A joint initiative of Ludwig-Maximilians University’s Center for Economic Studies and the Ifo Institute
CESifo GmbH · Poschingerstr. 5 · 81679 Munich, GermanyTel.: +49 (0) 89 92 24 - 14 10 · Fax: +49 (0) 89 92 24 - 14 09E-mail: [email protected] · www.CESifo.org
CE
Sifo
Co
nfer
ence
Cen
tre,
Mun
ich
Area Conferences 2013
CESifo Area Conference on
Public Sector Economics11–13 April
Beyond the Labor Income Tax Wedge: The Unemployment-Reducing Effect of Tax Progressivity
Etienne Lehmann, Claudio Lucifora, Simone Moriconi and Bruno van der Linden
Beyond the Labor Income Tax Wedge: The
Unemployment-Reducing Effect of Tax Progressivity∗
Preliminary version - Please, do not quote without authors’
permission
Etienne LEHMANN †
ERMES (TEPP) University Pantheon-Assas Paris 2 and CREST
Claudio LUCIFORA‡
Universita Cattolica del Sacro Cuore and IZA
Simone MORICONI§
Universita Cattolica del Sacro Cuore, Milano
Bruno VAN DER LINDEN¶
FNRS and IRES Universite Catholique de Louvain
March 26, 2013
Abstract
This paper argues that, for a given overall level of labor income taxation, a more progres-sive tax schedule reduces the unemployment rate and increases the employment rate. Wefirst review some theoretical arguments: progressivity increases employment because em-ployment is much more responsive for low-paid workers and because progressivity induces awage-moderation effect. We then test our arguments on a panel of 21 OECD countries over1998-2008. We empirically capture progressivity by the change in the burden of taxationbetween 67% and 167% of the average tax rate. Our empirical findings address potential en-dogeneity issue and confirm that controlling for the burden of taxation at the average wage,a more progressive taxation reduces the unemployment rate and increases the employmentrates.
Keywords:
JEL code:
∗We wish to thank participants at a seminar at CREST, with a particular mention to Pierre Cahuc, FrancoisFontaine and Jean-Baptiste Michau for their valuable comments and suggestions. Usual caveats apply.†Email: [email protected]. Address: CREST, Timbre J360, 15 boulevard Gabriel Peri, 92245,
Malakoff Cedex, France. Etienne Lehmann is also research fellow at IRES-Universite Catholique de Louvain,IDEP, IZA and CESifo. Etienne Lehmann is also a junior member of IUF which is gratefully acknowledged forits financial support.‡Email: [email protected]. Address: Department of Economics - Universita Cattolica 1, Largo
Gemelli, 1 - 20123 Milano, Italy.§Email: [email protected]. Adress: Department of Economics - Universita Cattolica 1, Largo Gemelli
- 20 123 Milano, Italy. Simone Moriconi is also associated to CREA, University of Luxembourg.¶Email: [email protected]. Address IRES, Universite Catholique de Louvain, Place Mon-
tesquieu 3, B1348, Louvain-la-Neuve, Belgium. Bruno Van der Linden is also research fellow at IZA, CESifo andexternal member of ERMES - Universite Paris 2.
1
I Introduction
There is a general consensus among economists that higher labor income taxation has a detri-
mental effect on unemployment. Empirical studies have shown the existence of a positive rela-
tionship between tax wedge on labor income and equilibrium unemployment1. Income taxation,
however, is a rather complex policy with multiple dimensions that are only partially accounted
by the average tax wedge on labor income. Many OECD countries, after the Great Crisis, have
experienced higher unemployment and larger public debt, being confronted with the need to
combine fiscal consolidation measures with policies to curb unemployment. For this reason, a
better understanding of the effects of labor income taxation on the functioning of the labor mar-
ket seems important. In particular, we need a better description on how the different dimensions
of labor income taxation affect labor market performance and how to limit their adverse effects
on unemployment. This paper proposes a first step in this direction by investigating the effect
of both average labor income taxation, and tax progressivity on unemployment. It argues that,
for a given aggregate level of labor income taxation, a more progressive tax schedule can reduce
unemployment.
We first review theoretical arguments in support of the unemployment-reducing effect of tax
progressivity. The first mechanism is a composition effect that occurs because the labor demand
for low-skilled workers is more sensitive to taxation as compared to high-skilled workers, also
gross wage for low-skilled workers is deemed to be more rigid than that of high-skilled workers.
The second mechanism is a more traditional wage moderation effect. Since a more progressive
tax schedule makes any increase in the after-tax wage more costly for employers, the latter will
resist more any wage increase claimed by employees, thus moderating the adverse wage effect
on labor demand.2 We also argue that these unemployment-reducing effects of tax progressivity
are very likely to remain in the presence of labor supply responses. Although tax progressivity
may be detrimental to labor supply along the intensive margin, as typically argued in public
finance, tax progressivity remains beneficial for employment (and unemployment), with only an
ambiguous total effect on aggregate production. Next, we empirically investigate the effects of
taxation on labour market performance using a panel data of 21 OECD countries over 1998-
2008. We derive our tax indicators for the total tax wedge - for workers at the average wage -,
and tax progressivity - measured comparing the fiscal wedge of workers at 67% and at 167% of
the average wage -, from the OECD tax database. In particular, we exploit differences in output
shocks and labour market institutions, across countries and over time, to assess the overall effects
of fiscal policies on unemployment.
Our paper contributes to the well-established literature that uses panel data to explain un-
employment patters across OECD countries.3 Empirical studies typically investigate the impact
1e.g. Layard and Nickell (1999), Daveri and Tabellini (2000), Nickell et al. (2005) among others.2See e.g. Hersoug (1984), Pissarides (1985, 1998), Lockwood and Manning (1993).3See the time series analysis on different OECD countries by Bean Layard and Nickell (1986), Layard Nickell
and Jackman (1991) and Nickell and Layard (1999) and the panel data analyses by Blanchard and Wolfers (2000),Daveri and Tabelinni (2000), Belot and Van Ours (2004), Nickell Nunziata and Ochel (2005), Griffith et alii (2007),
2
of macroeconomics shocks and (time-varying) labor market institutions on aggregate unemploy-
ment. In this literature, labor income taxation is generally captured by a single indicator, the
tax wedge for the average worker, which is found to be a key determinant of the unemployment
rate (Daveri and Tabellini (2000), Nickell et alii (2005)).
Another empirical literature to which our paper is related explores the effect of tax progres-
sivity on wages using time series data, either at the aggregate level or at specific industry or
sub-groups of workers.4 The typical result is that tax progressivity reduces the gross wage, at
least for blue-collar workers.5 Note, however, that the change in aggregate wage may confound
true wage responses with heterogeneous employment responses that alter the wage distribu-
tion. Such composition effects therefore make the results hard to interpret in term of a wage
moderation effect. 6
Finally, there is an extensive literature that uses micro-data to evaluate the effect of tax
reforms and making-work-pay programs in selected countries. For example, policies such as the
EITC (Earned Income Tax Credit) in the US, or the WFTC (Working Families Tax Credit) in
UK7 have been shown to improve transitions from nonemployment to employment. As these
policies shifts the tax burden away from some disadvantaged groups of employed (e.g. employed
lone parents), we interpret them in a way that is consistent with an increase in progressivity.
One advantage of the literature that uses micro-data to evaluate the effects of programs tar-
geted to specific subgroups, is the possibility to exploit quasi-experimental methods to identify
their causal effect on labor market outcomes - e.g. on the extensive margin of labor supply.
However this also comes at a cost, since the focus on selected programs in a specific country has
implications for the external validity of the results and their relevance for other countries.
Our main results support the usual findings that higher labor taxation increases unemploy-
ment. Moreover, we show that controlling for tax progressivity the estimated impact of the tax
wedge on unemployment becomes larger. The novelty of our findings, however, is the sizable
unemployment-reducing effect of tax progressivity: for any given level of taxation, we find that
a more progressive tax schedule reduces unemployment. Although not typically done in the
panel-data literature, we also address the potential endogeneity of fiscal policy. Since the fac-
tors that drive changes in taxation are often correlated with other developments in the economy,
as well as with changes in unemployment, both reverse causality and omitted variable bias are
likely to affect the estimates. Our empirical strategy exploits exogenous variations in institu-
tional, social and political factors that influence a country’s fiscal policy, to identify the effect
Bassanini and Duval (2009) among others. See also Prescott (2004), Rogerson (2005, 2007) and Rogerson andWillenius (2009) who account for the different trends in total hours of works across OECD by difference in taxpolicy in calibrated macroeconomic models.
4Malcomson and Sartor (1987), Lockwood and Manning (1993), Holmlund and Kolm (1995), see also thesurveys by Sørensen (1997) and by Røed and Strom (2002).
5Hansen Pedersen and Sløk (2000).6Brunello and Sonedda (2009) use panel data to estimate the effect of tax progressivity on wages. Manning
(1993), uses quarterly time series for the UK, and estimates also an auxiliary unemployment equation augmentedwith a tax progressivity indicator.
7e.g. Eissa and Liebman (1996) and Blundell and Shepard (2012) among many others
3
of taxation on unemployment (and employment). In practice, we instrument the tax wedge and
tax progressivity indicators using the following variables: a narrative record for the tax com-
ponents of fiscal consolidation policies, an index of trust in civil services, and a measure of the
political orientation of the parliament. Results show that OLS tend to underestimate the effects
of taxation on unemployment. According to our preferred specification, a one percentage point
decrease in the average tax rate reduces unemployment by 0.95 percentage points. This has
to be complemented by the unemployment effect of a unit increase in tax progressivity8 which
decreases unemployment by 1.14 percentage points. We also find that employment rates9 tend
to decrease with labor income taxation and to increase with tax progressivity. In line with the
common wisdom in public finance which emphasizes the disincentive effects of tax progressivity
along the intensive margin of labor supply, we find that a more progressive tax schedule has
a negative impact on average production per worker. Hence, we argue that the design of an
optimal tax schedule should not simply focus on the tradeoff between the equity gain of a more
progressive tax schedule against the adverse effect on the incentives to work harder, but should
also include the employment-enhancing (unemployment-reducing) effect of tax progressivity (See
Hungerbuhler et alii (2006) and Lehmann et alii (2011)).
The paper is organized as follows. We review the theoretical arguments on the unemployment
effects of tax progressivity in Section II. The empirical strategy is outlined in Section III, where
we also discuss the validity of our instruments. The dataset is described in Section IV and the
empirical results are discussed in Section V. Finally, Section VI concludes.
II Theoretical framework
In this section, we use a matching model a la Diamond-Mortensen-Pissarides to derive theoretical
predictions about the effects of taxation on the steady-state unemployment rate. We start with
a model without labor supply responses and then introduce participation and in-work decisions
into the model.
II.1 The model without labor supply responses
Time is continuous and discounted at the common rate r > 0. All agents are risk-neutral. An
homogeneous consumption good is produced by different types of perfectly substitutable labor
indexed by the corresponding productivity level i. The different labor markets are perfectly
separated: a type i individual can only occupy a type i job.10 Let yi, Li, Ni, ui, δi and wi
denote respectively the productivity, the level of employment, the number of participants, the
unemployment rate, the exogenous destruction rate and the pre-taxed (gross) wage (or labor
8We define a unit increase in tax progressivity as the combination of a half percentage point decrease in thetax wedge for workers at 67% of the average wage with a half percentage point increase in the tax wedge forworkers at 167% of the average wage
9The employment rate is the share of the working age population that is employed. It is thus equal to theproduct of the participation rate to one minus the unemployment rate.
10These assumptions of perfect substitution and of perfect separation are only made to simplify the exposition.
4
cost) for individuals of type i, with obviously 1− ui = Li/Ni.
We assume congestion externalities in the matching process. Following Diamond (1982),
Mortensen and Pissarides (1999) and Pissarides (1985, 2000), we assume that the flow of hirings
is given by a matching function Mi(υi, Ni − Li) of the stock υi of vacant jobs of type i and
the stock Ni − Li of unemployed of type i. Function Mi(., .) is assumed to be increasing and
concave in each of its argument and to exhibit constant returns to scale. The rate at which jobs
are filled is a decreasing function qi(.) of the tightness ratio θi = υi/ (Ni − Li) in labor market
i, with q(θi) ≡ Mi(1, 1/θi). Symmetrically, the rate at which an unemployed finds a job is an
increasing function pi(.) of tightness θi, with pi(θi) ≡Mi(θi, 1) = θiqi(θi). The equality between
exitsMi(υi, Ni−Li) out of and entries δiLi into unemployment gives the employment level and
the unemployment rate at the steady state:
Li =pi (θi)
δi + pi (θi)Ni and ui =
δiδi + pi (θi)
(1)
On each labor market i, a filled job generates a profit flow yi−wi and it provides an expected
intertemporal profit denoted Ji:
Ji =yi − wir + δi
(2)
Firms create vacancies as long as the flow cost of search ci > 0 is smaller than the expected
returns to search. The latter is equal to the rate qi (θi) at which jobs are filled times the
intertemporal value Ji of a filled job. As firms create more and more vacancies, tightness
increases and the job filling rate decreases. This occurs until the following free-entry condition
is met:ci
q (θi)= Ji =
yi − wir + δi
(3)
Combining (1) and free-entry condition (3) leads to labor demand in market i. The fraction
1 − ui of participants of type i who are employed is a decreasing function of the gross wage
wi.This relationship and its equivalent when wi is replaced by ni are denoted LD in Figure 1.
A rise in the gross wage reduces the intertemporal profit (2) made on a filled job. So, firms find
it less profitable to create jobs, tightness decreases and the unemployment rate increases.
We consider a nonlinear income tax function T (.) that only depends on wages w. The average
tax rate at wage wi is denoted τi ≡ T (wi)/wi and the net wage is ni ≡ (1− τi)wi. We call 1− τithe retention rate. A change in the average tax rate τi does not affect job creation if it holds
for a fixed gross wage wi. In the left part of Figure 1 where the gross wage wi is on the vertical
axis, a rise in the average tax rate τi does not shift the LD curve. Conversely, keeping the net
wage ni fixed, a rise in the average tax rate increases labor cost wi, thereby inducing firms to
create fewer jobs. In the right part of Figure 1 where the net wage ni is on the vertical axis, a
rise in the average tax rate τi shifts the LD curve inwards.
We denote bi the instantaneous value of being unemployed among type i individuals. This
value sums untaxed unemployment benefits and the value of time out of work. The expected
lifetime utility of a type i employed individual Ei, respectively an unemployed one Ui, verifies
5
wi WS
A
B
Decline in ψi
Rise in τi
θi
1-ui
LD
C
ni WS
Rise in τi
Decline in ψiA
θi
1-ui
LDRise in τi
B
C
Figure 1: The effects of taxation
the following asset equation:
r Ei = wi − T (wi) + δi (Ui − Ei) (4a)
r Ui = bi + pi (θi) (Ei − Ui) (4b)
The permanent income rEi of an employed worker of type i is equal to her instantaneous
utility wi − T (wi) minus the average loss δi (Ei − Ui) in case of job destruction. A symmetric
interpretation applies for unemployed workers. We assume Nash bargaining over the wage and
denote γi ∈ [0, 1) workers’ bargaining power. We show in Appendix A that:
Ei − Ui1− τi
=γi
1− γiΨi Ji (5)
where Ψi is the Coefficient of Residual Income Progression (hereafter the local CRIP) at wage
wi defined by Musgrave and Thin (1948) as:
Ψ(w) ≡ 1− T ′ (w)
1− T (w)w
= 1 +d ln
(1− T (w)
w
)d lnw
(6)
A one percent increase in the gross wage increases the net wage by a relative amount equals
to the CRIP. The latter is also equal to one plus the wage elasticity of the retention rate
1− (T (w)/w). A higher CRIP comes from a lower marginal tax rate T ′(wi) or a higher average
tax rate τi and is associated with less tax progressivity. With a lower CRIP, a marginal increase
of the gross wage remains as costly for the employer, but provides less additional income to the
worker. A more progressive tax schedule therefore affects the sharing rule (5) as does a decrease
in the workers’ bargaining power (Pissarides (1985, 1998), Lockwood and Manning (1993)). This
is the wage moderating effect of a more progressive tax schedule. We then obtain the following
gross and net wage setting equations, denoted WS in Figure 1 (See Appendix A):
wi =γi Ψi
1− γi + γi Ψi(yi + ci θi) +
1− γi1− γi + γi Ψi
bi1− τi
(7a)
ni =γi Ψi
1− γi + γi Ψi(1− τi) (yi + ci θi) +
1− γi1− γi + γi Ψi
bi (7b)
6
In the absence of taxation, Nash bargaining implies that workers extract a share γi of the total
surplus Ji+Ei−Ui while the firm extracts a share 1−γi. Therefore, the worker’s pay is a weighted
average of the instantaneous value in unemployment on the one hand and of the productivity
level yi augmented with the expected hiring cost per unemployed ci θi on the other.11 As the
latter increases when the labor marker becomes more tight, i.e. when the unemployment rate
decreases, the wage Equations (7a) and (7b) are represented by upward-sloping curves labeled
WS in Figure 1.
To analyze the impact of labor taxation on wage formation, we first consider a rise in the
average tax rate τi, holding tax progressivity Ψi constant. This reduces the total surplus of the
match that the worker and the employer share when they bargain over the wage. The surplus
Ji accruing to the firm decreases via a rise in the gross wage wi, which corresponds in the left
panel of Figure 1 to an upward shift of the WS curve (see (7a)). The surplus Ei − Ui accruing
to the worker shrinks via a reduction in the net wage ni, which corresponds in the right panel
of Figure 1 to a downward shift of the WS curve (see (7b)). Taking labor demand into account,
the equilibrium shifts from A to B, where employment and the net wage are lower while the
unemployment rate and the gross wage are higher. It is worth noting that if bi consisted only
of unemployment benefits indexed on the net wage, the tax rate would have no effect on the
unemployment rate nor on the gross wage (see e.g. Pissarides (1998, 2000)). This is because a
rise in the tax rate, by decreasing the net wage, decreases the level of unemployment benefits.
This effect turns out to offset the direct increasing impact of the tax rate on the gross wage.12
Put another way, the effect of the average tax rate τi relies on an imperfect indexation of
unemployment benefits plus the value of time out of work on the net wage.
Second, we consider a more progressive tax schedule (a lower Ψi) holding the average tax
rate τi unchanged. From (5), this affects the sharing rule as does a decrease in the relative
bargaining power γi/(1 − γi). A locally more progressive tax schedule therefore reduces the
workers’ effective bargaining power γi Ψi/(1− γi + γi Ψi), that is the weight of productivity in
the wage Equations (7a) and (7b). The WS wage curve shifts downwards in the two panels of
Figure 1, so the equilibrium moves from A to C. Employment increases while the unemployment
rate, the net and the gross wages decrease. This wage moderating effect of tax progressivity thus
provides a first argument justifying why we expect a more progressive tax schedule to decrease
the unemployment rate.
The local CRIP at at given wage w only captures progressivity in the neighborhood of w.
The following example illustrates the limitation of the local CRIP at w. Consider a piecewise-
linear tax system. Assume the only change from one year to the next is a small shift of a
threshold between two tax brackets from above to below a given wage level w (e.g. a “bracket
creep” phenomenon). Then, the marginal tax rate at w experiences a dramatic change, inducing
11For ci θi = ciυi/ (Ni − Li). When a job-seeker is hired, the employer saves the cost of searching for an otherapplicant.
12Plugging bi = ρ (1 − τi)wi into (7a), Equations (3) and (7a) would become a two-equation system in wi andθi that does not depend on τi.
7
a large shift of the CRIP at wage w, while the overall tax system has been almost unchanged.
We therefore choose to capture the progressivity of the tax system by a “global CRIP” that is
equal to the (log of) the ratio of the retention rates at wages levels w1 and w0 with w1 > w0.
The global CRIP between w0 and w1 is defined as:
Ψw1w0≡ ln
(1− T (w1)
w1
1− T (w0)w0
)=
∫ w1
w0
(Ψ(w)− 1)dw
w(8)
where the last equality is obtained by the integration of (6) between w0 and w1. The global
CRIP aggregates the local CRIPs between w0 and w1 and a lower global CRIP is associated
with a globally more progressive tax schedule between wages w0 and w1. The equality
n1
n0=w1
w0exp(Ψw1
w0)
stresses that the global CRIP measures how the tax system reduces after-tax wage inequality
between gross wage w0 and w1.
In addition to the wage moderating effect of a lower local CRIP, a lower global CRIP may
also reduce the aggregate unemployment rate if employment of low-paid workers at wage w0 is
more elastic to a change in the retention rate than employment for high-paid workers at wage
w1 > w0. The idea that low-paid employment is more responsive than high-paid employment
is quite common in the literature (e.g. Juhn et alii (1991), Kramarz and Philippon (2001),
Immervoll et alii (2007)). An increase in the log of the retention rate 1 − τ0 at w0 would
lead to an increase in low-paid employment that outweighs the decrease in employment induced
by an equivalent decrease in the log of the retention rate 1 − τ1 at wage w1. This leads to a
composition effect according to which a a lower global CRIP reduces unemployment. In addition
to this mechanism, there is no way to decrease the global CRIP between w0 and w1 without
reducing the local CRIPs in between, which also contributes to reduce unemployment trough
the wage moderating effect.
Prediction 1. In the model with exogenous labor supply, a rise in the retention rate (a decline
in the average tax rate) and a more progressive tax schedule (a decline in the global CRIP) reduce
the unemployment rate and increase the employment rate.
II.2 Extensive and intensive margins of labor supply
Extensive margin. The next step introduces participation decisions in each labor market.
For this purpose, we assume that individuals have different values I of being out of the labor
force. When an individual enters into the labor force, she is unemployed and searches for a job.
Among individuals of type i, only those for which I ≤ Ui choose to participate to the labor
market, where:
Ui =(r + δi)bi + pi(θi) nir (r + δi + pi(θi))
from (4a) and (4b). The value I of being out of the labor force is assumed continuously dis-
tributed among individuals of type i according to the CDF Gi(.). Let N i denote the exogenous
8
size of the working age population of type i. The participation rate in the population equals
Gi (Ui), the size of the labor force is Ni Gi (Ui).
From Equations (1) and (3), the fraction of employed participants 1 − ui is independent of
the size of the labor force. Because of congestion externalities, firms recruit workers more easily
when the size of the labor force increases. Whenever the participation rate increases holding
the gross wage wi constant, firms create more jobs until tightness, thereby the unemployment
rate, return to their initial values. The level Li of employment thus increases in the same
proportion as the size of the labor force. Consequently, total employment Ni Gi (Ui) (1− ui)and the employment rate Gi (Ui) (1− ui) are decreasing in the gross wage through labor demand
and are increasing in the net wage through the participation margin.
As displayed by Figure 1, a decline in the local CRIP Ψi, holding the average tax rate τi
constant, decreases the net wage ni but increases the exit rate out of unemployment pi (θi). The
total impact on the incentives to participate is therefore theoretically ambiguous. We show in
Appendix A that a decline in Ψi increases (decreases) the participation rate if the unemployment
rate is inefficiently high (low). This is because a decline in the local CRIP affects the labor market
outcome only by reducing the workers’ effective bargaining power. For a given retention rate τi,
participation is maximized whenever the effective bargaining power satisfies the Hosios (1990)
condition.13 However, the effect of tax progressivity on the unemployment rate is unchanged by
the introduction of the participation decision.
Figure 1 also shows that a rise in the tax rate τi, holding progressivity Ψi constant, decreases
the net wage ni, increases the gross wage wi and reduces the exit rate out of unemployment
pi (θi). Searching for a job thus becomes less interesting (i.e. Ui decreases), inducing pivotal
individuals to exit the labor force. The participation rate decreases. The employment rate and
the level of employment decrease because the size of the labor force is lower (a labor supply
effect) and a smaller fraction of participating agents is employed (a labor demand effect).
The empirical literature concludes that the extensive responses (i.e. participation decisions)
are concentrated on low-wage subgroups such as low-skilled workers or secondary earners (e.g.
Juhn et alii (1991), Immervoll et alii (2007) or Meghir and Phillips (2010)). This suggests
that increasing by 1% the retention rate 1− τi on the bottom half of the wage distribution and
decreasing the retention rate by 1% on the top half would increase overall participation through
a composition effect on participation. From (8), such a change in the profile of the retention
rate is associated with a decline in the global CRIP, that is, with a globally more progressive
tax schedule.
Prediction 2. In the model with bargained wages and endogenous participation, a rise in the
average tax rate increases the unemployment rate and decreases the employment rate. A rise
in tax progressivity (a decline in the CRIP) decreases the unemployment rate. It increases
(decreases) the participation rate if the unemployment rate is inefficiently high (low).
13This point was suggested by Pierre Cahuc.
9
Extensive and intensive margins in a competitive setting. The preceding conclusions
that tax progressivity reduces unemployment are in deep contrast with a long tradition in public
finance where tax progressivity reduces incentives to work. We argue that these two views are
not contradictory as they focus on different objectives, employment on the one hand, in-work
effort on the other hand.
The public finance literature typically assumes away frictions on the labor market, so full
employment prevails. However, even in such a frictionless environment, one should not only
consider the intensive margin of the labor supply. The empirical literature suggests that the
extensive margin is key (e.g. Heckman (1993), Meghir and Phillips (2010), Roed and Strom
(2002)). In a competitive setting, an individual chooses to work if and only his net income
wi − T (wi) is larger than his instantaneous value of staying out of the labor force i, which
is assumed continuously distributed. The extensive margin elasticity is empirically higher for
low-skilled workers. An increase in the log of the retention rate 1 − τ0 at w0 would lead to an
increase in low-paid participation that outweighs the decrease in participation induced by an
equivalent decrease in the log of the retention rate 1−τ1 at wage w1. This leads to a composition
effect in participation according to which a a lower global CRIP increases participation, thereby
employment. In sum, we expect that a more progressive tax schedule increases employment and
decreases output per worker, leading to an ambiguous impact on total production.14
Introducing the intensive margin in the matching framework. Turning back to en-
vironments with unemployment and wage negotiation, Sorensen (1997, 1999), Hansen (1999),
Fuest and Huber (2000) Roed and Strom (2002) and Parmentier (2006) have considered the
impact of tax progressivity when in-work effort is endogenous. Increasing income tax progres-
sivity reduces in-work effort through the traditional labor supply effect. Therefore jobs tend
to become less productive, which may also be detrimental for employment. Moreover, a more
progressive tax schedule still reduces the share of the surplus that accrue to the workers, which
is beneficial for employment through the above-mentioned wage moderation effect. In general,
the total effect on employment is ambiguous. This ambiguity can be resolved under some further
specific assumptions. For instance, Cahuc and Zylberberg (2004) obtain that the wage moder-
ation effect dominates the labor supply effect under multiplicatively separable preferences. A
more progressive tax schedule then always increases employment and always decreases the un-
employment rate and output per employed. The effect on total production remains ambiguous.
Hansen (1999) obtains similar analytical results under different specifications. Numerical simu-
lations under different assumptions for individual preferences find that employment is increasing
in tax progressivity while output per worker is reduced (Sorensen (1999), Parmentier (2006)).
The following predictions are derived in Appendix A under additively separable preferences.
14Immervoll et al. (2007) uses a microsimulation model with intensive and extensive labor supply responsesto compute the efficiency costs of two prototypical tax reforms that increase tax progressivity. They show thattheir “working poor policy” which pays more attention to the disincentive effects along the participation marginentails less efficiency costs than their “demogrant policy”. This suggests distortions along the extensive marginare quantitatively much more important to consider than the intensive margin.
10
Prediction 3. In the model with bargaining over wages and in-work effort, a rise in tax pro-
gressivity (a decline in the CRIP) reduces in-work effort. It also reduces the unemployment rate
if taxation is initially not too progressive. The effect on total production is ambiguous.
Predictions 2 and 3 confirm that while the negative effect of tax progressivity on unem-
ployment is robust to considering participation effects on the extensive margin, results are less
straightforward when we consider the intensive margin. Thus the sign of the effect of tax pro-
gressivity on the total hours of work is at best ambiguous.
III Empirical strategy
We estimate the effects of average tax rates and tax progressivity on unemployment rates and on
other labor market indicators in 21 OECD countries15 using information drawn from different
data sources, over the period 1997-2008.
Our measures of labor taxation are based on average tax rates (ATR) of single individuals
at different points of the earnings distribution, namely: 67% of the average wage, the aver-
age wage (i.e. 100%) and 167% of the average wage, provided by the OECD tax database.16
These indicators encompass income taxation by central and local governments and employers
and employees social security contributions, and are harmonized over time and across OECD
countries.17 While the focus on singles allows us to avoid many confounding factors originating
from household composition and intra-household participation decisions, it also has a drawback
since we are missing the contribution of specific policies which are restricted to households with
kids. Another feature worth noticing is that, since the wage distribution is likely to differ across
countries and over time, the average tax rates computed at 67%, 100% and 167% of the average
wage, may reflect actual taxation at a percentile of the wage distribution that are different.
From the above information, we then computed the tax retention rates
retji,t = 1− T (j ×AWi,t)
j ×AWi,t= 1−ATRji,t for j ∈ {67%, 100%, 167%}
with respect to the average wage (AWi,t) in country i and year t. The two measures of taxation
that we use in the empirical analysis are: the average tax burden, measured by the retention
rate at 100% of the average wage, ln(ret100); and the tax progressivity indicator captured by
the global CRIP, measured as the ratio of retention rates at 167% and 67% of the average wage,
ln(
ret167%i,t /ret67%
i,t
). Note that the latter follows closely the global CRIP we derived in (8),
where w0 and w1 are measured, respectively, at 67% and 167% of the average wage. 18
15The countries we consider are: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany,Greece, Ireland, Italy, Japan, Netherlands, Norway, New Zealand, Portugal, Spain, Sweden, Switzerland, UnitedKingdom and the United States.
16The OECD Tax database are drawn from http://www.oecd.org/tax/tax-policy/oecdtaxdatabase.htm, SectionB) 3.b, Table I.5.
17Since the OECD tax database only starts in 2000, we use the information provided by the OECD taxing wagedatabase to extend the relevant time series back to 1997. Details on the two database and their harmonizationare given in the Data Appendix.
18Given w0 and w1, the ratio w1/w0 is constant over time and across countries.
11
Our baseline specification is the following equation:
Yi,t = β1 ln(
ret100%i,t−1
)+ β2 ln
(ret167%
i,t−1
ret67%i,t−1
)+ ν ·Xi,t + αi + ϕt + εi,t (9)
where Yi,t is an indicator of labor market performance in country i and year t, Xi,t is a vector of
control variables, αi and ϕt are, respectively, country- and time-fixed effects, while εi,t is the error
term. The parameters of interest for the empirical analysis are β1 and β2. The vector of control
variables Xi,t includes a set of macroeconomic shocks, such as the output gap (outputgap), the
change in inflation (inflchange), and the long term interest rate on government’s bonds (irate).
It also includes a baseline set of labor market institutions, namely, the average unemployment
benefits replacement ratio (UBRR), union density (UnionDensity), an index of the degree of
coordination in wage bargaining (wcoord) and an synthetic index of employment protection
(EPL) (Nickell, Nunziata and Ochel, 2005).19.
The labor market performance variable, Yi,t, measures either the aggregate unemployment
rate, or group-specific unemployment rates. According to our theoretical predictions we expect
a rise in the retention rate (a decrease in the average tax rate) to reduce the unemployment rate
(i.e. β1 < 0), while a rise in the global CRIP (a less progressive tax schedule) is expected to
increase unemployment (i.e. β2 > 0). Alternatively, when Yi,t measures the employment rate,
we expect β1 > 0 > β2.
One reason for concern in estimating equation (9) by OLS is due to the potential endogeneity
of the tax indicators. Changes in taxation can be driven by different economic considerations,
such as (exogenous) long-term fiscal consolidation plans, (endogenous) fiscal policies induced by
cyclical variation in output (and unemployment), as well as other developments in the economy
affecting both the choice of taxation as well as unemployment. For example, a negative shock
to unemployment that reduces the tax base and increases social expenditures, when the public
budget has to be balanced, also generates a negative externality on retention rates. Alternatively,
a government may react to an increase in unemployment by cutting taxes and reducing the CRIP
to stimulate employment. In both cases above, reverse causality is likely to affect the estimates.
A further source of bias may also derive from different types of (unmeasured) labor market
policies - such as ALMP, direct job creation or early retirement - that, at the same time, lower
the unemployment rate and increase tax rates to finance the measures taken. In this case, the
omitted variable that affects unemployment is also correlated with the tax indicators. Note that,
while the macro-empirical literature on the determinants of unemployment does not generally
address such endogeneity issues 20, we take a number of steps in this direction. First, since tax
reforms take time to be decided, we enter our tax indicators in equation (9) with a one-year
lag, which also contribute to mitigating reverse causality biases. Second, we use an instrumental
variable estimator, based on exogenous variations in institutional, social and political factors that
19These data are drawn from: OECD Labor Force Statistics, OECD Economic Outlook, OECD Main EconomicIndicators, ICTWSS database and World Bank Development Indicators.
20See Nickell et alii (2005), Blanchard and Wolfers (2000), Griffith et alii (2007), Bassanini and Duval (2009)and Arpaia and Mourre (2010) for a survey. A notable exception is Nunziata (2005).
12
influence a country’s fiscal policy, to identify the (causal) effect of taxation on unemployment
(and employment). In practice, we instrument the tax wedge and tax progressivity indicators
using the following variables: a narrative record for the tax components of fiscal consolidation
policies, an index of trust in civil services and a measure of the political orientation of the
parliament.
Our first instrument is based on information drawn from country’s fiscal consolidation plans
and using the narrative approach pioneered by Romer and Romer (2010). The data we use
record multi-year tax increases and spending cuts for 17 OECD countries from 1978 to 2009
(Devries et alii 2011). Information on fiscal reforms is reconstructed using historical records,
available in official documents (i.e. budget reports, central bank reports, IMF reports, OECD
Economic Surveys and other country-specific sources), with the aim of identifying size, timing,
and main motivation for the fiscal actions undertaken by each country. In particular, in order to
guarantee the ’exogeneity’ of fiscal measures with respect to cyclical fluctuation, only long-term
structural fiscal plans primarily designed to put public debt on a sustainable path are considered.
To illustrate what in our data is a typical change in taxation motivated by long-term structural
consideration, consider the fiscal consolidation efforts (i.e. mainly in terms of higher taxation)
undertaken by several European countries to conform to the ’Stability Pact’ for accession to
the Monetary Union. While this was agreed under the terms of the 1992 Maastricht Treaty, it
was not up until the very last moment that these measures were taken and implemented. In
other words, it is the precise timing of the tax hikes, for long-waited reforms, what the narrative
indicator measures; while tax changes motivated by business cycle fluctuations are not recorded.
To construct our instrument we focus only on the changes in taxation induced by a country’s
long-term structural fiscal consolidation plan. In particular, we exploit that part of the tax wedge
on labour which originates from all the fiscal consolidation policies implemented over the years.
In practice, we construct the (Taxhike) variable as an index which, in country i at time t,
cumulates all the tax hike episodes occurred up to t-1.
Our second instrument relies on the idea that redistributive policies require a high level of
trust and confidence in public services. The more people believe that public institutions are
trustworthy, the more they are willing to let the State implement redistributive policies. So, we
expect that where confidence in public services is high, a more progressive taxation is observed.
This instrument has to property to be highly correlated with tax progressivity (i.e. the global
CRIP), but excludable from the unemployment equation. Available evidence supports these
properties: Sapienza et alii (2007) argue that respondents’ beliefs regarding the functioning of
the civil service are not directly correlated with economic activity, thus with unemployment
performance. Studies that obtain a direct effect of trust on economic activity, in general use
a measure of ‘trust in others’, rather than trust in specific institutions such as public services
(see e.g. Algan and Cahuc (2006, 2010) and Guiso et alii (2008)).21 Since low confidence in
21Algan et alii (2011) construct a composite index of distrust for public institutions, which combines distrustfor the civil service with distrust for the parliament and the justice system. We neglect the latter two dimensionsof distrust, as we are mostly interested in describing the social propensity to finance public good provision and
13
public services may also affect unemployment insurance generosity, it is important to include
the unemployment benefit replacement ratio among the controls. In practice, our measure of
(dis)trust in civil services (Trust) is given by the percentage of individuals, in each country, that
report low or no confidence in civil service; that is, the share of people that responded “none
at all” to the question: “how much confidence do you have in the civil service?” in the World
Value Survey (WVS).22
The third instrument we use is grounded on the notion that the political orientation of
parties in Parliament, quite independently of the state of the economy, is correlated with the
propensity to tax. In general, left-wing politicians are typically expected to support higher tax
levels and more progressive taxation as compared to right-wing politicians (Summers et alii
(1993), Persson and Tabellini (2000), Ardagna (2004) or Nunziata (2005) among others). In
this context, it is worth noticing that a long standing literature in political economy argues that
the political orientation of parties may affect, besides taxation, also monetary and fiscal policies,
as left-wing politicians, compared to right-wing ones, are more likely to implement keynesian
policies. We take this into account in different ways. First, we include cyclical indicators, such as
the output gap, as well as indicators of monetary policy, such as the real interest rate and change
in inflation, among the controls. 23 Second, there is evidence suggesting that adverse economic
performances may reduce the probability of reelection of incumbent politicians (Drazen, 2000).
In other words, this would imply after a negative shock to the economy an increase in leftism,
if the incumbent is right-wing, and the opposite if the incumbent is left-wing. This ’probability
of reelection channel’ induces de facto a nonlinearity in the effects of the business cycle (e.g.
unemployment) on leftism, which we exploit for identification. 24 In practice, our Leftism
instrument is measured as the difference between the shares of seats of left-wing parties with
respect to the share of seats of right-wing parties in the parliament.25 More details on all the
variables used in the empirical analysis are provided in the data Appendix B.
IV Data and descriptive statistics
We assembled a unique data set which combines information, drawn from different sources on
taxation and other labor market institutions, on labor market performance and other socio-
economic characteristics for 21 OECD countries over the period 1997-2008.26
redistribution.22Information on the (dis)trust indicator in WVS is only available every five-years. We introduce it in first
stage regression with a five-years lag.23These variables are expected to control for the keynesian channel in (9) such that there is no residuals impact
of leftism on the business cycle.24We find support to this hypothesis in the data: out of 35 country-specific economic crisis episodes - defined
as GDP being one percentage point below ist potential level in a given year, or by half a point for two consecutiveyears -, leftism obtained a relative majority in the first election after the crisis in 21 cases, while right-wing partiesprevailed in the other 14.
25The leftism variable in our first stage regression is entered with a lag - i.e. with t−2 given that tax indicatorsare already lagged t− 1 in the unemployment equation.
26The countries we consider are: Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany,Greece, Ireland, Italy, Japan, Netherlands, Norway, New Zealand, Portugal, Spain, Sweden, Switzerland, United
14
To get a broad overview of our tax data, we plot in Figure 2, the average value by country,
over the sample period, of both the average tax retention rates ret100%i,t and (the exponential of)
our global CRIP, namely ret167%i,t /ret67%
i,t . Figure 3 shows, for the same indicators, the country’s
change between the 1997-1999 and the 2006-2008 sub-periods. For convenience, we also report
the overall sample means (dashed horizontal and vertical lines) that partition the graph into
four quadrants, according to the level and change of OECD countries’ tax burden (i.e. in terms
of average taxation and tax progressivity). In practice, each quadrant identifies for each country
a different long-term tax structure (Figure 2), and the major tax reforms that occurred over the
sample period (in Figure 3).
In terms of the levels of average tax burden and progressive taxation (Figure 2), the overall
patterns shows, with notable exceptions, a positive correlation between the two tax indicators,
suggesting that countries that tax more (i.e. with lower average retention rates, ret100% are
also characterized by a higher progressivity (i.e. a lower retention rates ratio, ret167%/ret67%).
The bottom-left quadrant shows countries with a high tax burden, these are mainly Nordic
and continental European countries. In the upper-right quadrant we find mostly Anglo-Saxon
and Mediterranean European countries (as well as Switzerland and Japan) characterized by a
relatively lower tax burden.
Figure 2: Average of the tax retention rates (100%APW) and the progressivity (167% vs67%APW) by country over the 1997-2008 period. Sources: OECD Tax Database and OECDTaxing wages and authors’ calculation.
When we focus on changes in the tax structure (Figure 3), we notice that the majority of
countries, over the 1997-2008 period, exhibit small variations and appear to be located in the
upper-right quadrant suggesting an overall trend, for most OECD countries, in the reduction
of tax burdens. Some countries (e.g. France, Greece, New Zealand, Austria and Great Britain)
show an increase in global progressivity. The overall pattern of changes in countries’ tax structure
(i.e. both changes in the level and progressivity of taxation) show a (weakly) positive correlation:
a number of countries, however, stand out from the fitted line showing substantial changes in the
Kingdom and the United States.
15
structure of taxation which suggest that a significant reform of the tax system occurred. The
latter shows three different patterns: first, Japan and The Netherland, where the average level
of taxation increased while progressivity remained relatively stable, and second, Ireland which
decreased substantially the tax burden both in terms of average taxation and progressivity.
Figure 3: Changes of the tax retention rates (100%APW) and the progressivity (167% vs67%APW) by country over the 1997-2008 period. Sources: OECD Tax Database and OECDTaxing wages and authors’ calculation.
Figures 4 and 5 highlight our main argument showing a snapshot of the correlation between
taxation (i.e. both average tax and tax progressivity) and aggregate unemployment across
countries. To account for (time invariant) unobserved factors, that can be correlated with both
taxation and unemployment, thus playing a counfounding role, we specify change in each variable
between the 1997-1999 and the 2006-2008 sub-periods.
In line with our theoretical priors, changes in average tax retention rates Figure 4 are shown
to be negatively related to changes in unemployment (i.e an increase in the average tax burden
is associated to a higher unemployment rate); while changes in our global measure of progressive
tax retention ratio 5 is shown to be negatively correlated with changes in unemployment (i.e an
increase in the ratio of our global CRIP is associated to a lower unemployment rate). Coun-
tries that, over the period 1997-2008, experienced an increase in average taxation (in particular,
Japan and The Netherland), generally show an increase in unemployment. The opposite occurs
in countries where a decrease in average taxation (in particular, Ireland, Sweden and Finland)
is associated with a decrease in unemployment. Interestingly, the changes in tax progressivity
and unemployment show a (weakly) positive relationship. This suggests that countries which
increased tax progressivity (in particular, France, New Zealand and Italy) experienced a (mod-
erate) decrease in unemployment; while the opposite is true for countries where progressivity
decreased.
16
Figure 4: Change in average tax retention rates and change in unemployment between 2006-2008 and 1997-1999 by country. Sources: OECD Tax Database and OECD Taxing wages andauthors’ calculation.
Figure 5: Change in tax progressivity and change in unemployment between 2006-2008 and1997-1999 by country. Sources: OECD Tax Database and OECD Taxing wages and authors’calculation.
V Empirical results
V.1 Baseline specification
Table 1 presents results for our baseline specification with the aggregate unemployment rate
as dependent variable (i.e. OLS estimates are reported in columns (1) and (2), IV estimates
are shown in columns (3) to (5)). In Column (1) we report results that are consistent with
the specification typically used in the literature, whereby taxes affect the unemployment rate
only through the average tax wedge (e.g. Nickell and Layard (1999); see Bassanini and Duval
(2009) for a review). A one percentage point increase in the average retention rate, ln(ret100)
(i.e. a one percentage point decrease in the labor tax wedge) has a positive impact on the
unemployment rate, for the average OECD country, of about 0.09 percentage points. This
order of magnitude is consistent with previous findings, which suggest that one percentage point
change in average taxation may entail a change in the unemployment rate in the range of 0.02 and
17
0.2 percentage points, the former as reported in Blanchard and Wolfers (2000), the latter as in
Nickell and Layard (1999). Daveri and Tabellini (2000) report a much bigger effect in Continental
European Countries, they suggest that the unemployment reducing impact of one percentage
point tax cut may be close to 0.5 percentage points, due to the interactions between labor
taxation and different welfare models. In Column (2) we show results with a specification that
also considers the impact of tax progressivity on unemployment. Consistent with Prediction 1, a
lower average tax rate (as described by a marginal increase of ln(ret100)) and a more progressive
tax schedule (as described by a marginal decrease of ln( ret167ret67 )) are both associated with a lower
unemployment rate. The effect of the average tax rate is statistically significant at the 5% level,
while the effect of progressivity is only weakly significant. From the coefficient on ln( ret167ret67 ) in
Column (2), we can compute the effect of a half-percentage point decrease in the average tax
rate at 67% of the average wage, together with a half-percentage point increase in the average
tax rate at 167% of the average wage. Such a tax reform induces a rise in tax progressivity
that decreases the global CRIP ln( ret167ret67 ) by 0.016 points, thereby reducing unemployment by
about 0.06 percentage points27. After accounting for tax progressivity, the estimated effect of
one percentage point increase in the average retention rate on the unemployment rate rises to
0.11 percentage points.
However, as previously discussed, OLS estimates may be biased and inconsistent due to
the endogeneity of the tax variables. In columns (3), (4) and (5), we deal with those issues
implementing an instrumental variable estimator (IV). In particular, in Column (3), we re-
estimate the specification of column (1) using the variables Taxhike and of Leftism (lagged
twice) to instrument ln(ret100) 28. In Column (4), we introduce tax progressivity but consider
this variable as exogenous and instrument ln(ret100) only, as in Column (3). In Column (5),
we instrument both ln(ret100) and ln( ret167ret67 ), using the same instruments as before, as well as
the Trust variable 29 First-stage estimates show that the Taxhike and Trust indicators have
a strong statistically significant impact on the ln(ret100) variable, while the Trust indicator
is mostly correlated with the global CRIP ln(ret167ret67
)variable (i.e. first-stage estimates are
shown in Table 7 Appendix C). First-stage estimates reported in Table 7 in the Appendix C
are reassuring about instruments’ correlation with the endogenous regressors, and the Hansen
J test confirms the validity of the over-identifying restrictions.30.
27The mean of ret67, ret100 and ret167 over the sample are respectively 66.35%, 62.19% and 57.42%. Thus,the decrease in the global CRIP induced by a typical reform computed at the mean is (0.5/66.35) + (0.5/57.42) =0.0162.
28Note that the Taxhike variable in the Devries et alii dataset is only available for 17 out of the 21 countriesin our sample. For this reason, the observations for the missing countries (i.e. Greece, New Zealand, Norway andSwitzerland) are set to zero letting the country dummies capture this effect in the estimation. In the robustnesschecks section we provide additional evidence imputing the information on (exogenous) long-term structuralchanges in taxation from an external source.
29Since the number of instruments exceeds the number of endogenous regressors, we can test the validity ofoveridentifying restrictions.
30The p values of the Kleibergen-Paap under-identification test show that we can reject the null hypothesisthat our model is under-identified, while the F statistics with one instrument (in Columns (3) and (4)) is slightlybelow the threshold level of 10, conventionally used as a rule of thumbs by Stock and Yogo under the assumptionof i.i.d residuals. Moreover the Anderson and Rubin test, which is robust to weak instruments, rejects at the 1%
18
OLS estimates IV estimates(1) (2) (3) (4) (5)
ln(ret100) –5.893** –6.680** –25.382*** –30.554*** –59.181***(2.664) (2.750) (9.466) (10.956) (22.709)
ln( ret167ret67 ) 3.859 10.156** 70.128***
(2.522) (4.404) (26.841)
UBRR 0.031 0.037 0.117** 0.146** 0.309**(0.025) (0.025) (0.052) (0.061) (0.123)
UnionDensity 0.066 0.078 –0.042 –0.029 0.059(0.055) (0.054) (0.077) (0.081) (0.184)
wcoord –0.541*** –0.545*** –0.588*** –0.605*** –0.701*(0.191) (0.188) (0.205) (0.221) (0.397)
EPL 0.753* 0.735* 1.096** 1.102** 1.103(0.405) (0.393) (0.457) (0.453) (0.749)
outputgap –0.378*** –0.375*** –0.460*** –0.465*** –0.487***(0.064) (0.064) (0.082) (0.085) (0.138)
inflchange –0.068 –0.064 –0.167* –0.172* –0.190(0.076) (0.077) (0.101) (0.104) (0.177)
irate –0.273* –0.299** –0.546** –0.658** –1.292**(0.141) (0.142) (0.252) (0.282) (0.524)
R2 0.89 0.89 0.86 0.85 0.53N 231 231 231 231 231Hansen J test 0.1380 0.1629 0.6423Anderson Rubin F test 0.0093 0.0057 0.0000
Table 1: Tax wedge, tax progressivity and the unemployment rate. Robust standard errorsin parentheses. Significance levels: ∗: 10%, ∗∗: 5%, ∗ ∗ ∗: 1%. p-values of Hansen J over-identification tests and of Anderson and Rubin F test of significance of endogenous regressorsare provided.
A comparison of estimated coefficients reported in Columns (3)-(5) with those in Column (2)
indicate that OLS estimates of ln(ret100) may suffer from attenuation bias. IV estimates indeed
suggest that one percentage point increase in the average retention rate implies a reduction
of the unemployment rate, for the average OECD country, between 0.41 and 0.95 percentage
points - i.e. an order of magnitude that is closer to the one suggested by Daveri and Tabellini
(1995). Symmetrically, an increase in tax progressivity ln( ret167ret67 ) - computed as described above
- determines a reduction in aggregate unemployment between 0.16 and 1.13 percentage points.31.
In other words, a reduction in the average tax rate combined with an increase in tax progressivity
can have a sizeable effect on the unemployment rate. Estimates of the other control variables
are in line with usual findings in the literature, namely: higher unemployment benefits tend to
increase unemployment, while more coordination in wage bargaining reduces it. An increase in
the output gap is associated with lower unemployment, while the negative coefficients of the
the null hypothesis that the endogenous regressors are not significant in the second stage.31It should be noted, however, that the lower bound estimate of 0.16 is obtained from a specification in which
tax progressivity is assumed to be exogenous (Column 4), while the estimated impact of 1.13 is obtained from aspecification in which also tax progressivity is instrumented.
19
real interest rate on government’s bonds and the change in inflation suggest that policies that
guarantee prices stabilization (in either the goods and capital markets) may be associated with
higher unemployment.
Overall, estimates in Table 1 yield three interesting considerations regarding the impact
of taxation on the unemployment rate. First, omitting the role of tax progressivity leads to
underestimate the impact of average taxation on unemployment. Second IV estimates, when
compared to OLS, show a considerable increase in the magnitude of coefficients, both in terms
of ln(ret100), as well as ln( ret167ret67 ). We interpret this finding as evidence that reverse causality
introduces attenuation bias on OLS estimates, - e.g. a government may react to an increase in
unemployment by reducing average labor taxes, in particular on low-paid jobs. Also omitted
factors affecting the unemployment rate, such as public employment and relief jobs, would be an
additional source of attenuation when negatively correlated with the ln(ret100). Last, but not
least, the impact of tax progressivity is shown to be as important as the impact of the average
taxation.
OLS estimates IV estimates(1) (2) (3) (4) (5)
ln(ret100) 3.125 4.814 20.994* 28.271** 60.140**(3.750) (3.938) (11.323) (12.973) (26.889)
ln( ret167ret67 ) –8.278** –14.465*** –81.155**
(3.527) (5.428) (36.104)
R2 0.97 0.97 0.97 0.97 0.92N 231 231 231 231 231Hansen J test 0.1713 0.2032 0.6706Anderson-Rubin F test 0.0330 0.0126 0.0007
Table 2: Tax wedge, tax progressivity and the employment rate. Robust standard errors inparentheses. Significance levels: ∗: 10%, ∗∗: 5%, ∗ ∗ ∗: 1%. p-values of Hansen J over-identification tests and of Anderson and Rubin F test of significance of endogenous regressorsare provided.
In Table 2 we replicate the same regressions of Table 1 replacing the unemployment rate with
the employment rate as the dependent variable. Most previous findings are confirmed also when
the effects of taxation are estimated on the employment rate, though, as expected, the signs are
now reversed as compared to Table 1. Focussing on our preferred specification in Column (5),
we find that a one percentage point increase in the average retention rate determines an increase
of the employment rate, for the average OECD country, up to 0.96 percentage points. Similarly,
a one percentage point increase in ln( ret167ret67 ) - defined as a half-percentage point decrease in the
average tax rate at 67% of the average wage and a half-percentage point increase in the average
tax rate at 167% - causes an increase in the employment rate up to 1.32 percentage points. Here
as well, a comparison of the coefficients on ln(ret100), in Column (3) and Column (5), indicate
that neglecting progressivity tends to underestimate the impact of the average tax wedge on
employment.
20
log(1− urate) log(prate) log(erate) log(GDPEmp ) log(GDPPop )
(1) (2) (3)=(1)+(2) (4) (5)=(3)+(4)
OLS estimates
ln(ret100) 0.100*** –0.003 0.096 –0.026 0.070(0.036) (0.040) (0.063) (0.072) (0.090)
ln( ret167ret67 ) –0.104*** –0.042 –0.146*** 0.135** –0.012
(0.035) (0.037) (0.055) (0.062) (0.065)
R2 0.86 0.98 0.97 1.00 1.00N 231 231 231 231 231
IV estimates
ln(ret100) 0.856*** 0.173 1.029** –0.533 0.496(0.317) (0.177) (0.455) (0.585) (0.391)
ln( ret167ret67 ) –0.981** –0.382 –1.362** 1.933*** 0.570
(0.383) (0.292) (0.595) (0.594) (0.494)
R2 0.38 0.97 0.90 0.98 0.99N 231 231 231 231 231Hansen J test 0.5803 0.8811 0.7333 0.6019 0.1605Anderson Rubin F test 0.0000 0.5671 0.0006 0.0000 0.0026
Table 3: Decomposing the effects of taxation on different indicators. Robust standard errorsin parentheses. Significance levels: ∗: 10%, ∗∗: 5%, ∗ ∗ ∗: 1%. p-values of Hansen J over-identification tests and of Anderson and Rubin F test of significance of endogenous regressorsare provided.
As a final exercise, in Table 3, we decompose the effects of taxation on labour market
performance using the same identification strategy as in Columns (5) of Tables 1 and 2. The
top panel reports OLS estimates, while the bottom panel shows IV estimates. In particular, we
consider the effect of taxation on different dependent variables, namely: in Column (1) we use
the logarithm of one minus the unemployment rate, in column (2) we take the logarithm of the
participation rate, while in Column (3) the logarithm of the employment rate is used instead.
In this way, adding the estimates of Column (1) and Column (2), by construction, we obtain
estimates reported in Column (3)32. Similarly, in Column (4) we use the logarithm of GDP per
worker as dependent variable, while in Column (5) the logarithm of the GDP per working-age-
population is used. Since, GDP per working-age-population is the product of the employment
rate times GDP per employed worker, the sum of estimates in Column (3) and Column (4),
by construction, give estimates reported in Column (5). When the logarithm of one minus the
unemployment rate is used as the the dependent variable (Column (1)), the estimated coefficients
provide the elasticity of tax indicators with respect to the fraction of the active population that is
employed. Results show that a higher taxation increases unemployment while more progressivity
decreases it (e.g. note that there is also an improvement in the statistical significance of tax
progressivity with respect to Table 1). Focusing on Column (3), we find that lower taxation and
32Note that, for consistency with the decomposition exercise, in Column (1) we use the (non-harmonised)unemployment rate instead of the standardised unemployment rate provided by OECD, as in Table 1. We havechecked that this change has little effects on the estimates.
21
higher progressivity decrease the employment rate considerably, however these effects seems to
be mainly driven by unemployment rather than by the the effects played by the participation
rate (e.g. which is non statistically significant both in OLS and IV estimates of Column (2)).
This results suggest that the emphasis that is usually placed, in the public finance literature,
on labor supply decisions along the extensive marginto to explain the employment effects of
changes in taxation, instead of wage moderating effects, may be misleading.
In order to quantify the impact of labor taxation along the intensive (in-work effort) mar-
gin, in Column (4) we use as dependent variable the (log of) GDP per worker. In line with
Prediction 3, we find that a rise in progressivity (a decline in CRIP ln( ret167ret67 )) reduces GDP per
employed worker. Therefore our finding that progressivity reduces unemployment and increases
employment is not inconsistent with the common wisdom that tax progressivity may also have
a detrimental effect on incentives to work harder. These estimates are highly significant. Con-
versely, the effect of ln(ret100) is never statistically significant. Despite the negative impact
of progressivity on output per worker shown in Column (4), we find that the overall effect on
output is not statistically significant. This may suggest that the effects of progressivity on em-
ployment are indeed large enough to offset the negative impact on the incentive margin. In sum,
Table 2 reconciles our view that tax progressivity reduces unemployment (Column (1)) and in-
creases employment (Column (3)) with the traditional view that it generates negative incentives
in terms of in-work effort (Column (4)). It also shows that the total effect on production is
ambiguous (Column (5)).
Skill AgeLow-skilled High-skilled Young Adults
OLS estimates
ln(ret100) –9.311** –5.428 –17.203** –8.776***(3.946) (3.355) (6.807) (3.011)
ln( ret167ret67 ) 8.504** 9.963*** 14.659* 9.828***
(3.588) (2.916) (7.826) (2.859)
R2 0.85 0.78 0.91 0.87N 231 231 231 231
IV estimates
ln(ret100) –82.798** –51.221** –139.108*** –69.584***(36.825) (25.118) (49.359) (24.623)
ln( ret167ret67 ) 123.079*** 64.475** 139.764** 78.557**
(40.349) (31.508) (61.439) (30.915)
R2 0.23 0.44 0.69 0.44N 231 231 231 231Hansen J test 0.8169 0.1195 0.3678 0.5088Anderson Rubin F test 0.0000 0.0110 0.0000 0.0000
Table 4: Effects on the unemployment rates of different subgroups. Significance levels: ∗: 10%,∗∗: 5%, ∗ ∗ ∗: 1%. p-values of Hansen J over-identification tests and of Anderson and Rubin Ftest of significance of endogenous regressors are provided.
22
Estimates in Tables 1, 2 and 3 implicitly assume that workers are homogeneous both in
terms of labour demand characteristics of the available jobs, as well as in terms of labor supply
responses to fiscal and labor market incentives. In Table 4, we report estimates of our preferred
specification (i.e. Columns (5) in Table 1) for selected sub-population of workers, namely using
the unemployment rate by skill and age (i.e. Columns (1) and (2) for skill, and Columns (3) and
(4) for age, respectively). The top panel report OLS estimates while the bottom panel shows
IV estimates. Some caution is needed when interpreting these estimates, since the distribution
of wages can vary a lot between these groups, while retention rates are not specific to each sub-
population considered. Still, a rough comparison of the magnitude and statistical significance of
the coefficients of ln(ret100) and ln( ret167ret67 ) can improve our understanding of the diverse effects
of taxation on unemployment across different groups of workers.
Estimates in columns (1) and (2) suggest that the impact of taxation and progressivity is
relatively larger (and statistically more robust) for low skilled workers as compared to high
skilled workers.33 Results reported in Columns (3) and (4) show a similar patters, whereby the
impact of taxation and progressivity on unemployment is larger for younger workers (i.e. age
group 15-24), as compared to older workers (i.e. age group 25-54).
V.2 Robustness checks
Baseline Identification Using Guichard et alii Using Public Debt(1a) (1b) (2a) (2b) (3a) (3b)
Second-stage results
UNR erate UNR erate UNR erate
ln(ret100) –59.181** 60.140* –56.339* 58.699 –61.979*** 65.666**(22.709) (26.889) (25.404) (30.567) (18.001) (21.855)
ln( ret167ret67 ) 70.128** –81.155* 72.217** –85.020* 70.128* –80.502*
(26.841) (36.104) (27.142) (36.796) (27.567) (36.990)
R2 0.53 0.92 0.53 0.92 0.51 0.92N 231 231 231 231 231 231Hansen J 0.6423 0.6706 0.8642 0.5608 0.6903 0.6153Anderson Rubin F 0.0000 0.0007 0.0000 0.0083 0.0000 0.0000
First-stage statistics
ln(ret100) ln( ret167ret67 ) ln(ret100) ln( ret167
ret67 ) ln(ret100) ln( ret167ret67 )
F of Excluded 5.976 6.391 6.260 5.680 16.571 7.518Shea Partial R2 0.0778 0.0430 0.0725 0.0433 0.1078 0.0431KP under 0.0009 0.0008 0.0007KP weak 4.12 4.23 4.37
Table 5: Robustness checks about instruments
In this section, we consider a number of potential robustness concerns for our empirical
33These two skill categories are based on educational attainment. Low skilled workers completed up to secondaryeducation, while high skilled workers completed tertiary education or more. The inclusion of individuals with ahigh school degree into the low skilled category can be disputed. However, this aggregation choice is unavoidabledue to the switch from the ISCED76 to the ISCED97 classification, which recoded lower-secondary educationfrom level 1 (primary) to level 2 (secondary).
23
analysis and run several sensitivity checks. In Table 5 we test the robustness of our results
using an alternative identification strategy based on different sets of instruments. To facilitate
comparisons, in Columns (1a) and (1b), we reproduce our results from the baseline specification
(Column (5) of Table 1, for the unemployment rate; Column (5) of Table 2 for the employment
rate). The bottom part of Table 5 shows first-stage results (i.e. note these are identical whether
the dependent variable in the second stage is the unemployment or the employment rate) 34
In Columns (2a) and (2b), first we replace the missing information (for Greece, New Zealand,
Norway and Switzerland) in the Taxhike instrument (from the Devries et alii dataset) with
information drawn from an alternative OECD dataset on fiscal consolidation (Guichard et alii
2007). Although the information on fiscal consolidation episodes provided in the Guichard et
alii dataset relies on an statistical algorithm (i.e. based on countries’ structural changes in the
cyclically adjusted primary balance), rather than on the ’narrative’ approach, the sequence of
tax hikes show a rather similar pattern in both dataset 35. Finally, in Columns (3a) and (3b), we
use the ratio of public debt over GDP (t−2) as instrument to replace the tax hike indicator. The
latter captures the idea that highly indebted governments need to use fiscal policy to consolidate
their budget (Gali and Perotti, 2005). To mitigate the risk of reverse causality we lagged the
variable twice. Moreover, the inclusion of cyclical controls is expected to account for any effect
of public debt on unemployment going through the channels of demand-management policies
(i.e. note that the typical Keynesian fiscal policies are better described by the ratio of public
deficit over GDP, rather than public debt over GDP ratio). In general results reported in Table
5, where we use alternative instruments, support earlier findings providing additional evidence
for the robustness of our estimates.
Additionally, we run a set of more traditional robustness checks. In particular, we experiment
a different set of control variables, alternative specifications to the baseline equation, various
estimation method to control for unobserved country specific shocks, as well as a different
clustering of the error term to account for common unobserved effects. In Table 6, for each
sensitivity check, we report the estimated coefficients of the tax variables and the Hansen test
for the overidentifying restrictions. The various robustness checks experimented are discussed
hereafter. We present all estimates using both the unemployment rates (Columns (1) to (3))
and the employment rates (Columns (4) to (6)).
In our baseline equation we use the output gap to control for overall business cycle conditions,
assuming that output fluctuations are exogenous with respect to the unemployment rate. To
check for the potential (endogeneity) bias that the inclusion of the output gap may determine, in
row (1), we re-estimated the model omitting it. Next, while in our baseline specification all the
tax variables are assumed to be pre-determined and entered with a year lag, in row (2) we check
the sensitivity of tax estimates when we replace the lagged terms with the contemporaneous
34Column (1a) displays the Shea Partial R2 and the F statistic of the significance test of excluded instrumentsfor the first-stage estimation of ln(ret100); Column (1b) provides the same statistics for ln( ret167
ret67).
35We checked the consistency of the two indicators - i.e. ’narrative’ and ’statistical’ - for the countries in whichinformation on both approach was available.
24
tax indicators. We further experiment how results are altered by considering only country
fixed effects (i.e. excluding the time dummies; row (3)), replacing country fixed effects and
time dummies with country specific trends (row (4)) and including in the specification both
time dummies and country specific trends (row (5)). To account for the presence of cross-
section correlated error terms, in row (6), we replace the time-fixed effects with a Correlated
Common Effect Pooled (CCEP) estimator (Pesaran (2006)), while in row (7) we implement
the Newey-West HAC estimator that delivers heteroskedasticity and autocorrelation consistent
estimates. In all the above cases the results are not significantly altered with respect to our main
specification. In row (8) to (11), we progressively exclude from our sample the countries that,
in the period considered in the empirical analysis, show significant changes in the structure of
taxation suggesting major tax reforms (i.e. France, Ireland, Japan and The Netherlands). In all
above cases, the overall results are unaffected by the change in the set of countries considered.
Finally, to capture the medium-run effects and to partially smooth the year-to-year variations,
we replicated the estimates using three years averages. Also in this case the overall results are
virtually unchanged.
VI Discussion and Conclusions
In this paper, we review a number of theoretical arguments that support the idea that tax pro-
gressivity may have an unemployment-reducing effect. We develop a simple theoretical model
in which while tax progressivity may be detrimental to labor supply along the intensive mar-
gin, its overall effects on employment and unemployment may be beneficial for labor market
performance (Boone and Bovenberg (2004)). We empirically test the effects of tax progressivity
on employment and unemployment using a panel data of 21 OECD countries for the 1998-2008
period. We propose a new measure global tax progressivity which is defined as the difference
in the fiscal wedge between 67% and 167% of the average wage for a single worker. We then
include our tax progressivity index to the list of time-varying indicators of labor market institu-
tions traditionally used to explain differences in equilibrium unemployment across countries. We
find that tax progressivity has a significant unemployment-reducing impact of a similar order of
magnitude as the unemployment-increasing effect of average labor market taxation. This effect
is more concentrated among low-skilled workers and among young workers. These results are
line with theories that claim tax progressivity reduces unemployment because it shifts tax bur-
den away from group of workers that are more responsive to taxation, and because it generates a
wage moderation effect in collective wage-setting that is favorable to labor demand. We also find
that a more progressive tax schedule increases the employment rate, but decrease production
per worker, leading to a negligible total impact on total production. Our central result that tax
progressivity increases employment comes thus hand by hand with the usual disincentive effect
of tax progressivity on the intensive margin of the labor supply that is central in the public
finance literature. In sum we add a new effect to take into account in the optimal design of
25
labor income taxation. Optimal progressivity not only trades off the equity gain of a higher
progressivity against the efficiency loss due to the disincentive effect along the incentive margin.
One has also to take into account the efficiency gains of a more progressive tax schedule through
a reduction in unemployment and a rise in employment. Our results need to be extended in
different directions, the most obvious one being to build indicators of tax progressivity over a
longer time period.
A Theoretical model
We here consider the general model with an intensive labor supply margin. Let `i be the effortprovided by employed individuals and the money-equivalent of this disutility.36 One can thinkof `i as hours of work or as the intensity of in-work effort. We assume that providing effort `ileads to a flow of output fi(`i), with f ′i(.) > 0 > f ′′i (.) and a flow of disutility `i. Denoting wias the total gross wage (and not the wage rate), Equation (4a) becomes:
r Ei = wi − T (wi)− `i + δi (Ui − Ei) (10)
The case without the intensive margin is retrieved by setting `i = 0 and f(`i) = yi below.Equations (2) and (10) imply respectively:
Ji =fi(`i)− wir + δi
and Ei − Ui =wi − T (wi)− `i − r Ui
r + δi(11)
Maximizing the (log of) the Nash product with respect to the wage and in-work effort leads to:
γi (1− T ′i )Ei − Ui
=1− γiJi
andγi
Ei − Ui=
(1− γi) f ′i(`i)Ji
where T ′i ≡ T ′(wi). Using (6) and Ψi = Ψ(wi), the first of these two equations gives the sharingrule (5). The second of these equations imply the labor supply condition:(
1− T ′i)f ′i(`i) = 1 (12)
which determines effort `i as a decreasing function of the marginal tax rate, independently ofany other variable. Combining the sharing rule (5) with (11) lead to:
γi Ψi (fi(`i)− wi) = (1− γi)(wi −
`i + r Ui1− τi
)Moreover, we get from (4b) and the sharing rule (5):
r Ui1− τi
=bi
1− τi+ pi(θi)
γi Ψi
1− γiJi =
bi1− τi
+ ciγi Ψi
1− γiθi (13)
where the second equality uses the free-entry condition (3). The (gross) wage equation is
wi =γi Ψi
1− γi + γi Ψi(fi(`i) + ci θi) +
1− γi1− γi + γi Ψi
bi + `i1− τi
which gives (7a) in the case of exogenous labor supply by taking `i = 0 and f(`i) = yi. Equation(7b) follows directly. Combining this wage equation with the free-entry condition (3) leads to:(
1 +γi Ψi
1− γi
)r + δiqi (θi)
+γi Ψi
1− γiθi =
1
ci
(fi (`i)−
bi + `i1− τi
)(14)
36Introducing a more complex increasing and convex expression for this disutility leads to more cumbersomeexpressions without adding any new insight.
26
Equation (14) determines implicitly equilibrium tightness θi as a decreasing function of effort`i, of the average tax rate τi and of the CRIP Ψi. Using (1), it also determines the fraction1− ui of participants of type i that are employed.
With an endogenous labor supply margin, productivity is a function of effort and the disutil-ity of effort plays a role similar to the value in nonemployment bi. For a given level of effort `i, arise in progressivity (a decrease in the CRIP Ψi) increases employment through the same wagemoderating. Moreover, a rise in tax progressivity decreases effort `i. This reduction has twoopposite effect on the total surplus. On the one hand, production decreases, on the other handthe disutility of work also decreases. The net effect of hours of work on employment depends onhow the term fi (`i)− (bi+`i)/(1−τi) varies with effort `i. Using (12) a reduction in effort `i in-creases (decreases) this term whenever taxation is regressive (progressive) i.e. when Ψi > 1 (i.e.Ψi < 1). Therefore, by continuity, and provided that the taxation is not too progressive so thatthe labor supply effect of tax progressivity remains dominated by the wage moderating effect, arise in tax progressivity (a reduction in the CRIP Ψi) increases employment and decreases theunemployment rate.
To get the Let us denote Xi ≡ γi Ψi
1−γi . From (14), the effect of the CRIP Ψi on tightnesshappens only through a change in the “effective” bargaining power that is captured by a changein Xi. A rise in the CRIP Ψi holding the average tax rate τi constant increases participationonly if it increases the value of unemployed. Rewriting (13) as:
r Ui = bi + ci Xi θi(1− τi)
implies that a rise in the CRIP for a fixed τi increases participation if and only if Xi θi isincreasing in Xi. Denoting the elasticity of the job filling rate by η(θ) ≡ −θq′(θ)/q′(θ) anddifferentiating (14) in θi and in Xi = γi Ψi
1−γi gives
dθiθi
= −Xi
r+δq(θi)
+Xi θi
η(θi)(1 +Xi)r+δq(θi)
+Xi θi
dXi
Xi
Hence, Xi θi is increasing in Xi, thereby participation is decreasing in progressivity, if and onlyif Xi > η(θi)(1 +Xi). Given the definition of Xi, the latter condition is equivalent to
γi Ψi
1− γi + γi Ψi> η(θi)
that is to effective bargaining power being higher than the efficient one prescribed by the Hosios(1990) condition (see Pissarides (2000)), i.e. by unemployment rate being inefficiently high.
B Data Appendix
Instruments
DisTrustCivil: percentage of respondents which gives answer 4 (i.e., ‘none at all’) to ques-tions E069 8 in WVS1-5, V212 in EVS4, V207 in EVS3, q553i in EVS2, v546 in EVS1 (howmuch confidence in civil service). The period is as follows:
1980-89 : coverage by EVS1/WVS1 but for CHE, covered by EVS2. Surveys carried in 1981for AUS, BEL, DEU, DNK, ESP, FIN, FRA, GBR, IRE, JPN, NLD; 1982 for CAN, NOR, NOR,SWE, USA;
1990-94 : coverage by EVS2/WVS2. Surveys carried in 1990 for AUT, BEL, CAN, DEU,DNK, ESP, FIN, FRA, GBR, ITA, JPN, NLD, NOR, PRT, SWE, USA. Notice that we havetwo observations for ESP (in year 1990) corresponding to both WVS2 and EVS2 being carriedthat year.
27
1995-99 : coverage by EVS3/WVS3. Surveys carried in 1995 for AUS, ESP, JPN, USA; 1996for CHE, FIN, NOR, SWE; 1997 for DEU; 1998 for GBR, BEL, GBR, NZL; 1999 for AUT,BEL, DEU, DNK, ESP, FRA, GBR, GRC, IRE, ITA, NLD, PRT, SWE, USA. Notice that wehave two observations for ESP (1995 and 1999), DEU (1997 and 1999), GBR (1998, 1999), andUSA (1999), corresponding to both WVS3 and EVS3 being carried in those countries.
2000-04 : coverage by WVS4 but for FIN and NZL, covered by EVS3 and WVS5, respectively.This period is generally not covered by any EVS wave, thus the majority of European countriesis not surveyed. Surveys carried in 2000 for CAN, ESP, FIN, JPN; 2004 for NZL.
2005-08 : coverage by EVS4/WVS5. Surveys carried in 2005 for AUS, FIN, ITA, JPN; 2006for CAN, DEU, FRA, GBR, NLD, SWE, USA; 2007 for CHE, ESP; 2008 for AUS, CHE, DEU,DNK, ESP, FRA, GRC, IRE, NLD, NOR, PRT. Notice that we have two observations for AUS(2005 and 2008), CHE (2007 and 2008), DEU (2006, 2008), ESP (2007, 2008), FRA (2006,2008), NLD (2006, 2008), POL (2005, 2008), corresponding to both WVS5 and EVS4 beingcarried.
Observations were averaged out by country and period thus obtaining an unbalanced panelof 21 countries covering the period 1990-2008 in five years averages. Missing observations wereobtained by linear interpolation. The initial observation covering the period 1980-89, has notbeen used in the empirical analysis, but provided the basis to obtain the observation for theperiod 1990-94 by linear interpolation rather than extrapolation for countries where observationswere missing for this period.
Leftism: Unweighted distance between left party and right party in legislative seats, as a per-cent of all legislative seats (authors’ calculation on data from ‘Electoral, Legislative, and Govern-ment Strength of Political Parties by Ideological Group in Capitalist Democracies, 1950-2006: ADatabase’, (by Duane Swank. See http : //www.marquette.edu/polisci/facultyswank.shtml).
Pcdebt: General government gross financial liabilities, as a percentage of GDP (OECDEconomic Outlook).
Taxhike: dcoumented tax increases drawn by historical sources and records based onthe methodology developed by Romer and Romer (2010). (see Devries et alii, 2011: http ://www.imf.org/external/pubs/cat/longres.aspx?sk = 24892.0.
Other variables used in the analysis
EPL: Unweighted sum of the OECD synthetic index of employment protection legislation(OECD Employment Outlook).
UnionDensity: union density (% of unionized workers; OECD Employment Outlook).UBRR: average unemployment benefit replacement rates (average of replacement rates across
various earnings levels, family situations and durations of unemployment; OECD Benefits andWages Database).
Irate: Long-term interest rate on government bonds (OECD Economic Outlook).Outgap: Percentage deviation of output from trend (OECD Economic Outlook).Rexch: Ratio of home country’s prices to a weighted average of competitor country’s prices,
relative to a base year (2000) and measured in US dollars. Therefore an increase is an appreci-ation of the home country’s real exchange rate (OECD Main Economic Indicators).
Inflchange: Change in the inflation between two consecutive years (authors’ calculation ondata from the OECD Economic Outlook).
C First-stage results
28
Un
emp
loym
ent
rate
Em
plo
ym
ent
rate
ln(ret
100)
ln(ret
167
ret
67
)H
anse
nJ
test
ln(ret
100
)ln
(ret
167
ret
67
)H
an
sen
Jte
st(p
valu
e)(p
valu
e)
1.n
oou
tpu
tgap
-55.
31**
77.5
4***
0.60
-55.3
1**
77.
54*
**0.
496
(25.
32)
(28.
55)
(0.4
37(2
5.32)
(28.5
5)
(0.4
81)
2.
conte
mp
ora
neo
us
tax
ind
icato
rs-6
6.85
**76
.10*
*1.
09-6
6.8
5**
76.
10*
*0.4
17(2
7.47
)(3
3.45
)(0
.295
)(2
7.47)
(33.4
5)
(0.5
18)
3.
cou
ntr
yfi
xed
effec
ts,
on
ly-4
8.30
***
59.1
9***
1.44
3-4
8.30*
**59.
19*
**0.
003
(18.
67)
(17.
81)
(0.2
29)
(18.
67)
(17.8
1)
(0.9
57)
4.
cou
ntr
ysp
ecifi
ctr
end
s,on
ly-5
5.09
**77
.26*
**0.
339
-55.0
9**
77.
26*
**0.
316
(22.
89)
(26.
25)
(0.5
61)
(22.
89)
(26.2
5)
(0.5
74)
5.
cou
ntr
ysp
ecifi
ctr
end
san
dti
me
du
mm
ies
-58.
99**
*70
.19*
**0.
225
-58.
99*
**70.
19*
**0.
226
(22.
67)
(26.
73)
(0.6
35)
(22.
67)
(26.7
3)
(0.6
35)
6.
cou
ntr
yfi
xed
effec
tsan
dC
CE
Pes
tim
ator
-51.
80**
*62
.51*
**0.
485
-51.
80*
**62.
51*
**0.
068
(19.
28)
(22.
31)
(0.4
86)
(19.
28)
(22.3
1)
(0.7
94)
7.
HA
Cst
an
dar
der
rors
-59.
18**
70.1
3**
0.17
4-5
9.1
8**
70.
13*
*0.1
48(2
8.35
)(3
0.56
)(0
.676
)(2
8.35)
(30.5
6)
(0.7
00)
8.
Fra
nce
excl
ud
ed-6
5.36
***
59.8
9**
1.37
1-6
5.36*
**59.
89*
*1.
390
(20.
43)
(23.
66)
(0.2
41)
(20.
43)
(23.6
6)
(0.2
38)
9.
Irel
an
dex
clu
ded
-58.
18**
*62
.98*
*0.
321
-58.
18*
**62.
98*
*0.
104
(21.
59)
(25.
00)
(0.5
71)
(21.
59)
(25.0
0)
(0.7
47)
10.
Jap
an
excl
ud
ed-8
2.95
**76
.99*
*0.
283
-82.9
5**
76.
99*
*0.5
34(4
1.40
)(3
3.72
)(0
.594
)(4
1.40)
(33.7
2)
(0.4
65)
11.
Net
her
lan
ds
excl
ud
ed-6
7.97
**80
.52*
*0.
166
-67.9
7**
80.
52*
*0.0
61(3
1.88
)(3
4.74
)(0
.683
)(3
1.88)
(34.7
4)
(0.8
06)
12.
thre
eye
ars
aver
ages
-51.
69*
51.6
5**
0.13
2-5
1.69*
51.6
5**
0.498
(26.
51)
(25.
39)
(0.7
16)
(26.
51)
(25.3
9)
(0.4
80)
Tab
le6:
Rob
ust
nes
sch
ecks.
IVes
tim
ates
wit
hro
bu
stst
and
ard
erro
rs.
Han
senJ
pro
vid
esth
ep
-valu
eof
the
Han
sen
test
for
over
-id
enti
fica
tion
.S
ign
ifica
nce
leve
ls:∗
:10
%,∗∗
:5%
,∗∗∗
:1%
29
[3] [4] [5]ln(ret100) ln(ret100) ln(ret100) ln( ret167
ret67 )
Taxhike –0.0135** –0.0126* –0.0127* –0.0062(0.0068) (0.0068) (0.0068) (0.0060)
Trust –0.0830 0.1936***(0.0786) (0.0674)
Leftism –0.0475*** –0.0421*** –0.0461*** –0.0301(0.0143) (0.0154) (0.0148) (0.0192)
ln( ret167ret67 ) 0.2025**
(0.0855)UBRR 0.0045*** 0.0046*** 0.0044*** –0.0003
(0.0009) (0.0009) (0.0009) (0.0006)UnionDensity –0.0064*** –0.0054*** –0.0065*** –0.0043**
(0.0014) (0.0016) (0.0014) (0.0017)wcoord –0.0014 –0.0017 –0.0018 0.0021
(0.0064) (0.0064) (0.0063) (0.0029)EPL 0.0152 0.0135 0.0177* 0.0026
(0.0110) (0.0110) (0.0104) (0.0079)outputgap –0.0034* –0.0032* –0.0035* –0.0011
(0.0018) (0.0018) (0.0018) (0.0011)inflchange –0.0047** –0.0043** –0.0047** –0.0017
(0.0022) (0.0020) (0.0022) (0.0019)irate –0.0102 –0.0114* –0.0105 0.0062*
(0.0071) (0.0068) (0.0072) (0.0032)
R2 0.98 0.98 0.98 0.93F Test of Excluded instruments 8.444 6.828 5.976 6.391Shea Partial R2 0.109 0.090 0.0778 0.0430Kleibergen-Paap under-identification test 0.0000 0.0002 0.0009Kleibergen-Paap weak-identification test 8.44 6.83 4.12N 231 231 231 231
Table 7: First stage results. Robust standard errors in parentheses. Significance levels: ∗: 10%,∗∗: 5%, ∗ ∗ ∗: 1%. p values of Kleibergen-Paap rank LM test for under-identification test
30
References
[1] Algan, Y., P. Cahuc and A. Zylberbrg, 2002, Public employment and labour market per-formance, Economic Policy, 17(34), 7-66.
[2] Algan, Y., P. Cahuc and M. Sangnier, 2011, Efficient and Inefficient Welfare States’ IZADiscussion Paper No. 5445.
[3] Algan, Y. and P. Cahuc, 2006, Civic Attitudes and the Design of Labour Market Institu-tions: Which Countries Can Implement the Danish Flexicurity Model?’ CEPR DiscussionPaper No. 5489, February, Centre for Economic Policy Research.
[4] Algan, Y. and P. Cahuc (2010) Inherited Trust and Growth, American Economic Review,100(5): 2060-92.
[5] Arpaia, A. and G. Mourre (2010) ‘Institutions and performance in European labor markets:taking a fresh look at evidence’ Journal of Economic Surveys.
[6] Bassanini A., R. Duval (2009) Unemployment, institutions and reform complementarities:re-assessing the aggregate evidence for OECD countries Oxford Review of Economic Policy,25, 1.
[7] Bean, C., R. Layard, and S.J. Nickell (1986) The Rise in Unemployment: A multicountrystudy Economica, 53: S1-S22.
[8] Belot, M. and J. Van Ours, 2004, Does the recent success of some OECD countries inlowering their unemployment rates lie in the clever design of their labor market reforms?,Oxford Economic Papers, 56(4), 621-642.
[9] Bertola G., 2009, Fiscal Policy and Labor Markets at Times of Public Debt, CEPR Dis-cussion Paper 8 037.
[10] Blanchard, O. and J. Wolfers, 2000, The role of shocks and institutions in the rise ofEuropean unemployment: the aggregate evidence, Economic Journal 110/ 462: C1-C33.
[11] Blundell, R. and A. Shepard, 2012, Employment, hours of work and the optimal taxationof low-income families, Review of Economic Studies, 79(2), 481-510.
[12] Boone, J. and Bovenberg, L., 2004, The optimal taxation of unskilled labor with job searchand social assistance, Journal of Public Economics, 88(11), 2227-2258.
[13] Botero, J.C., Djankov, S., La Porta, R. and F. Lopez-de-Silanes, 2004, The regulation ofLabor, Quarterly Journal of Economics, 119, 1339-1382.
[14] Brunello G. and D. Sonedda, 2009, Progressive taxation and wage settino when unionsstrategically interact, Oxford Economic Papers, 59, 127-140.
[15] Butler J., P. Giuliano, and L. Guiso, 2009, The Right Amount of Trust, NBER WorkingPaper 15 344.
[16] Cahuc, P. and A. Zylberberg, 2004, Labor Economics, MIT Press, Cambridge, MA, US.
[17] Daveri, F., and G. Tabellini, 2000, Unemployment, growth and taxation in industrialcountries, Economic Policy, 15, 47-88.
[18] Devries P., J. Guajardo, D. Leigh and A. Pescatori, 2011, A New Action-based Dataset ofFiscal Consolidation, IMF Working Paper 11/128, International Monetary Fund.
31
[19] Diamond, P., 1982, ‘Wage determination and efficiency in search equilibrium’, Review ofEconomic Studies, 49, 217-227.
[20] Doerremberg, P. and A. Peichl (2010), ‘Progressive Taxation and Tax Morale’, IZA Dis-cussion Paper, No. 5378.
[21] Drazen, A., 2000, Political Economy in Macroeconomics, Princeton University Press,Princeton.
[22] Eichhorst, W., Feil, M. and P. Marx, 2010, Crisis, What Crisis? Patterns of Adaptationin European Labor Markets, IZA Discussion Paper, 5045.
[23] Eisa, N. and J. Liebman, 1996, Labor supply responses to the earned Income tax credit,Quarterly Journal of Economics, 111(2), 605-637.
[24] Falk, M. and Koebel, B., 2001, A Dynamic Heterogeneous Labour Demand Model forGerman Manufacturing, Applied Economics, 33, 339-348.
[25] Fitzenberger, B. (1999), Wages and Employment Across Skill Groups. An Analysis forWest Germany, ZEW Economic Studies, 6, Physica, Heidelberg.
[26] Fuest, C. and B. Hubert, 2000, Is tax progression really good for employment? A modelwith endogenous hours of work, Labour Economics, 7, 79-93.
[27] Freier, R. and V. Steiner, 2007, Marginal Employment and the Demand for HeterogenousLabour: Empirical Evidence from a Multi-Factor Labour Demand Model for Germany,IZA Discussion Paper 2577.
[28] Gali, J. and R. Perotti (2003) ”Fiscal Policy and monetary integration in Europe”Economic Policy, October 2003, pp.533-572.
[29] Giavazzi, F., Schiantarelli, F. and M. Serafinelli, 2009, Culture, Policies and Labor MarketOutcomes, NBER Working Paper 15 417.
[30] Griffith, R., Harrison R. and G. Macartney, 2007, Product market reforms, labour marketinstitutions and unemployment, The Economic Journal, 117, C142-C166.
[31] Guichard, S., M. Kennedy, E. Wurzel and C. Andre, 2007, What Promotes Fiscal Con-solidation: OECD Country Experiences, OECD Economics Department Working Paper,No. 553.
[32] Guiso, L., Sapienza, P., and L. Zingales, 2008, Long term persistence, NBER Workingpaper 14 278.
[33] Hamermersh, D., 1993, Labor Demand, Princeton University Press.
[34] Hansen, C. T., 1999, Lower tax progression, longer hours and higher wages, ScandinavianJournal of Economics, 101, 49-65.
[35] Hansen, C., Pedersen, L and. Sløk, 1995, Progressive taxation, wage setting and unem-ployment: theory and swedish evidence, Swedish Economic Policy Review, 2, 423-460.
[36] Heckman, J., 1993, What Has Been Learned about Labor Supply in the Past TwentyYears?, American Economic Review, 83, 116-121.
[37] Hersoug, T., 1984,Union Wage Responses to Tax Changes, Oxford Economic Papers, 36,37-51.
32
[38] Holmulund, B. and A. Kolm, 1995, Progressive taxation, wage setting and unemployment:theory and swedis evidence, Swedish Economic Policy Review, 2, 423-460.
[39] Holm-Hadulla, F. Leiner-Killinger, N., and M. Slavik, 2011, The response of labour taxa-tion to changes in government debt, ECB Working Paper, No. 1307, March.
[40] osios, A.,1990, On the Efficiency of Matching and Related Models of Search and Unem-ployment, Review of Economic Studies, 57, 279-298.
[41] Hungerbuhler, M., E. Lehmann, A. Parmentier and B. Van der Linden, 2006, Optimalredistributive taxation in a search equilibrium model, Review of Economic Studies, 73,743-767.
[42] Immervoll, H., Kleven, H., Kreiner, C. T. and Saez, E., 2007, Welfare reforms in Europeancountries: a Microsimulation analysis, Economic Journal, 117, 1-44.
[43] Juhn, C., K.M. Murphy, R.H. Topel, J.L. Yellen and M.N. Baily, 1991, Why has theNatural Rate of Unemployment Increased over Time?, Brookings Papers on EconomicActivity, 75-142.
[44] Koskela, E. and R. Schob, 2007, Tax progression under collective wage bargaining andindividual effort determination, CESifo Working Paper 2024.
[45] Koskela, E. and R. Schob, 2009, Is tax progression good for employment? Efficiency wagesand the role of the pre-reform tax structure, FinanzArchiv: Public Finance analysis, 65,51-72.
[46] Lehmann, E., A. Parmentier and B. Van der Linden, 2011, Optimal income taxation withendogenous participation and search unemployment, Journal of Public Economics, 95,1523-1537.
[47] Lockwood B. and Manning A., 1993, Wage Setting and the Tax System: Theory andevidences for the United Kingdom, Journal of Public Economics, 52, 1-29.
[48] Lockwood, B., Sløk, T. and T. Tranaes, 2000, Progressive taxation and wage setting. someevidence for Denmark, Scandinavian Journal of Economics, 102, 707-723.
[49] Malcomson, J. and N. Sartor, 1987, Tax push inflation in a unionized labor market, Eu-ropean Economic Review, 31, 1581-1596.
[50] Manning, A., 1993, Wage bargaining and the Phillips curve: The identification and spec-ification of Aggregate wage equations, Economic Journal, 103(416), 98-118.
[51] Meghir, C. and Phillips 2010, Dimensions of Tax Design, in The Mirrlees Review, Institutefor Fiscal Studies (eds), Oxford University Press, Oxford, UK.
[52] Mortensen, D. and Pissarides, C. 1999, New developments in models of search in theLabor Market, in O. Ashenfelter and D. Card (eds.), Handbook of Labor Economics, vol 3B, North-Holland, Amsterdam.
[53] Musgrave, R. A. and Thin, T. 1948, Income tax progression, 1928-48, Journal of PoliticalEconomy, 56, 498-514.
[54] Nickell, S.J. and R. Layard, 1999, Labour market institutions and economic performance,in: Ashenfelter, O. and Card, D. Handbook of Labor Economics, Amsterdam, North Hol-land, 3029-3084.
33
[55] Nickell, S.J., L. Nunziata, and W. Ochel, 2005, Unemploment in the OECD since the1960s. What do we know?, The Economic Journal, 115, 1-27.
[56] Nunziata, L., 2005, Institutions and Wage Determination: a Multi-country Approach,Oxford Bulletin Of Economics And Statistics, 67, 435-466.
[57] OECD Taxing Wages, 2009, Special feature: consumption taxation as an additional burdenon labour income Organization of Economic Co-operation and Development.
[58] OECD (2012), OECD Tax database, Organization of Economic Co-operation and Devel-opment.
[59] Pagano, M., and P. Volpin, 2006, The Political Economy of Corporate Governance, Amer-ican Economic Review, 95, 1005-1030.
[60] Parmentier, A., 2006, The effects of the marginal tax rate in a matching model withendogenous labor supply, IRES Discussion Paper 2006− 11.
[61] Pesaran, M., 2006, Estimation and inference in large heterogeneous panels with a multi-factor error structure, Econometrica, 74(4), 967-1012.
[62] Persson, T. and G. Tabellini, 2000, Political Economics: Explaining Economic Policy,MIT Press, Cambridge, MA, US.
[63] Pissarides, C. A., 1985, Taxes, Subsidies and Equilibrium Unemployment,Review of Eco-nomic Studies, 52, 121-34.
[64] Pissarides, C. A., 1998, The impact of employment tax cuts on unemployment and wages:the role of unemployment benefits and tax structure, European Economic Review, 42,155-183.
[65] Pissarides, C. A., 2000, Equilibrium Unemployment Theory, Second Edition, MIT Press,Cambridge, MA, US.
[66] Røed, K. and S. Strøm, 2002, Progressive Taxes and the Labour Market: Is the TradeoffBetween Equality and Efficiency Inevitable?, Journal of Economic Surveys, 16, 77-110.
[67] Romer, Christina D., and David H. Romer, 2010, The Macroeconomic Effects of TaxChanges: Estimates Based on a New Measure of Fiscal Shocks, American Economic Re-view, 100 (3), 763-801.
[68] Sapienza, P., A. Toldra and L. Zingales, 2007, Understanding Trust, NBER Working paper,13 387.
[69] Sørensen, P. B., 1997, Public finance solutions to the European unemployment problem?,Economic Policy, 25, 223-64.
[70] Sørensen, P. B., 1999, Optimal Tax Progressivity in Imperfect Labour markets, LabourEconomics, 6, 435-52.
[71] Summers L., Gruber J. and R. Vergara, 1993, Taxation and the structure of labor markets:the case of corporatism’ The Quarterly Journal of Economics, 108, 385-411.
34