Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5 407
JEL Classification: J22, J31, I38
Keywords: labor supply, welfare trap, net replacement rate
An Empirical Analysis of Welfare Dependence
in the Czech Republic*
Martin GUZI—Masaryk University, Brno, Czech Republic, and CELSI (Central European Labor
Studies Institute), Bratislava, Slovakia (Martin.Guzi@econ.muni.cz)
Abstract
The scope of this paper is to empirically test whether the potential disincentive effects
of the Czech social security system affected the labor flows from unemployment to
employment over the period 1995–2005. Combining individual data from the Czech
Labor Force Survey and the Czech Household Income Survey, the analysis exploits
the difference between the available social benefits and the net household income when
a person is employed. Estimates imply that individuals who receive relatively higher
social benefits are also more likely to remain unemployed and it is shown that the groups
most affected are those with low education and long spells of unemployment. The paper
confirms that the level and persistence of unemployment in the Czech Republic after 2000
can be partly attributed to the nationwide level of social support that constitutes a welfare
trap for some individuals.
1. Introduction
The combination of tax and social security systems affects labor market dynamics.
The scope of this paper is to explore whether the potential disincentive
effects created by the Czech tax and social security systems reduced the labor flows
from unemployment to employment over the period 1995–2005. The employment
and social policies are subject to incentive compatibility constraints given that they
have to make work pay. The interaction of tax and social security systems defines
the disposable income of individuals and, therefore, influences the decision of the unemployed
to accept a job.
In the late 1990s, the amount of social benefits paid to the unemployed was
relatively generous; indeed, the Czech social welfare system was ranked the second
most generous in the OECD in 1996 (OECD, 1998).1
Moreover, the incremental benefit
provided to families with children was proportionally larger in the Czech Republic
than in any other OECD country (OECD, 1998). OECD studies pointed out that
the combination of benefit withdrawal and the tax system in the Czech Republic
could lead to a distorted labor supply (OECD, 1998; OECD, 2004). In 1998, OECD
representatives issued the recommendation for the Czech Republic to “re-examine
the basis upon which benefits in the social assistance and state social support system
are determined. To preserve work incentives, additional benefits awarded to larger
families need to be reduced in line with international practice”.2
At the same time,
*
This work was supported by the project “Employment of the Best Young Scientists for International Cooperation
Empowerment” (CZ.1.07/2.3.00/30.0037) co-financed from the European Social Fund and the state
budget of the Czech Republic. I would like to thank Daniel Munich, Kamil Galuscak, Jozef Zubicky, Ondrej
Schneider, Ricarda Schmidl, Jan Kmenta, Randall Filer, Mikolaj Herbst, Michael Moritz and two anonymous
referees for their valuable comments. All errors remaining in this text are the responsibility of the author.
1
The benefit generosity is compared relative to the average economy wage rather than in absolute terms.
2
OECD (1998), p. 87
408 Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5
the economic transformation in the late 1990s prompted a steep increase in the unemployment
rate. The unemployment rate doubled following the recession in 1997,
while the long-term unemployment rate more than tripled between 1996 and 2000
(see Figure 1 in Appendix 1). After 2000, the unemployment rate remained high even
though the economy was growing (see Jurajda and Munich (2003) for discussion).
The tax and social security systems in the Czech Republic were assessed by
several studies as generating a welfare trap for a wide range of households (e.g. Jahoda,
2004; Schneider, 2004; Jurajda and Zubricky, 2005; Flek and Vecernik (2005); Galuscak
and Pavel, 2007). Results from studies suggest that high net replacement rates are
likely to attenuate work incentives for individuals with children, as well as those who
have lower chances of getting a better-paid job. For these individuals, the potential
income from employment may not be significantly higher relative to the available
income from social benefits. Galuscak and Pavel (2007) estimate that around onethird
of all employed individuals in the Czech Republic in 2006 had low incentives
to avoid short spells of unemployment given that it did not significantly reduce
their earnings. These findings are typically based on the theoretical considerations for
selected types of households, with the potential income of the unemployed usually
approximated with the income of the average production worker in the economy and
compared to the amount of available benefits.
Several studies (e.g. Sorm and Terrell, 2000; Lauerova and Terrell, 2005) have
examined the behavior of the unemployed in the Czech labor market directly using
microdata but have not considered the role of social benefits. One exception is
the study of Commander and Heitmueller (2007), who use microdata and empirically
test the impact of social benefits on the labor supply behavior of the unemployed in
the Czech Republic, Hungary and Poland. However, the measure of the generosity
of social benefits is simplistic in their analysis, with the authors assuming the average
level of benefits relative to the national average wage for several household types.
The high approximation of social benefits at the household level reflects the main
drawback of the paper and, consequently, the authors find only weak evidence for
the role of social benefits in the Czech labor market.
This paper explores the idea from Commander and Heitmueller (2007) but
significantly improves the computations of household income under working and
non-working alternatives. Given that the Czech Labor Force Survey does not include
any income information, the Czech Household Income Survey is used to estimate
potential income in the local labor market for the unemployed. This information
allows us to calculate the net replacement rate (NRR) based on the parameters of
the taxation system and rules for means-tested social benefits at the household level.
The analysis subsequently proceeds to examine the link between the generosity of
social benefits and individual labor supply behavior. The purpose of the paper is to
test the hypothesis that high social benefits constitute a welfare trap for the unemployed
and to identify the existence of a welfare trap among different groups.
The focus of the analysis is on the period 1995–2005, during which the long-term
unemployment rose from 2% to 6%. We explore the extent to which the development
of unemployment can be attributed to the state social support scheme. Based on
the findings from recent studies which evaluate changes in the tax and social security
systems introduced in 2007 and 2008, we conclude that the main findings from
the analysis are valid and that the welfare trap is still present in the Czech social system.
Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5 409
The remainder of the paper is organized as follows: the next section discusses
the empirical findings of labor market policies on individual labor supply behavior.
Section 3 describes the Czech social security system. Section 4 proposes a simple
job-search model to derive the behavior of the unemployed with available social
benefits. Section 5 provides a description of the data set used and presents summary
statistics. The calculation of NRR for each household is described in Section 6, while
Section 7 presents the findings and Section 8 concludes the paper.
2. Literature Review
Both active and passive labor market policies were introduced in the transition
economies during the 1990s to relieve tensions in the labor market and provide
income support for jobless workers. Government interventions through an active
labor market policy (ALMP) provide training and guidance to the unemployed. Indeed,
it is documented that the increased expenditure on ALMP has a positive impact
on employment prospects in EU-15 countries, and it has also been shown that youth
measures and public employment services reflect the most efficient allocation of
ALMP resources (European Commission, 2004). The level of expenditure on ALMP
is substantially lower in the countries of Central and Eastern Europe (CEE), and thus
it is not surprising that unemployment development does not seem to be affected
by ALMP in these countries (Lehmann and Muravyev, 2009). The weak efficiency
of ALMP programs in the Czech Republic was previously confirmed in Munich,
Svejnar and Terrell (1999). Flek and Vecernik (2005) mention that expenditure on ALMP
appeared to be insufficient to reverse the rising unemployment rate in the Czech
Republic in the late 1990s.
Passive labor market policies ensure that individuals can subsist during periods
of unemployment with more resources allocated to these programs.3
On the one
hand, the availability of income support for the unemployed renders joblessness less
painful, thus allowing for a longer job search that leads to a better job match in
the labor market. Wulfgramm and Fervers (2013) find that workers in European countries
with more generous income support for the unemployed achieve higher employment
stability upon re-employment. The authors suggest that this outcome is possibly
driven by the intensity of ALMP programs via skill level increases and information
deficit reductions.
On the other hand, generous social benefits can negatively affect the jobsearch
intensity of unemployed workers and, conditional on the wage offered, higher
benefits reduce the economic incentives to accept a job offer. The literature provides
many examples showing that most of the unemployed want to work and the evidence
of negative aspects of welfare participation on transition to work is documented. In
Germany, Schneider and Uhlendorff (2006) confirm that transitions to employment
during 1992–2000 were more likely to be observed for unemployed individuals with
a higher potential wage relative to the level of social benefits. Portugal and Addison
(2008) identify disincentive effects of unemployment benefits on the exit rate from
unemployment using Portuguese employment surveys between 1992 and 1997.
Petrongolo (2009) evaluates the UK reform in 1996 that introduced tighter search
requirements for social benefit claimants. She concludes that the reform was success-
3
The Ministry of Labor and Social Affairs reports that the share of ALMP in GDP was 0.07% during
the period 1995–2000. The average spending on passive programs amounted to 0.23% of GDP.
410 Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5
ful in moving unemployed individuals into the labor market through raising the costs
of remaining on social benefits. Van Ours and Vodopivec (2006) find that the rate of
finding jobs among the unemployed in Slovenia largely increased after 1998, when
the benefit entitlement period was substantially shortened. The exit rate remained
unchanged for the unemployed whose entitlement period did not change; therefore,
the authors interpret the effect as causal. Boeri (2000) finds a positive relationship
between the level of social benefits and the (self-reported) reservation wages of individuals
in the transition countries with generous social benefits increasing the opportunity
costs of employment and leading to high reservation wages. Boeri explains
that the distribution of reservation wages does not increase uniformly but rather rises
predominantly at its lower end. Consequently, high social benefits increase the chances
of low-productive workers remaining out of employment.
Both the tax and social security systems contain measures targeted at poorer
households and families with children. Prusa (2001) discusses the redistribution and
tax policies in the Czech Republic prior to 2000 and Jahoda (2004) in 2003. Both
studies conclude that there is little interaction between these two systems with
the welfare trap likely to arise for low-income individuals who transition from unemployment
to employment. Schneider (2004) shows that the tax and social security
systems in the Czech Republic heavily redistribute income towards low-income
groups. Working with aggregate figures from 2001, Schneider finds that taxes rise
and social benefits are withdrawn when household income moves up from the bottom
decile, creating strong disincentives for labor market participation. Similarly higher
benefits targeted to families with children may lock individuals in unemployment due
to the welfare trap. Jurajda and Munich (2003) use the 2001 Czech Labor Force
Survey to show that the propensity for long-term unemployment increases largely in
families with more than three children. Jurajda and Zubricky (2005) discuss the parameters
of the tax and social security systems, showing that the level of social benefits
for individuals from low income and large families remains relatively high in the case of
long-term unemployment. Therefore, the guaranteed household income from social
benefits suggests very little motivation for individuals to exit unemployment.
Several studies have empirically examined the behavior of the unemployed in
the Czech labor market using microdata. Ham, Svejnar and Terrell (1998) use data on
unemployed men from 1991–1993 to show that higher unemployment benefits and
a longer entitlement period lead to longer unemployment duration. However, the authors
argue that the estimated elasticities are moderate and comparable to estimates obtained
from Western Europe. The important finding demonstrated by the authors is that in
the early 1990s the Czech labor market absorbed the low-skilled unemployed at a rate
similar to the rate at which it absorbed the skilled unemployed. The study by Sorm and
Terrell (2000) analyzes worker mobility across different labor market states during
1994–1998. It considered individual characteristics as determinants of labor mobility
and concluded that labor market flows during the studied period were efficient with
a low incidence and short duration of unemployment. Lauerova and Terrell (2005)
explore the female-male differences in labor market flows over the period 1993–1996,
finding that women have significantly lower probabilities of exiting unemployment
than men. Such chances are particularly low for married women. Commander and
Heitmueller (2007) study flows in the labor market with respect to the role of social
benefits during 1993–2003, finding weak evidence that individual decisions to transition
Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5 411
from unemployment to employment relate to the amount of social benefits. However,
this result can be partly attributed to the fact that the authors use a simple approximation
of benefit generosity at the household level.
The findings from the literature evaluating the dynamics in the Czech labor
market are very inconclusive. The findings based on income simulation for selected
households suggest that the combination of the tax and social security systems in
the Czech Republic creates a welfare trap, i.e. social benefits are accepted as an alternative
to low and insecure earnings. Empirical studies find that the less educated tend
to have a higher incidence and longer duration of unemployment, though the association
between social benefits and high unemployment was not directly confirmed.
This paper fills the gap and demonstrates the existence of a welfare trap, finding
a negative influence of the high NRR on the probability of transitioning from unemployment
to employment.
3. The Czech Social Security System
The Czech government implemented extensive reforms to its tax and social
security systems in the early 1990s. The social security system described in this
paper was introduced in 1995 and had only undergone minor changes until 2005.4
Workers who become unemployed are eligible to receive unemployment benefits for
a period of six months with the amount calculated from their previous net income.
The unemployed who are jobless for more than six months are entitled to social
benefits of unlimited duration. Social benefits are not taxable and are subject to
means testing. In practice, they are paid to keep household income above the minimum
subsistence level (MSL), which is defined by the Ministry of Labor and Social
Affairs and represents the minimum amount of money that a household of a given
composition would require for its subsistence. The MSL scheme defines a personal
benefit for individuals by age and a household supplement to cover necessary household
expenses. The generosity of the social system is illustrated in Table 1, which
shows MSL benefits expressed in percentages relative to the net income of an average
production worker. The MSL for a given household is defined as the sum of
personal benefits of all family members and the household supplement. Table 2 in
Appendix 1 demonstrates the MSL computed for several typical households. It is
observed that the MSL was initially set at relatively high levels before falling over
time. Galuscak and Pavel (2007) calculate that while the average wage in the Czech
economy between 1996 and 2006 increased by 106%, the amount of social benefits
rose by 66% for single individuals, 57% for a couple without children, and 51% for
a couple with two children. The authors explain that this decreasing trend in benefit
generosity mainly occurred due to relatively high (wage) inflation and a lack of
indexation of social benefits. However, social benefits remained relatively high for
some groups throughout this period. It should be noted that it is standard to express
social benefits relative to the national average wage despite the income of the majority
of workers being lower. Therefore, the presented values are taken as a lower
boundary to illustrate the generosity of social benefits.
Previous studies emphasized that higher social benefits targeting families with
children may constitute a potential welfare trap. As an example, Table 2 illustrates
4
For a detailed description of the Czech tax and benefit systems, see Galuscak and Pavel (2007). An update
to the tax-benefit policy is published annually at http://www.oecd.org/social/benefits-and-wages.htm.
412 Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5
that the guaranteed income from social support for a couple (if both spouses are
unemployed) with two children in 2000 was at 102% of the national net monthly
wage of an average production worker. The amount of benefits at that level may
constitute sufficient income for a family residing in a depressed region, while rendering
an employment alternative as a less attractive option. However, benefit dependency
among the long-term unemployed can lead to mental, social and material deprivation
as documented by Mares and Sirovatka (2005) in the Czech Republic.
4. Theoretical Framework
A simple job-search model represents a useful framework to illustrate the likely
impact of social benefits and job-search intensity on the transition from unemployment
to employment. This model is familiar within the existing literature on jobsearch
theory formalized by Mortensen (1986). In the model, individuals can be
either employed or unemployed and maximize the lifetime utility in continuous time.
Unemployed individuals receive benefits b and invest search time (or intensity)
[0,1]s = to find a job. Search effort cost ( )c s generates job offers at rate ( )sλ from
a known wage distribution F(w). The standard assumption follows that search costs
are convex in effort while returns are concave, thus
( ) 0, ( ) 0, ( ) 0, ( ) 0c s c s s sλ λ′ ′′ ′ ′′> > > <
Employed individuals are paid a wage w and face an exogenous risk of job lossδ .
An individual who has a job does not search for another one. The unemployed
choose an optimal level of job-search effort s and determine the optimal reservation
wage Rw . The flow value of unemployment and employment can be written as
follows, respectively:
[ ]{ },
max ( ) ( ) ( ) ( )
RR
ws w
rU b c s s W w U dF wλ= − + −∫ (1)
and
[ ]( ) ( )rW w w U W wδ= + −
where r represents the intertemporal discount rate. In theory, the reservation wage is
defined at the level that makes a jobseeker indifferent between accepting a job and
remaining unemployed. From ( )RrW w rU= it follows that the flow value of unemployment
is equal to the reservation wage RrU w= , which is derived from (1) as
a function of the parameters of the model:
[ ]
( )
max ( ) 1 ( )R ws R
s
w rU b c s F w dw
r
λ
δ
 
= = − + − 
+ 
∫ (2)
The optimal reservation wage is an implicit function of benefits and search
intensity. The optimal search effort s*
is set at the level that maximizes the intertemporal
utility of a jobseeker. The first order condition for the choice of search
intensity is obtained by differentiating formula (2):
( )
( ) [ ]
*
*
1 ( )
wR
s
c s F w dw
r
λ
δ
′
′ = −
+ ∫ (3)
Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5 413
Equations (2) and (3) form a system that implicitly determines the reservation
wage and search effort. From equation (2), it follows that a higher b increases the reservation
wage while rendering unemployment more attractive relative to employment.
Formally:
( )
( )
( )
1 1 0
( ) 1
R R
R
R
dw dws r
F w
db r db r s F w
λ δ
δ δ λ
+
= − − = >  + + + −  
The dependence of the reservation wage on search effort is ambiguous in sign
given that differentiation leads to:
( )
[ ]
( )
1 ( ) ( )
( ) 1
R
wRR
dw r s
F w dw c s
ds rr s F w
δ λ
δδ λ
′+  
′= − − 
++ + −    
∫ (4)
A search effort below the optimal level implies a positive effect, while a search
effort above the optimal search level implies a negative effect on utility. In the basic
model, a rise in benefit increases the reservation wage, but it is assumed that search
effort is not conditional on a benefit that is unsatisfactory. The next step is to define
the search effort as an implicit function of benefit. Differentiating equation (3) with
respect to b implies:
( )
( ) [ ]
( ) ( )
* ** *
*
1 ( ) 1 0RwR
s sds ds dw
c s F w dw F w
db r db r db
λ λ
δ δ
′′ ′
′′ − − + − =  + +∫
With the help of (4), the result is:
( ) ( )
( ) ( )
( ) [ ] ( )
1
* *
*
*
1
1 ( ) 0
1
*
R
wR
R
s F w sds
F w dw c s
db rr s F w
λ λ
δδ λ
−
 ′ ′′−    ′′= − − <
 ++ + −    
∫
An unemployed person finds a job at rate ( ) ( )*
1 Rs F wλ −   ; therefore,
higher benefits effectively decrease the job finding rate via both a decrease in jobsearch
effort and an increase in the reservation wage. This result implies that higher
benefits increase the duration of unemployment.
5. Data
5.1 Data and Sample Selection
The empirical analysis relies on the quarterly Labor Force Survey (LFS) data
from 1995 to 2005.5
It is a rotating sample, and each quarter 20% of individuals in
the sample are replaced. The survey design allows the tracking of individuals over
two consecutive periods (quarters) in order to identify the change of individual labor
market status in the second period. The LFS follows the ILO definition of unemployment,
i.e. an unemployed person has no employment, actively searches for a job,
and is able to accept a job offer. In the Czech Republic, registration with the labor
5
Labor Force Survey data for the Czech Republic have been collected quarterly since 1993 by the Czech
Statistical Office (CSU). Sample sizes cover more than 250,000 individuals per year. The number of respondents
is proportional to the size of the district. Households are chosen randomly and all members of
households are surveyed.
414 Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5
office is necessary in order to collect social benefits, though labor offices have
limited tools to screen the willingness of the unemployed to work (Galuscak and
Munich, 2007). The aim of the paper is to demonstrate the existence of a welfare
trap and therefore the analysis concentrates on the group of unemployed eligible to
receive social benefits of unlimited duration. The final sample includes individuals
who are jobless for longer than six months; therefore, they can collect social benefits
and their household income never falls below the MSL (see Section 3). The final
sample includes the unemployed who are the heads of households or spouses. Other
persons living in the household, such as the parents of spouses or other relatives, do
not enter the analysis (around 2% of the sample). Due to different retirement schemes,
the sample is limited to working-age individuals in the range of 18–54 years.6
Individuals who report full health disability are dropped from the sample. The LFS
contains information about personal characteristics such as age, gender, the highest
level of educational attainment, unemployment duration and the type of activity performed
prior to unemployment. Family composition and information about the age
and number of children in the household are used to determine the MSL. Unfortunately,
the LFS contains no income information, which is therefore obtained from
the Czech Household Income Survey collected by the Czech Statistical Office in
2002.7
5.2 Summary Statistics
The final sample includes 28,338 unemployed individuals, of whom around
two-thirds comprise women. Table 3 in Appendix 1 presents the descriptive statistics
of the variables used in the analysis, reported separately for men and women. On average,
the transition from unemployment to employment is observed for 9% of individuals
and does not differ between genders. The individuals who transition from
unemployment to inactivity are treated as unemployed and their inclusion does
not have an effect on the final results (around 2.6% of flows from unemployment).
In terms of educational attainment, women are more educated relative to men in
the sample. Overall, the majority of unemployed (77%) attained lower secondary or
primary education. Men in the sample are slightly older than women, while the share
of married women is higher than the share of married men. In terms of activity performed
prior to unemployment, a quarter of unemployed women worked in the household
or provided childcare. By contrast, most unemployed men were employed prior
to becoming unemployed, and about 12% engaged in other activities (such as
military service or education). Longer detachment from the labor market can nega-
6
In 1995, the statutory retirement age was 60 for men and 57 for women with no children, 56 for women who
raised one child, 55 for women who raised two children and 54 for women with three or more children.
7
The Czech Household Income Surveys were collected in 1996 and 2002. The later survey is chosen while
Filer, Jurajda and Planovsky (1999) show that the Czech wage structure stabilized in the late 1990s. The standard
Heckman (1979) model is applied to estimate the wage equation on the sample of workers taking into
account the selection to employment. Income is estimated for the sample of individuals 18–54 years old
who are full-time employees, excluding the self-employed, students and persons working less than 30 hours per
week. Family characteristics such as the presence of children, other household income and the presence of
employed persons other than the spouse are used to estimate participation in the labor market. A potential
full-time gross monthly wage is estimated for every individual in the LFS sample and the estimation is
performed separately by gender. The estimated wages for years other than 2002 are subsequently adjusted
for regional wage growth (see Appendix 2 for details).
Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5 415
tively affect future prospects in the labor market. Interestingly, the share of unemployed
by duration is almost identical by gender. Since 2002, the Czech LFS has
included information on job-search channels used by the unemployed to seek work in
the last period.8
Job-search intensity is constructed as the number of search channels
used. On average, unemployed individuals report using three channels to seek employment,
with higher search intensity likely to accelerate the transition to employment.
Given that the gender differences in personal characteristics and incentives to
exit unemployment are expected to lead to different results, an analysis is also
performed separately by gender.
5.3 Regional Patterns
One of the key sources of variation for the analysis lies in the spatial heterogeneity
in the economic conditions and in the nationally determined policy because
differences in employment opportunities between districts are not reflected in the social
security system, i.e. the MSL is based solely on household composition. However,
wages are set in the local labor market, and thus the actual generosity of social
benefits varies geographically. Taking information from statistical yearbooks of
the Czech Statistical Office, Table 4 in Appendix 1 documents the wage differentials
and the widening unemployment rate between districts over time. In every year,
77 districts are divided into quintiles by the level of the average wage in the district
relative to the national wage and by the district unemployment rate. Average values
for districts in the first and fifth quintiles are reported. In particular, the districts in
the first wage quintile record between 79% and 86% of the national gross wage,
while districts in the fifth wage quintile record between 102% and 107% of the national
gross wage. The variation in the unemployment rate between districts is even
more pronounced, increasing from 6% to 15% in districts in the fifth quintile, while
remaining below 5% in districts in the first quintile over the period 1995-2005. These
findings imply that territorial differences in earnings opportunities determine the relative
generosity of social benefits and therefore the working prospects of the unemployed.
In this paper, regional variation in earnings opportunities is accounted for in
the NRR calculations. The district unemployment rate is included in the main
analysis to control for labor demand in the labor market (the same result is obtained
if the vacancy-unemployment ratio is used rather than the unemployment rate).9
6. Household Welfare Participation
6.1 Income Estimation
Household net income is obtained under two alternatives in order to test
the impact of welfare participation on an individual’s labor supply decision. First,
the individual potential gross income under the working alternative is obtained from
8
The following seven search channels are considered: looking for a job through a public employment
office, through a private employment agency, through friends or relatives, contacting employers directly,
inserting or answering advertisements in newspapers or journals, studying advertisements in newspapers
and journals, or by other means.
9
The district unemployment rate is a sufficient control for demand-side effects if labor demand elasticities
remain unchanged over time. Babecky, Galuscak and Lizal (2011) show that firm-level labor demand elasticities
remained broadly constant in the Czech Republic from 1993 to 2009.
416 Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5
the complementary data set for every person and their spouse in the sample (see
Appendix 2 for details). Subsequently, household net income is computed based on
the parameters of the tax and social security systems and accounts for family
composition. Calculations account for personal income tax, with social security
contributions and rules for means-tested social benefits applied.10
In contrast to
previous studies, the estimation of household income is significantly improved in this
paper. Commander and Heitmueller (2007) assume NRR computed for ten household
types relative to the national average wage, while Galuscak and Pavel (2007) undertake
the estimation assuming that the potential entry wage for the unemployed equals
50% or 67% of the national average wage.
Second, personal income under the non-working alternative is approximated
by the MSL of the household, under the assumption that the household collects
the available social benefits. Mares (2001) roughly estimates non-take-up rates in
the Czech Republic to vary between 10% and 30% depending on the type of social
benefit, which is rather satisfactory. If an unemployed person lives with a working
spouse, the household income is equal to the sum of the net income of the working
spouse and means-tested social benefits.
6.2 Net Replacement Rates
Having household income under both working and non-working alternatives
enables us to calculate the NRR for every individual, which is expressed as the ratio
of net household income when a person is unemployed to the net household income
under the alternative situation when the individual is employed. NRR represents
a useful measure to assess the link between generous social benefits and unemployment
persistence (e.g. Commander and Heitmueller, 2007; Jurajda and Zubricky,
2005). The ratio takes values from 0 to 1, with a higher NRR increasing the reservation
wage of the unemployed, thereby reducing incentives to enter employment. For
example, an NRR close to 1 means there are no monetary incentives to look for a job
given that the household receives the same level of income regardless of employment
status. However, if accounting for other costs associated with the job search and
the costs of participation in the labor market (i.e. transportation costs), even an NRR
lower than 1 provides little incentive to search for a job. Table 5 details the average
NRR computed for the total LFS sample as well as separately for men, women and
groups of different characteristics. The decreasing trend of the NRR reflects the declining
generosity of the social security system. Rates are significantly higher for
women relative to men, which is attributed to their lower earning opportunities in
the labor market. The lowest rates are recorded for men and highly educated individuals
who have better prospects in the labor market in terms of high potential
earnings. Conversely, the highest rates are observed for individuals with children
and those who are low-educated. A clear pattern emerges indicating that the NRR
increases with the length of unemployment, which points to the selection of unskilled
individuals for long-term unemployment. The share of individuals with an NRR
10
I thank Stepan Jurajda and Jozef Zubricky who collected the parameters of tax and social benefit systems
in the Czech Republic for the period 1995–2005. I adapted their calculations of net income and social
benefits from excel tables to STATA (do-files are available upon request).
Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5 417
above 0.8 is calculated at the bottom of Table 5. The pattern shows that the incidence
of high social benefits is prevalent among the unemployed with children, the loweducated,
and the long-term unemployed. Therefore, the existence of a welfare trap is
likely to be present among these groups.
7. Results
In this section, we test for the effect of the NRR on the transition probabilities
of the unemployed to employment, controlling for individual socio-demographic
characteristics, local labor market attributes, and regional and time-fixed effects.
7.1 Estimation Strategy
The model is estimated as the reduced form equation defined as the probability
of transition from unemployment to employment. The indicator function E is
defined. The individual makes the decision to remain unemployed ( )0iE = rather
than enter employment for which they are qualified ( )1iE = because earnings or
other working conditions are less attractive than the option of not working. In the estimation,
constraints on the demand side are approximated by local labor market characteristics
(i.e. the district unemployment rate and regional fixed effects). The key
variable in the model is the incentive to enter employment in the presence of social
benefits. The probability of transitioning from unemployment to employment is
expressed as:
( ) ( )=1|i i i iP E X NRR XΦ α β= +
(5)
where NRR is the ratio of household income under the non-working and working
alternatives, iX includes individual characteristics, (.)Φ is the logistic cumulative
distribution function, and equation (5) is estimated by the standard Logit model.
The estimated coefficient on NRR tests for the existence of the welfare trap. In order
to explore the hypothesis, the sensitivity of the estimated parameter is explored
among different groups of unemployed but also to the inclusion of job-search
intensity.
7.2 The Effect of Social Benefits on the Transition from Unemployment
to Employment
Equation (5) is estimated for different groups with the results reported in
Table 6. Column 1 shows the baseline model estimates from the total sample.
The coefficient on NRR is significant and negative, in line with the hypothesis,
which means that individuals who receive relatively higher social benefits are also
more likely to remain unemployed. Estimates imply that, ceteris paribus, if the NRR
were to decrease from a value of 0.8 to 0.68 (a decrease of one standard deviation to
the mean value), there would subsequently be an associated change in the transition
probability from 8.7% to 9.2%. The existence of the welfare trap and its prevalence
among different groups is discussed further below. The estimated effects of demographic
characteristics on transition probabilities are consistent with the previous
literature. Estimates imply that married persons are more likely to leave unemployment
for a job, as empirically confirmed by Sorm and Terrell (2000). Unemployed
418 Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5
persons who live with an employed spouse exhibit a higher propensity to enter
employment. Coefficients on a female dummy in Table 6 are negative, thus suggesting
that women are disadvantaged in the transition to employment with at least
two reasons discussed within the existing literature. Women are placed in a disadvantaged
position first by having responsibility for childcare (Bicakova, 2010)
and second by lower earnings opportunities in the labor market (Jurajda, 2003).
The presence of young children in the family implies a negative impact although
variables are not significant at the conventional levels.11
In general, people with less
education have a lower propensity to enter employment relative to those with more
education. Furthermore, workers who were not employed prior to unemployment
display a lower ability to exit unemployment. This predominantly concerns women
who worked in the household or provided childcare. A longer duration of unemployment
has a rather strong negative effect on the outflow from unemployment. All
individuals in the sample have been unemployed for at least six months. Estimates
imply that the chances of exiting unemployment decrease by around three percentage
points for those unemployed for longer than 12 months and by 7 percentage points if
the period of unemployment lasts for more than two years. Individuals with partial
health disability have a lower propensity to leave unemployment for a job by 3 percentage
points. A higher unemployment rate in the local labor market indicates fewer
employment opportunities and consequently lower chances of finding a job. Estimates
from the baseline model in Column 1 imply that, ceteris paribus, an increase
of one standard deviation in the unemployment rate is associated with a decline of
0.25 percentage point in the propensity to leave unemployment for employment.
Finally to confirm that results are not driven by the number of children,
the equation is estimated including the interactions of the NRR with the number of
children in the household.12
The estimates confirm the robustness of the benchmark
regression, while the effect of the NRR is negative and significant (the size of the coefficient
is larger in magnitude -4.2 and significant at the 5% level) and the interaction
terms are not significant.
7.3 Which Groups Are Affected?
The transition from unemployment to employment varies with economic
incentives. Previous studies indicate that motivation may be particularly low for
those unemployed with children as well as for individuals who have lower chances of
getting a better-paid job. To test this hypothesis, equation (5) is estimated separately
for the unemployed living in families with and without children (see Table 6 in
Columns 2 and 3). The effect of social benefits (represented by the NRR) is negative
and significant at the 5% level for childless individuals, while it is not significant
for those with children. This result points to the existence of a welfare trap within
11
Low significance possibly arises because the presence of children delivers the reverse impact on labor
supply behavior by gender. When the equation is estimated separately by gender, the presence of a threeto
five-year-old child in the family translates to a lower probability of transitioning to work for women by
1.2 percentage points and the coefficient is significant at the 5% level. For men, the estimate implies a significant
positive effect of 1.4 percentage points. The presence of older children in the family has no association
with the dependent variable.
12
I would like to thank Mikolaj Herbst, who suggested the robustness check. The results are available on
request.
Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5 419
the former group but not within the latter group. An alternative explanation consistent
with the estimates is that social benefits attached to families with children are
high (as shown in Table 5) though the variation in the NRR is insufficient to explain
the outflow from unemployment. Accordingly, this means that the transition probability
for this group is determined by factors other than the level of social benefits.
Estimates suggest that it is rather the childless unemployed with low-earnings opportunities
who are vulnerable to the welfare trap. To further support this argument,
equation (5) is estimated separately for individuals with low (primary or lower
secondary) and high (upper secondary or tertiary) educational attainment. Given that
education is a strong predictor of labor income, the withdrawal of means-tested
benefits associated with entering low-paid work can lead to no significant increase in
total income in the case of low-educated individuals. The results in Columns 4 and 5
reveal that the effect appears to be concentrated in the groups with low education;
indeed, for the group with high education, the effect is close to zero and statistically
insignificant. Overall, the results reveal that relatively high social benefits constitute
a welfare trap for potentially low-income workers and the existence of a welfare trap
was not confirmed for those unemployed with children.
7.4 Unemployment Duration Dependence
The last three columns of Table 6 present the results from the specification
containing individuals by the duration of unemployment. The negative duration
dependence was confirmed by Sorm and Terrell (2000), implying that the longer
an individual is unemployed, the less likely they are to leave that state. Negative
dependency arises due to the unobserved heterogeneity that those who are unemployed
for longer periods are less motivated or have other characteristics that render
them less favorable to employers. According to that hypothesis, the welfare trap
is more likely to be present among the long-term unemployed who have the lowest
chances of improving their economic conditions in the labor market. The estimate on
the NRR is negative and significant for the group of unemployed with a duration
longer than two years, while coefficients are not significant for those unemployed
with shorter durations. Estimates indicate that the long-term unemployment observed
in the Czech labor market is accompanied by the existence of a welfare trap.
7.5 Gender Differences
As discussed above, women are disadvantaged in the transition from unemployment
to employment. Relative to men, women face lower earnings possibilities
and, consequently, the relative level of social benefits is higher for women. For this
reason, the amount of social benefits can have a varying impact on the economic
incentives of men and women to find a job. Equation (5) is estimated separately for
men and women and for groups along different dimensions in Table 7 in order to
examine whether there is a heterogeneous effect of social benefits on the labor supply
behavior of men and women. The dimensions considered are the presence of children,
education and unemployment duration. In general, the results reveal that women are
more vulnerable to the welfare trap than men. The existence of a welfare trap is
confirmed for women without children, the low-educated and the long-term unemployed,
while the estimate on the NRR for women living in families with children is
proven not to be significant. This also means that the transition probability for this
420 Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5
group is determined by other factors (such as education, the economic status of
the spouse, the age of the children, etc.) rather than the level of social benefits. For
men, the average estimated coefficient on the NRR is negative and significant but is
imprecisely estimated for the subgroups of the male sample. Finally, the estimates of
models that include observations before and after 2000 are presented.13
These estimates
are consistent with the findings of Sorm and Terrell (2000), who document
that the labor market was characterized by high mobility of workers with short
periods of unemployment prior to 2000. The existence of a welfare trap is confirmed
in the period after 2000. The estimate on the NRR is significant for women at the 1%
level, while it is not significant at the conventional level for men.
7.6 Job-Search Intensity
The theoretical framework derived in Section 4 demonstrates that higher jobsearch
intensity increases transitions to employment. The relationship is tested
empirically for the sub-sample in the period 2002–2005, given that the information
on search channels is not provided for the whole period. Table 8 shows the estimates
of the baseline model for the sub-sample together with the estimates separately by
gender. Next to it, the equations are estimated with the additional control of jobsearch
intensity. Estimates on search intensity provide evidence that those unemployed
who use multiple job-search channels are more successful in finding a job and
exiting unemployment. Importantly, the inclusion of the search intensity variable
only slightly affects the estimates on the NRR. The existence of a welfare trap is
documented for women; however, it is not significant for the total sub-sample
(t statistics are 1.54) and men (t statistics are 0.86).
8. Conclusions
The social security system in the Czech Republic has been assessed by several
studies as generating potential disincentive effects (welfare trap) for some unemployed
individuals. This paper combines the information from Czech Labor Force
Surveys and the Czech Household Income Survey to demonstrate the effect of the tax
and social security systems on individual flows from unemployment to employment.
The analysis presents empirical evidence that relatively high social benefits reduce
the incentives to exit unemployment for individuals with low-earnings opportunities
in the labor market. The analysis documents the disadvantaged position of women
in the Czech labor market. Due to lower earnings in employment, women face high
replacement rates relative to men. The estimates imply that women’s outflows to
employment are particularly influenced by high social benefits and the existence
of a welfare trap persists even when job-search intensity is controlled. This finding
contributes to the discussion initiated by Lauerova and Terrell (2005) on the persistent
and large unemployment gender gap in the Czech Republic.
In general, the findings agree with the previous research showing that labor
market flows in the Czech Republic were efficient in the late 1990s and the existence
of the welfare trap is confirmed in the period after 2000. The analysis uses data until
2005 and therefore further research is necessary to show whether the reform of
the tax and social security systems introduced between 2007 and 2008 were effective
13
The results are robust to the choice of split around 2000.
Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5 421
to improve work incentives of the groups identified in this paper. Recent studies
suggest that these reforms were not strong enough to significantly narrow the work
incentives of low- and middle-income households (Pavel, 2009; Galuscak and Pavel,
2012). In another study, Dusek, Kaliskova and Munich (2013) calculate the effective
participation tax rate (the proportion of gross earnings lost in tax and withdrawn
benefits) using the Czech SILC 2011 household survey. The authors demonstrate
high rates (when the rate approaches one, it means that there is no financial reward
from work compared to non-work) among low income households and particularly
for second earners (usually women).
The main findings from the analysis therefore remain relevant in the current
situation and the policy reform will need to balance its redistributive aims with work
incentives and particularly refocus incentives towards transition to work for lowskilled
workers and women. This can be achieved with (i) an increase of the statutory
minimum wage; (ii) a decrease of the marginal tax rate for low-income earners; and
(iii) the phasing out of social benefits over a certain period instead of the sharp
withdrawal of benefits. Ultimately, a better harmonization of the tax and social security
systems in the direction of fewer social welfare programs and lower marginal tax
rates will ensure that the incentives to leave unemployment are not hampered by high
social benefits. Empirical findings also confirm that measures improving monitoring
and the enforcement of job search are efficient in accelerating the transition to
employment.
APPENDIX 1
Figure 1 Unemployment Rate
0
.02
.04
.06
.08
.1
Theshareoflaborforce
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Total unemployed Unemployed for 6+ months
Source: Labor Force Survey 1995–2005, the Czech Republic
422 Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5
Table 1 Minimum Subsistence Income
(% average of monthly net income)
Year Personal benefit depends on age
Household supplement
depends on household size
0–5 6–9 10–15 above 16 1 2 3 4 5
1995 27 20 22 26 12 16 20 20 22
1996 24 18 20 23 13 17 21 21 24
1997 24 18 20 23 12 16 20 20 22
1998 23 17 19 22 14 19 23 23 26
1999 22 16 18 21 16 21 26 26 29
2000 21 15 17 20 15 20 25 25 28
2001 20 15 17 20 16 20 25 25 28
2002 19 14 15 19 15 19 24 24 26
2003 18 13 15 18 14 18 22 22 25
2004 17 12 14 17 13 17 21 21 24
2005 16 12 13 16 13 18 22 22 24
Note: Amounts are computed relative to the nominal monthly net income of an average production worker
living in a single household (see Column 2 in Table 4)
Source: Author’s computations based on information from the Ministry of Labor and Social Affairs.
Table 2 Minimum Subsistence Income by Household Type
(% average of monthly net income)
Year Single
Single+
+children
Couple
Couple+
+children
1995 38 92 67 117
1996 36 86 63 109
1997 35 85 62 108
1998 37 86 64 108
1999 37 86 64 107
2000 36 81 60 102
2001 36 81 61 101
2002 33 75 57 94
2003 32 71 54 89
2004 30 67 50 84
2005 29 66 49 82
Notes: Subsistence is computed from Table 1 as the sum of personal benefits for all family members and
the household supplement. A family with two children aged 3 and 8 is assumed.
Source: Author’s computations based on information from the Ministry of Labor and Social Affairs.
Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5 423
Table 3 Summary Statistics—Individual Characteristics
Total
mean
s.dev
Men
mean
s.dev
Women
mean
s.dev
N 28 338 9 384 18 954
Transition to employment 0.09 0.29 0.09 0.29 0.09 0.29
Female 0.67 0.47
Married 0.61 0.49 0.56 0.50 0.63 0.48
Spouse is employed 0.48 0.50 0.31 0.46 0.57 0.50
No children 0.38 0.49 0.48 0.50 0.33 0.47
Child 0–2y 0.04 0.20 0.11 0.32 0.01 0.08
Child 3–5y 0.15 0.36 0.13 0.33 0.17 0.37
Child 6–9y 0.25 0.43 0.18 0.38 0.28 0.45
Child 10–15y 0.30 0.46 0.23 0.42 0.33 0.47
Edu: primary 0.33 0.47 0.35 0.48 0.32 0.47
Edu: lower sec 0.45 0.50 0.50 0.50 0.42 0.49
Edu: upper sec 0.20 0.40 0.12 0.33 0.24 0.43
Edu: tertiary 0.03 0.16 0.03 0.18 0.02 0.14
Age 39.81 9.10 40.91 9.25 39.26 8.98
Spell 0.5–1 years 0.32 0.47 0.31 0.46 0.32 0.47
Spell 1–2 years 0.28 0.45 0.27 0.44 0.28 0.45
Spell >2 years 0.41 0.49 0.42 0.49 0.40 0.49
Before un.: employment 0.76 0.43 0.88 0.33 0.70 0.46
Before un.: household 0.08 0.27 0.01 0.08 0.11 0.32
Before un.: childcare 0.09 0.28 0.00 0.04 0.13 0.33
Before un.: other 0.08 0.27 0.12 0.32 0.06 0.24
Partial disability 0.13 0.34 0.15 0.36 0.12 0.33
Search intensity 3.74 1.24 3.71 1.24 3.75 1.23
Note: Information on search intensity is only available for the 2002–2005 period.
Source: Labor Force Survey 1995–2005, the Czech Republic.
424 Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5
Table 4 Wage Level and Unemployment Rate Statistics at National and District Level
Year
National avg
Avg wage in districts
as % of (1)
Unemployment rate
in districts
gross wage
(CZK)
net wage
(CZK)
lower
quintile
upper
quintile
lower
quintile
upper
quintile
(1) (2) (3) (4) (5) (6)
1995 8170 6291 86 107 1.15 5.83
1996 9684 7457 86 106 1.47 6.73
1997 10698 8344 85 106 2.53 9.50
1998 11709 9133 84 107 4.06 12.53
1999 12651 9868 84 107 5.20 15.48
2000 13484 10383 83 106 4.35 15.60
2001 14793 11391 80 103 4.49 15.42
2002 15857 12210 79 102 5.14 16.62
2003 16917 12857 80 102 5.61 17.38
2004 18035 13707 80 102 5.83 17.08
2005 18937 14392 80 102 4.88 15.24
Notes: The average nominal gross monthly wage (in CZK) and registered unemployment rate were collected in
77 districts. The average nominal net wage (in CZK) assumes the effective tax rate of a single person
without children. In every year, districts are divided into quintiles by the level of the average gross wage
and unemployment rate. Average values for districts in lower and upper quintiles are reported.
Source: Czech Statistical Office.
Table 5 Net Replacement Rate of Different Groups in the Sample
Year Total Men Women
Child-
less
Has
children
Low
edu
High
edu
Spell
0.5–1y
Spell
1–2y
Spell
>2y
1995 0.74 0.67 0.77 0.61 0.79 0.76 0.63 0.72 0.73 0.80
1996 0.72 0.63 0.76 0.59 0.78 0.74 0.62 0.71 0.72 0.77
1997 0.70 0.63 0.74 0.59 0.77 0.73 0.62 0.70 0.68 0.76
1998 0.71 0.64 0.74 0.60 0.77 0.74 0.62 0.68 0.71 0.76
1999 0.71 0.65 0.75 0.61 0.77 0.75 0.61 0.68 0.71 0.76
2000 0.70 0.62 0.73 0.58 0.76 0.73 0.59 0.68 0.69 0.73
2001 0.69 0.61 0.73 0.59 0.75 0.71 0.61 0.66 0.69 0.71
2002 0.68 0.60 0.73 0.57 0.76 0.71 0.59 0.66 0.67 0.70
2003 0.67 0.58 0.71 0.55 0.74 0.69 0.57 0.64 0.66 0.69
2004 0.65 0.56 0.70 0.55 0.73 0.68 0.54 0.61 0.64 0.68
2005 0.64 0.54 0.69 0.54 0.71 0.67 0.54 0.63 0.62 0.66
average
NRR
0.69 0.60 0.73 0.57 0.75 0.71 0.59 0.67 0.68 0.71
% NNR>
>0.8
0.21 0.17 0.23 0.10 0.28 0.26 0.03 0.15 0.19 0.28
Note: Individuals with a low level of education are defined as those who have primary and lower secondary education.
Individuals with upper secondary and tertiary education are defined as having a high level of education.
Source: Author’s computations based on the Labor Force Survey and Czech Household Income Survey.
Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5 425
Table6TransitionProbabilityfromUnemploymenttoEmploymentandNRR
TotalChildlessHaschildrenLoweduHigheduSpell0.5–1ySpell1–2ySpell>2y
(1)(2)(3)(4)(5)(6)(7)(8)
NRR-0.034**-0.053**-0.03-0.035**0.016-0.049-0.02-0.043**
(0.017)(0.023)(0.035)(0.018)(0.051)(0.044)(0.035)(0.019)
Married0.019***0.02***0.018***0.022***0.0020.043***0.027***0.004
(0.004)(0.006)(0.006)(0.004)(0.013)(0.011)(0.009)(0.005)
Spouseisemployed0.012***0.0040.016**0.01**0.0170.0120.015*0.009*
(0.004)(0.006)(0.007)(0.005)(0.012)(0.011)(0.009)(0.005)
Childdummy0–2y0.0050.0050.0040.017-0.0040.0030.013
(0.007)(0.009)(0.008)(0.023)(0.019)(0.016)(0.009)
Childdummy3–5y-0.004-0.003-0.002-0.009-0.005-0.0110.006
(0.004)(0.005)(0.005)(0.012)(0.011)(0.010)(0.006)
Childdummy6–9y-0.004-0.004-0.004-0.003-0.011-0.005-0.001
(0.004)(0.004)(0.004)(0.010)(0.010)(0.008)(0.004)
Childdummy10–15y0.0030.002-0.0010.018*0.004-0.010.01**
(0.004)(0.005)(0.004)(0.010)(0.010)(0.008)(0.004)
Female-0.009**0.003-0.017***-0.004-0.037***-0.021**-0.019**0.008
(0.004)(0.006)(0.006)(0.004)(0.011)(0.010)(0.009)(0.005)
Edu:lowersec0.029***0.011**0.043***0.025***0.064***0.035***0.008**
(0.004)(0.005)(0.006)(0.003)(0.011)(0.008)(0.004)
Edu:uppersec0.04***0.016**0.056***0.089***0.038***0.016***
(0.005)(0.007)(0.007)(0.012)(0.010)(0.005)
Edu:tertiary0.027***-0.0010.043***-0.0160.066***0.029-0.001
(0.009)(0.013)(0.013)(0.013)(0.022)(0.019)(0.013)
426 Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5
TotalChildlessHaschildrenLoweduHigheduSpell0.5–1ySpell1–2ySpell>2y
(1)(2)(3)(4)(5)(6)(7)(8)
Age/1000.384**0.250.4160.361**0.5210.647*0.4230.21
(0.156)(0.184)(0.256)(0.163)(0.441)(0.386)(0.329)(0.199)
Agesq/10000-0.706***-0.517**-0.731**-0.64***-1.016*-1.153**-0.82*-0.4
(0.204)(0.239)(0.339)(0.213)(0.577)(0.508)(0.430)(0.253)
Spell1–2years-0.032***-0.03***-0.033***-0.025***-0.062***
(0.003)(0.005)(0.005)(0.004)(0.009)
Spell>2years-0.072***-0.074***-0.069***-0.063***-0.108***
(0.004)(0.005)(0.005)(0.004)(0.011)
Before:household-0.023***-0.028-0.024***-0.024***-0.022-0.052***-0.028**-0.005
(0.006)(0.019)(0.007)(0.007)(0.015)(0.016)(0.013)(0.006)
Before:childcare-0.018***-0.019***-0.017**-0.021-0.056***-0.005-0.008
(0.006)(0.007)(0.007)(0.015)(0.017)(0.012)(0.006)
Before:other-0.012*-0.002-0.025**-0.016**0-0.017-0.012-0.008
(0.006)(0.007)(0.010)(0.007)(0.017)(0.018)(0.013)(0.006)
Partialdisability-0.03***-0.026***-0.029***-0.026***-0.047**-0.053***-0.038***-0.009*
(0.006)(0.007)(0.008)(0.006)(0.020)(0.016)(0.012)(0.005)
Unemploymentrate-0.005***-0.003***-0.007***-0.004***-0.011***-0.011***-0.005***-0.002***
(0.001)(0.001)(0.001)(0.001)(0.002)(0.002)(0.001)(0.001)
Constant-0.152***-0.077*-0.189***-0.148***-0.143*-0.299***-0.191***-0.105**
(0.031)(0.040)(0.053)(0.034)(0.085)(0.077)(0.066)(0.041)
N2833810726176122200163378990779811550
Notes::Logitmodelestimatesandmarginaleffectsarereported.Yeardummiesand14regionalfixedeffectsareincluded.Thefollowingarethebasegroups:male,primary
education,single,nochildren,unemploymentduration0.5–1year,employedbeforeunemployment,nodisabilityandPragueregion.Standarderrorsinparentheses,
significancelevel:***1%,**5%,*10%.
Source:LaborForceSurvey1995–2005,theCzechRepublic.
Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5 427
Table 7 Estimates of NRR for Different Groups by Gender
Total Men Women
All -0.034** -0.043* -0.059**
(0.017) (0.026) (0.023)
Childless -0.053** -0.040 -0.077**
(0.023) (0.036) (0.030)
Has children -0.030 -0.073 -0.015
(0.035) (0.070) (0.043)
Low edu -0.035** -0.028 -0.078***
(0.018) (0.026) (0.027)
High edu 0.016 -0.174 0.039
(0.051) (0.112) (0.062)
Spell 0.5–1 years -0.049 -0.116 -0.047
(0.044) (0.074) (0.062)
Spell 1–2 years -0.020 0.032 -0.106**
(0.035) (0.057) (0.049)
Spell >2 years -0.043** -0.040 -0.057**
(0.019) (0.025) (0.027)
Year 1995–2000 -0.018 -0.031 -0.023
(0.027) (0.041) (0.039)
Year 2001–2005 -0.044** -0.043 -0.088***
(0.022) (0.034) (0.031)
Notes: Figures in the table are the estimates of NRR from separate regressions. All models have the same
specification as in Table 6. Standard errors in parenthesis, significance level: *** 1%, ** 5%, * 10%.
Source: Labor Force Survey 1995–2005, the Czech Republic
Table 8 Estimates of NRR and Search Intensity
Total Men Women Total Men Women
(1) (2) (3) (4) (5) (6)
NRR -0,038 -0,033 -0,067** -0,037 -0,033 -0,064
(0.024) (0.039) (0.034) (0.024) (0.039) (0.034)
Search intensity 0,005*** 0,006** 0,004**
(0.002) (0.003) (0.002)
N 12699 4242 8457 12699 4242 8457
Notes: The sample is limited to the period 2002–2005. All models have the same specification as in Table 6.
Standard errors in parenthesis, significance level: *** 1%, ** 5%, * 10%.
Source: Labor Force Survey 1995–2005, the Czech Republic
428 Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5
APPENDIX 2
Heckman’s sample selection model is applied to estimate a wage equation
controlling for the selection into employment. In the first step, the probit selection
equation is formulated:
( ) ( )=1| =i i iP E Z ZΦ γ
where Z includes different explanatory variables that affect the likelihood of participation
of individuals in waged work ( )1iE = . The predicted values from the probit
regression are used to calculate the Inverse Mills Ratio (IMR) for each observation in
the sample:
( )
( )
=
1
i
i
i
Z
IMR
Z
φ γ
Φ γ−
where (.)φ and (.)Φ are the density function and distribution function of the standard
normal distribution, respectively. In the second step, IMR is added as an additional
explanatory variable in the Mincerian wage model:
*
=i IMR i iW IMRβ β ε+ +iX
where *
iW is the wage, and vector iX includes observed variables relating to
the worker’s productivity, and εi is an error term. IMRβ is the covariance between
the error terms from the wage and selection equations. Error terms in both equations
are assumed to be jointly normally distributed. The IMR as an additional regressor
accounts for the bias due to the non-random nature of the sample of wage earners.
The system is estimated separately for men and women. The results presented in
Table 10 imply that the presence of young children in the household is associated
with the lower participation rate of women and less so in the case of men. The availability
of other household income has negative associations with participation while
the presence of another employed person in the household implies the lower participation
of women. The significant estimate on IMR in the wage regression points to
the negative selection into employment. Estimating the potential entry-level income
of unemployed workers in the local labor market, the choice of variables in the wage
regression is limited due to the fact that the prediction of income for the sample of
unemployed workers does not allow us to consider work characteristics (the same
approach is used in Schneider and Uhlendorff, 2006). The estimated parameters
( ) ( )=1| =i i iP E Z ZΦ γ of the log-wage equation are used to calculate a potential
monthly full-time gross wage of every individual in the LFS. The wages for years
other than 2002 are subsequently adjusted for the regional wage growth. Predicted
gross monthly earnings that fell below the Czech statutory gross minimum wage
(180 cases) were set to the respective level of the minimum wage.
Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5 429
Table 9 Wage Estimation (Heckman‘s Sample Selection Model)
Eq. 1: selection to employment Eq. 2: logarithm of gross monthly wage
Women Men Women Men
Work experience -0.001 0.057*** Work experience 0.008*** 0.02***
(0.013) (0.016) (0.003) (0.003)
Work experience sq. /100 0.018 -0.132*** Work experience sq. /100 -0.011* -0.043***
(0.032) (0.039) (0.006) (0.007)
Edu: lower sec 0.606*** 0.95*** Edu: lower sec 0.109*** 0.064*
(0.092) (0.110) (0.026) (0.038)
Edu: upper sec 0.789*** 1.264*** Edu: upper sec 0.424*** 0.293***
(0.095) (0.127) (0.027) (0.042)
Edu: tertiary 1.000*** 1.405*** Edu: tertiary 0.714*** 0.6***
(0.132) (0.181) (0.032) (0.045)
Partial disability -1.730*** -1.417*** Partial disability -0.363*** -0.389***
(0.167) (0.171) (0.078) (0.072)
Married 0.043 0.683*** The inverse Mills ratio -0.076*** -0.265***
(0.065) (0.094) (0.026) (0.074)
Child dummy 0–2y -1.984*** -0.077 Constant 9.163*** 9.446***
(0.086) (0.133) (0.038) (0.058)
Child dummy 3–5y -1.347*** -0.271** N 3121 3202
(0.082) (0.137) R2 0.354 0.328
Child dummy 6–9y -0.391*** -0.05
(0.075) (0.124)
Child dummy 10–15y -0.083 -0.11
(0.070) (0.098)
Other household income -0.040* -0.156***
(0.024) (0.030)
Other econ. active person -0.410*** -0.045
(0.038) (0.050)
City size 5,000–50,000 0.132* 0.156*
(0.069) (0.090)
City size 50,000–100,000 0.188* 0.309**
(0.109) (0.144)
City size above 100,000 -0.124 -0.15
(0.113) (0.141)
Unemployment rate -0.036*** -0.041**
(0.012) (0.016)
Constant 1.495*** 0.779***
(0.204) (0.266)
N 4019 3473
Pseudo R2
0.378 0.2448
Notes: Estimation method: probit model for the selection equation and OLS regression for the wage equation.
The sample includes individuals aged 18-54 years old who are unemployed or full-time employees
(excluding self-employed, students and persons working less than 30 hours per week). Work
experience equals age minus 6 minus imputed years of schooling. Fourteen regional fixed effects are
included in both equations. Standard errors in parentheses, significance level: *** 1%, ** 5%, * 10%.
Source: Czech Household Income Survey, 2002.
430 Finance a úvěr-Czech Journal of Economics and Finance, 64, 2014, no. 5
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