitution, and diversion of money in exchange
(VON PISCHKE and ADAMS, 1980).
174
Xiangping Jia, Franz Heidhues, Manfred Zeller
responsibility in a village can get more credit; the activeness in self-run business
is a crucial determinant of formal credit application.
In the presence of partial observability, the credit rationing of rural household is
conditional on the outcome of the credit application. By measuring the asymptotic efficiency of the parameter, MENG and SCHMIDT (1985) found that the cost
of partial observability is very high and thereby it is worth obtaining and using
extra observability information.
4.1.3 Informal credit access
Model VI in Table 3 presents the determinants of the credit rationing in the informal credit market. Several conclusions can be drawn, as follows. Initial assets
play important role because they can be easily observed and monitored in informal credit markets. The problem of information asymmetries is mitigated in the
informal market. In comparison, the observed assets can not be used as physical
collateral in formal credits.
In an agrarian society rural inhabitants are subject to substantial risks and numerous uncertainties. In the presence of poorly developed insurance markets,
credit can serve as a close substitute for desired insurance (BINSWANGER and
ROSENZWEIG, 1986). Though without interest and collateral requirement or even
a written contract, ‘quasi-credit’, a term which originated from PLATTEAU and
ABRAHAM (1987) and was further explored by FAFCHAMPS (1999), contains an
implicit obligation to reciprocate.8
4.2 An interlinked sector model
In the preceding section, we analyzed the credit rationing in formal and informal
credit markets respectively. Nevertheless, these two are rarely independent and
separated. In Table 4, credit rationing in both markets is jointly estimated by
starting a bivariate probit specification. We can not accept the null hypothesis
that credit rationing in both markets is independent and uncorrelated (ρ is significantly different from zero). Formal and informal credit markets are related.
8
The reciprocal credits are always embedded in long term relationships and repeat interaction (FAFCHAMPS, 1999). Unfortunately, such evidence was not collected in the questionnaire related to our survey.
Taking the hands off the rural credit market
Table 3:
Credit rationing in single sector: A model comparison
I
Univariate
probit
II
Seemingly unrelated
bivariate probit1
III
Heckman
(Stage II)
(Stage I)
DV
ration_04
ration_04
apply_fm
gramnt_04
land_own
0.048**
(2.44)
-0.014**
(-2.06)
-0.233
(-0.88)
-0.630***
(-2.75)
-0.069
(-0.21)
-0.043
(-1.43)
-0.637**
(-2.51)
-4.387***
(-2.8)
2.974**
(2.52)
-0.005
(-0.02)
0.124***
(3.1)
-0.326
(-1.09)
0.047**
(2.42)
-0.013*
(-1.88)
-0.261
(-0.99)
-0.608***
(-2.71)
-0.109
(-0.34)
-0.043
(-1.42)
-0.582**
(-2.37)
-4.476***
(-2.91)
3.062***
(2.63)
0.021
(0.07)
0.132***
(3.2)
-0.272
(-0.94)
-0.062**
(-2.04)
-0.009
(-0.91)
0.501
(1.5)
0.267
(1.05)
-0.998**
(-2.14)
0.045
(0.78)
0.205
(0.74)
0.033
(0.02)
0.209
(0.15)
1.130***
(3.64)
0.045
(0.9)
0.059
(0.16)
1230.023
(0.87)
-351.963
(-0.76)
36646.22***
(3.00)
-5713.729
(-0.60)
-2906.090
(-0.13)
2828.796
(0.77)
3127.048
(0.27)
agehead
edu1
edu3
deprt
lgini
social
aginc_rt
aginc_rtsq
selfrun
lgmed_tui
grant01_03
infgrant01_0
3
knowbank
apply_fm
-0.030
(-1.15)
-0.010
(-1.15)
0.457
(1.39)
1.225***
(4.68)
0.036
(0.86)
-22207.69
(-1.48)
IV
Who was
granted
V
Willing to
borrow
grant_04
Willing
-0.071**
(-2.30)
-0.010
(-1.00)
0.476
(1.46)
0.113
(0.41)
-1.076**
(-2.25)
0.055
(0.90)
0.029
(0.09)
3.228
(1.47)
-1.985
(-1.21)
1.258***
(3.98)
0.031
(0.64)
-0.296
(-0.70)
-0.006
(-0.32)
-0.006
(-0.85)
-0.265
(-0.97)
-0.188
(-0.91)
-0.558*
(-1.72)
-0.023
(-0.75)
0.125
(0.57)
0.223
(0.15)
-0.337
(-0.30)
0.020
(0.07)
0.102***
(2.75)
-0.035
(-0.12)
VI
Univariate
probit
infration_04
0.019
(0.87)
-0.003
(-0.33)
0.316
(1.15)
-0.233
(-0.94)
-0.870**
(-2.26)
-0.077**
(-2.4)
1.436
(0.78)
-0.789
(-0.57)
0.385
(1.28)
0.048
(1.08)
-0.242
(-0.97)
_cons
Obs
F-test
175
-0.030
(-0.18)
1.112
(1.54)
-0.002
(-0.01)
0.998
(1.37)
1.081***
(3.4)
-2.074
(-2.1)
336
336
336
LR
χ 2 (13)
=41.07
Wald
χ
2
(26)=73.33
Prob> χ =0.000
2
30121.58
(0.61)
-1.290
1.001***
(3.19)
-2.824
(-2.58)
336 (censored obs=298)
χ (8)=14.89
2
Prob> χ =0.0613
Wald
2
0.389**
(2.37)
-0.592
(-0.84)
336
-0.992
(-1.23)
336
336
LR χ (13)
LR χ (13)
LR χ (11)
=41.07
=19.68
=19.26
2
2
2
Notes: 1. The likelihood-ratio test of ρ = 0 : χ 2 =22.823, Pr> χ 2 =0.0000. We can not accept
the null hypothesis that the two estimation are uncorrelated and independent. The
figures in parentheses are corresponding z-value.
*, **, ***
Significant at the 10-percent, 5 percent, and 1 percent level, respectively .
Source: Authors.
Besides the bivariate specification, a univariate probit with endogeneity is specified as well. In the presence of endogeneity, whether a household cooperates
with others in farming activities (tie) is used as instrumental variables to identify
the credit rationing in formal sector. The selection of the instrumental variable is
176
Xiangping Jia, Franz Heidhues, Manfred Zeller
very challenging because few variables can be unrelated to the disturbance in
formal credit rationing but highly related to the informal credit rationing. The tie
in a local village is very important in the reciprocal credit between kin and
friends, and it is presumably unrelated to formal credit access. The Wald test of
exogeneity, however, shows that we can not reject the null hypothesis that the
probability of informal credit rationing is exogenous from the formal credit rationing. A simple univariate probit can be used to jointly estimate the credit
rationing.9
Table 4:
Interlinked formal and informal credit rationing
Bivariate probit1
DV
infration_04
ration_04
infration_04
land_own
0.050**
(2.51)
-0.015**
(-2.21)
-0.212
(-0.80)
-0.626***
(-2.74)
-0.058
(-0.18)
-0.043
(-1.42)
-0.669***
(-2.71)
-4.535***
(-2.91)
3.113
(2.64)
0.009
(0.03)
0.123***
(3.07)
-0.468
(-1.60)
-0.084
(-0.54)
0.018
(0.83)
-0.003
(-0.37)
0.291
(1.07)
-0.241
(-0.98)
-0.912**
(-2.37)
-0.071**
(-2.20)
agehead
edu1
edu3
deprt
lgini
social
aginc_rt
aginc_rtsq
selfrun
lgmed_tui
grant01_03
knowbank
lgexp_soc
infgrant01_03
9
Univariate Probit
1.443
(0.79)
-0.761
(-0.56)
0.366
(1.26)
0.059
(1.33)
ration_04
0.950***
(4.74)
0.047**
(2.33)
-0.015**
(-2.09)
-0.342
(-1.25)
-0.606***
(-2.59)
0.146
(0.44)
-0.028
(-0.90)
-0.764***
(-2.81)
-4.959***
(-3.09)
3.304***
(2.73)
-0.158
(-0.57)
0.118***
(2.93)
Probit with
endogeneity2
ration_04
-0.384
(-0.08)
0.047*
(1.84)
-0.013
(-1.18)
-0.195
(-0.30)
-0.607*
(-1.92)
-0.112
(-0.12)
-0.053
(-0.72)
-0.654
(-0.95)
-4.042
(-0.80)
2.748
(0.85)
0.007
(0.01)
0.118**
(2.02)
0.010
(0.36)
-0.487**
(-2.02)
One of the possible reasons for the exogeneity might be the selection of instrumental variables. The choice of instruments should be based on the understanding of formation of the informal and reciprocal credits. Unfortunately, this topic is not covered in our analysis. This
shortcoming begs further analysis on the informal credit and nature of agrarian institutions
in the presence of imperfect markets.
Taking the hands off the rural credit market
_cons
Predicted
probability3
0.083
(0.14)
probmg1=0.639
p11=0.221
p01=0.028
IV: tie
-1.096
(-1.36)
probmg2=0.249
p10=0.417
p00=0.334
1.027
(1.39)
pr=0.521
pr: the univariate predicted probability of
success Pr(y=1)
177
1.159
(1.65)
pr=0.637
-0.055
(-0.73)
Notes: 1. Likelihood test of ρ = 0 : χ 2 =28.52, Pr> χ 2 <0.001.
2. Wald test of exogeneity: χ 2 =0.07, Pr> χ 2 =0.785. 3. p11 calculates the bivariate
predicted probability Pr(y1=1, y2=1); p10 calculates the bivariate predicted
probability Pr(y1=1, y2=0), so do p01 and p00; probmg1 calculates the univariate
predicted probability of success Pr(y1=1)
Source: Authors.
In Table 4, the discussion centers on the predicted probability when credit rationing is jointly estimated in both markets. In the scenario of a single sector, the
households are formally credit rationed at the probability of about 0.639. In the
scenario of interlinked formal and informal sectors, we predict the probability of
formal credit rationing as well. If the reciprocal loans between households function as an efficient substitution for the institutional loans, the jointly estimated
probability of formal credit rationing is expected to be significantly lower than
in the case of the single sector. Unfortunately, the figure is 0.521 when both of
the credit markets are jointly estimated. The reciprocal mechanism can not fully
substitute for institutional lenders.
5
CONCLUSION
The objective of this paper was to measure the credit rationing in a purposively
selected rural setting in China. Here, we explore the interdependence between
formal and informal credit markets. Several conclusions can be drawn from the
study. First, there exists pervasive rationing in the highly regulated formal credit
market in rural China. Second, the subsidized credit policies favor local elites,
instead the targeted poor strata; and the earmarked credit programs are less effecttive. Third, informal credits, in a form of reciprocal arrangement, weakly substitute for the institutional loans. Different segments of borrowers are systematically sorted out across different loan types. The rural credit market is highly
fragmented.
The well functioning financial system is positively linked to long-run economic
growth (LEVINE, 2004).10 Government intervention not only shapes the structure
and function of financial intermediaries, but also has a disproportionately
beneficial impact on the poor. Nonetheless, the ubiquitous failure of intervention
10
In LEVINE’s reviewing paper, he also lists some opponent research about the financegrowth nexus.
178
Xiangping Jia, Franz Heidhues, Manfred Zeller
in the rural credit market suggests government should "take hands off" direct
intervention. Market failure does not mean governments are able to be free from
the problem in affected markets. This, however, also does not mean that government should be inactive in promoting credit markets. Institution building that is
innovative and efficient in tackling the information problems in screening credit
applications, strengthening incentives and enforcement, improving court system,
and decentralizing market power is an option to mitigate the imperfect information problem rooted in rural credit markets. Secured land rights are crucial for
widening formal credit access, and improved access to credit and insurance is
likely to contribute to reducing poverty. Subsidized credit programs, however,
can hardly be a way to seek income redistribution or sustainable poverty reduction. Good intentions (such as interest subsidies) always paves the way for disastrous outcomes (such as rent-seeking by non-target groups).
ACKNOWLEDGEMENTS
We highly acknowledge the scholarship support from the state of BadenWuerttemberg (Landesgraduiertenfoerderung) via the Faculty of Agricultural
Sciences, University of Hohenheim. We are also grateful to the China Ministry
of Education (MOE) and Deutsche Forschungsgemeinschaft (DFG) for their
support at the early stage of this study.
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FOOD INDUSTRY
Sustainable rural development: What is the role of the agri-food sector?
MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central & Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 183-199.
RURAL DEVELOPMENT POLICY AND FOOD INDUSTRY
DEVELOPMENT: INVESTIGATIONS OF SMALL FIRMS IN DENMARK
DEREK BAKER, JENS ABILDTRUP∗, ANDERS HEDETOFT∗∗
ABSTRACT
Food industry firms in remote areas face a set of constraints, which have motivated the form and function of assistance instruments under various regional and
rural development programmes. Recent food industry developments present new
challenges to these firms, for which available assistance may be less appropriate.
This paper employs telephone interviews and workshop discussions with firms
in isolated locations to investigate their satisfaction with assistance programmes,
their ability to innovate (through product introductions) and respond to challenges in the food industry (the emergence of power buyers). Further investigation was carried out on the topic of firms’ formation of networks, and the use of
available assistance in doing so. Firms’ evaluations of support received in satisfying specified objectives are not correlated with their views on which objectives should be addressed. Some concrete suggestions for network activities had
been made, but overall the development is at an early stage.
Keywords: Regional development, rural development, food industry, policy.
1
INTRODUCTION
Food industry firms in remote areas face a set of constraints on their development associated with their small local markets, isolation from larger markets and
remoteness from the business mainstream. Such firms often face highly seasonal
supply, and demand, patterns and produce low product volumes. Local and parochial product attributes provide the only basis for product differentiation, the
effectiveness of which can be reduced by non-availability of key inputs and ingredients. Skill shortages and poor social and physical infrastructure may also limit
firms’ capacities. Assistance to firms in this situation lies at the heart of regional and rural development policy instruments across a range of programmes.
∗
∗∗
Senior Researcher, Division of Technology and Production, and Researcher, Division of
Environmental Economics and Rural Development (respectively), Institute of Food and
Resource Economics, Faculty of Life Sciences, University of Copenhagen, Denmark.
Email: [email protected]
Consultant, Centre for Regional and Tourism Development, Nexø, Denmark.
184
Derek Baker, Jens Abildtrup, Anders Hedetoft
Against this background, the food industry is undergoing rapid consolidation,
and most particularly "power" buyers, including retailers, have emerged. These
conditions place new demands on small food industry firms that they are illequipped to handle. In particular, innovations in products and processes may
become more difficult to develop and implement. Assistance programmes may
not address these problems either in their design or in the arrangements they offer.
This paper reports on a structured set of discussions with eleven small food industry firms operating in isolated parts of Denmark. Its objectives are to evaluate
regional and rural development assistance, as experienced by these firms, for its
ability to solve the problems they face. Particular emphasis is given to the
firms’ capacity to innovate (through new products) and deal with power buyers.
A popular strategy amongst firms was the formation of networks, and this was
also examined for its suitability for support under various assistance schemes.
A further objective of the work programme was to provide firms with the opportunity for structured discussion of policy with government staff, and researchers.2
This paper has four sections. In the second, available assistance programmes are
outlined, the method used to recover information from firms and the setting for
discussions are detailed, the participating firms are characterised, and formal
evaluations of assistance received and the targeting of assistance more generally
are presented. The third section provides a summary of discussion with firms,
and the final section presents conclusions and policy recommendations.
Both rural development policy and regional business policy target the development and economic growth in remote or disadvantaged locations of Denmark.
However, lagging peripheral regions are in particular addressed by the regional
business support programmes (REGERINGEN, 2006). The objective of Danish rural
development policy is that all areas in Denmark will be attractive areas for development and settlement and thereby sustaining the geographical dispersion of the
population and economic activity (INDENRIGS- OG SUNDHEDSMINISTERIET OG
FØDEVAREMINISTERIET, 2004). Its more specific objectives are:
1. Reduction of the income disparity between rural and urban areas through
economic growth in rural areas;
2. Increased employment in rural areas;
3. Increased settlement of rural areas; and
4. Enhanced supply of environmental and cultural services in rural areas.
In Denmark there are five support programmes that to some degree are geographically targeted at rural or lagging regions and are relevant to agro-food
enterprises (see Table 1). All are implemented on a re-imbursement basis of
2
This research is funded by the Danish Innovation Law, and administered by the Danish Ministry of Agriculture,
Food Industry and Fisheries.
Rural development policy and food industry development
185
some proportion of non-recurrent expenditures. Although local government
agencies and private firms are eligible for many of these programmes, there is no
facility for applications by groups or networks of firms.
2
MATERIAL STUDIED
Some 15 small Danish food industry firms were approached in late 2006 and
invited to participate in research into the reach and effectiveness of regional
and rural development policies in addressing their problems. Eleven firms
agreed to be interviewed by telephone and to attend a workshop to discuss the
issues with government staff and the researchers. Telephone interviews were
conducted in November 2006 and subsequent discussions with the firms were
held in February and March 2007. These delivered a set of responses that characterised firms’ commercial size and operations, use of regional and rural development assistance and managers’ opinions about effectiveness and targeting
of such assistance.
In order to focus the discussion at the workshop (5 March 2007), two prominent
current food industry issues were emphasised: New product development and
introduction; and the exercise of market power by large firms in the food chain,
particularly retailers. In response to firms’ emphasis on local networking and
complementary actions by firms, some workshop discussion was dedicated to
this topic. Workshop attendance entailed 5 food industry firms, a researcher
from Bornholm’s Centre for Regional and Tourism Research, a representative of
the EU’s LEADER+ programme, a staff member from the Directorate of Food,
Fisheries and Agribusiness in the Ministry of Food, Agriculture and Fisheries
working on implementation of regional development policy, and two researchers
from FOI.
Table 1:
Programme
The Rural Development Programmes
The LEADER+ programme
The innovation law
("Innovationsloven")
Danish regional and rural development programmes
Legal basis
Implementing agency
Detail
Targets
Two principal schemes (relevant
to the agro-food industries):
• "subsidy scheme for imCompetitiveness and the value added of existing agricultural prodproving the processing and
ucts, and the development of new food and agricultural products.
Council Regulation
marketing of agricultural
The Directorate for Food,
(EC) Nos. 1257/1999
products"; and
Fisheries and Agri Busiand 1698/2005 for
ness,
the periods 2000Ministry of Food, Agri2006 and 2007-2013,
• "subsidy scheme for proculture, and Fisheries
respectively
moting the adaptation and
Living and business conditions in rural areas
development of rural areas"
(the so-called "article 33").
Four priority themes:
The Directorate for Food, To encourage local communities 1) use of know-how and new technologies to enhance the comFisheries and Agri Busipetitiveness of products and services of rural areas;
Council Regulation
to initiate economic, social, and
ness,
2) improvement of the quality of life in rural areas;
(EC) No 1260/1999
Ministry of Food, Agri- cultural activities in rural areas 3) assistance to small enterprises with market access for local
culture, and Fisheries
products; and
4) exploitation of local natural and cultural resources.
To promote innovation and
The Directorate for Food,
Priority topics include the working environment, food documentaFisheries and Agri Busi- enhance research and develoption, food safety, exports, organic production, processing for nonDanish regulation
ness,
ment effort in the agricultural, food use, applied research, animal welfare, eating quality, traceabil318 (7 May 2001)
Ministry of Food, Agriity, quality control and environmental protection.
culture, and Fisheries
food and fisheries sectors
The rural fund for
financing experimental
projects in rural areas, Funded from annual Ministry of Interior and
and information and
budget allocations
Health
research initiatives
("Landdistriktspuljen")
To improve the potential for
development of rural areas
Eligible investments
•
•
•
•
Non-recurrent costs associated with environment, hygiene, food safety, documentation of production processes, traceability,
organic production and animal health.
17% of eligible costs or 25% in target
areas.
Non-recurrent costs associated with establishment of networks, renovation and use
of abandoned buildings, investment in infrastructure, and marketing of regional
products.
25% of eligible costs; 50% for government
agencies.
•
•
Non-recurrent expenditures
Both public and private agencies can
apply.
•
•
Non-recurrent expenditures
Maximum 50% of eligible costs, 55% for
firms in disadvantaged locations
Support of new activities and/or pilot projects, research and informa- •
tion projects
A broad range of eligible items, although
not recurrent expenses.
Three priority themes:
The objective 2 programme of the EU
Structural Funds
Council Regulation
(EC) No 1783/1999
(The EU Regional
Fund) and Council
Regulation (EC) No
1784/1999 (The EU
Social Fund)
National Agency for
Enterprise and Construction, The Ministry of
Economic and Business
Affairs
Source: Authors’ compilation.
1)
To increase wealth and employment in regions with structural problems through im2)
provement of the conditions for
development and adaptation
3)
development of regions (support to local agencies in the form
of infrastructure investments, consulting services, analysis and
research);
Grants subject to approval by local groups.
development of small and medium-sized firms (support of
product development, plant construction, technology transfer,
consulting services and environmental improvements); and
development of competence (training and development of
educational institutions and processes).
Rural development policy and food industry development
187
Firms were identified in association with relevant authorities in some isolated
regions and contacted twice. In the first case an interview was conducted and
firms were invited to a workshop to discuss the connection between their firms’
development and regional and rural development policy. In the second case,
points raised in the telephone interviews were re-visited and the content of discussions at the proposed workshop were finalised.
Some 11 firms (7 from Bornholm, 4 from Northwestern Jutland) were interviewed, of which 6 provided complete responses and support for the workshop.
Firms participating in the study generally employed 4-10 people and had 2006
sales of 4-15 million DKK. Around 10-30% of products sales were "local", with
the remainder going outside the area: An exception was a food processor for
which some 80% of sales were to local firms for further processing. Most firms
had some degree of vertical integration (e.g. ownership of a retail outlet and/or
specialised distribution equipment), and a few were engaged in farming.
All firms interviewed had received support from regional and rural development
programmes. Three firms had received support for investment in production facilities under the Objective 2 programme or the Rural Development Programme
and most of the firms had received support for marketing under the LEADER+
programme or the Rural Development Programme.
Almost all firms owned and used a brand, but none used a brand that was owned
or administered by a local network. Almost all firms supplied large retail chains,
but just one supplied retailers’ own-label brands. Most firms reported that in the
last 5 years their main product or service had changed, their production and
marketing procedures had changed and their relationships with local firms had
all changed considerably. The only exceptions were new firms. Changes in the
main product mainly involved an extended product line (rather than "truly new"
products); changes in process involved more value addition; and new relations
with local firms typically involved formal or informal networks. Other than
locality, firms were unable to describe what common factor mobilised their network.
When firms were asked to describe their greatest single advantage, all mentioned the uniqueness of location. The older firms cited their established, known
and reliable brands in various markets, and their business status in the locality.
Younger firms cited high quality and uniqueness of products: Particularly the
uniqueness of their location.
Derek Baker, Jens Abildtrup, Anders Hedetoft
188
3
RESULTS
3.1 Problem definitions
When prompted about each of 19 proposed "problems" likely to be faced by
small food industry firms in a remote area, firms rated the problems according to
severity, or alternatively not as problems or as an advantage (see Table 2). The
most frequently cited "severe" problems were lack of information, the dominance of large firms as buyers and access to/complexity of government support.
Other common definitions of problems included cost or time involved in transport, lack of a business network extending to other locations (no firm claimed
that local networks were lacking), and paperwork. A few firms claimed that
there were advantages to having large firms as buyers (specifically, assistance
with product development), and to documentation demands (aptitude for traceability).
Table 2:
Firms’ assessment of problems faced
Isolation from consumers
1
4
Isolation from wholesale and retail network
1
4
Isolation from farm and food raw materials suppliers
1
4
Isolation from suppliers of other inputs and services
1
4
Inability to differentiate products
5
Lack of information about market trends
4
2
Lack of information about new technologies
3
3
Lack of skilled staff
2
Lack of a local business network
3
6
Lack of a business network involving other locations
3
3
Standards and procedures (required by buyers) in production and processing
1
2
3
Standards and procedures (required by regulation) in production and processing
1
1
4
Having to provide documentation and information as part of running the business
3
1
The dominance of large firms as buyers
4
Cost or time involved in transport
2
2
2
Lack of government support
2
2
2
Lack of clear information about government support
4
2
Inappropriate objectives, purposes and targeting of government support
4
2
Complexity and delays in applying for government support
6
Source: Authors.
An advantage
Not a problem
Moderate
Problem identified in interview
Severe
Severity of problem
2
1
1
Rural development policy and food industry development
189
3.2 Evaluation of assistance
Although almost all of the firms contacted had utilised regional and rural development assistance funds in the past, most declined to discuss details of the programme employed, the amounts and the purpose of the assistance. Firms did
provide indicative information about the effectiveness of the assistance used, in
response to prompting in regard to a set of broader policy objectives as proposed
by the authors. Table 3 lists the 25 possible policy targets offered, and the frequency of responses to two questions:
1. According to the firm’s experience, to which extent did the assistance
received achieve the nominated target (on a scale -3 = "assistance was a
major barrier to achieving this to +3 = "assistance was a major help in
achieving this") – averages are presented in the middle column of table 3;
2. What role should each of the nominated policy objectives play in regional
and rural development policy (on a scale 0 = "no role" to +3 = "a major
role") – averages are presented in the right hand column of table 3.
Firms rated assistance received very favourably (average of 2.6 out of possible 3.0)
for its ability to "meet the needs of firms in this locality". Firms ranked this objective first amongst the positive impacts of the received assistance, and first
equal for its appropriateness for being addressed by regional and rural development assistance.
Firms also ranked specific new product introduction objectives (identifying and
introducing new products, as well as new technical procedures) 3rd and 2nd
respectively as being achieved by assistance received. However, the scores were
low at just 1.0 and 1.2 of a possible 3.0. Firms’ rated the effectiveness of the assistance they had received at 0.8 (rank 4th) in assisting development of locationspecific unique food products, and 0.6 for networking (three objectives – between
firms locally, in other locations, and in adding value) and ranked them 5th equal.
Firms’ assessments of the assistance on broader development objectives (local
employment, retention of added value) were very low (0.0 out of possible 3.0).
Business-oriented objectives (links with buyers and suppliers) also scored rather
poorly and ranked 9th.
Firms’ opinions about the appropriateness of regional and rural development
policy for addressing the specified objectives present a different pattern. Solution of transport and logistic problems was ranked first equal, with solution of
other location-specific "uniqueness"- related problems and "food industry opportunities" ranking 3rd, 4th and 5th. Meeting the needs of food industry firms was
ranked the 6th most appropriate target of regional and rural development assistance: Albeit from a sample comprised of food industry firms. Firms’ ranking of
the objective "establishing links with buyers" (12th) was far higher than "establishing links with suppliers" (22nd).
Derek Baker, Jens Abildtrup, Anders Hedetoft
190
Table 3:
Firms’ evaluation and targeting of policy instruments
Experience of effectiveness
of assistance in satisfying
specific policy objectives
Opinion as to the
appropriateness of
regional and rural
development in
achieving specific
policy objective
-3 = strongest negative
effect; +3 = strongest
positive effect
0 = no role; +3 = a
major role.
(rank)
(rank)
Meeting needs of firms in this locality
2.6 (1)
3.0 (1)
Meeting needs of food industry firms
0.2 (12)
2.0 (6)
Identifying and serving new markets for food products
0.0 (15)
1.0 (18)
Identifying and introducing new food products
1.0 (3)
0.5 (24)
Identifying and implementing new technical procedures for
food processing
1.2 (2)
1.2 (12)
Identifying and implementing new ways of organising the firm
0.2 (12)
0.5 (24)
Identifying and implementing new ways of co-ordinating with
other firms
0.6 (5)
1.8 (7)
Overcoming problems associated with isolation
0.0 (15)
2.5 (4)
Overcoming other problems (i.e. not isolation) unique to this
locality
0.2 (12)
2.7 (3)
Developing food industry opportunities unique to this locality
0.8 (4)
2.3 (5)
Helping establish links with suppliers
0.4 (9)
0.7 (22)
Helping establish links with buyers
0.4 (9)
1.2 (12)
Helping firms in this locality to work together with each other
0.6 (5)
1.7 (8)
Helping firms in this locality to work together with firms
elsewhere
0.6 (5)
1.2 (12)
Identifying and implementing the benefits of formal
co-operatives
0.0 (15)
1.2 (12)
Helping in identifying how to add value to food products
0.4 (9)
1.0 (18)
Helping in providing the necessary investments to add value to
food products
0.0 (15)
1.5 (9)
Helping in providing the necessary organisational change to
add value to food products
0.0 (15)
1.0 (18)
Help in working with other firms to add value to food products
0.6 (5)
0.8 (21)
Ensuring that value added is retained in the local economy
0.0 (15)
0.7 (22)
Solving transport and logistic problems
0.0 (15)
3.0 (1)
Creating local employment
0.0 (15)
1.5 (9)
Raising local skill levels
0.0 (15)
1.2 (12)
Maintaining local population levels
0.0 (15)
1.2 (12)
Maintaining a stable age distribution in the local population
0.0 (15)
1.3 (11)
Nominated objective of regional and rural development policy
instruments
Correlation between assessment of effectiveness and of significance of role (Pearson’s)
26%
Correlation between rankings of effectiveness and rankings of significance of role (Spearman’s)
3%
Source: Authors.
The final rows of Table 3 show the Pearson correlation between firms’ assessments of policy performance over each policy objective and appropriateness for
Rural development policy and food industry development
191
addressing that objective, and the Spearman correlation for the same variables
(but addressing rankings). The Pearson correlation coefficient (26%) is insignificant at the 10% level of the test, and the Spearman correlation coefficient is
close to zero. This means that although firms express some satisfaction with assistance received, they indicate that policy is inappropriately targeted across a
broad range of possible objectives.
Firms’ ranking of broad development objectives (e.g. local employment) is 9th
out of 24. Their ranking of social objectives (maintaining local population and
influencing its age distribution) is 11th and 12th: Rather higher than enhancing
value addition by organisational change (18th and 21st) and retaining value added
within the local community (22nd).
3.3 New product introduction
Firms generally reported an abundance of ideas for new products and few technical problems in developing the products. Two exceptions concerned the
sourcing of raw materials and ingredients. Where differentiation of products required specialist activities by farmers, special stock control within the firm or
investments in equipment, constraints on new product development were experienced. Where specialist ingredients (e.g. herbs and flavourings) from outside
the area were needed, delays in locating a reliable supplier held up product development. The major problems, however, related to information and analysis:
–
–
Information about trends in market behaviour and prices, and in consumer
preferences; and
Analysis of likely and actual impacts of new products on the existing product
line.
Several firms reported a shortage of facilities and services for "testing" (including
certification) of products and processes. Several firms operated retail establishments (e.g. restaurants) where consumer testing was carried out. Market access for
new products was not widely reported by firms as a problem. Moreover, large
retail chains were reported to have assisted firms with product labelling, delivery
of product information and other key steps. Most firms used a wholesaler, in
some cases as an exclusive sales outlet. The firms reported no significant barriers
to new product development as a consequence of sales to wholesalers.
Firms were unable or unwilling to list cost items associated with new product
development. In general, staff time was not counted and the costs of technical
tests were unknown. Instance of product failure was not reported, and its costs
not factored into overall costs of new product development and introduction.
Two firms reported that new product development was a form of promotion, designed to sell more of the main product lines: The firms could not comment fully
192
Derek Baker, Jens Abildtrup, Anders Hedetoft
on the extent to which this was effective, and did not substitute sales away from
the main products.
Two firms supplied ethnic shops with special fresh products. They reported
logistic problems (high transport and storage costs relative to those of mainland
firms) to be a major barrier to both introduction of new products and accessing
new buyers. One firm reported similar problems in assembling fresh ingredients
brought in from outside the area.
Entry into export markets (as one form of new product introduction) drew a
separate set of comments from firms. Barriers included unfamiliarity with foreign
countries’ administrative tasks, the need to identify freight carriers and warehousing services, securing information about buyers and advice on payments
systems. One firm had paid a fee to a government agency to assist, but had received "advice on strategy, rather than practical help".
Almost all firms listed their locality as being a valuable promotion item in new
product introduction and sales of the existing product line. Firms expressed the
view that local origin of new products and their raw materials formed a central
element in product promotion. However, most firms also reported using a variety
of non-local inputs and raw materials, particularly herbs, spices and ingredients
not available in the locality.
3.4 Power buyers
In general, firms expressed the view that "power buyers" were a problem for the
future, and reported few such problems at present. There had been isolated cases
of buyers requesting payment of slotting fees (payments to ensure access to supermarket shelves), and pressure to produce retailers’ own-label brands, but these
were not the norm. One firm reported that a buyer had requested a contribution
toward in-store promotions, but that the request was withdrawn when the manager
objected.
One firm reported that "power buyers’" contracts were extremely exacting and
provided facility for high costs to the supplier of any breach of supply conditions. However, that firm reported that such contract clauses were never actually
utilised: This was interpreted as a safeguard for the buyer rather than a threat. A
different firm reported being disadvantaged by contracting arrangements with
power buyers due to recent increases in raw materials costs, but that firm noted
that this was not a consequence of market power, but rather of the use of contracts.
There was general favourable comment about the relations experienced with
power buyers. They provided specialist advice on product and packaging design,
labelling, logistics, information provision, regulatory compliance and the operation of HACCP systems. The persons employed as buyers were recognised as
pleasant and honest to deal with.
Rural development policy and food industry development
193
Most firms reported that their scale of operation and (in some cases) newness in
the business detracted from their credibility as reliable suppliers. Some firms
(but not all) reported that a minimum supply was required for serving large
buyers. However, this issue was reported to be a disadvantage in dealing with all
buyers, not only large chains and those with market power. Prices paid by power
buyers were reported to be about 20% below that offered by wholesalers, but the
size of orders was adequate compensation, in the view of the firms.
One firm reported a strategy of selling no more than 20% of total volume to any
one buyer. The manager reported that this had cost him one customer due to the
volume restriction this imposed. As stated above, several firms operate retail
establishments providing high mark-up sales outlets, although these are highly
seasonal in operation. One firm stated that it refused to sell to power buyers, preferring to target high value, high priced small customers. That firm acknowledged that this would be difficult as (i) its own volumes grew and (ii) industry
consolidation reduced the number of small buyers in the market. One firm expressed the desire to serve institutional buyers (hospitals, the armed forces,
prisons) as a means of avoiding power buyers.
Several firms reported a developing trend toward use of a "quasi-private label".
In this model, retail firms’ names appear on the label, but so does the name of
the manufacturing firm, with the locality’s name displayed very prominently.1
Firms interpreted this as high demand for the locality’s products. On the topic of
retailers’ own-label brands, two firms welcomed offers from retailers, as commitment to a long term commercial relationship offering savings in marketing
costs.
For almost all the firms, the favoured stance on power buyers was the establishment of a network of firms in the locality.
3.5 Networks of local food industry firms
A previous network of food industry firms in the locality had operated under
open membership, including firms selling non-local products. That network had
been criticised for lacking focus on members’ needs, and for having an ineffective decision-making structure. Moreover, firms expressed the view that the
former network had not established and maintained a commitment to quality that
is essential in the modern food industry.
One successful initiative of the previous network was the employment (as a consultant) of a "food ambassador" who conducted promotions throughout Denmark.
This activity was supported by the LEADER+ programme, and notably it ceased
when the funding ran out. The food ambassador was later employed directly by
1
This model is most apparent on some wine labels in supermarkets.
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Derek Baker, Jens Abildtrup, Anders Hedetoft
a few of the largest firms, although his efforts generated benefits for all firms in
the locality.
Firms’ ideas on the purpose of the network were not entirely formed. The general
idea is to establish a joint effort in complementary promotion and marketing,
information provision and certain mutual support activities. This latter function
of the network would essentially be exchange of information and advice on
commercial and legal matters threatening one firm or another. Proposed complementary marketing actions included development of a catalogue and website,
joint promotions to tourists, use of a logo based on a consistent "story" about the
locality, and enforcement procedures for quality of products and reliability and
consistency of supply.
Firms were not able to specify the legal status that the proposed network might
adopt. The proposed network was described as a totally private organisation
with no links to government. These choices affect the ability of the network to
sign and comply with contracts, employ staff, administer quality certification
and trademarks, etc. It also affects the capacity of the network to absorb funds
available under various regional and rural development funding programmes.
One firm expressed its intention not to join the proposed network because its
products were "quite different to those of the other firms". This is a noteworthy
comment because of the network’s purpose of product complementarity. The
issue of whether member firms should be similar or dissimilar has, thus, not
been adequately addressed so far.
At this stage of planning, firms were generally unable to classify impacts of the
proposed network according to:
–
–
–
Public goods – Benefits that accrued to all local firms regardless of whether
they were network members;
"Club" goods – Benefits that are able to be confined to members of the
network only; and
Private goods – Benefits that are able to be confined to individual firms.
This classification has implications for both the form of funding of network
activities that might be adopted, and for any application for regional and rural
development assistance.
The manner in which the network might approach tasks affecting one subset of
members, as opposed to all members, has also yet to be decided. While a feepaying membership was favoured by prospective members, there was also a
stated desire to ensure that firms paid for the services provided. A key item not
discussed was whether the network would be a loss-making entity, and how losses
might be funded. Overall, transparency of arrangements was prized amongst the
firms, but arrangements for providing it had not yet been developed.
Rural development policy and food industry development
195
The twin challenges of initiating a network were discussed with firms:
–
Establishment – Getting firms to join; and
–
Sustainability – Getting forms to stay in.
The choice of activities to achieve these two ends has particular resonance for
the utilisation of regional and rural development funding programmes. In particular, recurrent expenditures are largely ineligible for subsidisation. Sustainability is further implicated by the degree to which the network’s benefits require
monopoly (in sales or representation): If the departure from the network of a few
firms reduces its benefits to the remaining firms then instability is (i) likely and
(ii) likely to be exploited by power buyers. Firms showed a good understanding of
these issues but had not yet reached a stage in design of the network that enabled
responses to these questions.
3.6 Discussion of assistance mechanisms
Most firms reported having used regional and rural development assistance the
past. The assistance commonly entailed expansion of processing facilities
(construction, equipment purchase) under objective 2, establishment of retail sales
outlets under various programmes, marketing studies under LEADER+, and
packaging under article 33. LEADER+ had also been used by a group of Bornholm firms to fund a "food ambassador". The firms expressed general satisfaction with the assistance, its administration and its impact. However, two concerns were expressed concerning:
–
–
The lack of information about forms of assistance and eligibility of certain
expense items; and
The necessity to lay out all plans for expenditures in advance, which reduced
flexibility in the use of funds later, as new information came to light or new
needs appeared.
Firms first requested information about what assistance would be available for
the introduction of new products. They emphasised that ideas and (for the most
part) technical issues were not problematic, but pre- and post introduction analysis and monitoring of new products presented a challenge. All firms felt the need
for information about products, markets and consumer trends.
Several firms proposed that assistance might be mobilised to establish a site for
trials of products (agricultural, processed and technical) and dissemination of
information to firms regarding their potential in local products. This might also
extend to testing and certification, in association with a local programme of
quality management.
Firms generally expressed a need for assistance with exports, particularly technical and colloquial knowledge and contacts in export markets. This would both
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Derek Baker, Jens Abildtrup, Anders Hedetoft
generate sales and information exchange with buyers about the potential for new
products.
4
DISCUSSION, CONCLUSIONS AND POLICY RECOMMENDATIONS
Firms in isolated locations claim to lack information about market trends and
new technologies. In general they do not claim to suffer due to their isolation
from consumers or trading networks, and do not claim that a shortage of skilled
staff is a severe problem. The cost of transport and logistics was seen as a
moderate to severe problem by most firms.
Firms claim that the burden of business- and regulation-related paperwork is
severe. Satisfying standards and procedures was not a major problem but firms
diverged in their assessment of "large powerful buyers": Some treated this as a
problem but others as an opportunity. Workshop discussion revealed that the
constraint on small firms’ ability to commit to large volumes was a major difficulty in dealing with large buyers. It also revealed some positive experiences
where co-operation with powerful buyers had helped with labelling and logistics.
New product introduction, and innovation more generally, was not constrained
by firms’ ideas and flexibility. Rather, firms claim to lack the analytical capacity
to determine how best to fit new products (i) into the existing product line and
(ii) into contracting and other arrangements with suppliers and buyers. Ideas for
firms’ product differentiation centred on "local" products. However, this concept
suffers from a lack of clear definitions of "local" (agro-food firms source many
other raw materials), particularly referring to ingredients or certain advanced
large-scale processing operations. Firms clearly want to employ the "local" identity as a central theme in a network of local food industry firms. This network
has some clear objectives and proposed functions, but much thinking remains to
be done before the concept is put into practice in a sustainable way.
Firms requested more information on available support under regional and rural
development initiatives. Although firms stated their general satisfaction with
assistance received, they criticised the burden imposed by its bureaucratic components: Paperwork; and inflexibility following implementation.
In a telephone assessment, firms claimed that government support was inappropriately targeted, was complex in administration and subject to delays. They also
claimed that too little information was available about the programmes. This
assessment was in some contrast to discussion at the workshop, where most
firms expressed satisfaction with the assistance they had received. Also in the
telephone interview, firms’ evaluation of assistance received was positive with
regard to some specific items, most notably "meeting the needs of firms in this
locality". However, firms claimed that the assistance they had received had not
Rural development policy and food industry development
197
helped achieve some business-related targets (e.g. adding value to products,
establishing linkages with suppliers and buyers). Firms also claimed that assistance received had not helped at all in reaching some social development goals
specified by the authors (e.g. retaining value added in the local community,
creating local employment, overcoming isolation and problems unique to this
locality).
Leaving aside the assistance received, firms’ assessment of what programmes
should target was mixed. Top priority was assigned to "meeting the needs of
firms", solving transport and logistic problems", "overcoming problems associated with isolation", and more generally supporting the local agro-food industry.
Firms’ view was that social targets (raising local employment, maintaining the
local population) were more important than some business and economic targets
(creation of value added and its retention within the local community).
There was a weak correlation between firms’ assessments of assistance received
and the extent to which each objective should feature in regional and rural development assistance. For example, firms claim that assistance received did little to
offset high transport costs and other issues associated with isolation, but should
target this as a very high priority. Although assistance was useful to firms in business re-organisation, this was assigned a very low priority as a policy objective.
The firms accessed in this research are actively working on the definition and
development of a network of small food industry firms based in a specific locality. The form and function of the network is based around the differentiation of
products due to the locality’s uniqueness, and the potential for complementary
amongst the firms. The nature of benefits to be generated (essentially, public or
private) have not been clearly identified by the firms. The means of cost recovery (essentially for generation of private or "club" goods) has not been addressed
by the firms. Firms are encouraged by previous experience with, and assistance
to, a local network, and have some ideas for some initial activities (e.g. release
of a catalogue of local food products).
A review of information provision mechanisms for small agro-food industries in
remote areas is required. Regardless of whether firms’ claims (a shortage of
information) are correct, the impression of exclusion and isolation is real and
needs addressing. The form of available information appears to lack sufficient
guidance on the types of expense, activity, or investment that may be applied for
by particular types of firm.
Firms’ complaints about bureaucracy and delay should be addressed in the review
of information delivery. At least part of the problem is that firms’ expectations
exclude the delays and procedures that are probably inevitable in this context.
Firms specifically requested information about the available opportunities for
support of innovation of various kinds, and particularly with new product
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Derek Baker, Jens Abildtrup, Anders Hedetoft
introductions. Several firms identified the need for specific skills and analytical
techniques in the planning and implementation of new product introductions,
which appear to be amenable to funding of consultancy services and marketing
studies. It is recommended that this element of support programmes (cutting
across several programmes and sources) be addressed in a targeted information
campaign.
Owing to the nature of new product introduction within the firm and between
trading partners, flexibility in implementation of supported projects has been
requested. It is recommended that nominated expenditure items in project plans
be subject to reviews during the life of the project, with scope for significant
changes in orientation and re-allocation of such spending as innovative activities
proceed, succeed and fail.
Practical assistance with exporting for small food industry firms has been requested. In particular, some firms objected to the "strategic" approach taken by government assistance agencies: They would have preferred direct answers to some
practical (perhaps "tactical") questions. It is recommended that regional and rural
development assistance programmes interface with other government agencies
to help participating firms access the advice they need in this regard.
Firms requested surprisingly little support in the matter of power buyers,
although they anticipate difficulties in the future. It is recommended that development programmes include awareness of such issues in their future design. In
particular, this might include support of information bureaux or mechanisms that
highlight consolidation trends and advise on the best approach for small firms in
specified commodity sectors. In addition, consultancies provided under the various
assistance programmes should be required to provide information related to
buyer power, in addition to market assessment of a more aggregate nature. This
would improve firms’ understanding of market access requirements in spheres
beyond the technical.
It is recommended that a review take place of the definition and concept of
"network" in regional and rural development assistance. This should define key
desirable tasks of networks of small agro-food firms, and provide an assessment
of the degree to which they might be promoted and secured by existing and/or
new policy instruments. This will necessarily address the eligibility of certain
types of expenditure for support, particularly recurrent costs. It will also address
whether assistance can be provided to a network as an independent agent, rather
than to the firms that make up the network.
Networks are capable of delivering several forms of benefit in a number of settings. The nature of these might dictate the likelihood of their being able to recover costs of various types from members and/or users. It is recommended that
a review be made of the capacity of regional and rural development programme
elements to assist in funding public goods components and functions of networks.
Rural development policy and food industry development
199
This will necessarily involve an examination of whether local government
should play a role in networks receiving assistance for delivery of public goods.
It is suggested that this would be unpopular with many firms.
Firms are struggling to define the conditions under which they would form networks. It is recommended that training be offered in this regard: It could draw
on, for example, Denmark’s tradition of co-operation at farm level and its successful operation of food processing and marketing. It could also draw on knowledge and experience bases about the use of the internet and communications
technology in networks.
A longer term problem facing firms is the sustainability of networks. First, they
may disband. Second, they may combine, fragment, or change form in some
other way. It is recommended that guidelines be established regarding assistance
to networks that undergo change: Two networks that merge should not, ideally,
be entitled to two sets of assistance per se. However, it would be nonsensical to
simply cut of support to one or the other network where separate activities were
being pursued. More generally, support of networks may require subsidisation of
their running costs. It is recommended that this possibility be reviewed and the
outcome of the review publicised.
REFERENCES
INDENRIGS- OG SUNDHEDSMINISTERIET OG FØDEVAREMINISTERIET (2004): The report
on rural areas – The government’s reporting to the Parliament [Landdistriktsredegørelsen 2004 – Regeringens redegørelse til Folketinget], Ministry of Interior
and Health, Copenhagen.
NATIONAL AGENCY FOR ENTERPRISE AND CONSTRUCTION (2000): Objective 2 programme for Denmark 2000-2006 [Danmarks Mål 2 program 2000-2006], Copenhagen, October 23, 2000.
REGERINGEN (2006): Report on regional growth policy [Regional politisk vækstredegørelse], The Government’s reporting to the Parliament Maj 24, 2004, The
Ministry of Economic and Business Affairs.
Sustainable rural development: What is the role of the agri-food sector?
MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central & Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 200-216.
DAIRY FOOD CHAIN RESTRUCTURING IN POLAND –
CAUSES AND IMPACTS*
DOMINIKA MILCZAREK, AGATA MALAK-RAWLIKOWSKA, JAN FAŁKOWSKI**
ABSTRACT
This paper discusses the nature of the restructuring of the Polish dairy sector.
Using both national statistics and qualitative data collected at the regional level,
we present the most important changes that have taken place in particular stages
of the supply chain. The most significant and advanced changes have been observed at the farm and industry levels. These have substantially affected not only
the production sphere, but also marketing practices and the whole institutional
environment within which farmers and processors function. To a large extent, an
adjustment process at the farm level was stimulated by the processors, who have
been encouraged to pursue restructuring by the ongoing process of Poland’s integration in the EU. Strict quality standards, a prerequisite for operating on the
export and domestic markets, have been of special importance. The milk quota
system is likely to become the most decisive factor determining the pace and
scope of future restructuring, as the limits set by the European Commission become more perceptible.
Keywords: Dairy sector, restructuring, market channel choices, Poland.
1
INTRODUCTION
Profound restructuring has taken place in the Polish dairy sector during transformation, with the most significant changes occurring in milk production and
processing. As an illustration of the restructuring at the farm level, one may look
at the sharp decrease in total output and total dairy cows. Further examples are
*
**
This research was conducted within the Regoverning Markets project. For further information, see the website: www.regoverningmarkets.org. We would like to thank our colleagues
from the project for fruitful discussions. We are grateful to JERZY WILKIN, CSABA CSAKI,
LIESBETH DRIES, and JIKUN HUANG for valuable comments on our work.
DOMINIKA MILCZAREK and JAN FAŁKOWSKI are researchers at Warsaw University, Department of Economic Sciences, AGATA MALAK-RAWLIKOWSKA is a researcher at Warsaw
Agricultural University, Faculty of Agricultural Economics.
Contact addresses: [email protected]; [email protected];
[email protected]
Dairy food chain restructuring in Poland
201
an increase in average milk yield, as well as fluctuations in the share of milk being
marketed (Table 1). However, the most striking example is the scale of outflow
of farmers from the dairy sector. Since the beginning of 1990s, this has
amounted to more than 1 million farms (Table 2).
Table 1:
Characteristics of milk production in Poland from 1989-2005
1989
Number of dairy
cows
[1,000 heads]
Index %
Milk yields
[litres/cow/year]
Index %
Milk production
[million litres]
Index %
Milk Deliveries
[million litres]
Share of deliveries in total milk
production %
1990
1994
1998
2000
2001
2002
2003
2004
2005
4994
4919
3863
3471
3098
3005
2873
2897
2796
2795
100
98.5
77.4
69.5
62.0
60.2
57.5
58.0
56.0
56.0
3260
3151
3121
3491
3668
3828
3902
3969
4083
4200
100
96.7
95.7
107.1
112.5
117.4
119.7
121.7
125.2
128.8
15926 15371 11866 12178 11494 11538 11527 11546 11478 11600
100
96.5
74.5
76.5
72.2
72.4
72.4
72.5
72.1
72.8
11385
9829
6269
7070
6583
7025
7219
7316
7997
8831
71.5
63.9
52.8
58.1
57.3
60.9
63.2
63.4
69.7
76.1
Source: IERiGŻ (Var. vol), GUS (Var. vol).
Table 2:
Number of dairy producers in Poland 1990-2005
1990
1996
2002
2003
2004
2005
A) Number of producers
[x1000]
1831
1309
876
810
735
712
Index %
100
71.5
47.8
44.2
40.1
38.8
B) Number of producers delivering
to processing (x1000)
835
560
376
356
312
294
45,60
42.78
42.92
43.95
42.45
41.29
n.a.
n.a.
n.a.
n.a.
76
50
–
–
–
–
52.8
48.3
as % of total producers
C) Number of producers delivering
directly to the market * (x 1000)
Share of producers delivering to the
market (B+C) in total number of
producers (A), %
Source: IERiGŻ (Var. vol), GUS (Var. vol).
202
Dominika Milczarek, Agata Malak-Rawlikowska, Jan Fałkowski
On the other hand, changes at the processing level can be illustrated by the ongoing concentration of the dairy industry or the level of undertaken modernisation1. It is important to notice that during transformation, two periods could be
distinguished, namely pre- and post-1995. During the former, dramatic deterioration was experienced in the sector’s overall situation. The latter, on the other
hand, has been characterised by a gradual stabilisation of output, increasing
prices and substantial improvements in the sector’s efficiency, as well as product
quality (SEREMAK-BULGE, 2005).
Significant changes have also taken place with respect to the retail stage of the
dairy supply chain. Traditional dairy shops were replaced, to a large extent, by
super- and hypermarket (SM/HM) chains, as well as discount shops. Nowadays,
modern retail chains account for over 40% of total dairy product sales. In fact,
independent shops retained their dominant position only with traditional products
(like traditional cottage cheese). Among reasons that explain this phenomenon, one
should mention the introduction of private labels and lower prices in modern
retail shops2 (DETAL DZISIAJ, 2005). Also important is the fact that changes at
the retail stage have substantially affected the situation in the wholesale segment. This is mainly because SM/HM chains started to purchase products directly
from processors, both domestic and foreign, thus neglecting wholesale companies.
Nevertheless, it must be stressed that wholesalers still play a very important role
in the Polish food sector. This is because they are often the only partners for independent shops in small towns and villages.
Although the aforementioned changes have affected the whole country, significant differences between regions with respect to the rate and scope of restructuring
have been observed. For example, 5 (out of 16) regions with large and increasing production accounted, in 2005, for 67% of the milk delivered to dairies.
These regions are: Warmińsko-Mazurskie, Podlaskie, Wielkopolskie, Mazowieckie
and Łódzkie. This development has been especially observed in the first three
regions, and can be at least partly attributed to favourable natural conditions and
the long tradition of local milk producers.
1
2
The number of processors decreased in the last decade by about 20%, and in 2004 fell to
265 dairies (SEREMAK-BULGE, 2006). Despite this change, the ownership structure of the
dairy industry has continued to be dominated by domestic cooperatives that account for
roughly 70% of market sales. Regarding the level of undertaken investments, from 19952005, they are estimated to be 6.2 billion PLN.
The number of private labels is rapidly growing, especially in outlets run by foreign operators. In 2004, ca. 59% of dairy products were sold as private label products in discount
shops, ca. 7% in HM, and ca. 3% in SM. Private label dairy products are usually 20-40%
cheaper than the equivalent name-brand products (for UHT milk even 70%) (DETAL
DZISIAJ, 2005).
Dairy food chain restructuring in Poland
203
The following sections aim to examine the issues presented above in more detail.
Section 2 presents changes that have taken place in the downstream segments of
the supply chain. Section 3 presents the restructuring process at the upstream
portion of the supply chain, whereas Section 4 concludes and provides some
policy recommendations. The presented material combines national statistics
and qualitative data collected at the regional level3. The selected study sites were
the Podlaskie and Warminsko-Mazurskie regions, both of which are located in
the north-eastern part of Poland. This choice was based on the importance and
extent of restructuring in the dairy sector in both regions. Though one has to be
cautious when generalising about obtained results, it is reasonable to suspect that
regions that have fallen behind in terms of restructuring would follow the path
chosen by those two regions. Therefore, understanding changes that took place
there may provide valuable insights and provide useful policy recommendations.
2
RESTRUCTURING OF DOWNSTREAM SEGMENTS IN THE SUPPLY
CHAIN
The analysis presented in this section is based mainly on interviews with experts
and representatives of firms operating in the processing, wholesale and retail
segments.
2.1 Processing segment
Improvement in the quality and assortment of the final product, and the improvement of the quality of raw milk itself, were seen as the two main changes
in the processing sector over the past 10 years. The concentration process was
also acknowledged and was seen as particularly important during the past 5-6
years. Large dairy companies were often the initiators of this consolidation process. Furthermore, important changes occurred in the profitability of the sector at
the time of and in the period following the accession process. After being
somewhat modest in 1990s, profitability increased in the year of EU accession,
which was a result of increased export demand and a very good Euro/Zloty exchange rate. However, in the following years the level of profitability progressively decreased; this was coupled with growing raw milk prices and an increase
in production costs.
Increased competition on the dairy market forces dairy processors towards
product specialisation. In large companies, this takes the form of dividing production among particular dairy plants, which allows them to provide consumers with
a wide assortment of products according to current demand. Smaller processors,
3
In total, 36 in-depth interviews were conducted with experts, purchasing and sales managers
from dairies, as well as wholesalers and retailers. In addition, 5 focus groups with farmers
were organised. Research was conducted in May and August 2006.
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Dominika Milczarek, Agata Malak-Rawlikowska, Jan Fałkowski
on the other hand, having a less developed marketing system and worse access
to funds, have limited possibilities to introduce innovations, and thus cannot adjust to consumer (or retail) requirements so quickly. Therefore, not being able
compete with larger companies in terms of size of deliveries nor variety of assortment, smaller companies try to find their niche and produce unique products
or products for further processing, such as SMP. Moreover, some small processors specialise in exports.
In the opinion of both experts and segment representatives, the most significant
factors influencing changes in the processing industry were: The transition period, which influenced the situation mainly in the 1990s; the pre-accession process, which started in 19984, and finally, integration with the EU. All these aspects required significant adjustments concerning institutions and policies. On
the one hand, necessary adjustments in the law were introduced. On the other
hand, support programmes for processors and producers were launched to assist
them in meeting consumer quality requirements. It was also mentioned that
transformation in the retail sector (together with its internationalisation and consolidation) was an important factor. Retail expansion opened new outlets for
dairy products, but at the same time imposed new requirement on dairies.
Difficulties and development constraints at the processing level are very important, not only for dairies but also for producers delivering to them; for producers,
the dairy plant is the most important segment of the market chain. It was observed that dairy processors not only play the role of milk purchaser, but also
assist in farm development, for instance, by organising traineeships or providing
short-term loans (see section 3). According to respondents, the main problems
processors are facing when competing on the market can be divided into two
groups: 1) barriers arising from the legal regulations, and 2) barriers concerning
the low economic efficiency of companies.
The milk quota system is the most frequently-mentioned legal barrier, both for
the milk-processing segment and for producers. The main problems concerning
milk quotas are: The limit that binds production5, and regional quota trade restrictions. The quota is allowed to be traded only between farmers who have
their holding in the same administrative region. This results in high quota prices
and inhibits the restructuring of milk production.
4
5
Despite the fact that the Polish pre-accession agreement was signed in 1994, the most significant arrangements concerning milk market regulation were prepared at the end of
1990s. Therefore, restructuring the dairy sector became more important.
Deliveries to processing during the first milk quota year (2004/5) were 13% lower then
quota assigned. However, due to very dynamic development of marketed milk production
in Poland milk quota in 2005/2006 was exceeded.
Dairy food chain restructuring in Poland
205
The other group of barriers relates to factors influencing the low economic efficiency of dairy processing. The main constraints here are:
–
–
–
–
Weak position in the chain (except for the largest companies), being a consequence of – on the one hand – producers’ pressure (especially those with
large deliveries) to obtain good milk prices, and on the other hand – retail
pressure to receive cheap products;
Low level of management skills and mentality of dairy employees (especially
in dairy co-operatives);
Low labour efficiency, which negatively affects dairies’ comparative advantage;
Level of consumption and low incomes of people, who can’t afford to buy
more expensive products. Smaller dairy processors especially have to compete on the local markets by lowering prices, which is extremely difficult
with a low processing margin.
Some experts also said that a significant barrier for processing development is
the co-operative ownership form. Unclear, disaggregated ownership rights result
in more difficult management and more complicated decision-making process.
Some experts mentioned that the problem lays in the co-operative law, which
hampers flexible management and restructuring of dairy co-operatives.
Large-scale processors usually look for possibilities to deliver their products to
SM/HM, where they can easily convey a large amount of produce. For those
processors, large-scale retailers are also more stable partners than wholesalers,
but they dictate stricter trade conditions and negotiate lower prices. The importance of a large retail channel has progressively risen since the end of 1990s,
when the dominant form was wholesale, local cooperative chains and independent
shops. But according to our experts, only about 5% of milk produce is still
channelled through the SM and HM, although for fresh milk products (yoghurts),
special cheeses and UHT milk, it reaches 20%. According to our research, in
both regions large dairies are selling from 30% to 60% of their products to large
retail chains, about 35-50% is channelled through the wholesale segment, and
about 5% is delivered to local chains or independent shops. For small dairies as
well as independent shops, the wholesale segment is dominant regarding share
of sales. Smaller dairies usually have an insufficient scale of production to deliver to SM/HM.
2.2 Wholesale segment
According to the respondents, the most important changes that took place in the
wholesale segment were: Concentration and specialisation processes, changes in
profitability, improvement in an assortment of dairy products, and technological
innovations. These changes started with the transition process at the beginning
206
Dominika Milczarek, Agata Malak-Rawlikowska, Jan Fałkowski
of the 1990s (when new private companies entered the market) and were further
stimulated by the entrance of foreign retail chains in the mid-1990s. The regional
experts also stressed the influence of dairy-processing concentration, which
allowed wholesalers to extend economies of scale.
Strong competition between wholesale companies caused a deterioration of profitability. In addition, profitability of the wholesale sector decreased due to competition with foreign SM/HM chains6.
During the last 10 years, many small wholesale companies, unable to face stiff
competition, went bankrupt. In addition, the number of wholesale companies
that sold dairy products decreased due to the fact that the most common strategy
adopted in such a highly competitive environment was to consolidate. One respondent said that the number of wholesale companies decreased from approximately 40 to 5 in the Warsaw agglomeration. Thanks to concentration, wholesale companies extended their operation.
Another strategy adopted in response to strong competition was specialisation in
dairy products. Wholesale companies benefited from a growing demand for
dairy products, as well as from increased competition between dairy processors.
Both these processes resulted in an improvement of quality and assortment of
dairy products.
It was also observed that large wholesalers introduced private labels as another
response to increased competition. Both interviewed wholesalers in the Podlaskie
region have private labels and control the quality of these products at the processing level. Further information tends to indicate that strong competition with
SM/HM chains has also accelerated the vertical integration of Polish-owned
companies.
Concentration and specialisation allowed wholesale companies to reduce costs.
However, another important factor allowing for cost reduction, according to our
respondents, was technological development. Wholesale companies introduced,
for example, the possibility of ordering either through Internet or by palmtops.
The abovementioned changes have occurred at both the national and regional
levels. However, several differences between the two regions can be observed.
In the Podlaskie region, the wholesale sector still plays an important role in
dairy product distribution. This is partially caused by the local government’s
strategy, which is very reluctant to allow SM/HM chains to enter the market. In
6
SM/HM chains have recently become an important direct purchaser of products from dairy
companies. All interviewed processing companies were directly selling their products to
SM/HM chains (the share ranged from 2% to 60% of total sales and has been increasing in
recent years).
Dairy food chain restructuring in Poland
207
Warmińsko-Mazurskie, where there were no such regulations, the role of wholesalers in dairy product distribution is of much lower importance.
In general, interviewed experts were of the opinion that the wholesale sector’s
role is diminishing in the dairy industry’s marketing chain. In both regions, the
share of wholesale turnover with large retail chains and with processing companies has decreased significantly. Both foreign and national large retail chains
have begun opening their own distribution centres7, and large processing companies tend to sell directly to retailers. However, the wholesale segment is still
an important intermediary between processors and small retailers (local chains
and independent shops) in the surveyed regions.
When describing the relationship between wholesale and other sectors, it is important to mention that both dairy processors and retailers prefer cooperation
with large wholesale companies. According to our respondents, the main reason
for this is the possibility of reducing transaction costs, including transport and
negotiations costs. Another important reason are marketing costs. Thus, dairy
products from large processors constitute a majority of the turnover of large
wholesale companies.
However, dealing with small processing companies does have certain advantages. They offer wholesale companies access to specific and original dairy
products, or to regional products with trademarks that are recognised by regional
consumers. Dairy goods produced locally are delivered mostly to the regional
retail segment, but also to several SM/HM chains located in the region. Thus,
consumption patterns could provide a chance for small dairy producers.
2.3 Retail segment
According to interviewed respondents, the most important changes that took
place in the retail segment are: The growth and geographical expansion of large
retail chains, the concentration process, increased competition, increased demand
for dairy products, and improvement in an assortment of dairy products. Representatives of retailers in both regions also stressed organisational changes. As in the
case of the wholesale sector’s restructuring, these changes were mostly caused
by the transition process at the beginning of the 1990s.
The growth and geographical expansion of numerous SM/HM chains resulted in
the weaker position of local chains and independent shops, as well as very strong
competition between large retailers. That may explain why the largest competitors
for the surveyed national retail chains in both regions are SM/HM chains. However, there are some differences between the regions. The local government in
7
In one surveyed foreign SM/HM chain that does not have its own distribution centre,
deliveries from large wholesalers amounted to ca. 10%; from large processing companies
ca. 80%; and imports ca. 10% of total deliveries in 2005.
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Dominika Milczarek, Agata Malak-Rawlikowska, Jan Fałkowski
the Podlaskie region has hindered the development of foreign SM/HM chains
because of possible damage to the environment. This is why foreign discount
shop chains are perceived as the main competitors for the surveyed retailers in
the Podlaskie region. On the other hand, SM/HM chains are the most important
competitors for the surveyed retailers in the Warmińsko-Mazurskie region.
The above differences between regions show the importance of government
policies (introduced both at the local and national level) in determining the retail
segment’s structure. It is worth mentioning that these polices also have an indirect
impact on the other food chain segments because of the retail sector’s bargaining
power. Despite these clear linkages, none of our respondents indicated government
policy and state intervention as one of the most important drivers of restructuring
in the dairy sector.
Due to strong competition, the concentration process of both SM/HM chains and
national local chains has recently begun. For example, national cooperative
chains8 (selling under the same brand in all of Poland) whose representatives
were surveyed in both regions, have started to consolidate their distribution systems. Another example of the concentration process is the local SM chain in the
Warmińsko-Mazurskie region. Recently, the company joined two other local
chains and currently has 16 outlets (in 1997 there was only one). They also plan
geographical expansion. Another strategy is to specialise in fresh products.
All interviewed retail representatives stressed quality improvement and increased demand for dairy products. According to the director of a local SM
chain in the Warmińsko-Mazurskie region, even though prices drive consumption decisions, the pattern of dairy product consumption has been changing.
"People start to be aware of what they eat," he said. "In the last few years,
demand for traditional dairy products9 increased 20-30% per year."
2.4 Power relationship in downstream segments
Dairy processing companies have historically had a dominant position in the
dairy industry. But their position is diminishing progressively. Notwithstanding
this fact, cooperation between processors, although generally assessed positively,
could still be strengthened10. Despite continued rapid consolidation in this sector,
it is increasingly the retail sector that dictates the rules, shaping the structure of
the processing industry and thereby influencing milk producers’ production
8
9
10
Which operated before transition process and which was privatised and split at the beginning
of 1990s.
Dairy products without any artificial flavours common in Poland like: Cottage cheese, sour
milk, etc.
The respondents stressed especially need for common effort to influence government policy
more efficiently.
Dairy food chain restructuring in Poland
209
decisions. Large retailers often set high requirements and dictate what, when,
how and how much is to be produced. Nevertheless, even these food retailers are
under strict and constant pressure since, according to our interviewees, ultimate
power is increasingly in the hands of consumers, who are ever more demanding
with regard to factors such as nutrient definitions, organic status, traceability of
products, etc. (OECD, 2005).
All interviewed persons stated that a new trend in consumption patterns is visible.
Consumers are paying more attention to dairy product quality. One respondent
said, "Before, consumers wanted to buy yellow cheese. Now they want to buy,
lets say, Gouda. And more often they want to buy Gouda from a given dairy
processor." Consumers also look for fresh products and are beginning to avoid
dairy products with long expiration dates. In addition, regional products become
more and more popular (even in some SM/HM chains). In the opinion of the interviewees, this could be a chance for small dairy processors.
3
CHANGES IN PRODUCTION AND MARKETING AT FARM LEVEL11
This part of the paper presents the restructuring process that has taken place over
the last decade in the highest upstream segment of the dairy supply chain, i.e., at
the farm level. It is important to note that changes in this stage of the chain took
place not only in the production sphere (level of output and production practices) but also in the way milk is being marketed, as well as the whole institutional environment in which farms operate.
3.1 Main changes: Production
To begin with, an increase in average herd, cow efficiency and consequently in
farm production has been observed. These changes were accompanied by an
outstanding improvement in milk quality. The process of increasing specialisation in milk production has also been remarkable. Interestingly, this tendency
seems to be common for both smaller and larger farms in at least two surveyed
regions. The former, however, due to relatively small-scale production, need to
look for additional non-agricultural income sources. The latter holdings, on the
other hand, rely on farming income alone.
Regarding production practices used by farmers, the recent decade has brought
about a radical shift towards modern technology usage (cooling tanks, milking
machines, etc.) and changes in feeding practices (shift to silage feeding). In
this context an important division within farms has emerged. On the one hand,
there are those who invested in new equipment, and on the other hand, those
who stayed with obsolete machinery and more traditional methods of farming.
11
This section is based on a chapter of JAN FAŁKOWSKI’s PhD dissertation which is being
prepared at the Warsaw University.
210
Dominika Milczarek, Agata Malak-Rawlikowska, Jan Fałkowski
Conducted interviews seem to indicate that only the former group will be able to
survive in milk production in the long run. This, in turn, implies that the latter
will ultimately have to quit and look for other sources of income.
This observation leads to the statement that notwithstanding the tremendous outflow of farmers from the dairy sector, which has taken place since the very beginning of transformation, a further decrease in the number of dairy farms
should be expected in the future12. On the one hand, it should provide more
scope for coping with the problem of excessive production fragmentation. On
the other hand though, it calls for efficient measures to be implemented in order
to provide those who quit with alternative job opportunities. As was indicated in
the conducted interviews, most farmers that decided to quit milk production either
shifted to other agricultural activities or took advantage of earlier pensions provided within the ‘structural rents’ programme13. The most common agricultural
activity undertaken by those who left the milk sector is beef production. Those
who left agriculture for good rented out their land or, less frequently, developed
agro-tourism and now farm only for subsistence purposes.
3.2 Main changes: Marketing channels
Simultaneous to the changes taking place in the production sphere, new trends
have been observable with respect to farmers’ milk usage and marketing
choices. First, a gradual increase in the share of milk being marketed has been
visible. From 1995-2005, this number increased from roughly 70% to 80%
(IERIGŻ, var. vol.). Three marketing channels have been used for milk sales, of
which direct milk collection from the farm has become the most important. On
the other hand, sales using collection points, as well as direct sales to consumers,
have been decreasing in significance. It must be stressed, however, that collection points, although regarded as at most a temporary solution, still constitute an
important alternative for milk marketing, especially for smaller farms. According
to estimates, the share of milk sold directly to consumers decreased from nearly
15% of total production in 1995 to roughly 4% in 2005 (IERiGŻ, var. vol.). The
share of milk collected from the farm showed the opposite tendency, increasing
from 5% in 1993 to 20% in 2001 (NOWAKOWSKI, 2002). It should be stressed,
however, that in recent years this trend has significantly sped up. As evidence,
one may take the fact that in surveyed regions (in 2006) milk collected directly
from the farm ranged from 76%-100% of the dairies’ supplies.
12
13
As shown in Table 1, in 1990 there were 1.8 million farms that had cows in Poland. In 2005
this number amounted to 711,000, whereas only 344,000 sold milk on the market. The latter figure may therefore be taken as an upper estimate of the number dairy farms one can
expect in Poland a few years from now.
According to surveyed farmers, the group of those who quit was dominated by smaller
producers with herds up to 10 cows.
Dairy food chain restructuring in Poland
211
3.3 Main changes: Institutional environment
Finally, it is worth noting that significant changes have taken place with respect
to the institutional environment within which farms have been operating. On the
one hand, these changes have consisted of introducing a milk quota system after
Poland’s accession to the EU. On the other hand, they have embraced all the
necessary adjustments that had taken place within the dairy industry long before
accession, starting in the mid-1990s. The aforementioned adjustments were
shaping the new institutional environment, which was being shaped through
various governmental policies, such as the quality premium programme, as well
as numerous measures being undertaken by processors themselves. The latter
have comprised a whole range of assistance programmes targeted at farmers in
order to encourage them to undergo thorough modernisation. In that sense, they
should not only be seen as mere support programmes, but also, or perhaps predominantly, as measures trying to correct for various market imperfections that
have prevented or discouraged farmers from investing. As such, they have taken
the form of preferential credits, the provision of collateral or inputs, as well as the
provision of consultancy and traineeship. Last but not least, they have comprised
premiums for high quality milk or large deliveries (DRIES and SWINNEN, 2004).
3.4 In search of causes
When looking for the causes of the abovementioned changes, one encounters
several obstacles. This is because those spheres under examination, i.e., production, marketing and institutional, seem to be highly interdependent. Therefore, it
seems plausible to expect that changes taking place in one of them are very
likely to stimulate adjustments in other spheres, creating the appropriate feedback. Consequently, changes in all of them take place, practically speaking, at
the same time. This in turn, makes it very difficult to state which of them could
be regarded as leading and which as following. Conducted interviews seem to
allow for posing the hypothesis that changes in the institutional environment
have led to changes in other spheres.
The spiritus movens behind changes in the institutional environment, not counting
the introduction of a milk quota system, was certainly the fierce competition that
the local dairy sector faced, both within and outside of Poland. Factors which
played a role here include, among others, recognition of more and more strict
quality standards (especially at the European level) and, to a lesser extent, foreign
companies investing in the Polish dairy industry.
Regarding the production sphere, several reasons could contribute to changes
that have taken place there. An increasing specialisation in milk production
might be seen as a result of substantial investments that needed to be undertaken
in order to meet quality standards. In effect, other production activities could
lack the necessary funding. Evidence from the conducted interviews provided
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Dominika Milczarek, Agata Malak-Rawlikowska, Jan Fałkowski
further explanations. In both examined regions, the dairy industry had been among
few processing industries that survived the process of transformation into a market
economy. Moreover, after shutting down rural collection points during the 1990s,
selling opportunities for agricultural products other than milk became significantly
confined14. In addition, increasing internal and external competition forced farmers
to look for the most efficient use of their endowments. Both regions under examination possess land of relatively poorer quality, which is most suitable for grassland and hence milk production.
An increase in the average herd size, and consequent increases in farm production could also be linked to milk quality issues. This is because investments in
quality improvement, if they were to become profitable, required a sufficient
scale of production. Moreover, it is reasonable to suspect that an increase in herd
size was at least partly related to anticipating the introduction of the quota system.
In order to reach the highest quota limits, farmers aimed to increase their production before the reference year. In addition, herd increases may also be linked
to a deterioration in profitability, which induced farmers to take advantage of
economies of scale. Last but not least, farmers were encouraged to increase their
herds by dairies that aimed to optimise their supplies. In order to achieve this,
dairies provided farmers with several measures, the two most common being
extra payments for large quantities delivered and low-interest heifer/cow loans15.
As presented in Table 3, the largest processors were the most successful in attracting large producers.
14
15
During communism, state-owned rural collection points, being the only opportunity for
farmers to sell their goods, played a very important role. Once the old system collapsed,
however, they lost significance and a majority of them went bankrupt. This resulted in the
necessity of establishing new ties with market institutions, a task with which many farmers
failed to cope. For milk, separate collection points existed. After the market economy was
introduced, farmers’ ties with the dairy industry were not broken up, since it was processors who were managing milk collection points. Consequently, compared to other farmers,
milk producers were in a relatively better situation.
It is important to note that support offered by dairies has not been confined to the second half
of the 1990s, but became a long-term policy (DRIES and SWINNEN, 2004) and is expected to
continue in upcoming years.
Dairy food chain restructuring in Poland
Table 3:
213
Share of small and large producers in total number of deliverers,
as well as share of milk delivered through traditional channel
with respect to dairy size, 2005
Large dairies
Mid-size dairies
Small dairies
Small producers
(%)
34-42
37-46
46-67
Large producers
(%)
11.5-14
5-11
2-6.6
Milk collected via
collection points
9-21
0-24
3.6-18
Source: Authors’ calculations based on 10 interviews with dairy representatives16.
Regarding the process of milk producer polarisation, it could surely be related to
households’ access to capital and farmers’ mentality. In addition, dividing farmers
into ‘modern’ and ‘backward’ seems to be related to age. Farmers’ reluctance to
undertake investments often stems from the fact that they are just waiting to become eligible for their pensions, and once they receive it, they intend to quit
their production. Furthermore, it seems that a lack of investments in the household might also be related to having no successors (FRENKEL, 2006). In addition,
recent findings indicate that farmers tend to prefer their children to work in urban
centres than on farms (HARDT, 2006). In this context, a lack of investments on
the farm could be seen not as a consequence of having no successors, but as a
conscious choice to withdraw from milk production.
With respect to the causes of changes in the marketing sphere, one may link
them to changes in the institutional environment, as well as in the production
sphere. One reason is surely related to the issue of milk quality. Selling to collection points became too risky because of the free-rider problem and a lack of
mutual trust between farmers. On the other hand, in many cases an increased
scale of production made deliveries to collection points, if not impossible, then
certainly inconvenient. The other thing which contributed to their decline was
the collection points’ own perception of being profit-making institutions intermediating between the farmers and processors. A dairy representative described
this phenomenon as follows: "Farmers leave collection points since they do not
want to have another middleman. They think that without this intermediary, they
could obtain higher prices and therefore perceive it as a ‘robber’."
4
CONCLUSIONS AND POLICY RECOMMENDATIONS
The paper aimed to describe the main causes and impacts of dairy restructuring
in Poland. Based on national statistics and a qualitative study conducted at the
regional level, an attempt was made to highlight the main characteristics of
16
The term ‘small producers’ refers to farmers delivering less than 25,000 litres per year,
whereas ‘large producers’ refers to farmers with annual deliveries exceeding 120,000 litres.
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Dominika Milczarek, Agata Malak-Rawlikowska, Jan Fałkowski
changes that have taken place along the supply chain. Integration with the EU –
including Common Agricultural Policy (CAP) implementation – has been the
main driving force behind dairy sector restructuring in Poland over the last decade.
Some of the main elements of this process were: Obligatory quality improvements;
pre-accession investment assistance; export opportunities; milk price increases;
the introduction of direct payments; and the introduction of a milk production
quota system.
It is expected that this process of policy-driven restructuring will continue in the
near future, as new regulations requiring additional investments from either the
processing or the milk producing sector, will become binding. Policy-driven restructuring will also be caused by reform to the organisation of the EU dairy
market, resulting from both future debate on the CAP, as well as WTO negotiations.
In the process of restructuring the dairy food chain, the relative size of actors
along the whole supply chain has played an important role. Large retail chains
and wholesalers seek large deliveries to lower their costs of transport and marketing. This in turn puts pressure on processors and ultimately on farmers. Size
also acts as a factor that strengthens bargaining power during negotiations. Since
size is also often positively correlated with access to funds (internal or external)
it substantially facilitates the modernisation process.
The questions then remain: Under which conditions can small farms survive;
how this can be facilitated (or stimulated); and should it be facilitated at all?
There is an obvious investment decision (related to size) necessary to gain access
to modern marketing channels, i.e., the purchase of a cooling tank. Apart from
this physical capital investment, the quota system puts an additional financial
constraint on small farmers wishing to expand, as the cost of buying one extra
unit of quota weighs relatively harder on smaller producers than on larger ones.
The agricultural market, including dairy production, is a subject of Common
Market Organisation, and thus is an important part of CAP. There is a limited
scope for domestic policy to influence this market. However, there are some
suggestions and implications for policy formation at the country and the European
level concerning the dairy sector. The following preliminary policy recommendations can be given:
–
The regional allocation of quotas puts an artificial limit to the ongoing farm
restructuring process. It is important to notice that this may also influence the
speed of restructuring at the dairy processing level. Therefore, reorganising
milk quota distribution in the country should be considered.
–
The adverse effect of regulations regarding quota allocation at the regional
level is further exacerbated by difficulties in finding land for sale, or even for
rent, as the direct payment allocation inhibits farmers from parting with their
land. There is an urgent need for more efficient measures that aim to develop
Dairy food chain restructuring in Poland
215
non-agricultural income sources in rural areas. This would encourage and
enable less efficient farmers to quit milk production.
–
–
–
Since small farmers lose in competition with larger ones regarding standard
milk products, an alternative could be producing unique, traditional products.
Therefore, strengthening rural development measures concerning production
and promotion of niche and regional products, as well as cooperation between farmers, should be seriously taken into consideration.
Notwithstanding the outstanding improvements in providing financial capital
to rural areas, a lack of funds remains one of the most important barriers to
development at the farm level. Therefore, money management through financial education should be strongly promoted among farmers.
Significant changes with respect to dairy market organisation can be expected
in the future. Therefore, it is necessary to prepare various scenarios of the
dairy sector’s situation after 2014, taking into account the likelihood of a
more liberal setting.
REFERENCES
DETAL DZISIAJ (2005): Od producenta do detalisty (From producer to retailer), Detal
Dzisiaj, No. 13 (174) 11/08/2005, <http://dd.tradepress.com.pl/>.
DRIES, L., SWINNEN, J. (2004): Foreign direct investment, vertical integration, and
local suppliers: Evidence from the Polish dairy sector, World Development, Vol. 32,
No. 9, pp. 1525-1544.
FRENKEL, I. (2006): Tendencje demograficzne na obszarach wiejskich (Demographic
trends in rural areas), Polska Wieś 2006. Raport o stanie wsi (Polish Village 2006,
Report on a situation in rural areas), FDPA, Warszawa, pp. 63-74.
HARDT, Ł. (2006): Opinie rolników na temat systemu dopłat bezpośrednich oraz
innych działań WPR w półtora roku po przystąpieniu Polski do UE (Farmers’
opinions on direct payments system and other CAP measures – One year and half
after accession of Poland to the EU), ABR Opinia na zlecenie Departamentu
Analiz i Strategii UKIE.
GUS (2005): Użytkowanie gruntów, powierzchnia zasiewów i pogłowie zwierząt
gospodarskich w 2005 roku (Use of land, crop area and farm animals in 2005),
GUS Warszawa 2005.
GUS (various volumes): Statistical yearbooks, GUS, Warszawa.
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NOWAKOWSKI, S. (2002): Dostawa, odbiór, i transport mleka surowego, Przemysł
Spożywczy 11/2002.
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Dominika Milczarek, Agata Malak-Rawlikowska, Jan Fałkowski
OECD (2005): Dairy policy reform and trade liberalization; trade and economic effects of milk price support measures; trade and economic effects of the milk quota
systems; Analysis of international dairy trade liberalization, OECD, Paris.
SEREMAK-BULGE, J. (2005): Rozwój rynku mleczarskiego i zmiany jego funkcjonowania w latach 1990-2005 (Developement of the dairy market and changes in its
functioning during the period 1990-2005), Program Wieloletni 21/2005, IERiGŻ,
Warszawa.
POLICY DESIGN AND EFFECTS
Sustainable rural development: What is the role of the agri-food sector?
MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central & Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 219-230.
STRATEGIES TO FACE THE SOCIO-ECONOMIC CRISIS IN A RURAL
TERRITORY: THE CASE OF THE BARONNIES PROVENÇALES
(DRÔME, SOUTHEAST FRANCE)
ANA POLETTO*, RICHARD RAYMOND**, EMILIEN BARUSSAUD***
ABSTRACT
While intensive agriculture is well developed in most of the Western Europe,
some territories face hardship because of their natural and demographic weaknesses. To tackle these problems, local actors have transformed environment and
landscapes into territorial resources which add value to their produce and justify
development projects and subsidies from national and European levels. Through
the case of the Baronnies Provençales, we see what measures can be taken, their
benefits and limits. If environment and landscapes are real driving forces for rural
development, they are not enough to ensure its sustainability.
Keywords: Mid-altitude mountains, landscape, AOC, France.
1
INTRODUCTION
As the European Union carries on with its enlargement, some rural territories in
long-time Member States still strive to integrate. Because of their location, relief,
climate or low demographical density, they cannot develop the highly productive and competitive agriculture that remains, to many territories, the main development support. These territories do not have access to the main subsidies of the
Common Agriculture Policy (CAP). Therefore, local actors must find alternative
ways of bringing in money to assure a survival and a sustainable development
for their territories.
*
University of Paris 7 – UMR LADYSS, c/o Marianne Cohen, UFR GHSS, Immeuble
Montréal,105 rue de Tolbiac, F-75013 Paris – France. Email: [email protected] and
[email protected]
**
Corresponding author. Ecole Nationale du Génie Rural, des Eaux et des Forêts –
AgroParisTech – 24, avenue des Landais B.P. 90054, F-63171 Aubiere Cedex 9 – France.
Email: [email protected]
***
University of Paris 7 – UMR LADYSS, c/o Marianne Cohen, UFR GHSS, Immeuble
Montréal,105 rue de Tolbiac, F-75013 Paris – France. Email: [email protected] and
[email protected]
220
Ana Poletto, Richard Raymond, Emilien Barussaud
In this context, environment and landscape become social resources on which
they can base local development projects. At the European and national levels, a
series of measures make this possible by granting subsidies or aids to actions
which aim at protecting the environment or the landscapes. Yet these initiative
have their limits when it comes to building a really sustainable development
dynamic. A rural territory development coordinator in southern France expresses
in a lapidary way a widespread thought: "When someone tells me that a territory
has landscapes, lavender and goat cheese, I understand it has nothing at all". Yet
landscapes, like other environmental resources, may be efficient resources to
build a sustainable rural development. It is worth therefore understanding the
conditions of this efficiency. Are there connections and/or contrasts between
these development supports and more classical ones, like the agro-food sector ?
A case study about the Baronnies Provençales should show us how French rural
territories are addressing their socio-economic problems by transforming environmental process and landscape in territorial resources and what side effects
can be observed.
2
METHODOLOGY
This paper gives a view of our researches in the Baronnies in the first semester
2006. These are aimed at studying how landscapes are changing and how these
changes are seen and dealt with by local actors. Given the interdisciplinary nature
of the subject, our methodology includes techniques from both nature and social
sciences, such as landscape and photo interpretation, vegetation survey and
semi-directive interviews. Besides the studies that we carried out ourselves, we
benefited from works previously conducted by fellow researchers from LADYSS
and CEMAGREF1.
The deliberate choice of tackling the sustainable development in a rural territory
issue through landscape allows us to grasp at a time:
–
–
–
The dynamics which cover the observed territory and leave their traces
in the landscape;
How evolutions in the territory are perceived by the actors who live
there or take care (at least partially) of its management and
The image of their territory that the local actors show to visitors or external populations.
Our field work was organised in two landscape/vegetation observation missions
and an interview mission. The first observation mission, in March 2006, was a
crossing of the Baronnies from Sisteron to Buis-les-Baronnies, thus following a
1
Specially those of COHEN and REY (2005) and DUFAU (2004), both in the Méouge Valley.
Strategies to face the socio-economic crisis in a rural territory
221
gradient from a mountainous environment to a Mediterranean one. Structures
and contents of the different landscapes were observed. It led up to a typology of
the different kinds of valley landscapes (mainly Jabron, Méouge, Ouvèze and
Menon). The second one, in May, covered about the same itinerary. It allowed
us to specify botanic contents of landscape (21 samples in main plant formations: Pine-wood, brush, scrub land, grassland…) and differentiate phases in
brush encroachment.
Concerning the interviews, they were made with 19 representatives of public
institutions (national, regional and local) and a farmer association2 in February.
All the chosen institutions deal with agriculture and/or forestry, two activities
that structure the physiognomy of the territory in the Baronnies. These actors
make rules, control, give advice or finance projects in these fields. Therefore,
they take part in defining problems, priorities and solutions. Interviews with
farmers have already been made in an exploratory campaign in the Méouge Valley
(DUFAU, 2004) and will soon be carried out in the whole territory, thus enabling
to establish a link between the visions of these two kinds of actors.
Figure 1:
The Baronnies Provençales, in Southeast France
Source: Authors.
2
Association syndicale autorisée des Amis de l’arbre, Chambre d’agriculture, Centre régional de la propriété forestière, Direction départementale de l’agriculture et de la forêt,
Direction départementale de l’équipement, EDF, Le Dauphiné Libéré (local newspaper),
Office national des forêts, Syndicat d’aménagement des Baronnies and three mayors (one
in the western side and two on the eastern one).
222
3
Ana Poletto, Richard Raymond, Emilien Barussaud
A TERRITORY IN CRISIS
The Baronnies are a 1225 km² mid-altitude mountainous territory in the South-east
of the Drôme Department (see Figure 1). Placed in the convergence of the Mediterranean Provence and the alpine domain, the region is not high enough for the
high mountain activities (ski, hiking, etc.) nor low enough to profit from the
coast-related tourism. The territory presents a gradient of climate (warmer in its
Western part, colder in the East), relief (lower on the West, higher in the East)
and cultures (a bigger diversity in the West side than in the East side). The main
types of landscape are shown in Figure 2.
After a peak of population in the second half of the 19th century, the territory
saw huge waves of migration towards urban areas during and after the World
Wars, which was a widespread tendency in rural France at the time. The population decrease was however more important here than in most of other French
territories: Today, we count no more than 17 inhabitants per km² in the Baronnies,
while the average in rural France is 35 inhabitants per km².
Nowadays, the Baronnies face increasing economic difficulties caused by international competition. The successive enlargements of the European Union have
been catastrophic to this territory whose topographic and climatic conditions do
not allow for high agricultural productivity. Furthermore, it does not have valuable
resources which could allow the local actors to take part in already structured
economic sectors (world heritage sites, snow activities etc.). Even if the demographic fall has been stopped, the socio-economic situation is tricky and many
farmers still go out of business for financial reasons. The situation is worse in
the eastern part of the territory, where the climate and the relief are harder, thus
limiting the possibilities for the farmers and reducing the accessibility and the
economic interest for the area.
The consequences of this socio-economic crisis can be seen in the landscape:
The decrease of the human population and the drop of the agricultural activities
have furthered the brush encroachment. Since the middle of the 19th century, the
afforestation rate has increased between 30% and 70% depending on the zones
(CONSERVATION DU PATRIMOINE DE LA DRÔME, 2006). In the extreme South-east
of the territory, 27% of the surface of the Méouge Valley saw its vegetation
thicken from 1948 to 1991 (COHEN and REY, 2005). Nowadays, half the surface
of the Baronnies are covered by forest-like vegetation (INVENTAIRE FORESTIER
NATIONAL, 1997). Even if protection forests planted from the end of the
19th century have contributed to this dynamic, they are a minor factor compared
with the agricultural and demographic decline (COHEN and REY, 2005).
This phenomenon, which has been observed throughout France and in Mediterranean mountain regions in neighbour countries, preoccupies local populations
and public institutions for its repercussions. Indeed, it increases the forest fire
Strategies to face the socio-economic crisis in a rural territory
223
risk, reduces the biological diversity and jeopardizes certain species. Besides, it
generates landscape closing, a threat to the symbolic, "traditional" Mediterranean landscapes which are highly appreciated in present-day Europe beyond the
borders of the Baronnies. Finally, research shows that people living in areas
where brush encroachment exists feel that they are loosing control over the
vegetation and that their identity is threatened (COHEN, 2003).
In the Baronnies, our interviews show that the brush encroachment anguishes
people because it is the visual translation of the hardship in which their territory
lives. At the same time, they fear that the landscape closing could make the
situation even worse by reducing the attractiveness and the accessibility of the
region. The forest fire risk is another great concern even if, in reality, the threat
is not as big as in neighbour Mediterranean areas (POLETTO, 2006).
As we will see, the brush encroachment is often among the arguments that justify territorial projects in the Baronnies. These are always linked to agriculture,
following a trend observed in rural territories all over France (see figure 3). Indeed, since multi-functionality became a key concept for the European rural
world, farmers have been seen as "environmental managers" (BERNARD, 1995;
and CHASSANY, 1999) and landscape conservation now depends on the maintenance of this profession.
Figure 2:
Landscape typology of the Baronnies’ valleys
Source: Authors.
Ana Poletto, Richard Raymond, Emilien Barussaud
224
Figure 3:
The various dynamics and their consequences in the Baronnies
Siting
Agriculture unfavorable
climate conditions
Situation
Economic development
and employment opportunities along the Rhône
Valley
Generally low agronomic quality soils
Erosion
Drift away
from the land
Population decrease
Decrease on the agricultural imprint
Present context
Economic hardship for
the farmers and the
territory
Globalization
Competition from other
territories
Crisis on the mid-quality
French wine industry
Little space maintenance
Reafforestation
Afforestation
Increase in the forest fire
risk
Landscape closing
Images of the territory
Residential activities
(appeal and repulsion)
Enhanced value and
depreciation of the
produce
Leisure industry
development
Biodiversity and
ecology
Source: Authors.
4
STRATEGIES TO FACE THE SOCIO-ECONOMIC PROBLEMS
The problems we listed above have been addressed by local professional, political
and governmental instances. Because the Baronnies can not produce in a low-cost
Strategies to face the socio-economic crisis in a rural territory
225
basis, its agriculture targets specific niches with high quality standards. The local produce benefits from a range of labels and certifications, the highlight being
the Appelation d’origine contrôlée (AOC) Olives and Olive Oil from Nyons (the
biggest town of the territory, in its Western end).
4.1 The quality labels: AOC, AOP and IGP
An AOC refers to the region or village from where a product comes. So that the
label is issued, the quality or characteristics of a product must be due to its geographical production environment (considered in a broad sense, which includes
both natural and human factors). Even if there are a few AOC for manufactured
products, the label concerns mainly the agri-food sector: Wine, spirits and
cheese are the most common examples.
The Appellation d’origine protégée (AOP) is an European equivalent of the
AOC issued to agricultural and food products other than wine and spirits. The
Indication géographique protégée (IGP) relates to a region or place where a
specific product is made and applies if the product bases a part of its specificity
on this geographical origin.
Schematically, the AOC and AOP apply if the specificity of the product comes
essentially from its geographical origin, while for the IGP, only a partial connection between the two elements is necessary. Both the labels were created in 1992.
In the Baronnies, the AOC Olives and Olive Oil from Nyons is an important part
of the territory development dynamics. Firstly, because it shows a collective
organisation among farmers who managed to add value to their products in order
to meet quality standards (GILLY et al., 2000). Secondly, the AOC serves as a
symbol of the territory. Indeed, in France, this label is known and appreciated by
many consumers. By purchasing the olives or olive oil from Nyons, these consumers also buy a symbolic part of the territory. Finally, in return, the territory
and the image that it supplies (i.e. the landscape) become value added elements
for the olive products. The authentic and traditional character attributed to the
firsts benefits, through a transfer effect, the later. Landscape and olives are therefore indissociable.
A team of economists has well shown how the associated promotion of quality
products and environmental services can create a sustainable territorial development model (HIRCZAK et al., 2005). In the case of the Baronnies, they emphasize
that, for the agricultural products which have managed to find an efficient niche,
the quality of the produce and that of the territory are indissociable. They form a
"goods and services shopping cart" (PECQUEUR, 2000).
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Ana Poletto, Richard Raymond, Emilien Barussaud
4.2 Parc naturel régional, pays and agri-environmental operation
Following a widespread tendency in present-day France, the local actors also take
part in comprehensive territorial projects, such as the recently launched Pays Une
Autre Provence («Another Provence» Pays) and the Parc naturel régional des
Baronnies provençales (Natural Regional Park of the Baronnies Provençales), still
in discussion. These institutions are aimed at creating new territorial configurations
and balances. Their role is to create and lead collective dynamics around territory projects that should be built and negotiated by local actors. They can also
concentrate financial resources and allocate them according to locally defined
priorities and strategies. Their final objective seems to be to foster a more sustainable management of territories.
Another strategy is the development of the rural tourism in the region. Many
farms offer accommodation, restaurants and/or direct selling of their own
products. This develops a diversification of the income. It also complements the
high quality standard strategy adopted for the agriculture by attaching a positive
territory image to the region’s produce.
At the same time, the local institutions surf in the wave of multi-functionality to
integrate environmental issues in their territorial projects. This is how the bush
encroachment was in the centre of a Local Agri-Environmental Operation held
in the Baronnies from 1997 to 2002. The operation was focused on olive tree
terraces and sheep breeding farms. The subsidies obtained were used to improve
the infrastructures in the sheep farms and clear the olive parcels from the scrub.
In all these projects, the landscape and the environment serve as supports to the
local development. They are resources for the tourism, offer an image of the territory and its produce, and justify public aids in the form of territorial or development projects.
4.3 Positive results: Improving the sustainability of the territory
These strategies appears to help solving the socio-economic problems that the
Baronnies faces. At least a part of the territory experiences a certain reborn. During
the last decade, local actors from both public and private sectors built up a new
territorial offer around the olive oil through a range of services which shape and
specify a local identity. The economists are optimistic in their conclusions: "The
territory flourishes around the olive oil, with a diversified offer on wine, aromatic plants, lavender, rural tourism, landscape etc." (PECQUEUR, 2006).
Of course, development is made day after day and it is not always easy for a territory to find its own specificity. Still, this case shows an interesting track to renew sustainable development public policies in rural territories (BENKO, 2006).
High quality standards and labels seem to be an efficient way of facing market
constraints in many sectors (the olives being the most successful case). Together
Strategies to face the socio-economic crisis in a rural territory
227
with the diversification strategy, they increase the financial security of the farms
and help maintaining a lively local economy, which should be profitable for the
whole population (not only the farmers).
The Local Agri-Environmental Operation has saved one or two farmers from
bankruptcy, according to one of our institutional sources. The Rhône-Alpes Region
points out the participative process to define the beneficiaries of the project as a
very positive aspect (JAUNEAU, 1997). The operation gave local actors the opportunity to discuss about the future of their territory, the first step towards a
sustainable development.
4.4 Side effects: Excluded people and issues
On the other hand, development projects based on environment and landscape
do not always take every aspect of the territory into consideration. The issues
which are excluded from the social and political process can be split into two
categories: Those that cannot be seen and those which are not represented by a
group of actors.
In the first category, we place the issues that are not observed neither on the
landscape nor in the social claims – that is, what does not pose problem in the
local level and therefore is not addressed by local institutions. Some of these issues
may nevertheless be a problem in a larger scale.
The second category refers to issues that bother a part of the population which
do not have enough social capital to build up or integrate an interest group. This
seems to be the case of the farmers living in the East of the territory, who suffer
most from the socio-economic crisis. This zone is too cold for the leading products of the goods and services shopping cart (olive and wine). The main regional routes are far away, which harm the tourism industry development. This
means that these actors do not benefit from the territorial identity that they contribute to create through their farming activities and their space maintenance.
After all, we can wonder about the perenniality of these landscape amenities,
highly estimated as a value added to certain products but kept partly by actors
facing hardship and whose activities are, in the long run, compromised. This aspect
lightens the optimism of the previously mentioned analyses. While the bush
encroachment is stronger in the eastern zone (BARUSSAUD, 2006), the financial
aids and the development projects do not seem to place their priorities here.
The mayors from the East are by the way quite sceptical about the territory projects such as the Pays or the Parc Naturel Régional. They feel they are left on
their own while the West benefits alone from the programmes (POLETTO, 2006).
But they do not seem to have much political weight outside their own villages
and therefore their demands are not well represented. As for the mayors from the
West, they seem to believe that the development benefits everybody.
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Ana Poletto, Richard Raymond, Emilien Barussaud
Concerning the high quality labels such as the AOC, they have excluded from
the market several farmers who can not meet the standards. Indeed, the specifications often require investments that some people, already on the edge of profi
tability, are not able to do. Once again, the problem is bigger in the East than in
the West. But, most of the time, the poorer farmers also lack the social and political resources that could help turning their problem into a local issue. The
decision makers are aware of the situation, but do not see what they could do
about it.
As for the Local Agri-Environmental Operation, its technico-administrative approach has clear limits when it comes to ensuring a real sustainability to the territories (BERNARD op. cit.). The budget allocated and the duration (only five
years) are unsuitable for the long-term solutions needed. Therefore, the operation appears more as an emergency measure than as a real development programme.
The tourist promotion, on its side, might be accelerating the increasing in the
number of second homes in the territory, whose consequences are feared by the
local inhabitants. These point out the second-home owners as responsible for an
explosion in the estate prices and thus the impossibility for youngsters to buy a
farm and assure the continuity of the socio-economic life in the Baronnies. This
problem, quite widespread in French rural space today, has already touched
nearby territories. However, it is uncertain to what extent it is really a consequence of the second-home buyers.
Finally, not all the environmental problems of the Baronnies are addressed in the
local actors’ strategies. The most notable example is the badland erosion, observed by scientists but ignored in the local policies. The farmers themselves
seem quite aware of the problem, although they do not know what its consequences are beyond the borders of their land. On the other hand, the local decision makers do not consider the erosion to be a problem in the territory. This
situation may be explained by the little space the badlands take in the landscape.
Nevertheless, research has shown that, in spite of their size, at least some of
these badlands are dynamic enough to cause the raising of the bed of the Durance
River and the silting of the dams. This environmental question, underestimated
in the local level, is addressed in the regional scale (that of the Durance basin
management) by national institutions like EDF and the CEMAGREF. Thus, if local
actors do not feel concerned by the subject, it is probably because they do not
suffer the consequences of the erosion and because the problem is treated by national bodies.
Strategies to face the socio-economic crisis in a rural territory
5
229
CONCLUSION
Environment and landscape are often used as bases for the development of rural
territories facing hardship. They have indeed become a driving force that enables
them to bypass their natural or social weaknesses. However, they are not enough
to ensure a sustainable rural development. Other factors, like the organisation of
the actors or the social capital, must be associated to the process, so that all the
issues identified at the local level can be addressed. In other words, each inhabitant should feel empowered to express their concerns and these ought to be taken
into consideration in the territorial programmes.
As for the problems which are not identified by local actors, a diagnosis from an
external body could bring them out. In this case, it would be up to the regional
or national-level institutions to deal with them, as it is presently the case with
badland erosion.
ACKNOWLEDGEMENTS
We would like to thank MARIANNE COHEN and the researchers from the «Landscape Dynamic, Erosion And Sustainable Development In The Mediterranean
Mountains» research programme, financed by the French Ministry of Ecology
and Sustainable Development.
REFERENCES
BARUSSAUD, E. (2006): Paysages et identités régionales dans les Baronnies, Mémoire
de maîtrise de géographie, Université Paris 7 Denis Diderot.
BENKO, G. (2003): Sous la globalisation, le poids des territoires, Sciences Humaines,
May/June 2003, pp. 120-123.
BERNARD, C. (1995): Elaboration d’un projet de gestion de l’espace dans les Baronnies
(Drôme): Entre un dispositif technico-administratif et une gestion patrimoniale,
Revue de géographie alpine, 3, pp. 65-82.
CHASSANY, J.-P. (1999): Processus de déprise agricole et enjeux socio-économiques,
Ingénieries: Eau, agriculture, territoires, hors-série, pp. 81-89.
COHEN, M. (org., 2002): La Brousse et le Berger. Une approche interdisciplinaire sur
l’embroussaillement des parcours sur le causse Méjan, Editions du CNRS, Collection Espace et Millieux.
COHEN, M., REY, F. (2005): Dynamiques végétales et érosion hydrique sur les marnes
dans les Alpes françaises du Sud, Géomorphologie: Relief, Processus, Environnement, 1, pp. 31-44.
CONSERVATION DU PATRIMOINE DE LA DROME (2006): Patrimoine des Baronnies.
Paysage, architecture et histoire, Département de la Drôme.
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Ana Poletto, Richard Raymond, Emilien Barussaud
DUFAU, B. (2004): Mesure de la dynamique du paysage du Val de la Méouge liée à
l’occupation du sol et son évolution (Baronnies méridionale Alpes du Sud),
Mémoire de maîtrise de géographie, Université Paris 7 Denis Diderot.
GILLY, J. P., PECQUEUR, B. (2000): Régulation des territoires et dynamiques institutionnelles de proximité: Les cas de Toulouse et des Baronnies, en France, in:
GILLY, J. P., TORRE A. (eds.): Dynamiques de proximité, L'Harmattan, Paris.
HIRCZAK, M. et al. (2005): Du panier de biens à un modèle plus général des biens
complexes territorialisés: Concepts, grilles d’analyse et questions, Actes du Symposium International INRA PSDR "Territoires et enjeux de développement régional", Lyon, 9-10 March 2005, [CD-Rom]
INVENTAIRE FORESTIER NATIONAL (1997): Département de la Drôme. Résultat du
troisième inventaire forestier (1996), IFN.
JAUNEAU (org., 1997): Evaluation des mesures agri-environnementales en Rhône-Alpes,
ISARA/ACER Campestre/DRAF Rhône-Alpes.
PECQUEUR, B. (2000): Qualité et développement territorial. (II) l'hypothèse du panier
de biens, Actes du Symposium INRA-DADP "Recherches pour et sur le développement régional", Montpellier (FRA), 11-12 January 2000, Grenoble: INRA-R&A,
tome 1, pp. 70-80.
PECQUEUR, B. (2005): Territoires: Le phénomène cluster, Sciences Humaines, horssérie 50, September/October 2005, pp. 44-45.
POLETTO, A. (2006): La prise en compte des dynamiques de paysage par les structures
d’encadrement des activités agricoles et forestières dans les Baronnies provençales
(Drôme), Mémoire de Master 2, Université Paris 7 Denis Diderot.
RAYMOND, R. (2004): De quelle nature parle-t-on ?, STRATES, matériaux pour la recherche en sciences sociales, Paris, CNRS, 11, pp. 43-56.
Sustainable rural development: What is the role of the agri-food sector?
MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central & Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 231-247.
EMPIRICAL ASSESSMENT OF FUZZY INTERVENTION-LOGICS:
THE CASE OF RURAL DEVELOPMENT IN EAST GERMANY
ANNE MARGARIAN∗
ABSTRACT
The assumptions of classical economic development theories often do not hold
in situations of structural break, or under different exogenous restrictions that
induce policy intervention. Evaluation and policy advice therefore have to rely
on situation-specific ad-hoc theories that do not claim general validity but are
well-adopted to prevailing circumstances. This paper proposes that when evaluating rural development, the intervention-logics of politics could serve as an ad
hoc theory. In order to test these theories, which often include many endogenous
and intervening variables – as well as conflicting goals – structural equation
modelling as a methodical approach is proposed. It is then applied to the evaluation of macroeconomic effects of farm investment aid in East German rural areas.
Keywords: Structural equations, rural development, policy-evaluation.
1
INTRODUCTION
Evaluation and political advice often have to deal with situations where the assumptions of standard theories do not hold because it is exactly then that politicians feel the need to interfere: Political measures are implemented in order to
reinforce economic dynamics and stabilise social situations. How is political advice and policy-evaluation in the field of rural development possible in the
absence of a sound theoretical framework?
While an explanation of observed effects often has to be searched for on the
micro-level using data from single households and enterprises, the goals of politics often are, or should be, measurable on the macro level of the economy and
society. For the evaluation of rural development policy, the following conclusions have been drawn:
1. Considering the nature of evaluation and policy advice, i.e., they are applied
sciences with practical tasks, indicators for assessing the effectiveness of
political measures and/or assessing intervention logics might well come
∗
Federal Agricultural Research Centre (FAL), Institute of Farm Economics, Braunschweig,
Germany. Email: [email protected]
232
Anne Margarian
from a highly aggregated level. This is often necessitated by a lack of
knowledge of the micro-foundation of observed phenomena. This strategy
of macro level indicators is currently being followed by the European Commission in their new evaluation guidelines (EUROPEAN COMMISSION, 2006).
2. Due to the lack of general theories that adequately fit situations with disturbed standard assumptions, policy advice, as well as evaluation, has to
rely on ad hoc theories, which do not aim for general validity but are welladjusted to the specific phenomena under observation and the prevailing
circumstances1. The intervention logic designed by politicians in order to
implement its measures (or to justify their implementation) could serve as
such an ad hoc theory to be tested by policy-evaluation.
Following are two main problems that hinder evaluation from successfully testing
political intervention logics quantitatively with existing data:
1. The proposed indicators on the macro-level are, due to their aggregation
level and the way they are arrived at, prone to measurement error, insensitive to unobservable micro-changes, and questionable in the method by
which they measure what they are supposed to measure.
2. The ad hoc theories of political intervention logics are not usually proper
scientific theories, especially in that they might not be worked out analytically in a one cause-one effect scheme.
The proposed methodological approach that seems to suit these problems especially well is structural equation modelling (SEM). This approach seems especially
appropriate theoretically, since it is a confirmatory type of analysis and evaluation
is supposed to test existing intervention-logics. Moreover, it allows for the consideration of many statistical problems that evolve from the complexity of social
systems such as error term dependencies, accounting for intervening effects
(SINGER et al., 2003), simultaneous models and multicollinearity among indicators
(SUHR, 2001).
Experience with SEM is rather restricted concerning the evaluation of politics in
rural development. However, this approach has been frequently applied in marketing and in studies concerning the success factors of enterprises. One example
from agriculture is DAUTZENBERG (2005). There are disciplines where much more
experience exists with the application of SEM, among them studies concerning
genetics or psychology, but also special economical branches such as travel
behaviour research2. One study on the impact of social capital on economic
1
2
A sceptical view regarding the validity of assumptions of standard economic theory can be
detected among experienced evaluators (MARGARIAN, 2006). Due to immediate and open
feedback from politics, evaluation often tests for the adequacy of underlying assumptions,
for example by questioning recipients.
See, for example GOLOB (2001).
Empirical assessment of Fuzzy Intervention-Logics
233
development in Italy (SABATINI, 2006) remarkably closely resembles the potential of SEM as discussed in this paper. As for the scope of the paper, it clarifies
the possibilities of a database extended by primary data and by the application of
latent variables. There are excellent textbooks on structural equation modelling,
among them BOLLEN (1989) and LOEHLIN (2004), the latter of which gives more
weight to application. Moreover, user-friendly software exists. For example,
Proc CALIS from the SAS-system has been used in this paper. A pioneering and
highly-developed tool is LISREL, but with MX, there also exists a high potential
form of freeware.
Regarding the structure of this paper, first, a short theoretical introduction with
respect to the fundamental aspects of structural equations without latent variables
is given. This is illustrated by an example derived from one possible intervention logic of farm investment aid (AFP) for rural development in Eastern
Germany (Section 2.1). The estimation of this model will be presented in
Section 2.2,, and the results will be discussed in Section 2.3. Then, problems
with the approach, specifically with respect to the presented application, are discussed and possible extensions presented in Section 3. Final conclusions are
drawn in Section 4.
2
STRUCTURAL EQUATIONS WITH OBSERVED VARIABLES
2.1 Theoretical foundation and application
Political measures often lack one single consistent intervention-logic3. In contrast
to other methods, the analysis of variances via structural equations enables the
scientist to reconstruct complex intervention-logics, including multiple and conflicting goals, super-goals and sub-goals4. Structural models allow for feedback
loops, as well as for intervening variables, and the demand for a measure can be
modelled simultaneously with the observed effects. Direct, indirect and total
effects can thus be calculated.
The basic model5 is (BOLLEN, 1989, p. 80-81)
y = By + Γx + ζ
,
(1)
where
B = m*m coefficient matrix
Γ (Gamma) = m*n coefficient matrix
3
4
5
An older but still very valuable discussion of the problem of political measures and their
justification and logical foundation can be found in HOMANN (1980).
For an exemplary discussion of the normative validation of policies’ goal-systems, see
MARGARIAN (2006a).
In Sections 2.1 and 2.2, the paper relies heavily on BOLLEN (1989) in its technical parts.
234
Anne Margarian
y = p*1 vector of endogenous variables
x = q*1 vector of exogenous variables
ζ (Zeta) = p*1 vector of errors in the equations.
In these structural models with observed variables, it is assumed that the observed variable exactly resembles the underlying construct without measurement
errors.
These models can be presented fairly easy in so-called path-diagrams6. Ideally,
once an intervention-logic has been formulated as a path-diagram, it should be
discussed with politicians in order to identify its weak points, i.e., high insecurity, or possible misunderstandings and interpretation. The intervention logic of
farm investment aid (AFP) in some East German states can be described as follows: The subvention of capital on farms for certain investments supports the
preservation of jobs. Moreover, investments are supposed to support farm activities that produce high gross product per hectare, thus supporting the local economy
and also preserving jobs. Farm investment aid is not directed to special farms
through administration, but rather distributed by demand. This capsulated description of one possible intervention logic shows that:
1. There are two direct result variables, growth of agricultural GVA and
preservation of jobs in the sector.
2. These are only the subgoals for the supergoals of strengthening the local
economy and residents’ income. Therefore, agricultural GVA and jobs not
only represent result variables, but are also supposed to serve as intervening
variables.
3. AFP itself, since its distribution is guided by demand and might partly be
caused by both the GVA produced in a region and the number of jobs on
farms, is therefore not exogenous to the model.
The problem is depicted in Figure 1 as a path-diagram, while for simplicity, the
endogenous character of AFP is not considered; other exogenous variables are
left out. Also, the expected direct effects of AFP are symbolised by bold lines,
while indirect effects are portrayed by dotted lines. The direct connection to
changes in total income is due to the fact that farm investment support is supposed to be accounted for as an income position in private farms; the direct connection with changes in total GVA is due to the often stated assumption by politicians, that investment aid via multiplicator effects stimulates the economy as a
whole.
6
There are software programs which enable the researcher to set up their model via graphic
interfaces. A second possibility for formulation is transforming the paths into equations,
one for every endogenous variable. A third possibility has been selected by the author to
assist with clarity should models grow complex: Direct formulation via matrices (see below).
Empirical assessment of Fuzzy Intervention-Logics
Figure 1:
235
Simplified Path Diagram of intervention-logic
ζ1
ζ2
ζ3
Change in
Employees
first sector
γ12
FarmInvestment
support/ha
γ13
γ15
β26
β25
Change in
employees
(total)
β63
β64
Change in
income
γ14
Change in
Gross
Value
added first
sector
Other
exogenous
factors
β53
Change in
GVA total
β54
ζ4
ζ5
Source: Author, in the style of BOLLEN (1989).
While single-direction arrows depict directions of causality, double-headed arrows
show correlations among variables. Since connections between endogenous
variables are supposed to be formulated explicitly in the structural part of the
model, correlations (double-headed arrows) are only admitted on exogenous
variables. If we formulate this model with matrices, it would look like this, according to Formula 1:
y1
0
y2
0
y 3 = β 31
y 4 β 41
y5 0
0
0
β 32
β 42
0
0
0
0
0
0
0
0
0
β 53 β 54
y1 γ 11
ζ1
0
y 2 γ 21
ζ2
0
0 * y 3 + 0 *x1+ ζ 3
y 4 γ 41
ζ4
0
0
y 5 γ 51
ζ5
(2)
With the vector of y’s represent the five endogenous variables in the path diagram, the β’s represent causal influences among endogenous variables, γ is the
influence of the exogenous variable x (farm investment support) and ζ as error
terms’ non-observed external forces that cause changes in the endogenous variables. No covariances are assumed between the error terms, so the covariance matrix of the ζ’s, a matrix called Ψ (Psi), is diagonal. Additionally, matrix B has
β’s only in the portion beyond the diagonal. These characteristics illustrate an
important property of our model: It is recursive. Recursive models do not contain reciprocal causation or feedback loops. Models with this characteristic are
easier to handle since identification is less of a problem, i.e., there should always
be a singular solution. In addition to B, Γ and Ψ in the model with observed
variables, we have to consider one more type of matrix in order to fully specify
236
Anne Margarian
the model: The matrix Φ (Phi), which contains the covariances between the
exogenous variables.
2.2 Data and estimation
In order to test this intervention-logic, an appropriate model must be designed.
This model must account for more factors than depicted in the simplified path
diagram above. In this model, development between 1999 and 2003 in the districts
under scrutiny is explained by the initial situation (baseline indicators for 1999),
development of the other respective indicators, and the possible influence of
AFP.
Development in 76 rural districts of the Eastern German states is compared. From
the 113 total districts, all urban districts have been excluded. Moreover, a test on
normality of the included variables showed that for the variables aggregated income in a region and development of engaged persons, single outliers existed.
The corresponding districts have therefore been eliminated from analysis, since
an analysis of variances generally reacts rather sensitively to non-normality.
Similarly, to reach a normal distribution, districts with a positive development of
their number of inhabitants have been excluded from the analysis (eight districts).
Ultimately, 77 districts remained in the sample. The model has been confirmed
for this data set. It has been suspected, however, that possibly some unknown
reasons, which are not accounted for in the model, lead to the reported lack of
AFP support in eight of the districts. Therefore, the analysis was carried out a
second time without these districts in the sample. Thereby, the fit of the models
became much better and, while significant changes in the estimate of other parameters did not occur, within these supported areas the variable for "income"
turned out to be significantly positively related to the distribution of funds.
Estimates based on this sample of 68 districts are presented in the following.
Employed data came from various sources: The macroeconomic account on the
level of districts (ARBEITSKREIS VOLKSWIRTSCHAFTLICHE GESAMTRECHNUNGEN
DER LÄNDER, 2007); data from the census of agriculture in 1999 and 2003; a collection of regional indicators published by BBR (2000, 2005); and from an
evaluation report on the investment support of food processing and marketing
enterprises (WENDT et al., 2006). Data on the distribution of AFP funds have
been provided by state ministries. Means and standard deviations of the baseline
indicators from 1999, as well as of the calculated proportional developments between 1999 and 2003 are presented in table 1. While the rate of change usually
followed approximately normal distributions, baseline indicators have been transformed to their natural logarithm for use in the model.
Empirical assessment of Fuzzy Intervention-Logics
Table 1:
237
Description of variables used in the models
Variable
Unit
AFP-Support per ha 00€
02
Employees primary sector
Persons
per ha 99
Agricultural GVA per ha
1,000 €
99
Proportion of employed Employed
inhabitants 99
/inhabitan
N
Mean
Standarddeviation
Min
Max
76
6.95
8.51
0.00
43.63
76
0.05
0.03
0.02
0.18
76
0.96
0.17
0.65
1.54
76
0.38
0.03
0.31
0.45
GVA per inhabitant 99
1,000 €
76
12.92
1.31
10.01
16.35
Income per person in 99
€
76
12738.26
567.38
11624.00
14587.00
68
2.37
2.18
0.00
12.00
76
-0.07
0.11
-0.29
0.20
76
0.05
0.07
-0.13
0.28
76
-0.07
0.04
-0.17
0.02
76
-0.06
0.10
-0.32
0.21
76
-0.15
0.12
-0.50
0.10
Food-processing
absolute
Enterprises
number
Change in income-tax per
person
difference
Change in GVA
from 03 to
99 related
Change in number of
to
employed persons
baseline
Change in agricultural
99
GVA
Change of employees in
agriculture
Notes: Changes are calculated from 1999 to 2003.
Source: Author’s calculation based on BBR (2000, 2005), agricultural census and ARBEITSKREIS
VGR (2007).
The situation in 1999 is shown by the following exogenous variables: GVA per
person; the proportion of employed persons from all inhabitants; income per
person; GVA of agriculture per hectare; agriculturally-employed people per
hectare; and the number of food processing enterprises. The amount of support
in a certain district is assumed to be influenced by these regional characteristics
and therefore becomes endogenous to the model. It is supposed that the GVA of
agriculture/ha, (since demand for funds is dependent on production types in a
region, as well as income, since investment has to be co-financed by the farmers)
as well as the number of food processing enterprises, have an influence. It is important to account for the latter, since they belong to the primary sector. Generally,
it has been assumed that baseline indicators exceed the influence on their own
development and on some of the other endogenous variables due to the close
interdependencies among them. For the same reason, covariances among all exogenous variables are also estimated. The model becomes non-recursive (see above)
with respect to one relationship: Change in employment is allowed to induce
change on the development of total gross value-added and conversely, the development of GVA is allowed to influence the development of overall employment
(reciprocal causation). No covariances among error terms and no feedback relations are assumed, however. Due to the indicator’s higher sensitivity towards
capital subventions, and to prove that there actually are measurable effects of the
Anne Margarian
238
measure, the variable "development of total income" has been replaced by "development of income tax". The remaining (endogenous) part of the model has been
formulated according to the path diagram above. The correlation matrix on
which the estimation is based is shown in Table 2.
Table 2:
Correlation matrix of the model
1
Change Income1
tax
2
3
4
5
6
7
8
9
10
11
1
0.15
1
0.23
0.57
1
0.19
-0.32
-0.12
1
0.03
-0.16
0.09
0.15
1
0.22
-0.10
-0.01
0.19
0.25
1
0.04
0.07
0.06
0.02
-0.47
-0.19
1
0.02
0.17
0.10
-0.20
-0.15
-0.38
0.52
1
0.51
0.18
0.36
-0.03
0.12
0.07
0.27
0.41
1
0.13
-0.23
-0.05
0.29
0.10
0.17
0.32
0.19
0.25
1
11 GVA per person 0.10
-0.19
0.01
0.03
0.33
0.20
-0.08
0.07
0.31
0.57
1
0.31
-0.08
-0.12
0.28
0.07
0.18
-0.15
0.00
0.27
-0.02
0.043
2 Change GVA
Change number
of employed
Change agric.
4
GVA
Change agric.
5
employees
3
6 AFP/ha
Employees in
agric. 99
agricultural
8
GVA/ha 99
Income per
9
person 99
share of
10
employed
7
12 food-processors
12
1
Source: Author’s calculation with Proc Corr (SAS).
In the estimation process, this Correlation matrix, or, preferably, the corresponding
matrix of covariances, has to be reproduced as closely as possible. BOLLEN (1989,
pp. 85-88) shows how the covariances between endogenous variables, exogenous variable and endogenous and exogenous variables can be reconstructed
based on Formula 1. For each of these parts of the total matrix of covariances,
one arrives at single formulas that consist of matrices Φ, Γ, Ψ, and B: The variances
and covariances are functions of the model parameters. SEM employs various
estimation procedures. The most common are generalised least-square (GLS),
maximum likelihood (ML) and unweighted least-square (ULS)7. In this paper,
ML has been used mainly for better possibilities for the assessment of model fit,
even though the sample size might be judged as being too small. For comparison, additional ULS estimates have been calculated. The resulting estimates are
comparable in magnitude and sign.
7
For a discussion of the pros and cons of the different estimation types, refer to BOLLEN
(1989, pp. 107-116).
Empirical assessment of Fuzzy Intervention-Logics
239
2.3 Results
Due to the rather large number of variables used in the model, a path diagram is
not being presented as a whole, but only for clarification of single relations.
Instead B, Γ and Φ are presented with the names of corresponding variables in
rows and columns. The matrix Ψ remains diagonal, so that the unexplained
Variances ζ are presented in vector form. Figure 2 presents matrix Φ with correlations between the exogenous variables of the first model.
Figure 2:
employees
first sector
per ha 99
GVA first
sector per
ha 99
Income
per person
99
employment 99
GVA per
person 99
Foodprocessors
Covariances between exogenous variables within the model (Φ)
GVA first
employees first
Income per
sector per ha
sector per ha 99
person 99
99
1.00
0.17
5.79
[p7]
0.52
1.00
0.14
0.17
3.77
5.79
[p13]
[p8]
0.27
0.41
1.00
0.13
0.13
0.17
2.17
3.10
5.79
[p18]
[p14]
[p9]
0.32
0.19
0.25
0.13
0.12
0.13
2.49
1.52
1.96
[p22]
[p19]
[p15]
-0.08
0.07
0.31
0.12
0.12
0.13
-0.69
0.57
2.40
[p25]
[p23]
[p20]
-0.15
0.00
0.27
0.12
0.12
0.13
-1.21
0.03
2.14
[p27]
[p26]
[p24]
employment 99
1.00
0.17
5.79
[p10]
0.57
0.14
4.03
[p16]
-0.02
0.12
-0.20
[p21]
GVA per
Foodperson 99 processors
1.00
0.17
5.79
[p11]
0.04
0.12
0.35
[p17]
1.00
0.17
5.79
[p12]
Notes: Due to the symmetric character of the matrix, only the lower half is presented. The
estimated value is given in the first line, standard-deviation in the second and corresponding t-value in the third. The fourth line shows the name which the parameter
was given in the estimation procedure.
Source: Author’s calculation with Proc Calis (SAS).
Even though the correlations are not extraordinarily high, it can be said that the
estimation of covariances could not have been dropped from the model without
severely affecting its fit. From the 15 estimated covariances, only a few are
clearly insignificant: Total gross value added in a district in 1999 does not seem
to be correlated with the proportion of employees in the first sector of 1999, the
gross value added in the first sector in a district in the same year, or with the
number of food processing enterprises in the district. The latter neither shows
significant covariance with the gross value-added in the first sector, nor with the
Anne Margarian
240
employment situation. Figure 3 depicts matrix Γ, which shows the influence that
the exogenous variables (the same variables from Figure 2) exert on endogenous
variables.
Figure 3:
Estimated influences from exogenous on endogenous parameters
employees first GVA first sector Income per
sector per ha 99
per ha 99
person 99
change in
income-tax
0.00
0.00
0.00
0.00
0.00
0.00
change in
GVA
0.00
0.00
0.00
0.00
0.00
0.00
Change in
employment
0.00
0.00
0.00
0.00
0.00
0.00
0.24
0.15
1.62
[g1]
-0.62
0.12
-5.20
[g2]
0.00
0.00
0.00
-0.38
0.13
-2.82
[g3]
0.10
0.13
0.76
[g4]
-0.47
0.12
-3.96
[g5]
Change in
GVA first
sector
Change in
employment
first sector
AFP-funds
per ha
0.43
0.11
3.79
[g6]
0.13
0.14
0.91
[g7]
0.38
0.12
3.19
[g8]
0.00
0.00
0.00
0.19
0.11
1.66
[ga]
0.23
0.12
1.87
[g9]
employment 99
GVA per
person 99
Foodprocessors
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
-0.22
0.10
-2.13
[g14]
0.00
0.00
0.00
0.14
0.11
1.31
[g18]
0.00
0.00
0.00
-0.10
0.12
-0.83
[g11]
0.28
0.11
2.45
[g12]
0.21
0.11
1.98
[g13]
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
-0.21
0.11
-1.96
[g20]
0.32
0.11
2.91
[g15]
0.00
0.00
0.00
0.11
0.11
1.01
[g17]
Notes: The estimated value is given in the first line, standard-deviation in the second and
corresponding t-value in the third. The fourth line shows the name that the parameter
was given in the estimation procedure.
Source: Author’s calculation with Proc Calis (SAS).
The assumption that the level of a baseline indicator influences its own development (see above) has been confirmed. For initial condition and development,
we observe a negative relationship for employees in the first sector, for GVA in
first sector and for overall GVA. This means that with respect to these indicators, we observe a converging development between different rural districts,
which is much clearer for the primary sector. Interestingly, there exists a positive relationship between disposable income in 1999 and the development of
income tax payments in the following years. With respect to the economic condition of rural district inhabitants, we therefore observe diverging development.
The single most influential exogenous variable is income per person in 1999. It
must be admitted that some of the causal influences of this indicator have been
introduced ad hoc in order to improve the model’s fit. The validity of these assumptions could then only be tested on a different sample. The positive causal
influence from income on the change in employment in the first sector surely
deserves further investigation. As assumed, the GVA of the primary sector per
Empirical assessment of Fuzzy Intervention-Logics
241
hectare influences the distribution of AFP funds. Money seems to flow into areas
with a lower intensity than the primary sector. On the other hand, the flow of
funds is also related to the disposable income of people in a region. This could
be explained by the fact that especially in regions with a high share of family
farms, investments are financed in part through disposable income and thereby
only realised if the income situation allows it. The presence of food processing
industries has a very positive influence on the development of gross value-added
in the primary sector, and a significant negative influence on employment in
this sector. Rationalisation seems to proceed fastest in these districts. Slightly
more funds flow into areas with more food processors. Figure 4 shows the relationship between the endogenous variables, i.e., the estimates of the β-Parameters
in Matrix B.
Figure 4:
Estimated relationships between endogenous parameters (B)
change in
income-tax
0.00
change in
0.00
income0.00
tax
change in
GVA
Change in
employme
nt
Change in
GVA first
sector
Change in
employme
nt first
sector
AFPfunds per
ha
change in
GVA
0.00
0.00
0.00
Change in
employment
0.11
0.11
1.00
[b1]
0.31
0.25
1.24
[b2]
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.27
0.24
1.10
[b0]
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Change in GVA Change in employ- AFP-funds
first sector
ment first sector
per ha
0.15
0.00
0.14
0.10
0.00
0.10
1.43
0.00
1.41
[b3]
[b7]
-0.27
0.00
0.00
0.10
0.00
0.00
-2.63
0.00
0.00
[b4]
0.00
0.11
0.00
0.00
0.10
0.00
0.00
1.09
0.00
[b5]
0.00
0.17
-0.05
0.00
0.13
0.12
0.00
1.35
-0.42
[b6]
[b9]
0.00
0.00
0.12
0.00
0.00
0.11
0.00
0.00
1.05
[b10]
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
Note : See Figure 3.
Source: Author’s calculation with Proc Calis (SAS);
Contrary to the stated aim of agricultural investment aid, the measure does not
seem to influence the intensity of agricultural production (change in GVA first
sector), at least in the short run. The significant and predicted influence on income
tax payments confirms the fact that the model would principally be capable of detecting structural influences of the measure, if there were any. Actually, the
model shows a small positive influence on the development of employment in
Anne Margarian
242
the first sector. This, as expected, has a slightly positive influence on overall
employment and a slightly positive influence on development of GVA in the
primary sector. This then leads to significantly higher income tax payments. The
model shows that in rural districts, agriculture seems to be one of the major
sources of income tax development. More interesting here, though, is that an increase in gross value-added in the primary sector seems to occur at the expense of
the development of overall GVA. This confirms the fact that every Euro can only
be spent once. Furthermore, it can be seen that while a change in employment in
the first sector only provokes minor development of overall employment, a change
of total GVA has a greater positive influence on the development of employment.
Figure 5 shows the most important findings of the model with respect to the intervention-logic.
Figure 5:
Path Diagram for central findings of the first model
+
Disposable
Income 99
+
Change in
Employees
first sector
+
+
+
FarmInvestment
support/ha
Change in
employees
(total)
+
+
Change in
Gross
Value
added first
sector
++
-Change in
GVA total
Source: Author’s picture.
The graphic should make clear that jobs in agriculture are costly in terms of
foregone opportunities: If disposable money is directed towards investments in
other than the primary sector, GVA and the number of jobs develop more positively. On the contrary, investments into the primary sector only have minor
positive influence on job development. At the same time, the development of the
overall economy is slowed by the concentration on agricultural investments; this
is depicted by the strong negative estimate for the arrow leading from change in
GVA in the first sector, to change in GVA total.
The last estimates to be presented are remaining variances of the endogenous
variables (ζs). They are:
–
Change in income tax
0.65
–
Change in GVA
0.62
–
Change in employment
0.61
Empirical assessment of Fuzzy Intervention-Logics
–
Change in GVA of primary sector
0.73
–
Change in employment in primary sector
0.65
–
and AFP funds per ha
0.79.
243
Therefore, about 32% of the total variance of the endogenous variables has been
explained. As matrix Γ in Figure 3 shows, development strongly depends on the
initial situation, which explains the biggest part of the variances.
How dependable are the model’s results? The assessment of fit is one of the major
weak points of SEM. Chi-square is only applicable for GLS- and ML-estimation
in the case of multinormality. In fact, multinormality is seldom tested for, even
though BOLLEN (1989) proposes a matrix-algebraic approach. Moreover,
Chi-square relies on sample size, therefore for large sample sizes it might become difficult to find a model that cannot be rejected (GOLOB, 2001). On the
other hand, Bollen writes that for small Ns, there is evidence that chi-square is
often too large, leading to rejections of the model. As a guideline for minimal
sample size, he writes: "A useful suggestion is to have at least several cases per
free parameter," (p. 268). In the literature, usually the application of a bundle of
measures of fit is proposed for overcoming problems of each single one. This is
done in Table 3. I closely follow both procedures and style from DAUTZENBERG
(2005).
Table 3:
Assessment of model fit
Goodness of Fit Index
Abbreviation
GFI
empirical
value
0.96
Threshold
>0.9
GFI Adjusted for Degrees of Freedom
AGFI
0.86
>0.9
Root Mean Square Residual
RMR
0.05
<0.1
Parsimonious GFI
PGFI
0.33
0.0-1.0
0.00
<0.08
Criterion
RMSEA Estimate
Chi-Square
Chi-Square DF
chi2
18.36
df
23.00
Pr > Chi-Square
0.74
Probability of Close Fit
Chi-Square/ DF
0.87
2
chi /df
0.80
Independence Model Chi-Square
259.92
Independence Model Chi-Square DF
66.00
Independence Model Chi-Square/ DF
chi2/df
<3.0
3.94
Source: Author’s table based on output from Proc Calis (SAS) and in close resemblance to
DAUTZENBERG (2005).
244
Anne Margarian
It can be concluded from Table 3 that the model reached a good fit with respect
to all criteria despite the "adjusted for degrees of freedom wellness of fit index"
(AGFI). The chi-square seems high, but in relation to the remaining degrees of
freedom of the model, it is nevertheless highly satisfactory. Moreover, the probability of rejecting the 0-hypothesis of a non-fitting model is high; the test therefore has not proven the model to be incorrect. A comparison with the independence model chi-square also shows that compared to a zero-parameter baseline
model, the fit improved significantly, since the chi-square dropped from 260 to
18. For more information on this criteria, the reader is referred to BOLLEN
(1989) and SAS (1999).
3
RESTRICTIONS OF THE MODEL
One main problem with the proposed approach of modelling structural relationships at the level of highly aggregated macro-variables is that in SEM, the researcher is supposed to model causal relations between variables, not correlations. The higher the aggregation level of observation, the more complex are the
hidden interrelationships that underlie the observable correlations between variables. It might not be possible to exactly picture these interrelationships, which
probably include reciprocal causalities and feedback loops, without running into
problems with identification. Moreover, the problem of excluded variables remains in SEM8. The more global the model, the more difficult it might become
to include all relevant causes for developments and, in our case, for the distribution of funds. Especially in the latter case, over- or underestimations of a
measure’s effects would result. Another drawback of highly aggregated models
is that single indicators might represent more dimensions of a situation than the
researcher is aware of. One example is the baseline-income variable in the presented model, which proved to have a highly significant influence on most of the
endogenous variables even though some of the modelled relationships cannot be
explained by direct causality.
However, structural equation modelling offers far more possibilities than discussed in the relatively simple example presented in this paper. In contrast to
other methods, SEM provides the possibility to test for the probability of mutual
causality such that the classical assumption that attitude causes action can be
challenged by the contrary assumption that action (revealed preferences) causes
attitudes9. This might turn out to be important in the treatment of the difficult
question of evaluating take-along effects.
8
9
For an excellent discussion on the problems of pseudo-identification in statistical models,
see BOLLEN (1989).
A study showing the possibilities of SEM in an exemplary manner is DOBSON et al.,
(1978).
Empirical assessment of Fuzzy Intervention-Logics
245
Probably the most important extension for evaluation is the inclusion of latent
variables. The construction of latent variables enables the researcher to:
1. Build latent constructs which depict what really is supposed to be measured,
for example the fuzzy goals of policy;
2. Assess the potential of single indicators in order to represent these latent
constructs;
3. Relate latent constructs to each other rather than many single indicators,
thereby reducing the model’s complexity;
4. Construct models that represent the linear or non-linear development of single
indicators over time and relate it to the development of other indicators.
Multi-level models, which enable the researcher to model dependencies in space
and time directly10, can be formulated via SEM-models as latent-growth models
(SINGER et al., 2003). The adoption of these more sophisticated techniques and
the restriction of clearly limited research questions will surely help to overcome
many of the existing problems.
4
CONCLUSIONS
The proposed SEM method produced satisfactory results if applied to the test of
a simplified version of an intervention-logic of the measure of AFP. The empirical result stating that the measure exceeds a measurable positive influence only
on the development of income tax payments, and to a much lower degree on the
development of jobs in agriculture, is theoretical acceptable. The interventionlogic’s assumption that AFP would increase a district’s gross value-added in agriculture has been refused for the short-term period. Moreover, the model provides
us with the insight that more jobs in agriculture are connected with more positive
development of GVA in agriculture in a district. This development, on the other
hand, means relinquishing growth of overall GVA. Creating agricultural jobs is
expensive. However, since we do not know whether investment alternatives
really existed, we cannot say whether it is too expensive. With respect to global
questions of rural development, the model’s results hint that agricultural development is of rather minor importance for the overall economic development in
the analysed rural areas. These results have to be treated with caution, however,
since social aspects were not part of the model.
It became clear that one drawback of the approach of testing the political intervention-logic directly, as if it were a scientific theory, is that in order to make it testable, the scientist will have to fill in the blank spaces of non-named parameters
10
For an example of an application that assesses structural change in agriculture, see
MARGARIAN (2007).
246
Anne Margarian
and causal links. The lack of a theoretic foundation then questions the application of SEM. On the other hand, in the process of setting up the model, deficits
in knowledge and in the causal fundaments of interventions become obvious.
SEM has another methodical advantage: It makes obvious all the assumptions of
linear regressions11 hidden in other models. Therefore, SEM could prove very
valuable in combination with other methods.
There are many possible extensions of the proposed approach; one of the most
important is the inclusion of latent variables. The presented model can only be
seen as a first step in the assessment of the potential of SEM for policy-evaluation in the field of rural development. However, it might well be worth continuing
in this direction.
REFERENCES
ARBEITSKREIS VOLKSWIRTSCHAFTLICHE GESAMTRECHNUNGEN DER LÄNDER (2007):
<http://www.vgrdl.de/Arbeitskreis_VGR/VR_ergebnisse.asp>.
BBR (Bundesamt für Bauwesen und Raumordnung) (2000, 2005): Indikatoren und
Karten zur Raumentwicklung (INKAR), Bonn.
BOLLEN, K. A. (1989): Structural equations with latent variables, New York, Wiley.
DAUTZENBERG, K. (2005): Erfolgsfaktoren von landwirtschaftlichen Unternehmen mit
Marktfruchtanbau in Sachsen-Anhalt. Eine empirische Analyse [Success-factors of
crop-farms in Saxony-Anhalt. An empirical analysis], Studies on the Agricultural
and Food Sector in Central and Eastern Europe, Vol. 32, IAMO, Halle (Saale),
<http://www.kirsti-dautzenberg.de/fileadmin/institute/pub/sr_vol32.pdf>.
DOBSON, R., DUNBAR, F., SMITH, C. J., REIBSTEIN, D., LOVELOCK, Ch. (1978):
Structural equations for the analysis of traveler attitude-behavior relationships,
Transportation 7, pp. 351-363.
EUROPEAN COMMISSION (2006): Rural development 2007-2013. Common monitoring
and evaluation framework. Draft fiches for baseline indicators, <http://www.inea.it/
ops/nuovaprog/regolamenti/QuadroComuneMV/riun02-05-06/Doc19.pdf>.
GOLOB, TH. F. (2001): Structural equation modeling for travel behavior research, University of California, Irvine, <http://repositories.cdlib.org/itsirvine/casa/UCI-ITSAS-WP-01-2>.
HILDEBRANDT, L., GÖRZ, N. (1999): Zum Stand der Kausalanalyse mit Strukturgleichungsmodellen. Methodische Trends und Software-Entwicklungen [The latest
developments of causal analysis via structural equation models], SFB 373 Papers, 46,
Humboldt-University Berlin, <http://edoc.hu-berlin.de/docviews/abstract.php?lang=
ger&id=25640>.
11
A thorough discussion, though not explicitly related to SEM, of "hidden assumptions" in
"simple models" is given in KEANE (2006).
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HOMANN, K. (1980): Die Interdependenz von Zielen und Mitteln [The Interdependency of Aims and Measures], Tübingen.
KEANE, M. P. (2006): Structural vs. atheoretic approaches to econometrics. Keynote
address at the duke conference on structural models in labor, aging and health,
September 17-19, 2005.
LOEHLIN, J. C. (2004): Latent variable models. An introduction to factor, path and
structural equation analysis, London.
MARGARIAN, A. (2006): Lack of knowledge and the science-theoretical foundation of
impact-assessment, Unpublished results of a survey among evaluators, Submitted
on request by the author.
MARGARIAN, A. (2006a): How to evaluate a measure without goals, in:
BERGSCHMIDT, A. et al. (eds.): Proceedings of the European Workshop on the
Evaluation of Farm Investment Support and Investment Support for Improvement
of Processing and Marketing of Agricultural Products. Working Papers in Agricultural
Economics
No.
03/2006,
Braunschweig,
FAL,
pp. 33-45,
<http://www.fal.de/nn_797086/SharedDocs/09__BW/EN/Publikationen/Sonstige/d
ownload__workshop__06__2006__en,templateId=raw,property=publicationFile.p
df/download_workshop_06_2006_en.pdf>.
MARGARIAN, A. (2007): Knowledge based control of structural change: Possibilities
and restrictions, in: Proceedings of the MACE-Conference in Berlin, Upcoming
April 2007, <http://www.mace-events.org/greenweek2007/4272-MACE.html>.
SAS (1999): Assessment of Fit, SAS OnlineDoc Version 8, SAS Institute Inc., Cary
<http://v8doc.sas.com/sashtml/stat/chap19/sect34.htm>.
SABATINI, F. (2006): Social capital and economic development, Discussion Paper
No 1.2006, University of Rome La Sapienza, <http://w3.uniroma1.it/spes/
publications.htm>.
SINGER, J. D., WILLETT, J. B. (2003): Applied longitudinal data analysis. Modeling
Change and Event Occurrence, Oxford.
WENDT, H., EFKEN, J., KLEPPER, R., KRAH, V., NÖLLE, J., SCHÄFER, M., TREFFLICH, A.,
UETRECHT, I. (2006): Länderübergreifender Bericht im Rahmen der Gemeinschaftsaufgabe Verbesserung der Agrarstruktur und des Küstenschutzes (GAK), FAL,
Braunschweig, <http://www.fal.de/cln_044/nn_791716/SharedDocs/11__MA/DE
/Publikationen/Evaluation/download__gak__bericht__2006__de.html>.
Sustainable rural development: What is the role of the agri-food sector?
MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central & Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 248-257.
COMPREHENSIVE RURAL DEVELOPMENT IN CHINA:
STRATEGY AND IMPLEMENTATION CHALLENGES
ACHIM FOCK ∗, KARIN FOCK∗∗
ABSTRACT
China’s national rural development strategy is developing rapidly. The current
strategy of a ‘New Socialist Countryside’ complements and balances the traditional focus on agricultural growth, farmers’ income and food security with
broader, non-farm, social and environmental objectives. Broadly speaking, this
development follows that of developed countries, though at a higher speed. The
paper analyses how these policies have evolved as well as the institutional
obstacles that their implementation is facing. Despite the particularities of its
political system China nevertheless encounters many of the problems and institutional challenges many other countries have in implementing a comprehensive
rural development strategy. China and other countries such as in Europe have
much to learn from each other, and more research in this area would be warranted.
Keywords: China, rural development, institutions.
1
INTRODUCTION
Agricultural and rural development policies are evolving worldwide. A general
trend is that the traditional focus on agriculture shifts to more comprehensive
rural development strategies that also addresses broader ‘structural’ and ‘regional’
issues. For instance, the OECD (2006) describes the recent trends in developed
countries as a "new rural paradigm" and emphasises the "focus on places instead
of sectors" as one of its key features.
These trends towards broader rural development policies reflect developments
such as growth of the non-farm sectors and shrinking importance – in relative
terms – of agriculture; pressures to reduce policy protection of the agriculture
sector; increasingly integrated agro-food chains; globalization and rapid developments in information and communication technology, meaning rural areas in,
*
∗∗
The World Bank. Email: [email protected]
Bonsilia Development Consulting. Email: [email protected]
Disclaimer: The findings, interpretations and conclusions expressed in this paper are entirely
those of the authors, and do not represent the views of the World Bank.
Comprehensive rural development in China
249
and between countries are ever ‘closer’; and increasing environmental and social
concerns.
Obviously, the developments pose new challenges and institutions have to adjust
to the changed paradigm. In particular, policies and administrative structures
need to reflect the increasing interdependencies that exist between sectors,
regions, and stakeholders at all levels. First, regions with local particularities
find themselves at diverse stages of economic development and have at times
diverging interests that need to be reconciled. Second, local governments have a
key role in implementing rural development policies and conflicts of interests with
higher levels governments pose challenges. Third, comprehensive approaches
require a strong level of cooperation and partnerships between sectors that is
challenging to achieve in practice. Consequently, policies and mechanisms need
to be put in place to develop political solutions between differing interests of a
multitude of stakeholders.
Like other countries, China has increasingly moved its traditional rural policy
focus on agriculture to a more comprehensive rural development approach. This
is well reflected in the country’s current strategy of building a ‘New Socialist
Countryside’. Not surprisingly, China faces some of the problems just listed.
The main objective of this paper is to analyze the main implementation challenges that China faces in implementing this approach and to show to what extent China’s experiences are relevant to other countries and vice versa.
Chapter 2 describes China’s rural policy development process, sketches the evolution of agricultural and rural policies, and outlines the country’s current rural
development strategy and program. Chapter 3 analyses the main institutional challenges China is facing in implementing its rural development policies. The paper
concludes with lessons China and other countries could learn from each other in
encountering similar challenges of formulating and implementing a comprehensive rural development strategy.
2
RURAL DEVELOPMENT POLICY IN CHINA
2.1 Policy processes
The development of policies in China generally follows a gradual approach,1
often based on local-level pilots. Agricultural and rural policies are no exception. This pragmatic way of policy formulation has been firmly established ever
since Deng Xiaoping put China on a transition to a market economy. The approach proved to be very successful. Most impressive is the degree to which the
1
For a more detailed analysis of the process of policy-making in China see, for example,
SAICH (2004).
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Achim Fock, Karin Fock
goal of rapid economic development, which dominated the policy agenda almost
unchallenged until recently, has been achieved. It also achieved a high level of
political consensus and, arguably, avoided instability. Consequently, this approach is deeply entrenched in China’s policy formulation.
At times ‘gradual approach’ means ‘piecemeal’ rather than ‘comprehensive’.
China’s accomplishments in agricultural and rural development have shown that
– overall – the policy formulation process in China resulted in successful interventions. However, occasionally the gradual policy formulation process results
in a number of uncoordinated efforts which are not always effective, and sometimes not in line with a broader strategy. As policy-making has moved from
‘opening up’ and ‘liberalization’, i.e. dismantling of institutions, to a phase of
rapid institution-building, this has become more evident. Comprehensive institutional policy reforms are more difficult to formulate in a ‘gradual’ approach, and
the necessary political will is harder to build than China’s hierarchical system
would suggest.
China’s gradual approach often builds on local-level pilots, which, if successful,
are scaled-up nationwide. While the Party and government leaders firmly control
the national policy formulation process, testing and piloting is widely used in
China before deciding on and implementing policies in the entire country.
China’s vast territory and huge population allows tests of considerable scale for
various rural policies throughout its numerous county, townships, and villages.
Policy diversity at local levels is fully accepted and sometimes promoted by the
central level. It is also based on the significant power at the local level and a
sense of competition between local governments that try out various reforms.
Many times, locally implemented pilots become so successful that other local
governments decide to replicate them so that policies already build up some
momentum from the bottom before the central government introduces them.
However, more systematic testing and piloting of alternative measures as well as
rigorous monitoring and evaluation systems are not yet widely used for decision
making and it is not always transparent for outsiders how pilots turn into countrywide policies.
Policy makers increasingly use research to inform themselves, but such ‘scientific’ elements of policy making are not yet the rule and generally on an ad hoc
basis. Moreover, although governments at all levels might request scientific input
and order scientific studies to inform their decision making, this frequently turns
out to be a one-way process rather than expert consultation. Similarly, while policy
stakeholders find more and more platforms to voice their concerns, broad and
active stakeholder involvement in policy formulation is still rare.
Frequently, China’s rural development strategy states general policy principles
with more details being developed by subsequent piloting and research in the
early implementation process. The ‘building of the New Socialist Countryside’
Comprehensive rural development in China
251
might serve as an example. It seemed little more than a slogan when first introduced by the central Government. However, the rhetoric showed the emphasis
national leaders put on improving the situation in rural China, and officials at all
levels, but also think tanks, research institutions, and other parts of the society,
refined the concept and filled it with increasingly comprehensive content. Today,
as is shown below, the development of a ‘New Socialist Countryside’ represents
a (still evolving) broad-based rural development strategy for China.
2.2 Policy development
Although China does not have a democratic system, the pragmatic, gradual approach to policy development nevertheless reacts to and follows closely developments on the ground. With agriculture productivity at extremely low levels in
mid-1970s and food security becoming a real threat with ever growing population, agricultural policy reforms were driving China’s overall development at the
beginning of its transition to a market economy. The first big agriculture sector
reform was the introduction of the household responsibility system, which moved
the responsibility for agricultural production away from the commune system to
individual households. After initial local, and often spontaneous ‘piloting’ of
household responsibility this reform was allowed to be rolled out nation wide,
formally endorsed and supported at the national level through the 1982 No. 1
Document by the Central Committee, and further formalized and strengthened in
two more No.1 documents of 1983 and 1984 (DU, 2006). Next, agricultural prices
and markets were liberalized and unified procurement and sale for many products
abolished. Other reforms further moved China to a monetized market economy
with price incentives, such as the decision to start to collect agricultural tax in
cash rather than in kind. After de facto introducing these policies in many areas
they were subsequently reflected in the 1995 No. 1 Document, which focussed
on the liberalization of prices and markets.
As a consequence of these early agricultural policies reforms, agriculture grew at
very high rates in the first half of the 1980s, and even realized higher than average growth rates. With agriculture having been revived, the political focus now
shifted on those who, in Deng’s words, would be allowed to ‘get rich first’, in
particular through industrialization and urbanization. For the following decade,
the strategies for economic development built on manufacturing, including in
rural areas through TVEs (Township and Village Enterprises), and resulted in
strong urban growth.
In the 1990s, issues related to agriculture and rural development were again
climbing to the top of the policy agency. As China had reached the level of a
low-middle income country, the income and wealth gap between rural and urban
areas had been rising to an extent that started to create tensions in the Chinese
society. More and more, rural areas were perceived as ‘left behind’ and suffering
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Achim Fock, Karin Fock
from ‘unjust’ policies, including fees and, more recently, land-takings. Also, was
increasingly recognized that environmental problems were severe, including in
rural areas where agricultural and other sectors were competing over natural
resources, in particular land and water.
Concerns about rising rural-urban inequality and inequity and continued issues
of food security brought agriculture back to the top of the political agenda. At
the beginning of this decade, the Rural Fee Reform was implemented, one of the
most fundamental agriculture sector reforms since the 1980s, quickly followed
by the abolition of agriculture taxes. Subsequently, the importance of rural development was underlined by issuing four more No. 1 documents since 2004 that
increasingly stressed the comprehensiveness of the agriculture and rural issues.
The No.1 Document 2006 building a ‘New Socialist Countryside’ then considerably broadened the rural strategy by including rural infrastructure, education,
health and other services and by emphasizing the need to balance between economic development and the environment.
2.3 Developing a ‘New Socialist Countryside’
China’s national policies for agriculture and rural development over the next
years are guided by the Eleventh Five Year Plan.2 This Plan reflects the call for
‘building of a New Socialist Countryside’, a concept well outlined in the earlier
No. 1 Document for 2006 (CCCPC and STATE COUNCIL, 2005).3
The Document refers to key issues such as the difficulties related to the widening
income gap between rural and urban residents, as well as ‘vulnerable’ rural infrastructure and lagging rural social services; and starts by calling for "coordinat[ion of] urban and rural economic and social development to steadily advance
the construction of a socialist new rural area". The need to strengthen rural infrastructure and rural social services feature as prominently as the "promot[ion of]
modern agriculture development" and income increase for farmers. Finally, the
document also emphasizes important rural reforms such as the rural tax and fee
reform and reform of public finance; and emphasizes governance issues at the
grassroots level as well as the leadership role of the Party.
This national strategy is being implemented through many new programs and
reforms, as well as significant and rapidly rising fiscal transfers for rural
2
3
The proposal of the plan was passed by the 5th Plenary Session of the 16th Central Committee of the Chinese Communist Party and approved by the National People’s Congress in
March 2006.
The more recent No. 1 Document for 2007 has again a stronger focus on agriculture, but it
stands firmly in the overall wider policy context, and should be seen as a means to ‘foster the
development of a New Socialist Countryside’. The Eleventh Five-Year Plan for the period
2006 to 2010 as well as other policy documents and speeches of senior leaders leave no
doubt that China is decisively following a comprehensive approach of rural development.
Comprehensive rural development in China
253
development. The central Government has been rolling out new programs in
almost all sectors of rural development: Support to agriculture, including direct
subsidies for grain producers as well as for improved seeds varieties and breeds
and agricultural mechanisation; numerous investments into rural infrastructure
and for environmental causes; a New Cooperative Medical System for the rural
population; a renewed commitment to free rural compulsory education; a new
rural social security programs, to name a few.
In parallel, numerous administrative reforms aim at improving the effectiveness
and efficiency of the government system. For instance, the central government is
strengthening its efforts to mitigate the vast inequality of fiscal resources across
regions; is shifting responsibilities from the township to county level; and is
promoting reforms in the management of public services provision.
Given the size of China and its policy development approach, it is not surprising
that this strategy and programs as formulated by the central government are not
uniformly reflected and implemented throughout the country. Even though
China is a unitary state, huge variations exist and are reinforced by the fact that
much of the political power lies with the local governments.
3
INSTITUTIONAL CHALLENGES
In its intention to combine economic and social objectives, the national rural development strategy of developing a ‘New Socialist Countryside’ faces a number of
institutional challenges. As discussed above, the strategy reflects social as well
as economic objectives and tries to balance not only rural with urban areas but
also the developments in the various regions.4 In essence, to effectively accomplish the economic and social goals on the agenda, China’s administrative structure, that been so successful in achieving the previously dominating objective of
economic growth, will have to adjust to the broader policy goals. Many changes
have already happened or are ongoing. However, not everything has yet moved
in the right direction. Moreover, the focus on rural areas poses a particular challenge as these are to a considerable extent governed by the lowest tiers of the
administrative system – remote from the central government and its national
goals.
First, the multi-tier ‘nested’ hierarchy of the administrative structure poses the
particular challenge of ensuring minimum implementation standards of national
goals and policies across the country. In general, the central government shows
the general policy direction, but leaves the detailed specification of policies and
4
WEN JIABAO (2004) introduced the concept of the five ‘balances’, those between balancing
urban and rural development, balancing development among regions, balancing economic
and social development, balancing development of man and nature, and balancing domestic
development and opening wider to the outside world.
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Achim Fock, Karin Fock
programs to the provinces; these then interpret policies and programs in the context of their location and often complement them with province-specific regulations. Municipalities and prefectures add another layer so that national ‘guidance’
is ‘filtered’ through several tiers of government before it reaches the level dominant in the implementation of rural policies, i.e. counties and townships. Administrative villages, though formally ‘self-governing bodies, are often seen by rural
citizens as yet another layer of ‘government’.
Local governments’ own objectives are sometimes competing for attention and
resources with objectives formulated at the central level. In particular, the traditional more narrow focus on growth through industrial development is stronger
in municipalities, counties, and townships than at the national level. This objective, its importance for overall well-being notwithstanding, serves also more
parochial local interests of establishing a local tax base, providing more direct
benefits to a politically stronger urban constituency and even directly to local
government employees themselves. Social and environmental problems created
by such approach are not always fully seen and perceived as partly ‘exportable’.
The multi-layered administrative structure is one reason why local governments
can and often do strongly pursue their own interest without harsh repercussions
to not implementing national priorities. Contradictions are generally not made
explicit given the strongly hierarchical government (and personnel) system –
though cases of ‘misunderstanding’ and ‘misintepretations’ of national policies
at the local levels happen – but they are nevertheless strong and pose a major
challenge to fully implementing the ‘New Socialist Countryside’.
Second, huge fiscal inequality across local jurisdiction is a substantial obstacle
for many poorer areas in central and Western China to comply with national
mandates. These inequalities are a result of China’s intergovernmental fiscal
system that leaves major government responsibilities to the lowest tiers of government, including the most resource-intense sectors such as education, health and
other social services. At the same time, own resources at the county and township level are traditionally low, in particularly in poorer areas. Local government
do not have tax-setting nor (legal) borrowing authority. The Rural Fee Reform
and the subsequent abolishing of agricultural taxes have further reduced the
abilities of ‘grassroots’ government to raise funds. The increase in land-related
non-budget resources is limited in poor areas and, given less transparency and
higher-level control, used for local governments’ interests rather than to achieve
national rural development objectives. While the central government is increasingly mandating higher standards for a more balanced rural development strategy,
the additional fiscal resources it provides are insufficient (WORLD BANK, 2007).
Third, policy measures intending to assuage the above fiscal difficulties are
themselves problematic. Given the above mentioned difficulties of achieving
full implementation of national policies at the local level, the central government
Comprehensive rural development in China
255
has increasingly tried to address particular rural issues through specific interventions designed and, at least partly, financed by the central level. For instance,
rural infrastructure or environmental programs such as afforestation are increasingly being financed through national-level programs. The rapid increase in
rural roads or household-level biogas use, for example, would not have been
possible without these programs.
This approach has significant problems: Firstly, it creates inefficiencies due to
violating the ‘subsidiarity’ principle by not sufficiently taking into account local
knowledge on the type of public services most needed; secondly, the approach
strains the administrative structure through the large number of transfers and
programs that have to be implemented. Finally, it binds scarce local budget resources as matching funds required at a minimum for administration and implementation of such programs.
Fourth, another significant challenge for implementing China’s comprehensive
rural development strategy is cross-sectoral as well as cross-regional coordination and cooperation. To achieve the multi-objective development goals, coordination and cooperation across sectors is needed at all stages from planning over
implementing to monitoring and evaluation. China does not have a comprehensive rural development or decentralization department to perform this function.
Coordination often happens only at the highest level and through the Party and
is inadequate at the working level.
Similarly, China lacks the mechanism for effective coordination and cooperation
across jurisdictions at the same level of government. Institutions such as associations of county governments do not exist. Partnerships between counties to solve
regional issues are extremely hard to forge horizontally. The traditional hierarchical structure with upward reporting as well as the ‘mode of competition’
between localities fostered in the environment of growth as dominant objective
are clear obstacles to horizontal partnerships. However, given significant spillover effects in an increasingly integrated rural society and economy, horizontal
cooperation is important.
Fifth, a final challenge to implementing the ‘New Socialist Countryside’ strategy
is the enforcement mechanisms. The administrative system relies strongly on
the personal responsibility system rather than institutional responsibility to deliver defined outputs. Moreover, too many personal incentives of government
employees are skewed. Most importantly, the generation of fees by public service
units is generally converted into financial remunerations for their employees.
Even without these limitations, enforcement mechanisms that rely almost exclusively a personal responsibility system, loose their effectiveness when objectives
are becoming more multi-dimensional. The greater complexity requires, in addition, rigorous monitoring and evaluation systems and an incentive system for
agencies.
Achim Fock, Karin Fock
256
4
CONCLUSIONS
Many analysts stress that China is unique and hard to compare with other countries. China itself also stresses its ‘Chinese characteristics’. And indeed, the political structure and state system, vastness of the territory, size of its population,
and the speed of China’s reforms and developments make China very special.
Similarly, rural development in China and its challenges are unique, if one takes
into the account its size – China accounts for almost 24 percent of the world’s
rural population – the enormous inequalities and inequities, and the speed with
which agriculture and rural areas are transformed.
Nevertheless, China’s rural development strategy and, in particular, the institutional challenges implementing it have many more parallels with those of other
countries than many might expect. Rural policies tend to happen at a higher
speed than in most other countries – partly reflecting the country’s fast socioeconomic developments – but are nevertheless responding to many issues which
are far from being unique to only China. In particular, in its evolving national
rural policy strategy China has rapidly recognized the strong linkages between
the rural and wider economy; the increasing global integration, on the one hand,
and need for local solutions, on the other; and the need to balance environmental
and social development objectives with economic ones.
Countries in which agriculture performance and living conditions in rural areas
have fallen back widely behind urban areas can learn from China’s rural development success that, first, a strong market oriented approach that builds on
liberalizing markets, user rights for land, and relatively low subsidies is successful. It needs, however, to be complemented with adequate social and other
policies. Second, investments in institution building and rural infrastructure and
services should not to be pushed back too far to avoid too large gaps in income
and living standards between rural and urban areas to develop. Third, a strongly
decentralized government structure offering leeway to lower levels of Government
to experiment and implement central policies is advantageous in identifying
good policies and taking into account diverse local circumstances.
Similarly, in its challenges in implementing its rural development strategy,
China can also look to other countries. First, China can strengthen the ‘scientific’ elements of the policy formation process by e.g. more systematic piloting,
much more rigorous and independent M&E, and an even more systemic link between research and policy-making at all levels of government. Second, with a
view to better balance diverse interests between central and local levels of governments, regions, and sectors, China can learn from others to stronger ‘institutionalize’ participation and coordination of various stakeholders. Third, China could
look into more sophisticated systems to hold levels of governments and government agencies accountable, through e.g. financial incentives or changes in
Comprehensive rural development in China
257
authority or autonomy given to them, supported by more sophisticated monitoring and evaluation systems.
The institutional challenges to implement a broader rural development strategy –
essentially stemming from the need to balance various local and sectoral interests – have parallels in China and many other countries.
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Report, Lessons Learned from the Dragon (China) and the Elephant (India),
December 2005, pp. 5-15.
CCCPC AND STATE COUNCIL (2005): Notes of the Central Committee of the Communist Party of China and the State Council on advancing the construction of a socialist
new rural area, No. 1 Document, December 31, 2005.
CCCPC AND STATE COUNCIL (2007): Suggestions of the Central Committee of the
Communist Party of China and the State Council on developing modern agriculture actively to foster the development of a new socialist countryside in a down-toEarth Manner, No. 1 Document of 2007.
DU, R. (2006): The course of China’s rural reform, IFPRI, Washington, D.C.
OECD (2006) The new rural paradigm: Policies and governance, OECD Rural Policy
Reviews, Paris, 2006.
SAICH, T. (2004): Goverance and politics of China, 2nd ed., Revised and updated,
Palgrave Macmillan, New York.
WEN JIABAO (2004): Report on the work of the government, Delivered at the Second
Session of the Tenth National People’s Congress, March 5, 2004.
WORLD BANK (2007) China – Rural public finance, The World Bank, Washington,
D.C., unpublished.
WORLD BANK (2007) China – Public services for building the new socialist countryside, The World Bank, Washington, D.C., unpublished draft report.
Sustainable rural development: What is the role of the agri-food sector?
MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central & Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 258-273.
WHO IS BENEFITING FROM RURAL DEVELOPMENT POLICIES?
ANDREA PUFAHL∗, REGINA GRAJEWSKI, BARBARA FÄHRMANN
ABSTRACT
Beneficiaries of rural development policies in the German states SchleswigHolstein, Lower Saxony, North Rhine-Westphalia and Hesse are analysed.
Beneficiaries are identified by means of the formal incidence analysis. This
includes a breakdown of public expenditures with respect to the type of supported
activities, regions, socio-economic groups and economic sectors. The descriptive
analysis is complemented by an econometric analysis of determinants of regional fund distribution. The results show that the distribution of funds is largely
determined by the type of supported activities, which direct funds to regions
with corresponding agricultural structures and environmental and socio-economic
conditions. Beneficiaries of rural policies reviewed extend from mainly farms or
farm-related institutions in North Rhine-Westphalia to mainly non-farm related
institutions in Schleswig-Holstein.
Keywords: Rural development policy, regional incidence, evaluation, Germany.
1
INTRODUCTION
The paper presents results from the evaluation of rural development policies of
the German states Lower Saxony (LS), Hesse (HE), North Rhine Westphalia
(NRW) and Schleswig-Holstein (SH) in Germany. Rural development policies
pursue multiple objectives, for example, related to agri-environmental issues, to
the agricultural structure and to the wider rural economy, by supporting a broad
spectrum of farm and non-farm related activities. Within the period of interest,
2000 to 2004, public rural development expenditures of the four states under
consideration were about 1.6 Billion Euros. Evaluation activities, launched by
the European Commission, aim to clarify whether implemented policies are appropriate means to achieve intended targets.
The legal framework for rural development programmes (RDP) is provided by
the Rural Development Regulation of the European Commission (EC)
No. 1257/1999. In Germany the federal states are in charge of implementing
∗
Federal Agricultural Research Centre (FAL), Institute of Rural Studies, Braunschweig,
Germany. Email: [email protected]
Who is benefiting from rural development policies?
259
RDPs according to their specific needs. Although Schleswig-Holstein, Lower
Saxony, North Rhine-Westphalia and Hesse are all situated in the northwestern
part of Germany, the situation of rural areas differs regarding their agricultural
structure and their environmental and socio-economic conditions. Implemented
programmes provide a wide variety of approaches and strategies to rural development.
The evaluation of rural development policies necessarily includes an analysis of
beneficiaries. Central questions in this respect are: 1) Who has been supported?
2) Where are the supported projects situated and 3) What kind of activities have
been supported? These questions are answered by employing the concept of the
incidence analysis. The analysis comprises all measures implemented according
to the Rural Development Regulation. The analysis clarifies the strategy of the
RDP implemented; who is seen as a major actor, and which topics are of major
concern in rural development.
2
CONCEPTS, METHODS AND DATA
2.1 Incidence analysis
The concept of incidence analysis originates from the field of public finance and
was adopted by regional and development1 economists to analyse the distribution
of public expenditures across regions or other entities (ECKEY, 1995, p. 269).
Although there are several levels of incidence, for the purpose of this study it is
sufficient to distinguish between formal and effective incidence. The formal incidence reflects how public expenditures are distributed across regions or other
entities, whereas the effective incidence measures the achieved effects, after adjustments processes have taken place. The presented analysis covers the formal
incidence of rural development expenditures.
The formal incidence of rural development expenditures is analysed with respect
to the type of supported activities (axes), regions, socio-economic groups and
economic sectors. Table 1 illustrates the assignment of supported activities to
each category. The classification by axis considers the thematic direction of
measures. Axis-A-measures aim at the improvement of the productive structure
of agriculture and forestry. They include, for example, the farm investment aid
scheme. Axis B covers activities focussing on the development of non-farming
activities or infrastructure in rural areas. A flagship measure is the village renewal
programme. Support compiled under Axis C aims at the improvement and maintenance of the agri-environment. Most prominent measures are agri-environment
programmes and the less favoured areas scheme.
1
The method is known as Benefit Incidence Analysis (BIA) in the field or development
economics (WORLD BANK, 2006).
Andrea Pufahl, Regina Grajewski, Barbara Fährmann
260
Table 1:
Classification of supported activities with respect to supported
activities (axes), socio-economic groups and economic sectors
Supported core activities*
Farm investment aid
Vocational training
Less favoured areas schemes
Agri-environmental schemes
Investment support for processing
and marketing facilities
First afforestation of farmland
Other forestry measures
Land consolidation
Village renewal
Agricultural infrastructure
Tourism
Nature conservation
Coastal protection, flood prevention
Notes:
Axes
A B C
■
■
■
■
Socio-economic groups
Farm households Other**
■
■
■
■
■
■
■
■
■
■
■
■
■
■
■
Economic sectors
Agriculture Other**
■
■
■
■
■
■
■
■
■
■
■
■
■1)
■
■
■2)
■
■
■
*
Supported activities vary among states.
'Other' groups/sectors may also include farm households/agricultural sector.
1) Lower Saxony. 2) Schleswig-Holstein.
Source: Authors’ illustration.
**
Administrative regions are not included in Table 1 because rural development
activities are supported in all 142 administrative regions ("Landkreis") of the
states of interest. The considered socio-economic groups of beneficiaries include
farm households and non-farm institutions (entitled as ‘other’), as well as the
agricultural sector and non-agricultural sectors (entitled as ‘other’). While supported activities to the benefit of ‘other’ entities/sectors may also be available
for farm related institutions, measures assigned to ‘farm households’ or to the
sector ‘agriculture’ are exclusively available to them.
2.2 Data
Table 2 gives an overview of analysed data and their sources. The analysis is
based upon aggregated expenditure data for the period 2000 to 2004. Variables
explaining the formal incidence of expenditures mainly represent the year 1999
and are drawn from various sources.
Who is benefiting from rural development policies?
Table 2:
261
Descriptive statistics and data sources
Variable
Expenditures A
Expenditures A
Expenditures B
Expenditures C
Variable Description
Unit
N
Public expenditures
Public expenditures, Axis A
Public expenditures, Axis B
Public expenditures, Axis C
Billion Euro
Billion Euro
Billion Euro
Billion Euro
142
142
142
142
31.22
2.86
7.28
5.39
33.62
4.16
11.92
7.20
2000-2004
2000-2004
2000-2004
2000-2004
1)
Euro/ha
%
Index
Euro/ha
Livestock/ha
%
%
%
Livestock/ha
Euro/LU
142
142
142
110
142
142
141
142
142
142
109.80
22.28
47.58
260.86
0.99
2.26
-3.16
59.92
0.04
6,318.63
376.79
15.03
12.09
109.17
0.58
6.87
3.01
39.88
0.10
20,167.98
2000-2004
2000
1999
1999
1999
1999
1995-1999
1999
1999
1999
1)
LU
142
2.41
1.73
1999
7)
Euro/capita
%
Euro/capita
Euro/capita
Euro/annum
n
142
142
142
142
136
142
142
43.80
11.00
319.41
28.41
2,822.29
749.16
19.87
72.99
2.67
351.01
37.67
353.86
1246.50
24.15
2000-2004
1999
1999
1999
1999
1999
1999
1)
Model Axis A: Agricultural production structure
Expenditures A
Public expenditures, Axis A
Share forest
Share of forested land
Soil index
Soil index (1=worst, 100=best)
Land rent
Land rent
Livestock density
Livestock density
Share horticulture farms Share of horticulture farms
Delta farms
Change of farm numbers
Share full-time farms
Share of full-time farms
Dairy cow density
Dairy cow density
GVA/LU
Gross value added per agricultural
labour units (LU)
Labour units
Number of agricultural LU
Mean
Standard
Deviation
Year
1)
1)
1)
2)
3)
4)
5)
6)
6)
7)
6)
7)
Model Axis B: Rural development
Expenditures B
Public expenditures, Axis B
Unemploy
Unemployment quota
Debt/capita
Debt of municipalities per capita
GDP/capita
Gross value added per capita
Wage
Gross wage of industrial worker
Migration
Net migration
Rural
Share of inhabitants in rural
communities
Popdensity
Population density
Objective5b
Objective-5b region
Person/qkm
1=yes, 0=no
142
141
676.98
0.23
783.41
0.42
1999
1999
7)
Model Axis C: Agri-environment
Expenditures C
Public expenditures, Axis C
Share forest
Share of forested land
Share grassland
Share of grassland
Delta grassland
Change share of grassland
Soil index
Soil index (1=worse, 100=best)
Share part-time farms
Share of part-time farms
N-surplus
Nitrogene surplus
Share Natura 2000
Share of Natura 2000 area
Euro/ha
%
%
%
Index
%
kg/ha
%
142
142
141
141
142
142
101
142
238.94
22.28
33.87
-0.38
47.58
51.90
100.67
5.85
715.99
15.03
22.33
2.25
12.09
19.30
32.05
7.20
2000-2004
2000
1999
1995-1999
1999
1999
1999
2003
1)
Regional dummy variables
SH
Schleswig-Holstein
LS
Lower Saxony
NRW
North Rhine-Westphalia
HE
Hesse
1=yes, 0=no
1=yes, 0=no
1=yes, 0=no
1=yes, 0=no
142
142
142
142
0.11
0.33
0.38
0.18
0.31
0.47
0.49
0.39
%
8)
7)
7)
7)
7)
9)
10)
2)
11)
11)
3)
7)
12)
13)
Abbreviations: Ha = Hektar of utilised agricultural area, LU = Labour units
Sources: 1) ZAHLSTELLEN (2006), 2) BBR (2005), 3) DOLL (1999), 4) LAND-DATA GmbH
(2000), 5) DESTATIS (div. Jgg.c), 6) DESTATIS (div. Jgg.a), 7) SÄBL (2004), 8) BA
(2005), 9) BBR (2003), 10) FÄHRMANN et al. (2003), 11) DESTATIS (div. Jgg.b),
12)
LANGE et al. (2006) 13) BfN (2006), BKG (2005).
262
Andrea Pufahl, Regina Grajewski, Barbara Fährmann
2.3 Regression analysis
Determinants of the regional distribution of expenditures are analyzed by using
multivariate linear regression models, written as
yt +1 = α + β1 x1t + β 2 x2 t + ... + β K x Kt + ut
where yt +1 denotes the natural log of public expenditures (multiplied by 1,000)
by axis at time t+1, α denotes the constant, β K denotes the estimated coefficients for K explanatory variables measured at time t. Regression analyses are
conducted by using linear and robust linear regression procedures provided by
SAS/STAT 9.1. The ordinary linear regression procedure uses the least-square
estimator, which minimizes the sum of the squares of the residuals:
n
⎛r ⎞
Q (θ ) = ∑ p⎜ i ⎟
⎝σ ⎠
i =1
where r = y − Xθ . Outliers were present in all three estimated models. Outliers in
the linear regression model are identified by studentized residual below (above)
–2 (2). The model is refitted after the exclusion of outliers.
Another approach to detect outliers and to provide stable estimates in the presence
of outliers is robust linear regression. The implement robust regression procedure uses an M algorithm, introduced by HUBER (1973). Instead of minimizing
the sum of squares of the residuals, a Huber-Type M estimator minimizes the
sum of less rapidly increasing functions of residuals:
n
⎡ ⎛r
Q (θ , σ ) = ∑ ⎢ p⎜ i
i =1 ⎣ ⎝ σ
3
⎤
⎞
⎟ + a ⎥σ , a > 0 (SAS INSTITUTE INC., 2004).
⎠
⎦
EMPIRICAL RESULTS
The formal incidence of rural development expenditures is examined with respect
to the type of supported activities (axes), administrative regions, socio-economic
groups and economic sectors. Determinants of the distribution funds by axes A,
B and are estimated in three separate models, one for each axis.
3.1 Regional distribution of expenditures
Map 1 illustrates the distribution of expenditures across regions in SchleswigHolstein, Lower Saxony, North Rhine-Westphalia and Hesse. Expenditures are
displayed for the entire programme and by axis. The light to dark grey shadowing
indicates the type of region, whereby only the dark grey regions are rural regions
as classified by the criteria of BBR (2003). About 13 % of the 142 regions are
classified as rural regions, whereas the majority are classified as urban or
Who is benefiting from rural development policies?
263
agglomerated areas. Nevertheless, Map 1 evidently illustrates that the amount of
funds per region rises with an increasing notion of rurality.
The distribution of expenditures is determined by different, intervening factors.
Total fund distribution per region is in the first place determined by its size and
by the economic capacity of the state. Within the period of interest, 2000 to
2004, Lower Saxony spent 2.029 Million Euro public funds for rural development policies, followed by North Rhine-Westphalia (1.047 Mio. Euro) Hesse
(703 Mio. Euro) and Schleswig-Holstein (653 Mio. Euro). These volumes reflect
the prosperity of a state, as measured by the gross domestic product, which is
e. g., higher in North Rhine-Westphalia than in Schleswig-Holstein. As known
from the evaluation of RDPs in the states of concern, the volume of RDP funds is
also influenced by the political importance placed on that policy field (FAL et al.,
2006). In that sense, Lower Saxony allocates more public funds to RDP than
Hesse does, reflecting a higher importance of agricultural issues on the political
agenda.
The distribution of funds by axes is determined by the existing agricultural, rural
and environmental structure of the region, which leads to a differentiated demand
for measures of Axes A, B and C. Axis A is dominated by the farm investment
programme, which has the highest acceptance in regions with intensive livestock
production, as for instance in the western part of Lower Saxony and in the lower
Rhine area (west of NRW). Most Axis A funds need to be co-financed by
private capital, which is more likely to be available in prosperous agricultural
regions.
Axis-B-measures comprise a wide variety of rural infrastructure, tourism and
village renewal measures. They dominate rural development expenditures in most
regions of Schleswig-Holstein, Hesse and Lower Saxony. Hesse, SchleswigHolstein and Lower Saxony have a long tradition in implementing rural development policies. The RDPs are pointedly used as a tool to promote rural development. Some of the measures are, however, closely linked to the agricultural
sector. For example Axis B in Lower Saxony also includes support for the construction of agricultural infrastructure (22 % of the total budget), which is
mainly to the benefit of farmers.
Andrea Pufahl, Regina Grajewski, Barbara Fährmann
264
Map 1:
Public expenditures of rural development programmes by axis
in Schleswig-Holstein, Lower Saxony, North Rhine-Westphalia
and Hesse (2000-2004)
Schleswig-Holstein
Share of axis
Production structure
Rural development
Agri-environment
Objective-2, Objective-5b (phasing out)
Public expenditures
in Euro
103,876,747
30,000,000
5,000,000
Lower Saxony
Typology of regions
North Rhine-Westphalia
Agglomorated areas
Urbanised areas
Rural areas
Hesse
Source: Data of the Paying Agencies of the respective counties, budget years
2000, 2001, 2002, 2003, 2004.
Federal Agricultural Research Centre
Up-date of the mid-term evaluation
acc. EC No. 1257/1999
Source: Data of the Paying Agencies of the respective counties, budget years 2000, 2001,
2002, 2003, 2004.
Who is benefiting from rural development policies?
265
Expenditures for environment-related programmes in Axis C are dominant in
regions with less favourable conditions for agricultural production. Less favoured
area payments are only available in designated areas with a low soil index. Agrienvironment payments are in principle available on the entire farmland but have
the highest acceptance in regions in which the intensity of the agricultural land
use is below the state average. A minority of agri-environmental measures, aiming
at habitat protection, water protection (LS) and the prevention of erosion (NRW),
are targeted to defined areas. Regions with a high share of Axis-C-measures are
mountainous areas in Hesse and in North Rhine-Westphalia. The request for
Axis-C-funds is lowest in intensively used agricultural areas. Environmentrelated programmes are almost exclusively financed by means of public funds.
3.2 Formal incidence by socio-economic groups and sectors
Figure 2 displays the share of public rural development expenditures differentiated by socio-economic groups and economic sectors. Socio-economic groups
include the farming population represented by farm households, while the nonfarming population represents the ‘other’ public or private institutions like rural
communities or non-farming households (EU-KOM, 2000).
The share of rural development expenditures allocated to farms, or farm households respectively, is about 75 % (82 %) in Hesse (NRW) and about 28 % in
Lower Saxony and Schleswig-Holstein. Agri-environmental schemes, the less
favoured area scheme, the farm investment scheme and forestry measures (only
NRW) account for the largest share of the rural development budget in Hesse
and North-Rhine Westphalia. Rural development expenses in Schleswig-Holstein
and Lower Saxony are dominated by expenditures for village renewal activities
and for the improvement of the agricultural infrastructure.
Economic sectors are distinguished into the ‘agricultural sector’ and ‘other’
sectors’. Around half of the rural development expenditures in Lower Saxony
and about two thirds of the total budget of North Rhine-Westphalia and Hesse
are explicitly targeted to the agricultural sector. Dominant measures are the farm
investment aid scheme, agri-environmental programmes, the less favoured area
scheme (NRW, HE) and the forestry schemes (LS, NRW). Schleswig-Holstein
spends only 38 % of total expenditures on the primary sector. Expenses for
coastal protection are excluded in Schleswig-Holstein and Lower Saxony as they
are not primary rural task to be financed from the rural development budget.
Andrea Pufahl, Regina Grajewski, Barbara Fährmann
266
Figure 2:
Share of rural development expenditures by socio-economic
groups of beneficiaries and by economic sectors
Farm households
100 %
North RhineWestphalia
Agricultural
orientation
Hesse
Other sectors
Agricultural sector
100 %
0%
Lower Saxony
Schleswig-Holstein
Territorial
orientation
0%
Other beneficiaries
Source: Authors’ illustration.
Combining the incidence of expenditures by socio-economic groups and by economic sectors, rural development policies can be characterised by having a more
agricultural (HE, NRW) or territorial orientation (LS, SH). This supports findings of BALDOCK et al. (2001), who underpin the broad variety of approaches
to rural development in Europe. However, it should be noted that the importance
of environmental objectives within rural policies in North Rhine-Westphalia and
Hesse are not acknowledged adequately by this classification.
4
DETERMINANTS OF THE REGIONAL DISTRIBUTION OF
EXPENDITURES BY AXIS
The following analysis complements the descriptive illustration of determinants
of the regional distribution of rural development expenditures. Linear and robust
linear models are estimated for each axis separately. To account for the varying
size of the region, the regressor variable, funds by axis, are set into relation to
the size of the target entity. Funds for Axis A and C are referenced to the amount
of hectares of farmland as they are both related to the agricultural land use.
Funds of Axis-B-measures are set into relation to the population size, as they are
meant to benefit the socio-economic situation of rural areas (see also Table 2).
Model estimates are displayed in Table 3. The comparison of estimated linear
and robust linear models reveals that the direction and magnitude of estimates is
Who is benefiting from rural development policies?
267
very similar. The model interpretation is based upon robust estimates, as they
are more reliable in the presence of outliers then.
Model Axis A estimates the determinants of the regional distribution of Axis-Aexpenditures per hectare farmland. Axis-A-measures are directed to the improvement of the agricultural and forestry production structure. Thus, the regional
distribution of expenses can be explained by characteristics of the existing agricultural/forestry structure. The robust model is statistically significant at the
1 % level or better, as measured by the F value. The model, as measured by the
R square, explains about half of the total variance. The share of unexplained
variance points out that important determinants are missing. They are likely to
be found at individual farm or enterprise level and in indicators describing the
dynamics of socio-economic developments.
Regions with a high share of forest receive significantly more funds per hectare
than regions with a low share of forest. The management of forest in areas with
a high percentage of forested areas constitutes an important part of the traditional land use. Forests have been and still are an important source of household
income. As the traditional role of forest management is deeply rooted in these
regions, the human capital for forest management is more readily available than
in regions with a minor percentage of forested area. Hence, the amount of acquired funds for forest investments reflects the importance and the intensity of
forest management in a region.
The lower the soil quality, indicated by the soil index, the higher the amount of
expenditures per hectare allocated to a region. The rationale underlying this relationship is that supported farm investments are predominantly investments into
livestock farms and into forests. Livestock farms are usually situated in regions
with a medium to low soil quality, while arable farms mostly manage soils with
highest indices. The livestock density reflects the regional specialisation to livestock keeping and is a determinant for the distribution of funds at the significance level of 5 %.
The share of full-time farms has a significant positive influence on the amount
of public expenditures allocated to a region. This relation is plausible as fulltime farms account for the largest share of total farm investments and farm
operators need to constantly improve the productive base of their major source
income. A high density of dairy cows per hectare significantly increases the
amount of public expenses. This reflects the fact that the support of dairy farms
has been an emphasis of the farm investment aid scheme. Further, the pace of
the structural change significantly determines the distribution of funds. Decreasing
farm numbers in the previous period, 1995 to 1999, seem to stimulate investments and hence, raise the demand for public investment aids. The effect is significant at the 1 % level.
268
Andrea Pufahl, Regina Grajewski, Barbara Fährmann
The share of horticulture farms is a significant determinant for the distribution of
public expenditures. Horticulture farms, as defined here, also include farms cultivating permanent crops such as wine. Farm investment support directed to horticulture farms is of high importance in Hesse and North Rhine-Westphalia, but
not in Lower Saxony and Schleswig-Holstein. This regional separation may
provide an explanation for the low significance of the estimate.
The gross value added per agricultural labour (GVA/LU) unit and the number of
agricultural labour units do not provide significant determinants for the distribution of Axis-A-funds. The parameter estimates of the regional dummies indicate
that, under similar agricultural structures, the allocation of a region in Lower
Saxony significantly increases the amount of funds spent for RDP.
Axis-B-measures comprise activities directed to the socio-economic development of rural areas. Thus, the macro-economic indicators are most relevant explaining the distribution of funds as estimated in Model Axis B. The robust
model is statistically significant at the 1 % level or better. The model explains
about 67 % of the total variance.
The most important determinant of the distribution of Axis-B-funds per capita is
the population density of a region. A low population density coincides with the
notion of rurality and confirms that rural development funds are predominantly
spent in rural areas. This fact is further supported by the significant influence of
the covariate ‘rural’, which represents the share of inhabitants in communities
with a population density below 150 persons/sq. km. The significant negative
influence of the state dummies of North Rhine-Westphalia and Hesse indicates
that significantly fewer funds per capita are spent there than in Lower Saxony
and Schleswig-Holstein.
No other factors are found to have a significant influence on the distribution of
Axis-B-funds per capita. The rate of unemployment has a negative, but insignificant influence. Unemployment rates tend to be lower in rural areas of North
Rhine-Westphalia and western Lower Saxony than in urban areas. This relationship is reversed for most parts of Hesse and Schleswig-Holstein. It was expected
that former ‘Objective-5b’ regions would benefit more from Axis-B-funds than
other regions as authorities implementing rural policies are already trained in the
acquisition of funds. The factor ‘Objective-5b’ is positive but insignificant.
Debts of communities per capita were thought to have a negative influence on
the amount of Axis-B-funds allocated to a region. Communities, especially in
Lower Saxony, are required to co-finance EU-expenditures for certain Axis-Bmeasures. If the financial situation of communities is very tense, their ability to
finance rural development activities, which are beyond their legal duty, decreases. However, presented results do not support this hypothesis, as the debt
per capita is a positive and insignificant determinant.
Who is benefiting from rural development policies?
Table 3:
Parameter estimates by axes, explaining the distribution of
rural development funds (2000-2004) across regions
Linear regression
Variable
Estimate
Model Axis A: Production structure
Intercept
Share forest
Soil index
Land rent
Livestock density
Share horticulture farms
Delta farms
Share full-time farms
Dairy cow density
GVA/LU
Labour units
LS
NRW
HE
Robust linear regression
Estimate
t-value
1072.86
12.63
-14.45
0.29
303.56
17.26
-147.02
21.71
3767.47
-0.01
27.65
1300.43
1016.12
1354.07
2.06
2.79
-2.48
0.53
2.44
2.16
-3.69
4.11
3.81
-0.76
0.64
6.93
5.23
5.28
**
***
**
Model Axis B: Rural development
Intercept
Unemploy
Debt/capita
GDP/capita
Wage
Migration
Rural
Popdensity
Objective5b
LS
NRW
HE
6048.45
-32.66
276.30
10.40
-0.69
-0.07
6.45
-2.41
256.31
118.46
-1542.36
-1315.31
6.76
-1.04
1.50
1.95
-2.81
-0.98
1.57
-8.39
1.47
0.60
-7.45
-5.72
***
Model Axis C: Agri-environment
Intercept
Share forest
Share grassland
Delta grassland
Soil index
Share part-time farms
N-surplus
Share Natura 2000
LS
NRW
HE
3009.04
18.52
13.46
30.00
-0.81
21.50
-3.45
9.71
-726.65
428.04
44.87
6.65
5.17
5.82
0.76
-0.16
5.21
-2.07
2.05
-5.49
2.93
0.24
Fit statistics
1)
2)
269
No. Observation
Model Axis A
101
Model Axis B
Model Axis C
96
95
1)
2)
**
**
***
***
***
***
***
***
*
***
***
***
***
***
***
***
***
**
**
***
***
Chi-square
957.82
12.83
-14.13
0.30
286.01
16.14
-143.93
23.06
3717.52
-0.01
43.40
1321.41
1002.90
1378.01
3.02
6.66
4.71
0.25
4.29
3.21
10.53
15.94
11.54
0.73
0.87
38.67
20.92
22.61
*
***
**
4955.46
-25.39
226.18
-1.01
-0.29
-0.04
10.20
-2.27
352.69
70.78
-1657.13
-1234.34
23.55
0.51
1.32
0.27
1.00
0.36
4.01
140.99
2.17
0.08
44.57
20.93
***
2227.14
23.01
16.42
-0.24
7.64
23.49
-2.37
10.32
-776.10
363.20
-54.42
24.65
37.85
53.58
0.00
2.39
29.53
1.88
4.20
31.84
5.48
0.07
R square (adj. R) No. Observations
1)
(0.58)
105
0.47
0.89
0.91
(0.87)
(0.90)
124
101
0.67
0.69
Administrative regions with zero costs are excluded from the analysis.
Notes: Asteriks denote statistical significance at 1 % (***), 5 % (**), or 10 % (*) level.
For variable description see Table 2
***
***
***
**
***
***
***
***
***
***
***
**
***
**
R square
0.64
The number of observations used in model estimation varies due to missing values and the exclusion of outliers.
**
*
***
***
***
270
Andrea Pufahl, Regina Grajewski, Barbara Fährmann
The improvement of rural incomes and the maintenance of the rural population
is a central concern of European rural development policy (EU-KOM, 2000). It
is worthy to be noted, that the ‘GDP/capita’ does not significantly differ among
rural and non-rural regions, but wages of industrial workers in rural areas are
significantly lower than in agglomerated areas. Nevertheless, neither ‘GDP/capita’
nor ‘wage’ have an influence on the distribution of Axis-B-funds per capita.
Only slightly, but insignificantly more funds are allocated to regions with outmigration.
The financially most important schemes financed under Axis C are agri-environmental measures and the less favoured area schemes (HE, NRW). Agri-environmental measures promote the adoption of environmentally friendly production
systems, while the less favoured area scheme compensates low incomes due to
natural disadvantages in order to ensure the maintenance of agricultural land
use. Important determinants for the distribution of Axis-C-funds per hectare
farmland are therefore related to the land use structure and the environmental
situation. The robust model explains about 68 % of the total variance and is statistically significant at the 1 % level or better.
Agri-environmental programmes mainly comprise grassland-based schemes,
such as, for example, the low input grassland management. The less favoured
area scheme in North Rhine-Westphalia almost exclusively applies to grassland.
Thus, the share of grassland has a significantly positive influence on the amount
of Axis-C-funds per hectare farmland allocated to a region.
A high share of part-time farms significantly increases the amount of funds allocated to a region. Present target regions of Axis-C-measures are mainly those
with unfavourable conditions for agricultural production. Although this is not
indicated by the soil index, it can be explained by the high share of mountainous
regions present in Hesse and North-Rhine Westphalia. Under given agricultural
structures, the required labour input was not adequately paid off and farm operators or their successors had to extend off-farm work, leading to a high share of
part-time farms. Another argument is that part-time farms are more likely to join
environment-related farm programmes than full-time farms as their production
intensity is already relatively low. In this way, part-time farms can further reduce
farm labour input, while ensuring a stable income.
Factors reflecting the quality of environmental conditions are the nitrogen surplus, as measured by a soil surface balance, and the share of Natura 2000 areas.
Regions exposed to high nitrogen balances do not receive more, but insignificantly less Axis-C-funds than regions with low nitrogen balances. This finding
confirms the fact that most Axis-C-measures are targeted to regions with a low
intensity of agricultural land use. This touches upon the issues ofwhether
incentives or legal instruments should be used to reduce or prohibit environmental damage stemming from agriculture. Under present conditions, incentive
Who is benefiting from rural development policies?
271
instruments such as agri-environmental programmes do not succeed in approaching regions with high nitrogen emissions. The share of Natura 2000 areas
on the total farmland has a significantly positive influence on the amount of distributed funds. In Germany, the federal states are legally obliged to ensure the
maintenance of a favourable conservation status of Natura 2000 areas. One important instrument in this respect are compensatory payments for farms managing land in Natura 2000 areas. There is also a tendency to target an increasing
amount of agri-environmental measures to Natura 2000 areas.
5
DISCUSSION AND CONCLUSION
To our knowledge, the presented analysis is the first to explore the formal incidence and its determinants of rural development expenditures on a regional
level. The presented analysis demonstrates that the formal incidence of expenditures is predominantly determined by the emphasis of supported activities and
the different agricultural, natural and socio-economic conditions present in a
region. The econometric analysis showed that important determinants of regional fund distribution can be identified. Taking these findings into account, a
better targeting of rural development policies could be achieved. This requires
that objectives be defined and followed by the authorities in charge. Targeting is
usually achieved by the definition of eligible regions and appropriate eligibility
criteria. A good example are Axis-B-measures in Hesse, which are targeted to
the most rural regions (see Map 1).
The analysis shows that the evaluation of rural development policies necessarily
has to precede a formal incidence analysis. A holistic image of the effects of rural
policies is only provided if the performance of programmes is made transparent.
Whether an agricultural, territorial or environmental orientation of rural development policies is appropriate needs to be judged against the background of the
present agricultural, environmental and socio-economic conditions. North-Rhine
Westphalia puts little emphasis on the development of the wider rural area, as
their socio-economic lagging regions are not rural but urban. Instead, the focus
on the preservation of landscapes and the environment is reasonable in densely
populated states as NRW.
Although reviewed rural policies of the states under consideration are very different, there are some common trends. The persisting agricultural orientation of
the rural development policies seems to be determined by ‘path-dependence’
rather than by a strategy adopted for rural development. None of the implemented agri-environmental measures succeeds in raising acceptance in regions
with severe environmental problems caused by a highly intensive agriculture.
Axis B rural development activities focus on the improvement of the rural infrastructure, while activities that directly support economic development and job
creation are rarely to be found.
272
Andrea Pufahl, Regina Grajewski, Barbara Fährmann
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Sustainable rural development: What is the role of the agri-food sector?
MARTIN PETRICK, GERTRUD BUCHENRIEDER (eds., 2007)
Studies on the Agricultural and Food Sector in Central & Eastern Europe, Vol. 39, Halle (Saale), IAMO, pp. 274-285.
ANTICIPATED IMPACTS OF GMO INTRODUCTION
ON FARM PROFITABILITY IN POLAND
MARIUSZ MACIEJCZAK, ADAM WAS∗
ABSTRACT
The paper takes one significant element of agriculture production – the use of
genetically modified organisms (GMO) – and considers it in relation to the
overall profitability of agriculture in Poland. In so doing, the paper aims to
examine Polish farmers’ opportunity costs of being non-GM, were they free to
use GMO. Specifically, the paper asks if, under ceteris paribus conditions, the
use of GMO plants in Polish farms would influence their economic results. To
answer this question, the scientific and theoretical assumption that GMO cultivation is permitted in Poland has been applied. The approach combines experience
of the new biotech-based system of agricultural production with a modelling
system that builds up and aggregates the impacts of individual farm responses
under actual and assumed situations.
Key words: GMO, coexistence, farm profitability, farm model, Polish agriculture.
1
INTRODUCTION
Growing concerns are observable in Poland over the coexistence of genetically
modified organisms (GMO) and non-modified organisms – both conventional
and organic (non-GM). So far, GMO use is restricted in Poland. According to
official data provided by the responsible authorities, currently there are no GMO
cultivations in Poland (THE SCOPE …, 2007). The use of GMO feeds is permitted, but under a special moratorium. However, since September 2004, the European Commission permitted, under strict conditions, GMO varieties to be grown
in the European Union (EU). Poland, as an EU member state, asked for a temporary prohibition, citing the need to strengthen existing laws on GMO plant cultivation (PRESS RELEASE..., 2005). Lifting this prohibition was recently considered
in the amended Legal act on genetically modified organisms (PROPOSAL OF
AMENDMENT …, 2007). But according to the position paper of the Polish government, the cultivation of GMO crops should be extremely limited or even
∗
Warsaw Agricultural University – SGGW, Nowoursynowska Str. 166, 02-787 Warsaw,
Poland, Email: [email protected], [email protected]
Anticipated impacts of GMO introduction
275
excluded. Thus, the regulations proposed in the amendment provide a chance for
minimising the risk connected to mixing plants’ reproductive material, or the
cross-pollination of GM and non-GM plants. It also enables the introduction of
appropriate control measures (THE SCOPE…, 2007).
Nonetheless, there is much opposition at various levels to the introduction of
GMO crops. As an example, all 16 Polish provinces have already announced that
they aim for a total ban of GMO crops (GMO FREE ZONES..., 2007). On the other
hand, there are many supporters of GMO use in Polish agriculture. These advocates claim that biotech-based agriculture could significantly increase yields and
reduce costs; they also claim that it has many other positive impacts which could
strengthen the competitiveness of Polish agriculture, as well as that of particular
farms (TWARDOWSKI, 2007). In the most recent survey on the public perception
of biotechnology, more than 50% of Poles are in favour of scientific research
using biotechnology and genetic engineering in the production and processing of
food. However, 65% of respondents are afraid that GMO in food products might
have a negative impact on the environment and human health (PUBLIC
PERCEPTION…, 2005).
It should be noted that agriculture is an open process, which means that perfect
segregation of the various agricultural production types, namely conventional,
organic or based on genetically modified organisms, is not possible in practice.
When considering the different aspects of GMO and non-GM systems, it must
be taken into account that in the EU, no form of agriculture should be excluded
and the ability to maintain different agricultural production is considered as a
prerequisite for providing a high degree of consumer choice (COMMISSION
RECOMMENDATION, 2003).
Thus, to cope with the emerging GM challenge, which is either prohibition or
implementation of GMO in Polish agriculture, biotechnology development policies of the EU, as well as the general trends of agricultural development, where
biotech-based systems are expanding rapidly, should be taken into account
(BROOKES and BARFOOT, 2006); naturally, the opinion of the Poles should also
be considered. From the economic point of view, the total ban of GMO might
directly influence the performance of Polish agriculture (ANIOL and BROOKES;
2005), as well as the existence of a black market for GMO in Poland
(ZAKOWSKA-BIEMANS and MACIEJCZAK, 2005).
The approach applied in this paper combines the (very short) experience of the
new biotech-based system of agricultural production with a modelling system
that builds up and aggregates the impacts of individual farm responses under
actual and assumed situations. As such, it is possible to gain an understanding of
the likely movement in incomes for a variety of assumptions, together with
changes in the balance of enterprises by farm type and in the aggregate, assuming
farmers strive for, or are forced to adopt through competition, profit-maximising
Mariusz Maciejczak, Adam Was
276
strategies. The results provide an indication of the impact of GMO application
on the performance of Polish agriculture, including the importance of different
GMO crops on the maintenance and prosperity of different farm types. The
employed comparative static approach does show the degree to which one significant element of agriculture production – the use of genetically modified organisms – could influence the sector.
2
THE MODEL
In preparing this paper, an exhaustive investigation has been completed comparing
the situations of 252 representative farms, with introduced or constrained GMO
crops, using a linear programming optimisation technique. The model was
constructed as an Excel spreadsheet and solved with the Solver function. The
applied farm model uses over 80 decision variables and over 200 constraints.
Each of the farm models optimise Net Farm Income (NFI) in a comparative static
approach. A set of balances has been incorporated into the model to secure internal integrity of the results. The most important of these are rotational ties for
crops. A animal feed nutrient balance is obtained whereby the model optimises
the use of fodder and calculates the necessary supply of concentrates. The balance
of animal places with buildings available is also included. By using the standards adapted to the technologies implemented in the modelled farms, the relationship between the labour force and tractors is achieved.
All parameters of the calculation were fed into the model in a disaggregated
form. These included: farm enterprises with associated yields and input requirements, product prices, input costs, costs of land lease and production quotas,
services, seasonal and permanent employment, and other financial burdens of
the farms. It is also possible to program in any type and amount of payment
from the Common Agricultural Policy (CAP).
2.1 Farm types
The set of 252 farm types are representative of some 90% of the agricultural
area in Poland; they have been assembled using statistical and FADN1 data as
well as expert knowledge. The farm types have been classified according to the
following criteria:
–
Intensity of production: Intensive and extensive;
–
Soil quality: Good, medium and poor soils;
–
Enterprise types: Cattle, pig, arable, mixed;
1
Farm Data Accountancy Network of EU.
Anticipated impacts of GMO introduction
–
277
Size: (6 groups of arable farms, 8 groups of cattle and pig farms, 20 groups
of mixed farms, assuming different sizes and also different proportions of
pigs and cattle).
After calculating the optimal results for every farm type model in every scenario,
the results were multiplied using the number of each type of farm in the total
Polish farm population.
2.2 Scenarios
Two time horizons, which take into account the short-term (2006) and mediumterm (2013) perspective, were assumed. For each time horizon, two scenarios
were created: "Non-GMO", which assumes restrictions for GMO crop development, and "GMO", which assumes unlimited coexistence of GMO and nonGMO crops, i.e., no buffer zones. In "GMO" scenarios, the availability of basic
GMO crops like Roundup Ready wheat, rapeseed, corn for grain, maize for
silage and sugar beets has been assumed. The run of the calibrated model for
2006 served as a reference scenario (non-GMO situation) for solutions generated
for "GMO 2006". This was done in order to explore the potential effects on
financial performance of farms applying GMO. The run of the "non-GMO 2013"
model was used as a reference for the future "GMO 2013" model in order to
examine the influence of upcoming CAP changes regarding the GMO issue.
Thanks to such assumptions, the model also reflected expected changes in agricultural policy, especially the level of support in line with the phasing-in of the
current SAPS2 payment scheme, as well as forecasted changes in prices and
costs (MAJEWSKI et. al., 2006). In the medium-term perspective, adjustments in
production structure have been assumed, while the short time perspective has
been constrained to preserve current status. However, the analysis does not consider dynamic changes between 2006 and 2013, due to overall difficulties in
distinguishing the single impact of introducing GMO crops from the impact of
agricultural policy.
3
RESULTS
Calculated farm model results were aggregated to obtain estimates for the whole
of Polish agriculture, as well as particular farm groups. The results have been
compared separately for the short- and medium-term perspective. To examine
the potential influence of GMO crops, a comparison of farm types has been
made according to various intensities of production, specialisation and soil quality.
In both time horizons, the introduction of GMO crops has a positive influence
2
Single Area Payment Scheme – direct payment scheme applied in most of EU New Member
States.
Mariusz Maciejczak, Adam Was
278
for Net Farm Income. However, the effects are not evenly distributed among
farms.
3.1 Impact in the year 2006
The increase of overall Net Farm Income due to the introduction of five GMO
"Roundup Ready" crops in 2006 reached 4.5%. This proved, therefore, the potential of new biotechnologies. Although the calculated models show differences
in growth rate between intensive and extensive farms, those differences are
rather small (Figure 1).
Figure 1:
Potential income effects of GMO crop introduction for 2006
by intensity of production
Changes of Net Farm Income (nonGMO 2006=100)
104,9
104,8
104,7
104,6
104,5
Overall
104,4
Intensive farms
Extensive farms
104,3
104,2
104,1
104,0
103,9
GMO 2006
Source: Authors’ calculation.
The model results show much stronger differentiation in the economic effects of
GMO implementation in the case of farm specialisation.
The highest increase of NFI is observed in the case of arable farms. This could
be explained by a higher share of crop production in total production, which
might be influenced by GMO crops. Farm types that specialised in animal production also gained from the introduction of GMO, but due to a limited share of
crop production in the production structure, the NFI increase is lower. The
slightly better situation of cattle farms could be explained by utilising the potential of GMO fodder maize. Low profits on the side of mixed farms are caused by
the relatively smallest share of crop production in terms of income creation
(Figure 2).
Anticipated impacts of GMO introduction
Figure 2:
279
Potential income effects of GMO crop introduction for 2006
by specialisation
Changes of Net Farm Income (nonGMO 2006=100)
110
108
106
Cattle farms
Pig farms
104
Arable farms
Mixed farms
102
100
98
GMO 2006
Source: Authors’ calculation.
Results of the model calculated for farm types differentiated by soil quality
show essential disparities in the economic effects of introducing GMO. Models
of farms located on the best soils show the possibility of highest NFI growth due
to GMO application. On the contrary, models of farms on poor soils do not show
any benefits from possibly acquiring modified species. Looking at a set of currently available modified species, this phenomenon can be easily explained.
Most GMO species require rich or medium soils for optimal growth. Limited
yield growth potential, together with the relatively high costs of new technology
do not create favourable conditions for applying GMO crops on poor soils
(Figure 3).
Mariusz Maciejczak, Adam Was
280
Figure 3:
Potential income effects of introducing GMO crops for 2006
by soil type
Changes of Net Farm Income (nonGMO 2006=100)
110
108
106
Good soils
104
Medium soils
102
Poor soils
100
98
96
GMO 2006
Source: Authors’ calculation.
3.2 Impact in 2013
The results of models for 2013 confirm the outcomes of scenarios for 2006. The
assumed introduction of full rates for the SAPS payment scheme and forecasted
worsening of trade-off conditions in agriculture had no influence on the economic effects caused by implementing GMO crops. The observed relative gains
are slightly smaller than in 2006. This could be explained by the increase of
overall income due to increasing direct payment rates. (Figure 4-6).
Further, relaxing some rotational constrains do not change relative NFI gains
resulting from GMO application. Optimisation of the cropping structure, which
leads to increased shares of corn and rapeseed at other cereals’ expense (Figure 7)
does not change the relationship between GMO and non-GMO species. In all
farm types analysed in both time horizons, the relative income increase due to
GMO introduction is hardly the same.
Anticipated impacts of GMO introduction
Figure 4:
281
Potential income effects of GMO crops introduction for year
2013 by intensity of production
Changes of Net Farm Income (nonGMO 2013 = 100)
104,5
104,5
104,4
104,4
104,3
Overall
104,3
Intensive farms
104,2
Extensive farms
104,2
104,1
104,1
104,0
104,0
GMO 2013
Source: Authors’ calculation.
Figure 5:
Potential income effects of GMO crops introduction for year
2013 by specialisation
Changes of Net farm income (SAPS 2013=100)
108,0
107,0
106,0
105,0
Cattle farms
104,0
Pig farms
Arable farms
103,0
Mixed farms
102,0
101,0
100,0
99,0
GMO 2013
Source: Authors’ calculation.
Mariusz Maciejczak, Adam Was
282
Figure 6:
Potential income effects of GMO crops introduction for 2013
by soil type
Changes of Net Farm Income (nonGMO 2013=100)
108
106
104
Good soils
102
Medium soils
Poor soils
100
98
96
GMO 2013
Source: Authors’ calculation.
Figure 7:
Cropping structure for GMO and non-GMO scenarios
100%
Wheat
90%
Barley
80%
70%
Corn
60%
Other cereals
50%
Proteins
40%
Oilseed
30%
Potatoes
20%
Sugar beets
10%
Fodder
0%
nonGMO 2006
nonGMO 2013
Source: Authors’ calculation.
GMO 2006
GMO 2013
Anticipated impacts of GMO introduction
4
283
CONCLUSIONS
The paper took one significant element of agriculture production – the use of
genetically modified organisms – and considered it in relation to a single factor –
the overall profitability of agriculture in Poland. This was carried out under strict
scientific rigor and under the theoretical assumption that GMO cultivation is
permitted in Poland without any coexistence limitations. The authors aimed to
discover whether, under ceteris paribus conditions, the use of GMO plants in
Polish farms would have an influence on their economic results. The applied
comparative static approach of an optimisation technique provided an opportunity to build up and aggregate the impacts of individual farm responses under
actual and assumed situations, respectively, for 2006 and 2013.
The modelling results show that GMO crops would have an influence on the
economic performance of Polish farms. It has been proven that from an economic point of view, the possibility of using GMO crops is likely to cause an
increase of Net Farm Income. Nonetheless, it should be noted that this impact is
not very crucial. The average farm income given the unrestricted availability of
GMO technology is only 4.5% higher compared to the GMO-free strategy. The
obtained results for 2006 show that in the short-term perspective, the effect of
introducing GMO will be greater, due to a generally lower income level. In the
medium-term perspective presented for 2013, which assumed changes in agricultural policy as well as adjustment in crop structure, the GMO effect of economic profitability for Polish farms is lower due to an overall NFI increase; this
is the result of CAP phasing-in.
However, the influence of GMO on Polish farm profitability depends significantly on the intensity of production, soil conditions, and the type of production.
These three factors are connected to the character of plant production. Firstly, in
both the short- and medium-term perspectives, intensive farms obtain a higher
income from introducing GMO compared to those which perform more extensively. Secondly, as GMO plants are more effective on good soil, farms that operate in such conditions will report higher income from GMO introduction than
those with poor soil. Finally, the impact on the type of production can be described
with apprehension. The more general approach shows that farms specialising in
plant production report higher profitability than those with animal production.
This is related to a higher share of crop production in income creation, which is
highly influenced by GMO technology. The lowest income increase was found
on mixed farms, which is due to their relatively smaller share of crop production
in income creation. Taking into account only farms specialised in animal production, introducing GMO crops contributes more for cattle farms in comparison
to pig farms. This is due to the possibility of acquiring GMO fodder maize.
As a final remark, it should be stressed that this analysis has only taken into account the effect of introducing GMO on the economic performance of Polish
284
Mariusz Maciejczak, Adam Was
farms. As such, it shows that the opportunity costs of being GMO-free for an
average farm is equal to approximately 4.5% of its NFI. However, it is important
to bear in mind that other issues, be they social, environmental, health or ethical
in nature, are of equal importance for the emerging challenge of possible GMO
implementation in Polish agriculture. In academic elaborations, only one of
these issues can be analysed at a time, but one should remember that only examining all of them can provide a comprehensive view that might be a coherent
guide for further development. Therefore, there is an urgent need to perform
exhaustive studies to answer further arising questions.
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LIST OF AUTHORS
Abildtrup, Jens, Institute of Food and Resource Economics, Faculty of Life
Sciences, University of Copenhagen, Denmark.
Adinyira, Emmanuel, Department of Building Technology, Kwame Nkrumah
University of Science and Technology, Kumasi, Ghana. Email:
[email protected]
Adjei-Kumi, Theophilus, Department of Building Technology, Kwame Nkrumah
University of Science and Technology, Kumasi, Ghana. Email: [email protected]
Barussaud, Emilien, University of Paris 7 – UMR LADYSS, c/o Marianne Cohen,
UFR GHSS, Immeuble Montréal,105 rue de Tolbiac, F-75013 Paris, France.
Email: [email protected]
Bokusheva, Raushan, Leibniz Institute of Agricultural Development in Central
and Eastern Europe (IAMO), Halle (Saale), Germany. Email: [email protected]
Bondarenko, Anna, Sumy National Agrarian University, Ukraine. Email:
[email protected]
Cimpoieş, Dragoş, Department of Management, The State Agricultural University
of Moldova, Chişinău, Republic of Moldova. Email: [email protected]
Danilowska, Alina, Department of Economics and Economic Policy, Warsaw
Agricultural University, Warsaw, Poland. Email: [email protected]
Derek, Baker, Institute of Food and Resource Economics, Faculty of Life Sciences,
University of Copenhagen, Denmark. Email: [email protected]
Fährmann, Barbara, Federal Agricultural Research Centre (FAL), Braunschweig,
Germany.
Fałkowski, Jan, Warsaw University, Department of Economic Sciences. Email:
[email protected]
Fock, Achim, The World Bank. Email: [email protected]
Fock, Karin, Bonsilia Development Consulting. Email: [email protected]
Gaisina, Sholpan, Innovation University of Eurasia, Pavlodar, Kazakhstan.
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288
List of authors
Grajewski, Regina, Federal Agricultural Research Centre (FAL), Braunschweig,
Germany.
Hedetoft, Anders, Centre for Regional and Tourism Development, Nexø,
Denmark.
Heidelbach, Olaf, Delegation of the European Commission to the Republic of
Kyrgyzstan. Email: [email protected]
Heidhues, Franz, Institute for Agricultural Economics and Social Sciences in the
Tropics and Subtropics (490), University of Hohenheim, Stuttgart, Germany.
Email: [email protected]
Jia, Xiangping, Institute for Agricultural Economics and Social Sciences in the
Tropics and Subtropics (490), University of Hohenheim, Stuttgart, Germany.
Email: [email protected]
Just, Flemming, Danish Institute of Rural Research and Development (IFUL),
University of Southern Denmark, Esbjerg. Email: [email protected]
Kosodiy, Roman, Sumy National Agrarian University, Ukraine. Email:
[email protected]
Maciejczak, Mariusz, Warsaw Agricultural University – SGGW, Nowoursynowska
Str. 166, 02-787 Warsaw, Poland. Email: [email protected]
Małak-Rawlikowska, Agata, Warsaw Agricultural University, Faculty of Agricultural Economics, Warsaw, Poland. Email: [email protected]
Margarian, Anne, Federal Agricultural Research Centre (FAL), Institute of Farm
Economics, Braunschweig, Germany. Email: [email protected]
Milczarek, Dominika, Warsaw University, Department of Economic Sciences,
Warsaw, Poland. Email: [email protected]
Mishenin, Eugeniy, Sumy National Agrarian University, Ukraine. Email:
[email protected]
Nuppenau, Ernst-August, Institute of Agricultural Policy and Market Analysis,
Justus-Liebig-University, Giessen, Germany. Email:
[email protected]
Oteng-Seifah, Samuel, Department of Building Technology, Kwame Nkrumah
University of Science and Technology, Kumasi, Ghana. Email:
[email protected]
Poletto, Ana, University of Paris 7 – UMR LADYSS, c/o Marianne Cohen, UFR
GHSS, Immeuble Montréal,105 rue de Tolbiac, F-75013 Paris, France.
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289
Pufahl, Andrea, Federal Agricultural Research Centre (FAL), Institute of Rural
Studies, Braunschweig, Germany. Email: [email protected]
Raymond, Richard, Ecole Nationale du Génie Rural, des Eaux et des Forêts –
AgroParisTech – 24, avenue des Landais B.P. 90054, F-63171 Aubiere
Cedex 9 – France. Email: [email protected]
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[email protected]
Was, Adam, Warsaw Agricultural University – SGGW, Nowoursynowska Str. 166,
02-787 Warsaw, Poland. Email: [email protected]
Zeller, Manfred, Institute for Agricultural Economics and Social Sciences in the
Tropics and Subtropics (490), University of Hohenheim, Stuttgart, Germany.
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