Crisis, Austerity and Automatic Stabilization

Document technical information

Format pdf
Size 312.3 kB
First found May 22, 2018

Document content analysis

Category Also themed
Language
English
Type
not defined
Concepts
no text concepts found

Persons

Gary Larson
Gary Larson

wikipedia, lookup

Clemens Fuest
Clemens Fuest

wikipedia, lookup

Organizations

Places

Transcript

Crisis, Austerity and Automatic Stabilization∗
Mathias Dolls†
Clemens Fuest‡
Andreas Peichl§
Christian Wittneben¶
Preliminary draft. Please do not cite or distribute.
This version: February 1, 2015
Abstract
We analyze how reforms of tax-benefit systems in the period 2007-2013 have affected
the automatic stabilization capacity for households as well as government budgets in
the EU-27 based on harmonized European micro data and counterfactual simulation
techniques. Factors like unemployment benefits or (progressive) income taxes can stabilize
individual (and aggregate) income and smooth consumption demand in case of an income
and unemployment shock. Our analysis allows to disentangle automatic changes in net
government intervention from those that take place after explicit government legislature
(discretionary changes) as well as changes in actual incomes and behavioral responses. We
find automatic stabilizers to be generally heterogeneous across countries—both in levels
and in terms of policy changes over the crisis. Stabilization coefficients vary from less than
25% in Eastern European countries to almost 60% in Belgium, Germany, and Denmark.
JEL classification: E63, E62, H31, H12
Keywords: Stabilization, Macroeconomic Stabilization, Fiscal Policy, Public Finance
∗ The
results presented here are based on EUROMOD version G2.0. EUROMOD is maintained, developed and
managed by the Institute for Social and Economic Research (ISER) at the University of Essex in collaboration
with national teams from the EU member states. We are indebted to the many people who have contributed to
the development of EUROMOD and to the European Commission for providing financial support for it. The
results and their interpretation are the authors’ responsibility. XXX + SILC Datasets Acknowledgments XXX!. +
Thanks. + StudentAssistants provided excellent research assistance.
† ZEW Mannheim. E-Mail: [email protected] Address: Centre for European Economic Research, P.O. Box 103443,
68034 Mannheim, Germany.
‡ ZEW, University of Mannheim. E-Mail: [email protected]
§ ZEW, University of Mannheim and ISER. E-Mail: [email protected]
¶ ZEW Mannheim. E-Mail: [email protected]
1
Extended Abstract [For Conference Submissions]
The sovereign debt crisis in Europe led to consolidation measures in many EU countries. In
some cases, fundamental changes in the structure of tax and transfer systems have taken place.
Yet, very little is known how these reforms changed the (automatic) fiscal stabilization effects
of national tax-benefit systems and in particular the degree to which households are protected
in the event of shocks to gross income.
Automatic stabilization is mainly provided through two channels. First, factors like unemployment benefits or progressive income taxes can stabilize individual (and aggregate) income
and smooth consumption demand in case of income and unemployment shocks (Auerbach
and Feenberg 2000, Dolls et al. 2012). The second channel is due to the progressivity of the tax
system. In progressive systems, negative income shocks can lead to lower marginal tax rates
which may increase labor supply incentives. The resulting labor supply responses can thus
have an additional stabilizing effect on income and consumption.
Based on harmonized European micro data and counterfactual simulation techniques, we
analyze how reforms of tax-benefit systems in the period 2007-2013 have affected the automatic
stabilization capacity for households in the EU-27. In particular, we combine 2007 pre-crisis
micro data from the EU Statistics on Income and Living Conditions (EU-SILC) with the different
tax-benefit rules in the period under investigation. This allows us to disentangle the effect of
changes in the tax and transfer systems (i.e. the ‘policy effect’) from changes in actual incomes
and demographics on the shock-absorption capacity of the tax and transfer systems and labor
supply incentives. The use of the microsimulation model EUROMOD in combination with
EU-SILC data offers a unified framework to analyze the effects of policy changes and derive
comparable results at the household level. We complement these results with an analysis of
macroeconomic data on government debt and the sensitivity of government budgets with
respect to output fluctuations, and provide (counterfactual) growth rates that would have
emerged in the absence of automatic stabilizers over the crisis.
Our paper also contributes to the literature on fiscal integration in Europe (see e.g. Bargain
et al. 2013) by providing new micro-estimates for the cushioning effects of national tax-benefit
systems in the European Union. These estimates are crucial for an ex-ante evaluation of
the effectiveness of different forms of supranational automatic stabilizers as discussed in the
current policy debate in Europe (European Commission 2012, Van Rompuy et al. 2012).
We find automatic stabilizers to be generally heterogeneous across countries—both in levels
and in terms of policy changes over the crisis. The amount of a shock to gross income that
is absorbed by the tax and transfer system varies from less than 25% in Eastern European
countries to more than 50% in Belgium, Germany, and Denmark. Countries with stronger
automatic stabilizers were relatively resilient during the crisis, while those with weak automatic
stabilizers experienced major economic contractions and increases in unemployment. In most
countries that changed their tax and benefit system, policy adjustments strengthened automatic
stabilizers in the long-term perspective by fiscal consolidation measures such as tax increases
which, however, can have destabilizing effects in the short term.
2
1 Introduction
The sovereign debt crisis in Europe led to consolidation measures in many EU countries. In
some cases, fundamental changes in the structure of tax and transfer systems have taken place.
Yet, very little is known how these reforms changed the (automatic) fiscal stabilization effects
of national tax-benefit systems and in particular the degree to which households are protected
in the event of shocks to gross income.
Automatic stabilization is mainly provided through two channels. First, factors like unemployment benefits or progressive income taxes can stabilize individual (and aggregate) income
and smooth consumption demand in case of income and unemployment shocks (Auerbach
and Feenberg 2000, Dolls et al. 2012). The second channel is due to the progressivity of the
tax system. In progressive systems, income shocks can lead to lower marginal tax rates which
may increase labor supply incentives. The resulting labor supply responses can thus have an
additional stabilizing effect on income and consumption.
Based on harmonized European micro data and counterfactual simulation techniques, we
analyze how reforms of tax-benefit systems in the period 2007-2013 have affected the automatic
stabilization capacity for households in the EU-27. In particular, we combine 2007 pre-crisis
micro data from the EU Statistics on Income and Living Conditions (EU-SILC) with the different
tax-benefit rules in the period under investigation. This allows us to disentangle the effect of
changes in the tax and transfer systems (i.e. the ‘policy effect’) from changes in actual incomes
and demographics on the shock-absorption capacity of the tax and transfer systems and labor
supply incentives. The use of the microsimulation model EUROMOD in combination with
EU-SILC data offers a unified framework to analyze the effects of policy changes and derive
comparable results at the household level. We complement these results with an analysis of
macroeconomic data on government debt and the sensitivity of government budgets with
respect to output fluctuations, and provide (counterfactual) growth rates that would have
emerged in the absence of automatic stabilizers over the crisis. We provide micro-estimates of
the effects on government budgets of the policy changes.
We find automatic stabilizers to be generally heterogeneous across countries—both in levels
and in terms of policy changes over the crisis. The amount of a shock to gross income that
is absorbed by the tax and transfer system varies from less than 25% in Eastern European
countries to more than 50% in Belgium, Germany, and Denmark. Countries with stronger
automatic stabilizers were relatively resilient during the crisis, while those with weak automatic
stabilizers experienced major economic contractions and increases in unemployment. In most
countries that changed their tax and benefit system, policy adjustments strengthened automatic
stabilizers in the long-term perspective by fiscal consolidation measures such as tax increases
which, however, can have destabilizing effects in the short term.
1.1 Motivation
A common critique of the European Stability and Growth Pact is that it does not leave enough
scope for member states’ governments to take anti-cyclical fiscal policy measures. We assess the
extent to which member states had room for fiscal policy by analyzing government deficits and
their cyclical and cyclically-adjusted components with a focus on the role that automatic fiscal
3
stabilizers played. We then use microsimulation to assess the changes in automatic stabilizers
provided by the tax and benefit system. The Great Financial Crisis of 2007 and the ensuing
recession and sovereign debt crisis was accompanied by policy reforms that potentially affected
automatic stabilizers in many EU countries. This paper analyzes the policy effect of changes
in the tax system and unemployment benefits. We isolate this effect from discretionary fiscal
policy measures as well as behavioral responses of households by holding constant pre-crisis
household income data and demographic characteristics and combining it with the tax and
benefit systems from 2007-2013.
This paper is a natural extension of our work (Dolls, Fuest and Peichl, 2012), where we
calculated automatic stabilizers for the 19 EU countries (using EUROMOD) and the United
States (using TAXSIM). We extend this analysis by using more recent data and a larger set
of countries. It builds on work by Auerbach and Feenberg (2000) and Pechman (1973, 1987),
using the measure of a tax system’s “built-in flexibility” as a measure of automatic stabilizers.
Our paper also contributes to the literature on fiscal integration in Europe (see e.g. Bargain et
al. 2013) by providing new micro-estimates for the cushioning effects of national tax-benefit
systems in the European Union. These estimates are crucial for an ex-ante evaluation of
the effectiveness of different forms of supranational automatic stabilizers as discussed in the
current policy debate in Europe (European Commission 2012, Van Rompuy et al. 2012).
Figure 1: GDP Growth Rates
Unemployment Rates
10
8
6
4
2
0
-2
-4
-6
-8
-10
dgdp
dgdp
10
8
6
4
2
0
-2
-4
-6
-8
-10
2000
2005
AT
BE
2010
DE
FR
2015
NL
2000
LU
FI
DK
2010
LV
SI
2015
SK
LT
dgdp
10
8
6
4
2
0
-2
-4
-6
-8
-10
dgdp
10
8
6
4
2
0
-2
-4
-6
-8
-10
EE
2005
2000
CY
2005
EL
ES
2010
IE
SE
2015
HU
2000
RO
IT
2005
MT
BG
2010
CZ
UK
2015
PL
PT
Source: AMECO database.
Figures 1 and 2, respectively, show the development of GDP growth rates and unemployment
4
Figure 2: Unemployment Rates
20
15
15
10
10
5
5
ur
20
ur
Unemployment Rates
0
0
2000
2005
AT
BE
2010
DE
FR
2015
NL
2000
LU
EE
2005
FI
DK
2010
LV
SI
2015
SK
LT
20
15
20
15
10
5
0
ur
ur
10
5
0
2000
CY
2005
EL
ES
2010
IE
SE
2015
HU
2000
RO
IT
2005
MT
BG
2010
CZ
UK
2015
PL
PT
Source: AMECO database.
rates for the EU-27 countries from 2000 to 2014. The worst decline in GDP occurs in 2009, with
the exception of Greece, which had GDP decline until 2011. Poland is also an exception in
that it maintains positive GDP growth over the entire course of the crisis. In general, southern
countries such as Greece, Spain and Portugal, and the baltics, saw the largest increase in
unemployment rates and the largest drop in GDP.
These changes in the economies led to changes in government budgets, through an increase
in unemployment benefits payments and a decline in government tax revenue. Using the
measures defined by the European Commission (see Girouard and André (2005) and the
updates by Mourre, Isbasoiu, Paternoster and Salto (2013); Mourre, Astarita and Princen
(2014)), it can be seen that increases in government budget deficits increased over the crisis. In
virtually all countries, it was the structural (cyclically adjusted) component of the deficit that
increased, not the cyclical component.
1.2 Literature
Research that relies on micro data includes the studies by Auerbach and Feenberg (2000), Dolls
et al. (2012) and Mabbett and Schelkle (2007). Kniesner and Ziliak (2002b) analyze changes in
United States tax reforms to study the impact on the insurance against variability of disposable
income and consumption. They find a stabilization of consumption through the income tax
5
Figure 3: Budget Deficits: EU27
Net borrowing
Cycl.-adj. component
2014
2013
2012
2011
2010
2009
2008
18
16
14
12
10
8
6
4
2
0
-2
-4
-6
-8
-10
-12
-14
2007
in % of (potential) GDP
EU27
Cyclical component
Output gap
Source: AMECO, Note: Estimate for 2014
during the 1980s of around 15 percent of an initial shock to gross income. They stress that, in
spite of there being efficiency gains (a reduction of the deadweight loss), there was also a “loss
from the reduction in collective insurance” (Kniesner and Ziliak, 2002b, p. 609). Kniesner and
Ziliak (2002a) find that the annual variation of consumption is decreased by 20 percent due to
income smoothing.
On the theoretical side, Agell and Dillén (1994) develop a Keynesian model of how automatic stabilizers cushion economic fluctuations. Agents are monopolistic consumer-producers
of imperfectly substitutable goods, and price adjustments are costly. Thus, there are two
inefficiencies: First, output is too low because of the monopolistic competition and second,
there is price stickiness. The first is an ordinary negative externality that can be cured by
a Pigou-Tax. The second is more difficult, as it hinges on the labor supply elasticity of the
agents. If households have a high labor supply elasticity, they are more likely to make quantity
adjustments to fluctuations in aggregate demand instead of adjusting prices, thus exacerbating
the externality caused by the price stickiness. Through a progressive tax system, the quantity
adjustment can be “penalized” to encourage price adjustments and thus mitigate harmful
(quantity) fluctuations. Mattesini and Rossi (2012) use a New-Keynesian model to study the
relation of progressive taxation and output volatility in the context of monetary policy. In their
model, there exists a trade-off between inflation stabilization and output stabilization, with
economies that have a more progressive tax structure facing a larger trade-off (Mattesini and
6
Figure 4: Budget Deficits
(a) Greece
(b) Spain
ES
Cyclical component
Output gap
Net borrowing
Cycl.-adj. component
Source: AMECO, Note: Estimate for 2014
Cyclical component
Output gap
Net borrowing
Cycl.-adj. component
Source: AMECO, Note: Estimate for 2014
2014
2013
2014
2013
2012
2011
2010
2009
2007
2014
2013
2012
2011
2010
2009
2008
18
16
14
12
10
8
6
4
2
0
-2
-4
-6
-8
-10
-12
-14
2008
in % of (potential) GDP
PT
18
16
14
12
10
8
6
4
2
0
-2
-4
-6
-8
-10
-12
-14
2007
2012
(d) Portugal
IE
in % of (potential) GDP
Cyclical component
Output gap
Source: AMECO, Note: Estimate for 2014
(c) Ireland
Net borrowing
Cycl.-adj. component
2011
2010
2009
2008
2007
18
16
14
12
10
8
6
4
2
0
-2
-4
-6
-8
-10
-12
-14
2014
2013
in % of (potential) GDP
Net borrowing
Cycl.-adj. component
2012
2011
2010
2009
2008
2007
in % of (potential) GDP
EL
18
16
14
12
10
8
6
4
2
0
-2
-4
-6
-8
-10
-12
-14
Cyclical component
Output gap
Source: AMECO, Note: Estimate for 2014
Rossi, 2012, pp. 827–828). The model shows a negative correlation for various OECD countries
of the standard deviation of output and labor hours with the degree of tax progressivity,
respectively. Similarly, Galí (1994) shows that output fluctuations (measured as the standard
deviations of output growth or detrended log GDP) are negatively correlated with government
size (measured by the share of tax revenue of GDP). Fatás and Mihov (2001) find the same
result. Dolls et al. (2012) find that government size is positively correlated with and a good
predictor of automatic stabilizers measured as the income stabilization coefficient, but much
less so for the demand stabilization coefficient. Grant, Koulovatianos, Michaelides and Padula
(2010, p. 972) focus on consumption and income data for the US and find that a redistributive
tax system decreases the cross-sectional variation (measured by the standard deviation) of
consumption, and thus provides insurance to households. They check if there is a significant
trade-off between insurance provision and distortionary effects of the tax system. While the
first effect is substantial, they find a lesser impact of redistributive taxation on the mean log of
consumption. They conclude that both channels are empirically relevant (Grant et al., 2010,
7
p. 973).
Kletzer (2006) develops a model of imperfect competition where progressive taxation can
increase welfare and explores the relation of automatic stabilization provided by distortionary
taxes when nominal wage rigidity is presents. Immervoll, Kleven, Kreiner and Saez (2007)
compare in-work benefits and traditional benefits, along intensive and extensive margins.
Low (2005) studies the intertemporal choice of labor and consumption in a life-cycle model,
in particular, how uncertainty affects the choice of working hours, consumption and savings
over the life-cycle. He finds two channels: Labor supply adjustments can take place either
before shocks are realized, so that the household has more income for self-insurance against
shocks, or households react to shocks by adjusting their hours of work (Low, 2005, p. 946).
While hours of work should track wages, induced by the elasticity of intertemporal substitution,
this effect is offset by the uncertainty, which causes individuals to work more when they are
young, even though the wages are low (Low, 2005, p. 972).
2 Data and Methodology
In this section we describe the methodological procedure to calculate automatic stabilizers,
both from a macro and from a micro perspective.
2.1 Income Stabilization
Measuring the stabilization provided by a tax system requires some form of assessment of how
a household’s tax payment (or benefit receipt) and thus, disposable income, varies with the
gross income. As described by Auerbach and Feenberg (2000, pp. 40-41), one measure that
comes to mind is the elasticity of the taxes with respect to income changes, a proportional tax
system having an elasticity of one, and progressive taxes having an elasticity greater than one.
The elasticity then serves as a measure of the progressivity of the tax system. The drawback of
using it as an indicator of the stabilizing effect is its definition as a relative measure, relating the
percent change of taxes to a one-percent change in income. As Auerbach and Feenberg (2000)
point out, the elasticity neglects information on the share of income to be payed as taxes. This
information, however, is important, as a large share of taxes of aggregate income means that
taxes can serve as a more effective automatic stabilizer. Auerbach and Feenberg (2000) use an
instrument proposed by Pechman (1973), namely, the ratio of changes in the disposable income
to changes in market income, which they refer to as the normalized tax change.
The mechanism behind the stabilizers is simple. Consider a household that has to pay a
proportional tax of 30 percent and faces a decline in gross income of 100 Euros. Then 30
percent of the shock would be absorbed by the proportional tax, leaving a decline of 70 Euros
of disposable income. For a progressive tax system, as is in effect in the majority of the
European countries, the stabilizing effect would be even larger (Dolls et al., 2012, p. 281). Let
the aforementioned household be subject to progressive taxation, and after the initial shock,
her marginal tax rate would drop to 25 percent. Then this provides an additional cushioning of
the decline in disposable income. Automatic stabilizers of this kind have been estimated by
Dolls et al. (2012) for 19 European countries and the United States.
8
They consider a five percent shock on market income, defined as
YiM = Ei + Qi + Ii + Pi + Oi ,
(2.1)
where Ei , Qi , Ii , Pi , Oi , respectively denote labor income, business income, capital income,
property income, and other income. The disposable income is equal to the market income minus
net government intervention, which consists of direct taxes and social insurance contributions
minus social benefits. Defining the net government intervention as Gi = Ti + Si − Bi , the
disposable income is
YiD = YiM − Gi = YiM − ( Ti + Si − Bi ).
(2.2)
The Income Stabilization Coefficient is denoted by τ I and measures how a shock on market
income ∆Y M translates to a shock on households’ disposable income ∆Y D :
∆Y D = 1 − τ I ∆Y M
This calculation can be done at the individual (that is, household) level, that is, aggregating
incomes over all households and then calculating the income changes as aggregates. This has
the advantage of allowing to disentangle a tax system’s built-in stabilization from discretionary
policy or behavioral effects, while general equilibrium effects will be neglected (Dolls et al.,
2012, p. 282).
The stabilization coefficient can be written as
∑ ∆YiD = (1 − τ I ) ∑ ∆YiM
i
i
⇔ τI = 1 −
∑i ∆YiD
.
∑i ∆YiM
τ I can be interpreted as the fraction of a shock that is absorbed by the tax benefit system.
Using (2.2), it is possible to decompose the income stabilizer into the stabilizing effect
provided by taxes, social insurance contributions and benefits. By definition, these three
individual stabilizers add up to the overall income stabilizer
τ I = τTI + τSI + τBI =
∑i ∆Ti
∑ ∆Si
∑ ∆B
+ i M
− i Mi .
M
∑i ∆Yi
∑i ∆Yi
∑i ∆Yi
(2.3)
So far, the Social Insurance Contributions (SIC) included those paid by the employees as well
as SIC paid by the self-employed. Social insurance contributions paid by the employers are
left out. This is ultimately an assumption of the incidence of the social insurance contributions.
Throughout this paper, we make the assumption that the employers have to bear their share
of the social insurance contribution and can not shift it to employees, so that it will not affect
the employees’ wages. This assumption is somewhat strong as employers may well try to shift
their share of the SIC to employees. Dolls et al. (2012, p. 286) compare income stabilization
coefficients including social insurance contributions by employers and find that only in some
countries the inclusion of the employers SIC substantially increases stabilizers. Results are not
directly comparable as the shock is now simulated on the gross income, which they define as
market income plus employers’ social insurance contributions.
9
There can be differences in the results, depending whether the changes in market incomes
and tax-benefit payments are summed up over the population first, or whether a stabilizer
is calculated individually for each household. It can happen that a household or individual
finds itself on a kink or discontinuity of the tax schedule, where extreme values for the tax and
benefit payments can occur. The results of this are very large stabilizers for some observations.
If the individually calculated income stabilizers are later aggregated into a value for the whole
country by calculating the population-weighted average over all observations, these outliers
can substantially distort the results. A correction can be made by dropping the top and bottom
percentile of income stabilizers from the sample. Still, the results differ. It is also possible,
that in some cases the individual stabilizer becomes negative. Then it will “cancel out” the
stabilizer of other observations, leading to a downward bias of estimated stabilizers.
2.2 Short Term Effects of Policy Adjustments
The income stabilization coefficient, or “built-in flexibility” measure, is constructed in a way
that it measures the long-term, or steady state, stabilization capacity of a tax and transfer
system. It does not take into account the additional effect on household disposable incomes
that occurs when changes of the tax and transfer system come into effect, nor should it do so.
Instead, it is a measure of a certain property of the tax and transfer system. In times of severe
disruptions in household incomes, to focuse exclusively on the measure of a long-term property
would be incomplete: The introduction of, for example, tax increases can be de-stabilizing in
the short run, adding to an already dramatic decline in household incomes, although it certainly
increases our measure of an automatic stabilization coefficient. Hence we complement the
income stabilization measure by a new measure that takes into account the additional burden
to be borne by households on introduction of the new policy. The measure is constructed as
follows. We now calculate the difference in disposable incomes for household i when subject
to tax policy in period t and when subject to tax policy in period t + 1:
θitI
=
∆YitM − (YitD − YiD(t+1) )
∆YitM
= 1−
= 1−
|
i
h
YitM − ( Tit + Sit − Bit ) − YiM
−
T
+
S
−
B
i ( t +1)
i ( t +1)
i ( t +1)
( t +1)
∆YitM
YitM − YiM
( t +1)
∆YitM
{z
=0
+
( Tit − Ti(t+1) ) + (Sit − Si(t+1) ) − ( Bit − Bi(t+1) )
∆YitM
}
2.3 Macro Budget-Measures
In principle, discretionary and structural fiscal policy measures are not trivially observable. A
common approach to single out discretionary and structural, or long-term, components of fiscal
policy is to decompose government budgets into a cyclical and a cyclically-adjusted (structural)
component (see Girouard and André (2005), and updates by Mourre et al. (2013) and Mourre
et al. (2014)). Using this approach, the cyclically adjusted budget CAB is the residual of the net
10
borrowing as a fraction of GDP (B/Y) and the cyclical component of the budget (CC):
CAB =
B
− CC
Y
As B/Y can be observed from government budget, finding a representation of the cyclical
component allows the calculation of the structural balance as the residual. The EU method
proposes that the cyclical component is the product of the economy’s deviation from potential
GDP (output gap) and a measure of how the budget changes with respect to changes in
GDP: CC = ε · OG, where OG = (Y − Y p )/Y p denotes the output gap, and ε denotes the
semi-elasticity of the budget, measuring the change in the budget in percentage-points with
respect to a percentage change in GDP. To finally derive a measure of the automatic stabilization
effect on economic activity, some indicator of how GDP responds to government intervention
is necessary: we call this the fiscal multiplier, FM. The stabilizing effect on economic activity
(AS) can then be written as the product of the cyclical component of government budget and
the fiscal multiplier:
AS = OG · ε · FM
(2.4)
It becomes apparent that the two key parameters in the calculations above are the budgetary
semi-elasticity ε, and the output gap OG (see Mourre et al., 2014, p. 9), so it is worth looking
more into it. The semi-elasticity is defined as follows:
d YB
ε = dY
Y
Further, it can be shown (see Mourre et al., 2014, p. 10) that
CAB =
B
Bp
− ε · OG = p ,
Y
Y
that is, the cyclically-adjusted budget is defined as the budget balance when output is at its
potential. The semi-elasticity, in contrast, is the percentage point change of actual net borrowing
as a fraction of GDP with respect to a percentage change in GDP. It can be further broken down
into a revenue and an expenditure component:
d YB
d YR
d G
Y
ε = dY = dY − dY
Y
Y
Y
In other words, the budgetary semi-elasticity is the difference of the semi-elasticity of revenue
and the semi-elasticity of expenditure. To fix ideas, consider the case of a recession. The
economy is below potential GDP, and the growth rate of GDP (dY/Y) is negative.1 We expect
the semi-elasticity of the revenue-to-GDP ratio to be close to zero, as taxes usually follow
the cyclical pattern of GDP. Total revenue as a fraction of GDP will hence remain roughly
constant (Mourre et al., 2014). The semi-elasticity of expenditure, meanwhile, is negative. Only
unemployment-related spending is cyclical, but it represents only a small amount out of total
spending. Hence, spending does not change much over the business cycle2 , while GDP does,
1 Note
2 This
that growth rate and (deviation from) potential GDP are distinct concepts.
may be different in severe recessions with austerity measures.
11
so the ratio of expenditures to GDP changes over the business cycle. In particular, this ratio
increases in bad times and decreases in good times. The change of the ratio with respect to
GDP growth rate is hence negative. In a recession, with negative GDP growth and GDP below
potential, we would expect the expenditure elasticity to take on a positive sign. Assuming a
zero revenue semi-elasticity, the overall budget elasticity has a negative sign. It can then be
seen from equation (2.4) that, given a negative output gap and some (positive) fiscal multiplier,
a stabilizing effect on economic activity occurs.
2.4 Scenarios
As a stylized “average crisis shock”, we consider a combination of a proportional decrease
in household incomes by 5% for all households and all countries, and an increase in the
unemployment rate by 5 percentage points. We model the increase in the unemployment
rate through reweighting. In particular, we increase the demographic weights of households
already observed to be unemployed in the data. In other words, we implicitly assume that high
productivity households are less likely to be affected by unemployment.
2.5 Data
We use the European microsimulation model EUROMOD, which comes with adjusted versions
of the EU-SILC database for each country. The EU-SILC is a harmonized, cross-sectional
dataset for the EU member states. For the macro measures, we rely on data from the AMECO
Database.
2.6 EUROMOD
To calculate the disposable incomes from (modified) gross incomes the European microsimulation tool EUROMOD is used. It contains the tax and benefit rules for 27 countries of
the European Union3 for several years and is able to apply them to a micro data set. Also,
simulations are possible, in the sense that the existing policies can be changed to evaluate
counterfactual reforms, for example, a change in the tax rate, tax schedule, or a change in
certain benefits. Datasets are available for many years, and these can be combined with many
of the different tax policies. One could, for example, apply the 2010 German tax system to the
micro data set of year 2008. To make the nominal values of incomes and policy parameters
from different years comparable, EUROMOD can use inflation data to uprate the values to the
same base year. The uprating factors are country and income specific (Jara and Tumino, 2013,
p. 32).
Furthermore, it is possible to introduce certain country-specific policies in another country
(“policy swapping”), for example, introduce the Belgian pension system for the elderly in the
UK. In the context of this thesis, however, EUROMOD is used as a simple tax-benefit calculator,
and not primarily as a simulation tool.
3 Since
July 1st 2013, Croatia is also a member of the European Union. It is, however, not yet included in
EUROMOD.
12
Gross incomes after the shock are simply calculated by multiplying observed household
incomes by 0.95. EUROMOD will then calculate the corresponding disposable income, that
is, apply the appropriate tax rules to calculate the after-tax income and then simulate social
insurance contributions as well as benefits and pensions the individual may be eligible for
(conditional on demographic characteristics and labor market characteristics, such as the
income from a previous employment or duration of former job) and add those to the after-tax
income. Sutherland and Figari (2013) provide an overview of the recent version of EUROMOD,
including applications, such as Bargain, Dolls, Fuest, Neumann, Peichl, Pestel and Siegloch
(2012) and more.
Table 1 provides an overview of datasets and policies used in this thesis for the simulation.
EUROMOD comes with micro data sets for all countries. The data sets are usually based on the
EU-SILC, which is a cross sectional survey of European households provided by Eurostat (2012).
In Austria, Belgium, Bulgaria, the Czech Republic, Greece, Spain, Italy, Lithuania, Luxembourg,
Poland and Slovakia the national versions of SILC, provided by the respective national statistics
institute, is used, either directly or in addition to the EU-SILC version (Sutherland and Figari,
2013, p. 9). In the UK, the FRS dataset is used.4 The datasets come from the 2008 version
of EU-SILC. The year refers to the year the survey is conducted (the data collection period).
Participants are usually asked to report the incomes of the previous year (the income year;
usually 2007). However, there are three exceptions. For France and Malta, the 2007 and 2009
EU-SILC versions are used, respectively. These datasets are chosen because, in the case of
Malta, 2009 is the first micro-data set to be available, while for France, the 2007 version is
“chosen to take advantage of good national SILC data for validation in this year” (Jara and
Sutherland, 2013, p. 7). The FRS used for the UK is the 2008/2009 release, and incomes are
reported for the current fiscal year (April until March).
Due to data limitations EUROMOD does not allow to use the 2008 datatset with all tax
legislations from 2007 until 2013. If it is not possible to keep the 2007 dataset constant for
all years, we switch to a more recent dataset. Table 1 gives an overview what dataset-policy
combinations we use.
The recent economic downturn began to affect Europe by the end of 2008 (Sutherland and
Figari, 2013, p. 16). As most data is of incomes in 2007 and the majority of the tax policies was
already in effect in 2008, the data and simulations can be expected to be clear of endogeneity
caused by policy responses that have occurred since the start of the crisis (Dolls et al., 2012,
p. 280).
In the context of the tax and benefits simulation it is important to keep in mind that it is
possible that the legal tax rules and regulations are not fully respected, or that households, in
spite of being entitled to certain benefits, refrain from actually making use of them, for example
due to a social stigma or some other form of costs for the households. Due to a lack of available
data, EUROMOD does not explicitly model tax evasion or the non-take-up of benefits. This
means that, in general, both a full benefits take-up as well as full tax compliance is assumed for
most countries. The problem that can arise is that the amounts of taxes payments and received
benefits is overestimated in the simulation, with the magnitude of the effect varying across
countries (Sutherland and Figari, 2013; Jara and Tumino, 2013). When calculating income and
4 According
to Sutherland and Figari (2013), the FRS will become the basis for the EU-SILC in the UK from 2013.
13
labor supply stabilizers, this could, in turn, lead to an overestimation of those stabilizers. The
full take-up and tax-compliance assumptions is regularly interpreted as describing the intended
effects of the tax and benefit system.Although not explicitly modeled, EUROMOD allows for a
simple correction at household level of benefits non-take up and tax evasion. These corrections
can be switched on and off or adjusted to suit the users needs (Sutherland and Figari, 2013,
p. 12).
The non-take-up of benefits is calculated for Greece, Ireland, Belgium and the United
Kingdom5 . Non-take-up is accounted for by assuming that only a certain proportion of
households, selected randomly from the sample, takes up their entitlement. This correction
applies to the whole household, and separately for each benefit. The fraction of non-take-up
households is taken from external statistics (Sutherland and Figari, 2013, p. 11).6
Tax evasion is accounted for in Bulgaria and Italy.7 The correction is done by splitting
self-employment and employment incomes in to components, with the first component being
reported properly to the authorities, while the second component is evaded (Sutherland and
Figari, 2013, p. 11).
Like other survey data, there are certain drawbacks to keep in mind when using EUROMOD.
For example, financial incomes are not well covered in the data, affecting the simulation of
capital taxes. Also, as SILC data are aggregated in annual terms, the necessary monthly-based
means-tests of incomes and assets for certain benefits cannot be carried out as detailed as
they should. Furthermore, the harmonization that is done (and that provides one of the great
advantages of comparability over the countries) is problematic as the tax and transfer systems
are very heterogeneous across countries. As benefits are aggregated according to their function
(such as old age, unemployment etc.), individual payments have to be recovered using some
kind of imputation procedure, which will reduce the precision of the estimates (Sutherland
and Figari, 2013; Figari, Levy and Sutherland, 2007).
Several adjustments are made to bring the EU-SILC data sets in a format that is expected
by EUROMOD. For instance, the EU-SILC variables are all in annual terms. To comply with
EUROMOD, they are converted into monthly values. Also, many incomes and financial
variables are first reported on household level in SILC and are then disaggregated to an
individual level.
14
Figure 5: Income Stabilization Coefficient 2013
Income Stabilization Coefficient
Uniform, Combined Shock 2013
.6
.5
.4
.3
.2
.1
0
BG LT CY SK LV EL HU SE EU27 UK LU FI AT DE BE
EE MT PL CZ ES RO PT SI IT FR EA18 NL DK IE
Direct Tax
SIC
Benefits
Source: Own calculations using EUROMOD. Calculated as the aggregate change in disposable income as a fraction
of market income.
3 Results
Figure 5 shows the results of the automatic stabilization coefficient using the 2013 tax policy.
The graph shows the calculations of equation (2.3), decomposed by component of the tax and
transfer system. Stabilizers are heterogenous across countries, ranging from a little over 0.2 in
Eastern and Southern European countries (Bulgaria, Baltics, Malta, Cyprus) at the lower end to
values around 0.5 in Western European and Nordic countries (Belgium, Germany, Denmark,
Austria). Ireland is an exception, with the second highest coefficient over 0.5. Ireland has
financed its budget consolidation after the crisis through tax increases, hence the increase in
automatic stabilizers.
3.1 Automatic Stabilizer over Time
Figure 6 summarizes central results. Changes in income stabilization coefficients over the years
are different across countries. Countries that have experienced major changes include Latvia
(increase after 2009), France (decrease after 2010), Ireland (increase after 2008), Greece (increase
after 2010), while other countries remain relatively constant. The evolution of stabilizers for the
5A
non-take-up calculation procedure in the EUROMOD parameter sheet is possible for Germany, but has been
switched off. If it is on, it improves the estimation of poverty and inequality, but will underestimate the number
of recipients of unemployment assistance, means-tested old-age assistance as well as general social assistance
(Jara and Sutherland, 2013, p. 40). As poverty and inequality is not the focus of this thesis, no correction was
made.
6 Details about these statistics can be found in Jara and Sutherland (2013, pp. 39–40).
7 Newer versions of EUROMOD will include other “countries where tax evasion is a widespread phenomenon”
(Sutherland and Figari, 2013, p. 11), such as Greece.
15
Figure 6: Income Stabilization Coefficients
Income Stabilization Coefficients
.5
TAU
.6
.5
TAU
.6
.4
.4
.3
.3
.2
.2
2006
2008
AT
2010
BE
DE
2012
FR
2014
NL
2006
LU
2008
EE
.5
.5
DK
LV
2012
SI
2014
SK
LT
TAU
.6
TAU
.6
FI
2010
.4
.4
.3
.3
.2
.2
2006
2008
CY
EL
2010
ES
IE
2012
SE
2014
HU
RO
2006
2008
IT
MT
2010
BG
CZ
2012
UK
2014
PL
PT
Source: Own calculations using EUROMOD. Calculated as the aggregate change in disposable income as a fraction
of market income.
EU-27 and the Euro Area (EA-18) shows, that averages remain relatively stable over time. In
2010, a slight in Automatic Stabilizers can be seen. What is striking is that stabilizers are much
higher in the EA-18 (average) than in the EU-27 countries (on average).
Figure 7 shows the change of the income stabilzation coefficient in 2007 to 2013. The largest
changes have occured in Hungary (-0.16), which has since 2007 adopted a flat tax, and Ireland,
which has increased taxes as a budget consolidation measure. Many of the countries hat have
been hit hard during the crisis, such as Estonia, Cyprus, Portual, Grees, Spain, and to a lesser
extent Italy, UK and France, have increased automatic stabilizers since 2007. Countries with
relatively high stabilizers, such as Denmark, Germany and Sweden, have decreased stabilizers.
Others, such as Belgium, Austria, Netherlands and Finland have changed stabilizers not at all
or only moderately.
Graph 8 shows the first differences of τ from year to year. If the country is plotted to the right
(left) hand side of the vertical bar, it has increased (decreased) stabilizers from the previous
year to the given year. It shows that shortly after the crisis (2007/2008, upper left panel), only
few countries saw an increase in the stabilization coefficient. Instead, countries hit by the crisis
(Spain, Baltics), saw a decrease in τ, due to tax reliefs in an attempt of stimulating the economy.
Widespread consolidation policies seem to push countries towards higher automatic stabilizers
from 2010/2011 (bottom left panel).
Figure 9 plots the changes in the stabilization coefficient attributed to social insurance
16
.6
Figure 7: Change in τ: 2013 vs. 2007
BE
DK
DE
.5
HU
NL
AT
IE
SI
.4
TAU 2007
FI
SE
IT UK
FR
RO
CZ
PL
.3
LU
SK
PT
ES
LV
BG
EL
LT
MT
EE
.2
CY
-.16
-.14
-.12
-.1
-.08
-.06
-.04
-.02
0
.02
.04
.06
.08
.1
.12
Delta TAU 2007-2013
Figure 8: XXX REARRANGE NAMES XXX – AS Changes: Year-to-year 2007-2013: τ
.6
.6
.6
Change in TAU after -5% income & +5% unemployment shock 2007 vs. 2008-2013
BE
BE
.5
SI
IT UK
LU
CZ RO
PT
PLSK
ES
EL
LV
BG
LT
FR
SIIT FR UK
LU
RO
CZ
PT
SK PL EL
BG ES
LT
MT
MT
-.02
0
.02
.04
.06
.08
.1
-.04
0
.06
.08
.1
.02
First Diff TAU 2011
.04
.08
.1
EE
-.04
-.02
0
AT
NL
TAU 2007
ES
FI
SE
IE
SI ITUK
RO
.3
RO
CZ
EL SKPL
BG
LV LT
MT
.2
.2
0
.06
HU
ES
MT
CY
.02
First Diff TAU 2012
.04
LU
CZ
FR
PT
SK
ELPL
LV
BG
LT
EE
CY
.2
PT
EE
CY
-.02
.5
.5
PT
EL
.04
DK
DE
NL
FI
IE
SE
SI FRUKIT
LU
.4
LU
RO
CZ
PL
ES
LV
SK BG
LT
MT
.3
TAU 2007
IE
.02
BE
AT
SI UK
IT
-.04
0
First Diff TAU 2010
HU
.3
FR
-.02
.6
.6
.5
SE
-.04
DK
DE
NL
AT
LV
CYEE
-.06
BE
HU
FI
.4
.04
First Diff TAU 2009
BE
DK
DE
TAU 2007
.02
.6
First Diff TAU 2008
-.02
.2
EECY
-.06
.4
-.04
.2
.2
EE CY
-.06
FI
SE
IE
.4
IE
.4
TAU 2007
HU
AT
NL
FI
SE
.3
CZ RO
ES PT
PLSK EL
LV
MT
LT
DK DE
TAU 2007
.5
.5
IT UK SI
LU FR
.4
.3
TAU 2007
SE IE
BG
HU
NL
AT
AT
NL
FI
BE
DKDE
HU
.3
DK
DE
-.04
-.02
0
.02
.04
First Diff TAU 2013
contributions, τSIC .
There is a negative correlation between size of the SIC-based stabilizer and change in the
SIC-based stabilizer from 2007 to 2013, that is, countries with a lower stabilzer have increased,
while those with a higher stabilizer have decreased or left constant the stabilizers.
17
Figure 9: AS Changes 2007-2013: τSIC
.2
SI
.15
HU
AT
DE
PL
BE
SK
NL
LU
BG
IT
EL
PT
RO
.1
TAUSIC 2007
FR
CZ
UK
LV
DK
IE
FI
.05
MT
SE
ES
CY
LT
0
EE
-.04
-.02
0
.02
.04
Delta TAUSIC 2007-2013
3.2 Macro-Measures: Automatic Stabilization and Austerity
Figure 10: EU-27: Output Gap and GDP Growth counterfactual
Delta GDP
w/o AS - low
w/o AS - intermediate
w/o AS - high
2014
2013
2012
2011
2010
2009
2008
4
3
2
1
0
-1
-2
-3
-4
-5
-6
2007
% of GDP
EU27
Output gap
Source: AMECO, Note: Estimate for 2014
The macro-based AS coefficient differs from the micro estimates, in that the micro estimates
18
represent “upper bounds” on the macro coefficient. The difference arises because the stabilizing
effect of (direct) taxes measured in the micro context is larger than in the macro estimation.
In the latter case, the revenue elasticity is close to zero (which measures the change in the tax
receipts when GDP changes), while tax payments react a lot on household level.
Also, the macro elasticity measures includes other margins, such as labor supply adjustments,
that we abstract from in our analysis.
Figure 11: EA-18: Output Gap and GDP Growth counterfactual
Delta GDP
w/o AS - low
w/o AS - intermediate
w/o AS - high
2014
2013
2012
2011
2010
2009
2008
4
3
2
1
0
-1
-2
-3
-4
-5
-6
2007
% of GDP
EA18
Output gap
Source: AMECO, Note: Estimate for 2014
Source: Own calculations using EUROMOD. Calculated as the aggregate change in disposable income as a fraction
of market income.
4 Conclusion
In this paper we analyze the changes in the tax and transfer system of the EU27 over the course
of the crisis and its aftermath. Based on harmonized European micro data and counterfactual
simulation techniques, we analyze how reforms of tax-benefit systems in the period 2007-2013
have affected the automatic stabilization capacity for households in the EU-27. We isolate this
effect from discretionary fiscal policy measures as well as behavioral responses of households
by holding constant pre-crisis household income data and demographic characteristics and
combining it with the tax and benefit systems from 2007-2013.
We assess the extent to which member states had room for fiscal policy by analyzing
government deficits and their cyclical and cyclically-adjusted components with a focus on the
role that automatic fiscal stabilizers played. We complement these results with an analysis
of macroeconomic data on government debt and the sensitivity of government budgets with
19
respect to output fluctuations, and provide (counterfactual) growth rates that would have
emerged in the absence of automatic stabilizers over the crisis. We find automatic stabilizers to
be generally heterogeneous across countries—both in levels and in terms of policy changes
over the crisis. Stabilization coefficients vary from less than 25% in Eastern European countries
to more than 50% in Belgium, Germany, and Denmark. Countries with stronger automatic
stabilizers were relatively resilient during the crisis, while those with weak automatic stabilizers
experienced major economic contractions and increases in unemployment. In most countries
that changed their tax and benefit system, policy adjustments strengthened automatic stabilizers
in the long-term perspective by fiscal consolidation measures such as tax increases which,
however, can have destabilizing effects in the short term. Relative to a counterfactual without
automatic stabilizers, the economic upswing has been dampened in 2007 and 2008, while there
has been a mitigation of the decline in GDP from 2009 onwards. Since then, due to negative
output gaps, automatic stabilizers have had a growth enhancing effect in the euro area.
20
References
Agell, Jonas and Mats Dillén, “Macroeconomic externalities: Are Pigouvian taxes the answer?,”
Journal of Public Economics, 1994, 53, 111–126.
Auerbach, Alan J. and Daniel Feenberg, “The Significance Of Federal Taxes As Automatic
Stabilizers,” Journal of Economic Perspectives, 2000, 14 (3), 37–56.
Bargain, Olivier, Mathias Dolls, Clemens Fuest, Dirk Neumann, Andreas Peichl, Nico Pestel, and Sebastian Siegloch, “Fiscal Union in Europe? Redistributive and Stabilising Effects
of a European Tax-Benefit System and Fiscal Equalisation Mechanism,” Economic Policy, 2012,
p. forthcoming.
Dolls, Mathias, Clemens Fuest, and Andreas Peichl, “Automatic Stabilizers And Economic
Crisis: US Vs. Europe,” Journal of Public Economics, 2012, 96, 279–294.
Eurostat, “2010 Comparative EU Intermediate Quality Report,” October 2012.
Fatás, Antonio and Ilian Mihov, “Government Size and Automatic Stabilizers: International
and Intranational evidence,” Journal of International Economics, 2001, 55, 3–28.
Figari, Francesco, Horacio Levy, and Holly Sutherland, “Using theEU-SILC for Policy Simulation: Prospects, some Limitations and Suggestions,” EUROMOD Working Paper No. EM
1/07, January 2007.
Galí, Jordi, “Government Size and Macroeconomic Stability,” European Economic Review, 1994,
38, 117–132.
Girouard, Nathalie and Christophe André, “Measuring Cyclically-Adjusted Budget Balances
for OECD Countries,” OECD Economics Department Working Papers, No. 434, 2005.
Grant, Charles, Christos Koulovatianos, Alexander Michaelides, and Mario Padula, “Evidence On the Insurance Effect of Redistributive Taxation,” Review of Economics and Statistics,
November 2010, 92 (4), 965–973.
Immervoll, Herwig, HEnrik Jacobsen Kleven, Claus Thustrup Kreiner, and Emmanuel Saez,
“Welfare Reform in European Countries: A Microsimulation Analysis,” The Economic Journal,
January 2007, pp. 1–44.
Jara, H. Xavier and Alberto Tumino, “Tax-Benefit systems, income distribution and work
incentives in the European Union,” International Journal of Microsimulation, 2013, 6 (1), 27–62.
and Holly Sutherland, “Baseline Results From the New EU27 EUROMOD (2007–2010),”
EUROMOD Working Paper No. EM 3/13, 2013.
Kletzer, Kenneth, “Taxes And Stabilization In Contemporary Macroeconomic Models,” International Tax and Public Finance, August 2006, 13 (4), 351–371.
Kniesner, Thomas J. and James P. Ziliak, “Explicit versus Implicit Income Insurance,” Journal
of Risk and Uncertainty, July 2002, 25 (1), 5–20.
21
and , “Tax reform and Automatic Stabilization,” American Economic Review, 2002, 92 (3),
590–612.
Low, Hamish W., “Self-Insurance In a Life-Cycle Model of Labour Supply and Savings,” Review
of Economic Dynamics, 2005, 8, 945–975.
Mabbett, D. and W. Schelkle, “Bringing Macroeconomics Back into the Political Economy of
Reform: the Lisbon Agenda and the ‘Fiscal Philosophy’ of EMU,” Journal of Common Market
Studies, 2007, 45 (1), 81–103.
Mattesini, Fabrizio and Lorenza Rossi, “Monetary Policy and Automatic Stabilizers: The Role
of Progressive Taxation,” Journal of Money, Credit and Banking, August 2012, 44 (5), 825–862.
Mourre, Gilles, Caterina Astarita, and Savina Princen, “Adjusting the Budget Balance for the
Business Cycle: The EU Methodology,” European Economy Economic Papers 536, 2014.
, George-Marian Isbasoiu, Dario Paternoster, and Matteo Salto, “The Cylcically-Adjusted
Budget Balance Used in the EU Fiscal Framework: An Update,” European Economy Economic
Papers 478, 2013.
Pechman, Joseph A., “Responsiveness of the Federal Individual Income Tax to Changes in
Income,” Brookings Papers on Economic Activity, 1973, 2, 385–427.
, Federal Tax Policy Studies of Government finance: 2, Brookings Institution, 1987.
Sutherland, Holly and Francesco Figari, “EUROMOD: The European Union Tax-Benefit
Simulation Model,” EUROMOD Working Paper No. EM 8/13, March 2013.
22
Table 1: EUROMOD: Countries and Datasets
Country
Collection
Year
AT
BE
BG
Austria
Belgium
Bulgaria
CY
Cyprus
CZ
Czech Republic
DE
DK
EE
EL
ES
Germany
Denmark
Estonia
Greece
Spain
FI
Finland
FR
France
HU
Hungary
IE
IT
LT
Ireland
Italy
Lithuania
2010
2008
2008
2008
2008
2008
2010
2008
2010
2007
2010
2008
2010
2008
2008
2008
LU
Luxembourg
2010
2008
LV
Latvia
MT
NL
PL
Malta
Netherlands
Poland
PT
RO
Portugal
Romania
SE
SI
Sweden
Slovenia
SK
Slovakia
UK
United Kingdom
2008
2008
2008
2008
2010
2008
2010
2008
2010
2009
2008
2008
2008
2008
2010
2008
2008
2010
2008
2010
2008/9
Source
National SILC
EU-SILC
EU-SILC
EU-SILC
EU-SILC + national variables
EU-SILC
EU-SILC
EU-SILC
National SILC
National SILC
EU-SILC
EU-SILC
EU-SILC
EU-SILC
National SILC
EU-SILC + national variables
EU-SILC + national variables
EU-SILC
EU-SILC
EU-SILC
EU-SILC + national variables
EU-SILC
EU-SILC
EU-SILC
EU-SILC
National SILC
FRS
Policy
Year
Tax
Evasion
Non
Take-up
2007-2013
2007-2013
2007-2013
2007-2012
2013
2007-2012
No
No
Yes
No
No
Yes
No
No
No
No
No
No
No
No
No
No
No
No
Yes
No
No
No
No
Yes
2013
2007-2013
2007-2013
2007-2013
2007-2013
2007-2011
2012-2013
2007-2012
2013
2007-2010
2011-2013
2007-2008
2009-2013
2007-2013
2007-2013
2007-2012
No
No
No
Yes
No
Yes
No
No
2013
2007-2012
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
Yes
2013
2007-2012
2013
2007-2013
2007-2013
2007
2007-2013
2007-2012
2013
2007-2013
2007-2010
2011-2013
2007-2012
2013
2008-2013
Source: Jara and Sutherland (2013).
Notes: Collection year also refers to the version of the dataset. Policy year indicates the EUROMOD tax
policy that is applied. Tax evasion and Non Take-Up refer to the simple EUROMOD corrections for tax
evasion and the only partial take-up of certain benefits. EUROMOD does not explicitly model either;
see section 2.6 in the text for more details.
23

Similar documents

×

Report this document