OSIPP Discussion Paper : DP-2011-E-001

Is longer unemployment rewarded with longer job tenure?
February 28, 2011
Miki Kohara†
Osaka School of International Public Policy, Osaka University

Masaru Sasaki
Institute of Social and Economic Research, Osaka University

Tomohiro Machikita
Institute of Developing Economies, Inter-disciplinary Studies Center, Japan External Trade
Organization
Abstract:
This paper examines whether or not a prolonged unemployment period can raise the quality of job
matching after unemployment. We focus on job tenure as an indicator of a good quality job matchafter unemployment. We match two sets of Japanese administrative data compiled by the public
employment security offices: one includes information about the circumstances of job seekers
receiving unemployment insurance, and the other includes information about job seekers applying forjobs. We first show a negative relationship between unemployment duration and the subsequent job
duration. Restricting the sample to job seekers who lower their reservation wage in the final 59 days
before expiration of unemployment insurance, we secondly show an even greater negative effect of
unemployment duration on the following job duration. The importance lies not only in the durationof unemployment. If job seekers keep a high reservation wage because of the benefits of
unemployment insurance, and lower it in response to the expiration of insurance, prolonged
unemployment will result in short job duration after unemployment.

Key Words: job search, quality of job match, unemployment duration, unemployment insurance
JEL Classification Number: J64, J65, J68†

Corresponding author; Osaka School of International Public Policy, Osaka University, 1-31 Machikaneyama,
Toyonaka, Osaka, 560-0043, Japan. E-mail: kohara@osipp.osaka-u.ac.jp. We appreciate Ministry of Health,Labour and Welfare for allowing us to use their administrative data, and the Japan Institute for Labour Policy andTraining for helping us to utilize them. We also appreciate Munetomo Ando, Yoshio Higuchi, Yasusada Murata,
Fumio Ohtake, Katsuya Takii, Seiro Ito, Hitoshi Sato, Kazushi Takahashi, Kazunari Tsukada, the seminar participants at
Kansai Rodo Kenkyukai, ARISH-NUPRI (Nihon University) Economic Workshop, and Institute of Economic
Development, and the members of Experimental Research on Efficiency of Job-matching, for their helpful comments.
Each author receives Grant-in-Aid for scientific research by the Ministry of Education, Culture, Sports, Science andTechnology (MEXT) of the Japanese Government, No.20730156, No. 20530196, and No. 21730212, respectively. The
first and the third authors receive Grant-in-Aid for Osaka University Global Centers of Excellence Program byMEXT.

I. Introduction

Unemployment insurance is often analyzed in terms of its effect on job search behavior
during unemployment. Search theory suggests that unemployment insurance can raise thereservation wage of job seekers, lower search efforts, lower the rates of exit out of
unemployment, and thus lengthen the unemployment period. Many empirical studies
support this discouraging effect of unemployment insurance on job searches. The jump
up in employment around the expiration of unemployment insurance and thus prolonged
unemployment duration until the expiration date is reported by many researchers, forexample, Moffitt (1985), Katz and Meyer (1990), Poterba and Summers (1995), Green and
Riddell (1997), Card and Levine (2000) for the U.S. results, and Carling, Holmlund andVejsiu (2001), Bover, Arellano and Bentolila (2002), Lalive and Zweimüller (2004), Lalive,
Van Ours and Zweimüller (2006), Lalive (2007), and Card, Chetty and Weber (2007) for
the European results.
A prolonged period of unemployment, however, does not always produce an undesirable
result. Longer periods of unemployment may lead to a better job match. A limited
number of studies have been conducted on this topic, as opposed to the abundant literatureon the effect that benefits of unemployment insurance lengthen unemployment duration.
The present paper examines the effect of long unemployment duration on job match quality
using Japanese microdata that contains information from before, during and after theunemployment period.
Among the limited amount of research on job match quality, several papers examine therelationship between unemployment duration and wage after unemployment. Addison,1

McKinley and Blackburn (2000), Gaure, Roed and Westlie (2008), and Ohkusa (2004)
suggest there is a higher wage after longer unemployment. In contrast, Classen (1977),
Van Ours and Vodopivec (2006), and Card, Chetty and Weber (2007) suggest there is alower wage after longer unemployment. The empirical results on the effect that longer
unemployment has on job match quality in terms of wage are inconsistent.
We focus on another side of job match quality: job stability after unemployment.
Focusing on job duration as a measure of job match quality is important in several senses.
First, a low wage at the point when the job began, which is used as a measure of job quality
in most empirical investigations of job matching, may not always indicate a bad match.
Rather than the wage level at the beginning of employment, a wage increase after that may
be an important indicator of job match quality, although wage history is seldom traced overtime. Secondly, workers may not place a high value on their wage. They consider many
aspects in assessing job quality, including work environment, work satisfaction,
convenience in daily life and so on. Job stability, in contrast, measures how agreeable
matching is between workers and employers, and reflects all of these aspects. Thirdly,
despite its importance, job stability after unemployment has not been sufficiently examined
empirically.
We will use two sets of administrative data compiled separately by Japanese public
employment security offices. One set is used for the administration of unemployment
insurance, that is, to record the circumstances of job seekers receiving unemployment
insurance. The other set is used for the administration of finding employment, in otherwords, to store information about job seekers applying for jobs. We need informationfrom both data sets to examine the relationship between job searching and job matching, so
2

we combine the two data sets using an identification number related to unemployment
insurance.
The use of these data has several advantages. First of all, our data follow up job losers’
behaviors before, during, and after unemployment. This makes it possible to examine theeffect of unemployment duration on subsequent job duration, and control for many
individual characteristics before and after unemployment.
Second, our data contains information related to the intensity of job searching (based on
job application). Although the data do not directly examine reservation wage, we canpredict changes in reservation wage by a change in the intensity of job searching. Thus,
we can control for changes in reservation wage, which is not sufficiently done in mostexisting empirical literature in spite of its importance in a theoretical sense.
Third, these data are compiled by public employment security offices for administrative
purposes. This makes it possible to avoid the problem of sample selection, because
respondents are restricted to recipients of unemployment insurance but are not self-selected,
unlike in general survey data. Fourth, the data represent all the unemployed who lost theirjobs during the same month in the same year throughout the country. This makes it
possible to control for conditions in the macro economy when they became unemployed.
Fifth, there has been little research examining the relationship between job search and thequality of job matching in Japan, while the prolonged recession and a dramatic increase in
unemployment in Japan have garnered attention in many countries.
Our empirical investigations first show that longer unemployment duration decreases job
duration after unemployment. We further show that this negative effect becomes greater
if we examine the cases where job seekers lowered their reservation wages and changed
3their intensity of job searching (based on job application) in the final 59 days before
expiration of unemployment insurance.

That is, longer unemployment duration does

lower job stability more seriously, if a job seeker once set a high reservation wage and gave
it up later when benefits of unemployment insurance came to lapse. If we consider thatjob duration is one of the indicators of a high quality job match, longer unemployment
duration owing to a high reservation wage does not lead to a better job match.
This paper is composed of four main sections. Theoretical background, the empiricalmodel and related existing literature are given in the next section. The administrative data
used in our estimations are introduced in Section III. The empirical results and theirimplications are reported in Section IV. Concluding remarks are given in the final section.

II. Theoretical Framework and the Empirical Model

A simple sequential search model incorporating tenure of a job after unemploymentshows that longer unemployment duration leads to a higher separation rate and shorter
tenure at a job after unemployment (Appendix shows the details). Suppose that workers
are either employed or unemployed at any one point in time. All of the unemployed firstreceive the benefits of unemployment insurance (UI, hereafter). The UI benefits expire
and the receivers become unqualified for UI at a Poisson rate . That is, the reservation
wage differs depending on the duration of unemployment. A recipient of UI benefits
accepts a job offer if the offered wage exceeds the reservation wage wR (Type h worker),
while an individual who is no longer qualified for UI benefits accepts the offer if theoffered wage exceeds the reservation wage wR (Type l worker).
4

We assume that

wR

wR .

Once workers start working after unemployment, an exogenous separation shock occurs
for both types of workers. The Type h worker, who has found a job before the expirationof UI benefits, does not stop working even if he or she faces an exogenous separation shock,and continue working until an exogenous death shock arrives. This is because the Type hworker started working when his or her reservation wage exceeded the value of
unemployment. In other words, the Type h worker would have a higher job matchingquality, because he or she was more selective during unemployment: a higher wage was
required to accept an offer.
The Type l worker, who has found a job after UI benefits began to expire, separates
from the post-unemployment job and becomes unemployed again once eligible for UI
benefits if his or her wage is under a certain wage level, wT.. This is the turnover wage for
the Type l worker, which is affected both by the reservation wage before and after
expiration of UI benefits (wR and wR , respectively). As explained in Appendix, the Typel worker is likely to separate from the post-unemployment job and search for a better job, as
wR increases. As wR decreases, the unemployed person is less selective in a job searchbecause he or she prefers to be patient with a lower wage for a while, waiting for anotherchance to be unemployed once eligible for UI benefits (the entitlement effect). Generous
UI benefits raising wR and lowering wR , result in a decrease in the job match quality, andencourage the Type l worker to shorten his or her subsequent job tenure. Moreover,compared to the Type h workers who started working before UI expiration and thus had ashorter unemployment duration, the Type l workers who started working after UI expiration
with longer unemployment duration would have shorter job tenure at the5post-unemployment job.
There are a limited number of empirical studies which examine whether or not longer
unemployment duration leads to lower quality job matching.

It is hard to obtain

information on workers' search behavior during unemployment, as well as their work
behavior after unemployment.
Among available studies, Centeno (2004) shows that generous UI benefits lead tolonger subsequent job tenure, using data from US job seekers mainly in the 1980s and1990s. Van Ours and Vodopivec (2006) find that longer unemployment duration has noeffect on the probability of finding a permanent job in Slovenia. Card, Chetty and Weber(2007) also find no relationship between long unemployment duration and subsequent job
duration in Austria. In contrast, Belzil (2001) shows that in Canada longer unemployment
duration reduces post-unemployment job duration because of a lower reservation wage
during the search period. Della Vigna and Paserman (2005) and Paserman (2007) showthat impatient job seekers decrease their reservation wage a lot once the UI benefits came to
expire, which raises the exit rates around the expiration date, and that the subsequent job
match quality, which is measured by wage in the studies above, thus would become lower.
Following the existing empirical studies, we will conduct reduced form estimates of theeffect of unemployment duration on separation rates in subsequent jobs. We will analyze
parametrically the hazard of job separation. We assume a non-constant hazard over timeto allow duration dependence created by heterogeneity. By the empirical test shown in the
Results section, we assume a log-normal distribution for the hazard rates:

λ t |x

1

t |x
t |x

xβ
1 ln t
2
σ
ln t
xβ
Φ
σ

1
exp
tσ√2π
1
6

,

where Φ denotes a normal distribution and  is positive. The explanatory variables, xi,
include individual characteristics and the variables related to job arrival rates and search
efforts.

The details are explained in Section IV.

ln β

∑

d ln t |x ; β1d ln 1

We maximize the likelihood oft |x ; β , where F and f are thecumulative density and its density of job duration , using BHHH algorithms1.
The important aspect in our analysis is to capture the change in reservation wages andsearch behaviors. Unfortunately, our data do not directly ask the change in reservation
wages during unemployment periods 2 .

Instead, we can observe the dates of job

applications. Using job application dates in conjunction with UI expiration dates, we
identify "late appliers" who started applying for a job later during the duration of UI
benefits.
Note that this identification depends not only on the unemployment periods, but also on
the periods remaining until the expiration of UI benefits. The length of unemployment
duration may reflect differences in individuals' heterogeneities other than changes inreservation wages.
1

For example, an individual with low ability may have longer

We can allow unobserved heterogeneity by setting the hazard function as λ t |x u instead of

λ t |x , adding the unobservable multiplicative error term u i , and assuming a gamma distribution
for u i with expectation of 1 and variance of  . We conducted the estimate under this setting ofunobservable heterogeneity, and confirmed that the variance component  is near zero andstatistically insignificant, and that the estimates shown later in Section IV have been hardly changed.
2

Krueger and Mueller (2008) directly measure search intensity by the number of hours devoted tojob search per day, and find that it falls as unemployment benefits become more generous, and rises
prior to benefit expiration. Unfortunately, our data do not contain any information on specific time
devoted to job searching.
7

unemployment duration and shorter job tenure, and thus we may find a negative
relationship between the two lengths. Likewise, those who have high value of working,and/or those who have strong incentive to work may also show a negative relationshipbetween the two lengths. In those cases, it is an individual's heterogeneity, and not alonger unemployment duration caused by exogenous reasons such as UI benefits, that raises
the separation rate at a post-unemployment job. The length of time until UI expiration, on
the other hand, can explain the effect of the change in reservation wages more directly,
because this length of time is linked to the institutional decisions on UI. We compare theresults for the entire sample to those restricted to the late appliers, considering that the latter
set and kept high reservation wages in the beginning of the search period and lowered themat the end of the search period in response to the expiration of UI.
The effect of unemployment duration on post-unemployment job duration may bedifferent between young and senior job seekers. In order to investigate this age difference,
we separate the whole sample into two groups. One group is composed of job seekers
between 16 and 44, and the other group is composed of job seekers between 45 and 64.

III. The Data

III-1. Two Administrative Data Sets
We use two administrative data sets compiled by the Japanese public employment
security offices. One is an administrative data set on unemployment insurance (Koyo
Hoken Gyomu Tokei), and the other is an administrative data set on job findings (Shokugyo
8Antei Gyomu Tokei). Although these are compiled separately for different administrative
purposes, we merged them using the UI identification number.
The sample is composed of the unemployed who lost their jobs in August 2005. They
were all eligible for UI, and appeared in person in public employment security offices toapply for UI.

Among them, we use the sample that started working after theunemployment period, because our focus is job duration after unemployment. Thus, oursample is composed of individuals who lost their jobs in August 2005, spent at least one
day unemployed, qualified for UI, and worked for at least one day upon finding a job.
We remove those who are over 65 years old, seasonal workers (Tanki Tokurei HiHokensha), and day workers (Hiyatoi Rodosha) because their job seeking behaviors and/or
the job market conditions for them may be different from the other individuals in thesample. Most part-time workers (those who work fewer than 20 hours per week), theself-employed, and civil servants are also removed, because they are not usually covered by
the UI system. The workers in fixed-term employment after unemployment are also
removed because some of them choose short-term employment as an appropriate job forthem.
The timing of the survey is summarized in Figure 1. One of the most importantvariables in this paper is unemployment duration, which is shown as a black dotted line in
the figure. This is defined as the period from the day of stopping the previous job until the
day prior to starting the subsequent job. During unemployment, job seekers go to a public
employment security office to find a job. At the office, they can search for openings
mainly on computers and/or in written documents. If a job seeker finds a suitable job, heor she goes to a counter to get direct counsel from a counselor. A counselor provides
9detailed information on the job, and provides advice as to whether or not to apply for thejob. If the job seeker decides to apply for the job, the counselor introduces him or her tothe employer as an applicant. The job seeker, who is now a job applicant, has aninterview, and the employer decides to hire him or her. The job applicant has to informthe public employment security office of receiving an acceptance, and starts working
shortly after receiving a formal notice of being hired. A rejected job seeker will continue
to search for a job3.
Another important variable in our study is job tenure after unemployment, which isshown as a thick black line in Figure 1. If the worker had already ceased working at the
final survey point (July 2005), his or her job tenure is not truncated but completed, andequal to the period from the first day of starting a job until the last working day.
Individual 1 in the figure is an example of this. If the worker continued working at thesurvey point, his or her temporally-measured tenure, which is the period from the first dayof starting a job until the survey point, is truncated. Individuals 2 and 3 are examples ofthis. We analyze a hazard rate of getting out of a job at one time point, t conditional on
surviving until t-14.
3

In Japan, job seekers qualified for UI benefits need to come to a public employment security

office to seek for job vacancies when they receive UI benefits. However, the unemployed can findjob vacancies through other sources such as newspapers and the internet, and make appointments
directly with the employer. Our sample does not include them. We cannot conclude that thisoverestimatesorunderestimatesthenegative

effectofunemployment

durationonpost-unemployment job duration. Job seekers who can receive UI may have high potential for
work: Japanese workers are not qualified unless they have worked for at least six months. On theother hand, job seekers who come to the employment security office to consult with the officers
have low employment potential or low productivity.
4

If a length of a temporally-measured job duration is regressed on a length of unemployment
10

As for the explanatory variables, we control for worker characteristics such as age, adummy variable indicating gender, a dummy variable indicating a married worker, andyears of education. For the information on a job before unemployment, we control for thejob tenure of the previous job, a dummy variable indicating whether or not the worker quita job involuntarily, monthly wage when the worker stopped the previous job, and themonthly wage difference before and after unemployment. To control for market labor
conditions, we include effective job rates in the local labor market when the worker started
a job after unemployment5.
After conducting the estimate in the entire sample, we restrict them to late appliers who
may have lowered the reservation wage later during a job search. Our data shows when
job seekers apply for job openings, and when benefits of UI expire. We identify those
who do not apply for a job opening 59 days prior to the UI expiration date as late appliers.
They have kept a high reservation wage while receiving UI benefits, and lowered it later in
response to the expiration of UI benefits.
The reason for focusing on 59 days is that it can be a threshold to judge the change inreservation wages, since first-applications for a job opening rise between 60 and 89 days
duration, the negative correlation between the two durations can be found by definition, because
longer unemployment duration means starting a job at a later point in time, and shorter
temporally-measured job duration after unemployment. In our sample, about twenty four percent
are a completed sample who once started working and went back to an unemployment pool one year
later at the final survey point.
5

As for post-unemployment wage, it is assumed to be exogenous for simplification. As for the

possibility of getting job training, it is not included in explanatory variables, but rather assumed tobe controlled for by the other explanatory variables. This is the same assumption made in manyother recent empirical studies. Our job duration after unemployment is a maximum of one year, sothat the effect of accumulation of human capital may be small.
11

before the UI expiration date: about 19.4% of job seekers in our estimated sample applied
for a job opening for the first time more than 90 days before the expiration date, 24.6% did
between 60 and 89 days before the expiration date, 15.8% did between 30 and 59 days
before the expiration date, 16.7% did between 0 and 29 days before or after the expiration
date, and 21.1% did 30 days after the expiration date. Thus, the job seekers that we
defined as lowering reservation wages in the later stages of UI benefits are 56% of thewhole sample6.
Figure 1 shows the example of timings of applying for job openings for the first time
during unemployment (upward arrow), and the timing of expiration of UI benefits (triangle).
In this example, Individual 3 is a late applier. Note that our focus is not just on the timingof the first application (the place of the upward arrow during unemployment), but also the
distance of the first application from the end of UI benefits (how far the upward arrow islocated from the triangle). Individuals 2 and 3 have identical lengths of unemployment
and subsequent truncated job tenure, while they are very different in the sense that
Individual 3 changed reservation wage in response to the expiration of UI benefits. In
order to find the effects of a change in reservation wage, we examine whether the
relationship between the length of unemployment and length of subsequent job tenure
would remain unchanged even after restricting the sample to late appliers.

III-2. Unemployment and Job Duration in Our Sample

6

The other thresholds such as 29 days before the UI expiration date, and anytime after the UI

expiration date, can also be examined. The problem of focusing on these thresholds is that theestimate sample, and thus the test power, is decreased.
12

Panel A of Table 1 shows descriptive statistics of the variables used in our estimate forthe whole sample. The average age at unemployment is 36 years old, about 51% are male,and 42% are married. The average tenure before unemployment is 1586 days (about 52.9
months), and the average monthly wage before unemployment is about 201 thousand yen.
These numbers are smaller than the averages in all of Japan (the average tenure is 13.4
years, and the average monthly wage is 372 thousand yen in 2005, according to the Basic
Survey on Wage Structure compiled by the Statistics Bureau of Japan), which is not
surprising since our data includes more young, female workers.
The average unemployment duration, which is also the search period, is about 128 days
(4 months). More specifically, the job seekers who found jobs during the first 29 days of
their job search make up 10.8%, those between 31 and 60 days are 17.6%, those between
61 and 90 days are 14.2%, those between 91 and 150 days are 17.7%, those between 150
and 210 days are 16.6%, those between 180 and 210 days are 8.2%, and those more than
210 days are 23.2%. During unemployment, all the job seekers in our sample were able toget UI benefits. The potential periods of UI benefit depend on age and tenure in theprevious job. About 76.7% receive 90 days, 8.5% receive 120 days, 3.7% receive 150
days, 4.2% receive 180 days, and the remaining 7.0% receive either 210, 240, 270, or 360
days.

About 48% get out of unemployment with at least one day of UI benefits

remaining.
The separation rates 6 and 12 months after starting work at a post-unemployment job
are 22.4% and 27.3%, respectively7. Figure 2 shows the empirical survivor function,
7

The last survey point is July 13, 2006, which is about one year after the starting date ofunemployment (August, 2005). Thus, the maximum (temporary) tenure after unemployment is
13

S t

Π

1

λ s , where  (s ) is the hazard function.

The figures are shown

separately by categories of the number of days of unemployment.

The longer theunemployment duration, the more workers separate from jobs after unemployment. The
two time periods may not be linearly correlated, so we use logarithms of unemployment
duration in our estimation.
As mentioned, we focus on the sample who had not applied for job openings until 59
days before UI expiration. Panel B of Table 1 shows descriptive statistics for them.
They are often young, female, and unmarried compared to the entire sample. Theirprevious job tenure before unemployment is shorter, and most of them quit the job
voluntarily (only 2% stop previous jobs involuntarily), suggesting that they are quitting jobs
repeatedly. Their monthly wage in the previous job before unemployment is also lower.
Their unemployment duration is longer, and their job duration after unemployment isshorter compared to the entire sample. Figure 3 shows job separation rates by job searchintensity.

Those who started applying for job openings at least 60 days before theexpiration date of UI seem to stay longer at their subsequent jobs.

IV. Results

Before examining the relationship between unemployment duration and subsequent job
duration, we determine the specification of a hazard function for job separation. Several
statistics such as Akaike's information criterion and plots of residuals suggest a log-normal
distribution for the hazard function.

The job separation rate in our data increases

343 days. Since about 70% are truncated, the average job tenure after unemployment is 163.52 days,or 5.45 months, assuming the maximum tenure for the truncated samples is 343 days.
14

progressively, and once the rate reaches its highest value, it starts declining gradually.
Table 2 shows the results using the entire sample. The coefficient of unemployment
duration has a negative sign and is significant at the 1% level. The longer unemployment
duration becomes, the shorter job duration is after unemployment. That is, assuming thatlong job duration reflects a high quality job match, a long period of unemployment lowers
the quality of the job match.
We obtain similar results for both the group of younger workers aged from 16 to 44 andthe group of older workers aged from 45 to 64. The estimates are larger for the lattergroup, which means that the negative effect unemployment duration has on subsequent job
tenure is stronger for older workers.
As for the other explanatory variables, the time at a job after unemployment becomesshorter as the workers grow older when they are below the age of 44, and longer as theworkers grow older when they are above the age of 45. Note that the individuals in our
sample are those who experienced unemployment at least once. The results may suggestthat the younger workers who came back to work from unemployment may quit their job
sooner than before—job duration for the younger workers becomes shorter when they quit
jobs repeatedly. This tendency is not found in older workers, who know that they facelower demand for their labor once they stop working.
Married workers and male workers over 45 years old stay longer at post-unemployment
jobs, because they may have dependents. The more educated people may have higher job
match quality because of higher productivity, although this effect is not found in theworkers over 45 years old. Job matching for senior workers may be influenced by otherfactors such as job experience rather than education level. Those who worked for a long15

period in their previous job work for a longer period again in the subsequent job. Those
who ceased the previous job involuntarily have shorter job duration after unemployment.
In other words, job quitters have high job separation rates. The significantly positive signof the coefficient of effective job rates suggests that good labor market conditions lead tohigher quality job matching. Finally, the wage of the current job makes younger workers
stay in the job, although wage incentives may not exist for older workers.
How is the change in reservation wages related to the quality of job matching? In order
to examine this, we restrict the sample to the late appliers. Table 3 shows the results
obtained for those who had not started job seeking until 59 days before UI expiration during
their unemployment periods. The coefficients of unemployment duration are negative andsignificant at the 1% significance level for both the younger and older samples. The
magnitude of the estimates is much larger than in the case of the entire sample unrestricted
to late appliers, which is shown in Table 2. That is, job seekers who have started applying
for job openings in less than 59 days before UI expiration separate from their subsequentjobs earlier than the others. This is found not only in younger workers, but also in senior
workers.

The prolonged duration of unemployment harms post-unemployment job

stability more seriously if the job seekers have lowered their reservation wage because of
UI expiration.
It might be thought that a larger negative relationship between the length ofunemployment duration and the length of subsequent job duration for late appliers has
arisen not by setting reservation wages higher but for other reasons. For example, a lateapplier may have low value of working, and thus she has longer unemployment and shorterjob duration. However, such an individual characteristic unrelated to UI settings cannot
16

explain our results, since our late appliers are those who changed search behaviors in
response to UI expiration. As another point, it may be thought that a late applier canalways get a better job: the longer the unemployed wait, the better offer they gain.
However, a possibility of getting a better job does not have any relation to UI expiration.
In summary, there is a negative relationship between unemployment duration and job
duration after unemployment in Japan. Moreover, longer unemployment duration does
hurt job stability more seriously if a job seeker kept reservation wages at a high level basedon the amount of UI benefits. The important implication of our results is not that anegative relationship between unemployment and post-unemployment job duration exists,
but that the situation would be worse if job seekers kept a high reservation wage with the
UI benefits. Prolonged unemployment duration will result in shorter job duration after
unemployment if job seekers lower their reservation wage in response to the imminent
expiration of UI benefits.

V. Conclusion

This paper examined whether or not a prolonged unemployment period can raise thequality of job matching after unemployment. We focused on job tenure as an indicator ofa good job match after unemployment. We matched two Japanese administrative data setscompiled by public employment security offices using an identification number related to
unemployment insurance.
Our empirical investigation first showed a negative relationship between unemployment
duration and the subsequent job duration. The paper then showed this negative effect17

could be greater for the job seekers who put a high reservation wage in the beginning of job
search and lowered it later in the final 59 days before the expiration of UI.

The

importance lies not only in the duration of unemployment. Prolonged unemployment
duration will not be rewarded with longer job duration after unemployment, especiallywhen job seekers lower their reservation wages later in response to the expiration of UI. If
we consider that job duration is one of the indicators of a good quality job match, longer
unemployment duration with lower reservation wage does not lead to a better job match.
There had been little research that examined the matching quality and controlled for thechange in reservation wage during unemployment. In addition, there had been little
research that investigated job match quality focusing on post-unemployment job stability.
The number of empirical examinations for Japanese cases had been especially limited.
Our results, which are based on the extensive micro data compiled by the Japanese
government, and which utilize information regarding the timing of applications for jobs aswell as the timing of expiration of unemployment insurance benefits, may prove as valuableevidence concerning the negative effect that long unemployment with a lowered reservation
wage has on subsequent job stability. The UI benefits could make the unemployed keep
their reservation wage higher, and thus lead to longer unemployment and shorter
subsequent job tenure.

18

Appendix. Derivation of wage schemes and comparative statics concerning theeffect of UI benefits on unemployment duration and job tenure after unemployment
The value functions of employment (W w ) and unemployment (U ) for the Type hworker who is qualified for UI benefits are given by:
rW w

w

rU

α

z

σW w ,R

W w(1)
U dF w

δ U

U

σU ,

(2)

where r is discount rate, z is unemployment benefits,  is death rate, and  is job arrival rate.
An offered wage is randomly drawn from the wage distribution F w . The Type hworker, who has found a job before the expiration of UI benefits, does not stop working
voluntarily since he or she started working when the offered wage exceeded the reservation
wage (wR ).
For the Type l worker who is no longer qualified for UI benefits, the value function of
being employed (W w ) is:rW w

w

λ max W w , U

W w

σW w ,(3)

where  represents an exogenous separation shock. After an arrival of a separation shock,the type l employed chooses either to remain employed or to quit and become unemployedwith eligibility of the provision of unemployment benefits. If eq.(3) is evaluated at thereservation wage for the type l worker (wR ), it is rewritten as:
rW wR

wR

λU

W wR

σW wR .

(4)

The max operator implies that the value of unemployment with eligibility of the provisionof UI benefits is higher than the value for the type l worker of being employed with thereservation wage: max W wR , U

U . It will be checked later. Equations (1)-(4)19and the reservation wage properties give:
σ

U

R

σ

 R
σ 

σ 

wR

(5)
α

z

σ  δ

σ

R

w

δ R
.
σ  δ

wR dF w

(6)

When a separation shock arrives, the type l worker, who has found a job after the
expiration of UI benefits, voluntarily separates from the post-unemployment job andbecomes unemployed again with the eligibility of UI benefits if the current wage is under acertain wage level, WT . This is referred to as the turnover wage at which the Type lworker is indifferent between the states of unemployment and employment: W wTU .

These conditions with eqs.(1) and (3) and reservation wage properties give:
wT

wR

(7)

Thus, we can summarize the two cases where the Type l worker faces as:(i) When wRw

wR is offered, the capital gain of being employed is given

by:
W w

w wR
.
r σ 

U

This is derived by eq.(3) with max W w , U

U , and eq.(4). The Type l worker

separates the current job and becomes unemployed when a separation shock arrives.
(ii) When w

wT

wR is offered, the capital gain of being employed is obtained:
W w

U

w wR
r σ 

This is derived by eq.(3) with max W w , U

 w wRr σ r σ.

W w , and eq.(5). Type l worker

remains employed in the current firm even though a separation shock arrives.
We can rewrite the value function of employment for the Type l workers as

20

rU

R

α

W w

U dF w

α

W w

R

U dF wσU .

RThis with the two wage conditions shown in cases (i) and (ii) gives:
r

wR

σ wR

α

w

R



wR dF w

wR dF w .

w

R

(8)

Solving the equations (6) and (8), we get
wR

r
r

σ
σ

z

δ

r
δ
σ

r

α
σ
δ

α r σ δr σ r σ 


α
σ

r

w



w

wR dF w

w

wR dF wR

wR dF w ,

R

and
wR

r


σ

r
r


r
r

σ
σ


z
δ



α r σ δ r σ r σ δ

σ
σ

αδ
σ r σ

r

A comparison of these wage equations implies wRRw

wR dF w .

R

wR . In addition, we obtain:r σ wR wRr σ r σ 

W wR

δ

wR
r σ

which ensures that, as raised in eq(3), max W wR , U

U ,

U .

These wage equations give a comparative statics system such as:

A12   wRh   B11 
A22   wRl   B21

 A11
A
 21

B12   z ,
B22   

where:
A

r

1

r

σ

A
A
A



σ
δ

α


r
δ

σ

1

r σ δ α
1 F wR
r σ


r

σ

α1
21

F wR

F wR
0,
0,
0,

0,

r

B
B

r
r



σ
σ

r

The last inequality holds since z

R

0,



σ δ
α
r σ

z



δ



σ

w

wR dF w

wR

0.

R

w

wR dF w shows the reservation

wage for UI-qualified unemployed people, which is wR at =0. This should be higher
than wR . In addition,
B

0,

B

0.

The Jacobian determinant is A11A22-A12A21>0. Thus,
dwR
dz

0,

dwR
dz

0,

dwR
dδ

0,

dwR
dδ

0.

Generous UI benefits either in terms of the amount of benefits (higher z) or in terms of thelength of eligibility (lower ) has a positive effect on wRh but a negative effect on wRl.
Finally, the average tenure at the post-unemployment job is1
σtenure htenure l

F

F

R

F

R



R

F

R

F

R

.

(9)

respectively for the Type h worker, and for the Type l worker. In sum, generous UI
benefits, changing both reservation wages of wRwT and wR , lead to a shorter tenure

for the workers who found a job after UI expiration.

Those who had a longer

unemployment period until UI expiration face a higher retention rate and thus shorter tenureat the post-unemployment job compared to those who had a shorter unemployment period.

22

References
Addison, J.T., and Blackburn, M.L. (2000), "The effects of unemployment insurance on
postunemployment earnings," Labour Economics, 7, pp.21-53.
Belzil, C. (2001), “Unemployment insurance and subsequent job duration: Job matching versus
unobserved heterogeneity,” Journal of Applied Econometrics, 16, pp.619-636.
Bover, O., Arellano, M., and Bentolila, S. (2002), “Unemployment duration, benefit duration andthe business cycle,” Economic Journal, 112, pp.223-265.
Card, D., Chetty, R., and Weber, A. (2007a), “Cash-on-hand and competing models ofintertemporal behavior: New evidence from the labor market,” Quarterly Journal of
Economics, 122. pp.1511-1560.
Card, D., Chetty, R., and Weber, A. (2007b), “The spike at benefit exhaustion: Leaving theunemployment system or starting a new job?” American Economic Review, 97, pp.113-118.
Card, D, and Levine, P.B. (2000), “Extended benefits and the duration of UI spells: Evidence fromthe New Jersey extended benefit program,” Journal of Public Economics, 78, pp.107-138.
Carling, K., Holumlund, B., and Vejsiu, A. (2001), “Do benefit cuts boost job finding? Swedish
evidence from the 1990s,” Economic Journal, 111, pp.766-790.
Centeno, M. (2004), "The match quality gains from unemployment insurance," The Journal of
Human Resources, 39, pp.839-863.
Classen, K.P. (1977), "The effect of unemployment insurance on the duration of unemployment andsubsequent earnings," Industrial and Labor Relations Review, 30, pp.438-44.
DellaVigna, S., and Paserman, M.D. (2005), “Job search and impatience,” Journal of Labor
Economics, 23, pp.527-588.
Gaure, S., Røed, K., and Westlie, L. (2008), "The Impacts of Labor Market Policies on Job Search
Behavior and Post-Unemployment Job Quality," IZA Discussion Paper, No.3802.
Green, D.A., and Riddell, W.C. (1997), “Qualifying for unemployment insurance: An empiricalanalysis,” Economic Journal, 107, pp.67-84.
Katz, L.F., and Meyer, B.D. (1990), "The impact of the potential duration of unemployment
benefits on the duration of unemployment," Journal of Public Economics, 41, pp.45-72.
Krueger, A.B., and Mueller, A. (2008), "Job Search and Unemployment Insurance: New Evidence
from Time Use Data," IZA Discussion Paper, No.3667.
23

Lalive, R. (2007), “How do extended benefits affect unemployment duration? A regression
discontinuity approach,” Journal of Econometrics, 142, pp.785-806.
Lalive, R., Van Ours, J.C, and Zweimüller, J. (2006), “How changes in financial incentives affectthe duration of unemployment?” Review of Economic Studies, 73, pp.1009-38.
Lalive, R., and Zweimüller, J. (2004), “Benefit entitlement and unemployment duration: The role ofpolicy endogeneity,” Journal of Public Economics, 88, pp.2587-2616.
Moffitt, R. (1985), "Unemployment insurance and the distribution of unemployment spells,"
Journal of Econometrics, 28, pp.85-101
Ohkusa, Y. (2004), “Programme evaluation of unemployment benefits in Japan: An averagetreatment effect approach,” Japan and the World Economy, 16, pp.95-111.
Paserman, M.D. (2008), "Job Search and Hyperbolic Discounting: Structural Estimation and Policy
Evaluation," Economic Journal, 118, pp.1418-1452.
Poterba, J.M., and Summers, L.H. (1995), "Unemployment benefits and labor market transitions: A
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pp.207-216.
Van Ours, J.C, and Vodopivec, M. (2006), “How shortening the potential duration ofunemployment benefits affects the duration of unemployment: Evidence from a naturalexperiment,” Journal of Labor Economics, 24, pp.351-378.

24

Figure 1. Timing of the Data

Stop working

Stop working

Find job

Individual 1

Completed

End of UIFirst application

Continue working
Truncated

Individual 2
End of UIFirst application
59 days

Continue working
Truncated, Late applier

Individual 3First application

End of UIAugust, 2005

July, 2006

Unemployment Duration

25

Job TenureFigure 2. Post‐unemployment job stability by length of unemployment duration

0.50

0.75

1.00

Kaplan-Meier survival estimates

0.25

240days210‐240days

0.00

181‐210days

0

100

200

300

400

analysistime
Job tenures after
unemployment(days)
searchgroup2
30
less than 30 =dayssearchgroup2
61‐90 days = 90
searchgroup2= 150
121‐150 days
searchgroup2= 210(log of years)
181‐210 days
searchgroup2= 346
over 241 days

searchgroup2
31‐60 days = 60
searchgroup2
91‐120 days = 120
searchgroup2
151‐180 days = 180
searchgroup2
211‐240 days = 240

Figure 33. Post‐unemployment job stability by job application during unemployment

1.00

Kaplan-Meier survival estimates

0.50

0.75

Those who started job
search by 59 days before UI
expiration

0.00

0.25

Those who had not started
job search until 59 days
before UI expiration

0

100

200
analysis time300

Job tenures after unemployment (days)

firstapply_fromexp_before60 = 0

400

firstapply_fromexp_before60 = 1

26

Table 1. Descriptive Statistics
Panel B. The sample of late appliers (for Table 3)Panel A. The entire sample (for Table 2)
Mean

Standard
deviation

Minimum

Maximum

MeanStandard
deviation

Minimum

Maximum

job tenures after unemployment

163.5199

89.10021

343

132.6334

76.92241

311

unemployment durations (days)

127.8522

85.668011

344

166.1999

76.77771336(log of days)

4.49491.046405.84064.97640.566405.817111

36.49833

11.21567

1665

34.6749

10.733816

64

3.55140.30172.77264.17443.50170.29322.7726

4.1589a dummy variable of male respondent

0.50850.4999010.4562

0.49810

1

a dummy variable of married respondent

0.41600.4929010.35360.47810

113.001061.95928991813.0448

1.8818918(log of years)

2.55370.1511

2.19722.89042.55810.1436

2.197225

2.890372

job tenures before unemployment (days)

1586.826

2067.493

1

16132

1503.6760

1703.3840

7

15152

6.6014

1.387209.68866.84710.96681.94599.62590.11030.31330

10.02580.158401

200.527101.4319

1

8210

184.9648

66.33151

1400

5.22450.389609.0131

5.15930.362907.244227

5.5419114.1484

‐8015

8020

‐0.5295

78.2763

‐3050

1260

‐0.0349

0.3283‐0.91630.6419‐0.03160.3307‐0.8916

0.6419age (years old)(log of years old)

education years (years)(log of days)
a dummy variable of stopping a job involuntarily
before unemployment
monthly wage in a job after unemployment(thousands of yen)(log of thousands of yen)monthly wage difference before and after
unemployment (thousands of yen)effective job rates when started a job after
unemployment (log of percentage)* The numbers of the observations are 76,565 and 22,204 respectively in the whole sample (Panel A) and in the restricted sample of late appliers (Panel B).

27

Table 2. The effect of unemployment duration on retention rates at post‐unemployment job
The entire age
group‐0.0687***
log of unemployment duration(0.0067)‐0.194***age (years of old)
(0.0272)
0.0083a dummy variable of male respondent(0.0162)0.1199***a dummy variable of married respondent(0.0165)0.4674***
education years(0.0503)(log of years)
0.1250***pre‐unemployment job tenures(0.0053)(log of days)
post‐unemployment wage
0.0705***(log of thousands of yen)
(0.0227)
wage difference before and after unemployment ‐0.0001(0.0001)(thousands of yen)a dummy variable of stopping pre‐unemployment ‐0.0686***(0.0228)
job involuntarily
0.2368***effective job rates when started(0.0248)
post‐unemployment job (log of percentage)
4.6841***constant(0 1948)(0.1948)
Number of the observations
76565
Log likelihood‐62483.12
Likelihood ratio test: all the parameters are zero. 957.71***28(a) Age 16‐44(b) Age 45‐64‐0.0597***(0.0079)‐0.3749***(0.0436)‐0.0302(0.0186)
0.1152***(0.0195)
0.7382***(0.0626)
0.1211***(0.0065)
0.1163***(0.0293)‐0.0001(0.0001)‐0.0771***(0.0266)
0.2456***(0.0315)
4.3674***(0 2446)(0.2446)56984‐46507.788
695.56***‐0.0902***(0.0126)0.8572***(0.1596)0.0939***(0.0342)0.1832***(0.0308)0.0754(0.0866)
0.1251***(0.0093)0.0408(0.0379)‐0.00005(0.00009)‐0.0998**(0.0450)0.2242***(0.0400)
1.6755***(0 7406)(0.7406)
19581‐15892.774
427.13***

Table 3. The effect of unemployment duration on retention rates at post‐unemployment job:for the samples who started applying for jobs in the final 59 days before expiration(a) Age 16‐44(b) Age 45‐64

log of unemployment duration‐0.4190***‐0.2537***(0.0276)(0.0495)‐0.5451***

0.972***(0.0817)(0.3330)‐0.0588*0.0883(0.0337)(0.0709)

0.0652*0.1088*(0.0364)(0.0615)

education years

0.7796***0.1731(log of years)(0.1168)(0.1856)

0.0950***0.0642**(0.0173)(0.0270)‐0.1321**‐0.1114(0.0570)(0.0876)‐0.0002‐0.0009**(0.0002)()(0.0004)()

a dummy variable of stopping pre‐unemployment 0.0060‐0.0681age (years of old)a dummy variable of male respondent
a dummy variable of married respondent

pre‐unemployment job tenures(log of days)
post‐unemployment wage(log of thousands of yen)wage difference before and after unemployment((thousands of yen)y )job involuntarily(0.0480)(0.0934)‐0.0344‐0.2879(0.0975)(0.1899)

7.9824***2.7881*(0.4784)(1.5537)

Number of the observations

17823

4381

Log likelihood‐13815.352‐3583.570

Likelihood ratio test: all the parameters are zero.

343.61***

69.98***

effective job rates when started
post‐unemployment job (log of percentage)
constant

29