ISS Discussion Paper Series F-155

What determines work hours?:
who you work with or where you work?
March 2011
F-155
Sachiko Kuroda† and Isamu Yamamoto‡
Institute of Social Science
The University of Tokyo

Abstract
By using a unique dataset on managerial-level employees who were transferredfrom Japan to European branches of the same global firms, we examine what
would happen to work hours when a worker moves from a long-hour-working
country to relatively shorter-hour countries. Even after controlling for businesscycles, unobserved individual heterogeneity, job characteristics, and work hour
regulations, we find a significant decline in Japanese work hours after theirtransfer to Europe, resulting from working-behavior influences of locally hired
staff. We also find that the reduction in hours worked highly depends on theextent of the workers’ interactions with local peers.

――――――――――――――――――――――――――――――
Data used in this paper are taken from a survey we administered to workers of global Japanesecompanies operating either in the UK or Germany, and the longitudinal data from the KeioHousehold Panel Survey (KHPS). The authors deeply appreciate Reiko Aoki, Shunichiro
Bessho, Chun Chung, Yuji Genda, Peter Haan, Masahiro Hori, Toshihiro Ihori, Seiichi Inagaki,
Yoshihiro Kaneko, Akira Kawaguchi, Daiji Kawaguchi, Katsuyuki Kubo, Wataru Kureishi,Ryo
Nakajima, Keisuke Nakamura, Haruko Noguchi, Fumio Ohtake, Takashi Oshio, Hideo Owan,
Takuji Saito, Kazuharu Sakamoto, Shinpei Sano, Dan Sasaki, Hiroki Sato, Yoko Takahashi,
Noriyuki Takayama, Ryuichi Tanaka, Atsuhito Toda, Emiko Usui, Kengo Yasui, andparticipants of 32nd Conference of the International Association for Time Use Research fortheir valuable comments. This research is supported by the Japanese government’s Grants in aid
for young scientists (Japan Society for the Promotion of Science; Research No. 22730188<Kuroda> and Research No. 20730164 <Yamamoto>), Program for Promoting Social Science
Research Aimed at Solutions of Near-Future Problems “Creation of Employment System thatenables Lifelong Growth for All People” (commissioned by the Ministry of Education, Culture,
Sports, Science and Technology) and Program of Intergenerational Equity (the grants from the
Ministry of Education, Culture, Sports, Science and Technology).The remaining errors aresolely of our own.

† The University of Tokyo (kuroda@iss.u-tokyo.ac.jp,
Waseda University, s-kuroda@waseda.jp)‡ Keio University (yamamoto@fbc.keio.ac.jp)

from April 2011 onward,

I. Introduction
The total time spent for market work differs substantially from country to country. In 2008,
the average annual hours worked per person in employment were 1,792 in the US, 1,653 in
the UK, 1,542 in France, and 1,432 in Germany (OECD [2009]). These countries’ annual
work hours were almost the same 40–50 years ago.
Several seminal studies have sought to explain such divergences of work hours
among countries, in other words, why work hours of Europeans have declined sharply overthe last few decades. 1 Prescott (2004) suggests that this is due to the increase in tax
distortions in European countries during the 1970s and 1980s, whereas Blanchard (2004)
attributes this to the differences in preferences and income effects among nationalities.
However, Alesina, Glaeser, and Sacerdote (2006) contend that neither tax distortions nor
differences in preferences fully explain the divergences. On the other hand, they emphasize
the presence of positive complementarities in either consumption or leisure.2 This paper
empirically examines whether such positive complementarities in leisure exist by using aunique panel dataset on managerial-level employees who were transferred from Japan to theEuropean branches of the same global companies.
In competitive markets where all workers act individually, competition with otherworkers would probably lead to an equilibrium in which everybody works longer hours (along-hour equilibrium).3 However, as Alesina, Glaeser, and Sacerdote (2006) argue, oncesome kind of coordination succeeds in achieving an environment where most people work
shorter hours, positive complementarities in leisure may induce many people to decrease their
1

However, Nickell (2006) maintains that there is yet no clear, simple theory which
consistently explains the cross-country pattern of labor inputs. Alesina, Glaeser, andSacerdote (2006) and Faggio and Nickell (2007) both point out that tax rates alone can
explain only a small amount of the differences in hours worked. They are also skeptical ofcultural differences since Europeans worked more or less the same as, or even somewhat
longer than, Americans before the 1970s.
2
Alesina, Glaeser, and Sacerdote (2006) call the effect a social multiplier. They suggest thatboth high taxes and direct pressure to work less brought about by a combination of strong
unions, generous welfare benefits, and social democratic governments during the 1970s and1980s served as a coordination device to work less in European countries. See also Glaeser,
Sacerdote, and Scheinkman (2003].
3
See, for example, Landers, Rebitzer, and Taylor (1996). Investigating two large law firms,
they show that, under a certain organizational setting, associate lawyers are required to work
long hours inefficiently because of competition.
1

work hours, and hence, a short-hour equilibrium is achieved. In other words, in anenvironment where most people—colleagues, staffs, bosses, clients, friends, families, andneighbors—work less (or take long vacations), an individual’s utility from not working (ortaking long vacations) may increase, further inducing him/her to work less. This is, of course,
an intriguing idea, but empirically identifying such an effect on hours worked is not easy.
This brings us to an interesting question. What would happen to individual behavior
if people are shifted from a long-hour to a short-hour equilibrium environment? Specifically,
how would the work hours be affected when a worker moves from a country where mostpeople work long hours (Japan) to countries where people work relatively shorter hours(European countries)? If workers are influenced by their peers and/or neighborhood, theirwork attitudes and work hours would converge to those of the group they belong to. This
paper tries to examine such positive complementarities in leisure, or what we call groupinteraction effects, using the previously mentioned datasets. Specifically, we assess whether,and to what extent, an individual’s work behavior would be affected by the group interaction
effects when the person’s working environment changes drastically, other things being equal.
When estimating the group interaction effect, we consider possible differences in job andHRM characteristics, business cycles, and work hour regulations. Furthermore, since theJapanese workers we assess in this paper are required by their employers to move from Japanto Europe (i.e., they do not move voluntarily as migrant workers do), our datasets arebasically free from the endogeneity problem.
Our paper is related to a growing body of literature on group interaction effects asdeterminants of individual behavior. Among these volumes of studies, Ichino and Maggi’s(2000) work is the closest to ours, besides that of Alesina, Glaeser, and Sacerdote (2006).44

Ichino and Maggi (2000) estimated the prevalence of shirking in a large Italian bank, andsuggested that episodes of absenteeism and misconduct, more prevalent by far in the south of
Italy, can be partially explained by group interaction effects. Regarding other related studies,
Glaeser, Sacerdote, and Scheinkman (1996) estimate the extent of neighborhood effects on
criminal behavior in US cities, finding that such effects are stronger for less serious crimes.
Using the confidential information of National Longitudinal Survey of Youth, which canidentify the street addresses of respondents, Weinberg, Reagan, and Yankow (2004) foundthat the social characteristics of a neighborhood increased annual work hours. Falk and Ichino(2006) conducted an experiment in which subjects were asked to fill letters into envelopes
with remuneration independent of output, and found that productivity increased when two
persons worked at the same time in the same room, rather than each person in a different
room, suggesting the importance of peer influence on productivity.
2

Their approach is similar to ours in the sense that both focus on individual behavior changes
using information on movers within the same firm. Our paper basically endorses theirfindings, but differs from them at least in the following respects. First, movers in our analysis
are transferred from one country to another where the working environment differs
substantially. Second, we mainly consider the number of hours worked, focusing especiallyon workers at relatively higher levels in each firm’s hierarchy.5 Third, our datasets contain
information on persons with whom the worker mainly interacts. This information isparticularly important to estimate the group interaction effects on movers since, even after
moving to other countries, some workers may spend most of their time communicating anddealing with workers in his/her home country. Fourth, we measure how Japanese staff’s work
hours would be adjusted to those of locally hired staff over time, using information on thenumber of years passed since the worker’s transfer to Europe. In other words, we measure
how the group interaction effects would evolve in a relatively longer time span.
The major findings of this paper can be summarized as follows. We find that thehours worked by Japanese staff have declined significantly after a shift to Europe, possibly
because of peer influence. On average, hours worked per week declined by more than 4
percent merely as a result of a transfer to European branches, after we controlled for
aggregate demand shocks, unobserved individual heterogeneity, and job characteristics aswell as work hour regulations. It is also shown that the degree of influence highly depends onthe extent of a worker’s interactions with local colleagues or clients. In addition, our results
suggest that peer behavior non-monotonically influences Japanese workers over time.
Specifically, for the first two years in Europe, hours worked by Japanese workers gradually
decline, and remained relatively constant for the next several years. After five years, however,
the hours worked decline further, converging to a level close to those of local peer workers.
This paper is organized as follows. In Section II, we present the basic fact thatJapanese staffs’ work hours declined after they were transferred to Europe and introduce theconceptual framework behind the phenomenon. In Section III, we explain our datasets. In
Section IV, we show our empirical results on how work hours would change when a worker
5

Most of the literature that analyzes the externalities of worker effort on coworkers’
behavior study either non-managers or blue-collar workers. For example, Mas and Moretti(2010) study the productivity of cashiers in a national supermarket chain, and Bandiera,
Barankay, and Rasul (2010) analyze the behavior of workers in the fruit-picking division of aleading UK farm producer.
3

moves from a long-hour-working country to relatively shorter-hour countries. In Section V,
we conduct some robustness checks and interpret our results. Section VI concludes the paper.

II. Overview and conceptual framework(1) Overview: change in hours worked
Our main data source is a survey we administered to workers of global Japanese companies
operating either in the UK or Germany. The two countries were chosen because the UK and
Germany are the two top countries in terms of the number of Japanese firms operating inEurope. 6 The survey was conducted within a two-month period from December 2009
through January 2010 by computer-assisted telephone interviews (CATI) with the online
questionnaire link forwarded to the respondents’ colleagues.7
The targeted respondents were (1) Japanese staff in the managerial level aged 30–50
years, originally hired in Japan and transferred to European branches and (2) locally hired
staff equivalent to the Japanese staff working in the same establishment in managerial
positions. The research agency was directed to collect a minimum of four samples percompany (two Japanese and two locally hired staffs). Our sample consisted of 344 Japaneseand 531 non-Japanese who worked in the UK (201 and 261, respectively) and Germany (143and 270, respectively). Industry composition differs between the UK and Germany.
Manufacturing, financial, and wholesale and retail sectors account for 34, 19, and 15 percent,respectively, in the UK and 59, 24, and 2 percent, respectively, in Germany. The descriptive
statistics are shown in Table 1 for Japanese respondents, whom we mainly focus on in thispaper. We limit our sample to those who were transferred to Europe after 2004. The following
paragraphs provide brief explanations and an overview of our datasets.
Both Japanese and non-Japanese respondents were asked to provide the following
two measures of labor supply: total hours worked per week and the amount of paid leave
taken per year. Japanese respondents were also required to provide this information for the6

According to the Japan Chamber of Commerce in Dusseldorf (Japanische Industrie- undHandelskammer zu Düsseldorf e.V.), the 2009 membership of Japanese firms was 566 inGermany and 316 in the UK, whereas that of France was 263 and Italy, 191.
7
The online survey was intended to collect information from workers not able to respond to
the phone survey because they were either busy or would not be in the office during daytime.
4time they were in their previous positions before being transferred to Europe.
Figures 1(1) to 1(3) compare hours worked by Japanese workers before (horizontalaxis) and after (vertical axis) moving to Europe. Looking at weekly hours worked in Figure1(1), we observe a large number of observations are plotted below the 45-degree line,
indicating hours worked before moving to Europe were much longer than after. Those who
used to work around 60 hours a week in Japan tended to decrease their work hours to about
50 hours. This trend is more evident for the paid leave taken per year shown in Figure 1(2).
We see most workers increased paid leave after moving to Europe. For those workers who
used to take only 10 to 15 days in Japan, for example, the leave is likely to be twice as muchin Europe. As a result, annual hours worked, calculated from weekly hours worked and paid
leave, also decreased as shown in Figure 1(3).
Figure 2 compares distributions of weekly hours worked across countries andnationalities. In Figure 2, “J before” is the distribution of hours worked by Japanese workers
while in Japan, “J after” is that in Europe (the UK or Germany), and “EU” is that of locally
hired managers.8 In the UK, as shown in Figure 1, weekly hours worked by Japanese
workers decrease after moving to the UK. Similarly, in Germany, hours worked by Japanese
workers seem to converge to those by locally hired managers. It seems that Japanese’ work
hours are influenced by locally hired managers whose work time is considerably shorter.

(2) Conceptual framework
We assume that the hours worked by Japanese workers after they moved to Europe decreased
substantially because of the interaction with European workers whose work hours are
relatively shorter on average. In this section, we provide a conceptual framework that
explains how a worker reacts to his/her coworker’s work time in the presence of groupinteraction effects.
Suppose worker i chooses hours worked hi and efficiency level (productivity or
effort) per work hour ei, given his/her marginal product per efficiency hour, wi. We assume
that both hi and ei are observable by worker i’s employer. Without the group interaction
8

Most of the Japanese respondents of our survey were managers, while non-Japanese
respondents comprised both managers and non-managers. Therefore, the comparisons arebasically conducted between Japanese and locally hired managers.
5effects,

workeri’s

problemistomaximizethestandard

utilityfunction,U(wi hi ei )  Ch (hi )  Ce (ei ) , in terms of hours worked and efficiency levels, whereU(),Ch (), and Ce () are increasing functions.

When worker i interacts with other coworkers in the workplace, however, the worker
maximizes the following utility function taking account of his/her coworkers’ work hours andefficiency levels.
U ( wi hi ei )  C h ( hi )  C e ( ei )  D h ( hi , h j )  D e (ei , e j ), j  1, , i  1, i  1, , N ,where  Dh (hi , h j ) and  De (ei , ej ) indicate possible disutility arising from the deviations ofworker i’s hours worked and efficiency levels from those of the other workers in the groupthat he/she belongs to (N is the number of workers in the group). Here, we assume
complementarities in hours worked and efficiency levels, and therefore similar work hours
and efficiency levels with other coworkers would increase worker i’s utility.
This setup is very similar to the ones proposed in other studies9 considering how
workers’ productivity is affected by that of other workers in the team production process.
Here, we do not necessarily limit the phenomenon to team work but extend it to all the jobs
that require interaction with coworkers in some way or another. We also explicitly
incorporate the group interaction effects in terms of both hours worked and efficiency levels.
Suppose that everybody works shorter, then worker i would incur more disutility fromovertime work. One of the reasons for this is a complementarity for work; that is, it becomesless productive to work alone after most of the coworkers leave the office. The other reason isloneliness or a sense of isolation when the worker spends his/her time in overtime work while
coworkers and friends enjoy leisure time. Similarly, when the worker’s efficiency level is far
below the coworkers’ average, his/her disutility would increase since he/she would feelashamed to be considered clumsy by his/her colleagues.
Under this setup, it is possible to explain how group interaction with European
coworkers would affect the working habits of Japanese workers transferred to Europe. Those
Japanese workers would typically face large work hour deviations from European coworkers
9See, for example, Kandel and Lazear (1992), Falk and Ichino (2006), Mas and Moretti(2009), and Bandiera, Barankay, and Rasul (2010). Kandel and Lazear theoretically describe
how peer pressure operates and how factors such as profit sharing, shame, guilt, norms,
mutual monitoring, and empathy interact to create incentives in the firm.
6

( hi  hj ). Thus, they tend to reduce their hours worked so that they minimize the disutility
from work hour deviation from European coworkers. Likewise, Japanese workers would findthe European way of working more efficient ( ei  ej ) and feel ashamed of their own
inefficient work style. Thus, Japanese workers would likely learn the efficient work style ofEuropean coworkers to reduce the disutility from deviations in the efficiency level. As aresult, their work hours would decrease and/or efficiency levels increase to the level of theircoworkers’; this occurs as a result of the group interaction effects.
It is often the case that hours worked and efficiency levels are closely related. When
worker i’s labor supply on an efficiency basis is expressed by yi  hi ei and it is fixed as yi ,hi and ei become interdependent. For example, in a case where a worker is employed by thefirm under an implicit contract to supply the fixed amount of labor service yi , the worker
could reduce his/her work hours only if his/her efficiency levels were increased. In otherwords, work hour reductions are possible when a worker finds more efficient ways ofworking so that the amount of labor supply on an efficiency basis remains unchanged.
Furthermore, since we focus on white-collar workers in the managerial level who are
exempted from work hour regulation, we assume fixed salary ( Si  (S( yi )  S(hi ei )) toproduce yi . Under these circumstances, the worker’s utility can be expressed as follows:
U [ S i ( y i )]  C ( hi )  D ( hi , h j ) wherey i  hi e i .

In this case, the labor supply function of worker i would include coworkers’ work hours.
Therefore, the group interaction effects should be observed so that worker i’s work hours areaffected by his/her coworkers’, other things being equal.

III. Identification strategy
The changes in hours worked which we saw in Section II may have been brought about byfactors other than the group interaction effects, such as the changes in job and HRM
characteristics or aggregate demand shock. Thus, when identifying the group interaction
effects, how we control for other factors is of paramount importance. To determine which
factors we must control for, we take into account the insights from interviews with Japanese7managers working for UK and German branches of global Japanese companies, conductedprior to the above survey. For the details of the manager interviews, see Appendix.
From the manager interviews, we assume that the annual after-tax net incomes,
employment conditions such as paid leave before and after the transfers from Japan to Europe
are not significantly different.10 This is because the transfers are not of the workers’ choice
but at the firm’s behest, and therefore the transferred workers are guaranteed the same
conditions, including salary and paid leave, as if they had continued to stay in Japan.
On the other hand, we find it important to control for the differences in job and HRM
characteristics (such as workload or performance assessment systems), work hour regulations,and business cycles since these factors would have changed after the transfer to Europe. To
control for these factors, we designed our survey to ask several questions concerning job andHRM characteristics as well as the group interaction between Japanese managers andEuropean coworkers.

(1) Control variables: job and HRM characteristics
First, to control for possible changes in job characteristics, we asked each respondent in thesurvey whether the following four conditions had changed (increased / decreased / stayed thesame) after moving to Europe: (a) I have a lot of work, (b) I have a certain amount of
discretionary power, (c) my job mostly involves team working,11 (d) I have a clear job
description. Using the answers, we control for the changes in job characteristics.
Second, in order to adjust for possible changes in the performance assessment
systems in European branches, we asked each respondent whether “people who workovertime or during holidays are valued highly” at one’s workplace and whether suchconditions had changed (increased / decreased / stayed the same) compare with one’s
previous workplace in Japan. We take this information as a change in performance
10

Regarding income, we also assume that there is no income effect on hours worked since
this paper focuses managerial level employees.
11
Bell and Hart (1999) suggest that team work is one of the possible factors that explain theexistence of unpaid work. Hamilton, Nickerson, and Owan (2003) find that the adoption ofteam piece rates at a plant improved worker productivity by 14 percent on average. We
therefore take into account whether a worker works in a team or not, although we do notnecessarily limit our interest to workers who work as a team.
8

assessment practices at workplace, and incorporate it in the analysis below.
Third, we asked a unique question to measure respondents’ coordination costs withinfirms, which we call nemawashi.12 Specifically, we asked the respondents the following
question: “When you need to get an approval or sign off for an important decision or a new
project, how many of your colleagues or managers do you have to talk to, on average, inorder to get the approval (or get a consensus/reach an agreement)?” We expect that the more
people one has to talk to, the longer his/her work hours become. Since Japanese respondents
are asked to indicate the number of persons for nemawashi in the current position, as well as
before moving to Europe, we are able to measure the change in coordination costs and use it
as one of the control variables.
Lastly, since most Japanese managers were exempt from overtime regulations inJapan even as they are after moving to Europe, the differences in working hour regulations
for most workers would not affect their working behavior. However, some workers in our
survey were promoted as managers after moving to Europe, while some were covered by theregulations both before and after moving to Europe. Regarding these workers, we will control
for the changes in the exemption status.

(2) Group interaction variables
In order to explicitly capture the group interaction effects, we ask the Japanese respondents toindicate (a) the number of years since they moved to Europe, (b) the number of non-Japanese
local friends and acquaintances outside the workplace, and (c) proportion of time spentdealing with local non-Japanese staff and clients. The number of years since relocation isintended to assess how the group interaction effect evolves over time. The number of
non-Japanese local friends and proportion of time spent with non-Japanese local staff andclients are used to examine whether those who interact more with local people inside andoutside the workplace tend to change their ways of working. We assume that the more local
12

In Japan, when making an important decision or starting a new project, workers tend to
spend quite a lot of time for in-advance negotiations behind the scenes, talking to manycolleagues or superiors to reach a consensus or to get approvals. This practice is callednemawashi in Japanese. The term nemawashi means laying the ground work, which
originally comes from the practice where one must dig around the roots a year or two before
transplanting a tree.
9friends one has, the more fun one feels by hanging out with them rather than working late in
the office. In this paper, we call this the neighborhood effect. Similarly, the more a person
works with local staff and clients, the more he/she would find it comfortable to adjust toEuropeans’ working habits. We call this the peer effect. Even after moving to Europe, if aperson mostly spends his/her time at office dealing either with his/her colleagues in head
office or local Japanese staffs, the person would be no different from one who works in Japan.
We especially focus on this peer effect variable since it enables us to distinguish peer effects
at the workplace from other factors. This is because the institutional factors specific to acertain workplace or region may induce worker behavior in the same direction even if thepeer effect is not present (Manski, 1993). For example, if there is a strict shop-opening-hour
legislation in the region, it may urge workers to finish work quickly in order to shop forgroceries on their way home. Our peer effect variable enables us to identify the genuinegroup interaction effect among workers. In addition, in order to control for institutional
differences between the UK and Germany, we also incorporate country fixed effects in theestimation below. Both neighborhood and peer effects are considered as types of groupinteraction effects.

IV. Group interaction effects on hours worked
In what follows, we conduct three types of analysis to measure group interaction effects.
(1) Difference-in-difference estimation
To assess the group interaction effects, we first take the difference-in-differences regression
approach to control for aggregate year-specific effects. Our survey was conducted from
December 2009 through January 2010. Therefore, the observed changes in hours worked
after Japanese workers moved to Europe most likely include the effect of aggregate demand
shocks such as the financial crisis of 2008. To isolate these effects from the group interaction
effects that may arise after the relocation to Europe, we construct a control group in which
workers were not transferred to Europe but stayed in Japan before and after the financial
crisis. For the control group, we use the Keio Household Panel Survey (KHPS), which is the10broadest household longitudinal survey in Japan.13 From KHPS dataset, we limit our samples
to managerial workers who have been transferred from one establishment to another within
the same company.14 Although these control group workers were transferred within the same
company, they continued to work in Japan even after the financial crisis. Thus, by subtracting
the change in the work hours of the control group from that of the treatment group, we areable to identify the group interaction effects.
With the indices (n1,, nN ) for our survey data and ( m 1 ,  , m M ) for KHPS data,
the estimation equation is expressed as follows:

hit   ( it ) EU it  t  f i  X it   uit, i  {(n1 ,  , nN ), (m1 ,  , mM )} , t  2004,  ,10,(1)

where hit is the log of weekly hours worked by individual i in year t;15 EUit, an indicatorvariable that takes 1 if an individual works in Europe and 0 in Japan; Ωit, the groupinteraction variables such as the number of non-Japanese friends; λt, the aggregate
year-specific effects; fi, the unobserved individual-specific effects; Xit, the observed
individual characteristics (the number of years since transfer and occupation dummies); anduit, the error term. The fixed-effect estimation of equation (1) yields the estimates of thegroup interaction effects α(Ωit), as well as aggregate year-specific effects λt.
Table 2 shows the estimation results of equation (1). Case (1) of Table 2 shows thathours worked by those who had been transferred to Europe decreased significantly—by 8.4
percent—after moving to Europe. In case (2), where we control for year-specific effects, on
13

The KHPS, sponsored by the Japanese government, is a longitudinal survey of individuals
conducted by Keio University every January since 2004. It has a broader coverage than any
such survey in Japan. The survey selects 4,000 individuals at random from the entire
Japan-resident population (male and female) aged 20 to 69 years using two-stage sampling.
According to Kimura (2005), who made a detailed analysis of the KHPS sample
characteristics, no significant differences are found in the distribution of major variables
compiled from the KHPS survey questions compared with other official statistics of Japan,
including the Population Census and the Labor Force Survey, both of which are taken by theStatistics Bureau of the Ministry of Internal Affairs and Communications.
14
Using only movers in the KHPS as a control group also accounts for the possibility thathours worked by the movers would increase until they get accustomed to the newenvironment. However, with non-movers of the KHPS included in our sample, we get very
similar results.
15
As mentioned above, our survey was conducted from December 2009 through January2010 by CATI. For convenience, we assume the survey year is 2010, even for the surveys
conducted in December 2009.
11

the other hand, the decrease in hours worked is 7 percent, which indicates that a 1.4 percent
decrease should be attributable to the aggregate year-specific effects. It is shown, however,even if we control for the aggregate demand shocks such as the financial crisis, we stillobserve significant group interaction effects, that is, a 7 percent decrease in hours worked by
Japanese who are transferred from Japan to Europe.
Cases (3) to (6) of Table 2 show the regression results, which took group interaction
variables into account. A proportion of work time with non-Japanese staff and clients issignificantly negative, while the number of years since their transfer to Europe and thenumber of non-Japanese friends are both insignificant. These results indicate that groupinteraction effects are mainly brought about by peer effects of the workplace. It is shown
from the estimated parameter that those who interact with local staff and clients for 80
percent of the total work time show a decrease of about 10.7 percent in hours worked.

(2) Controlling for job and HRM characteristics: hours worked and presenteeism
One of the limitations of the above estimation is that we have not so far controlled for the
possible changes in job characteristics after the worker moves to Europe. However, the KHPS
data do not contain such information. Therefore, in the rest of the analysis, we use only oursurvey data, which contain rich information on job and HRM characteristics.
As shown in Table 2, however, it is important to control for the aggregate demand
shocks. Hence, we explicitly include the aggregate year-specific effects estimated in Table 2
as follows:

hit   (it )EUit  ˆt  fi  Zit  uit , i  (n1,, nN ) , t  2004,,10 ,(2)

where Zit is a set of variables for job characteristics and other individual characteristics andˆ t ,a set of the estimated aggregate year-specific effects from equation (1). Since our survey

data relate to two periods of time, before (EUit = 0) and after (EUit = 1) moving to Europe, theequation to be estimated is simplified as follows:

hi ,10  hi ,   (i ,10 )  (ˆ10  ˆ )  (Zi ,10  Zi , )   i , i  (n1 ,, nN ) ,

12

(3)

where τ indicates a year before the move to Europe. In the estimation, we use weekly hours
worked as the dependent variable as in Table 2.

Weekly hours worked
Table 3 shows the estimation results for weekly hours worked. Looking at case (1), where we
do not include any year-specific effects, the group interaction effects are estimated as -7.9
percent. Once we include the estimated year-specific effects in case (2), those effects reduceto -4.1 percent.
As for the effects of the changes in job and HRM characteristics, we see significant
results of the workload, performance assessment practices and coordination costs within thefirm. It is interesting to note that the performance assessment (whether overtime is highly
valued) and the coordination cost (the number of persons laying the groundwork; nemawashi)
has positive effects on hours worked as we expected. It should be noted here that a firm’s
performance assessment practices and coordination costs might be both closely related to thework habits of peers. For instance, workers transferred to Europe might reduce in-advancecoordination, getting to know from their peers that excess consultation with bosses andcolleagues when carrying out a project is considered inefficient. If this is the case, theestimated coefficients for a firm’s performance assessment practices and coordination costs
would include group interaction effects. We may regard -4.1 percent as the minimum of theaverage group interaction effects. Furthermore, although not shown in the table, for those
who worked very long hours while in Japan, we found that the longer they worked in Japan,
the greater was the downward adjustment after the transfer. Specifically, for those who
worked more than 60 hours per week in Japan, the group interaction effects were -16.0
percent, compared to -7.9 percent for those who worked 50 to 60 hours per week.
Looking next at the group interaction variable in cases (4)–(6), the proportion ofwork time with non-Japanese staff and clients is significantly negative, as is the case in Table
2. Even after controlling for job and HRM characteristics and year-specific effects, we canconfirm the significant group interaction effects through peer effects of the workplace.
Table 3 also shows the effects of working-hour regulations. As stated above, most of
the workers in our sample are exempt from working-hour regulations. However, for those13

who are subject to the regulations, both in Japan and Europe, the hours worked declined
significantly. This indicates that stronger regulation on work hours would serve in reducing
hours worked by non-exempt workers.16 Lastly, we see that other variables in Table 3 such as
family (living with spouse and/or child) and region (the UK or Germany) are not significant
as a determinant of the changes in hours worked.

Annual hours worked and paid leave taken
We next see how group interaction affects the workers’ choice on annual hours worked andpaid leave. In Tables 4(1) to 4(3), we see that annual hours worked decrease by 5.2 percent
due to the group interaction effects—an amount greater than the weekly hours worked. In
addition, peer effects (the coefficient of the proportion of work time spent with non-Japanese
staff and clients) of annual hours worked are greater than those of weekly hours worked.
Tables 4(5) to 4(8) show a significant increase in the days of paid leave taken after a worker
moves to Europe. It is also worth noting that for paid leave not only the peer variable but also
the number of years since the move to Europe and the number of non-Japanese local friends
are significantly positive. These results indicate that workers tend to take more paid leave as
their stay in Europe becomes longer or the number of non-Japanese friends increases.

Attitude to work: presenteeism and customer-first mentality
In addition, we use the indicator variables of workers’ sentiments to see the changes in work
attitude that is closely related to hours worked. In the survey, we asked the respondents thefollowing two questions: (a) Is it difficult to leave if other people are still in the office? (b) If
you received an urgent request from an important client, which of the following most closely
describes your response in your current situation? The answer to the former question (“yes”
or “no”) was intended to determine whether an attitude of presenteeism17 exists in the16

Overtime regulations are stricter in European countries compare to that of Japan.
In general, the term presenteeism is used to describe the problems faced when employees
come to work in spite of illness, which can have negative repercussions on businessperformance. The term is also used to imply the expectation on the part of employers that
their employees be present at work regardless of whether any work is available or17

14

respondent’s workplace. For the latter question, the following two choices were indicated: (1)even if it was unreasonable, you would rearrange things at the office to respond to theirrequest, or (2) you would give the client a possible time frame for a response based on thecurrent situation in the office. This question was intended to see whether a customer-firstmentality, that is, the tendency to choose (1), exists in the workplace. It has long been said
that many Japanese firms invest great efforts to forge such a corporate culture among
employees. Since these variables are closely related to hours worked, the group interaction
effects should be observed in terms of not only the actual hours worked but also the attitude
to work.
Table 5 shows the group interaction effects on worker attitudes: presenteeism and thecustomer-first mentality. Probit estimates in Table 5 partially endorse such effects on attitudes,
indicating that both presenteeism and customer-first mentality decreased after workers moved
to Europe. As for presenteeism, the group interaction effects evolve as the residence inEurope becomes longer. Regarding the customer-first mentality, on the other hand, the peer
effects at the workplace seem to be important.

(3) Convergence to neighbor and peer worker levels
We have confirmed significant decreases in hours worked by Japanese workers after theirmove to Europe. However, we have not considered how close the hours worked would
converge to their neighbor and peer worker levels. To examine this, we estimate the following
adjustment function for hours worked:rh i ,10  h i ,   (  i ,10 )( h i  h i , )  ( Z i ,10  Z i , )    i , i  ( n1 ,  , n N ) (4)where h ir is the reference level of hours worked by Japanese worker i (i.e., log of hours
worked by the neighbor and peer workers) and the parameter θ indicates the degree of
convergence, which ranges from 0 (no group interaction effects) to 1 (large group interaction
effects and complete convergence). If the group interaction effects are large enough so thathours worked by those who are transferred from Japan to Europe are wholly influenced byaccomplished. In this paper, we assume the latter implication.
15

their neighbor and peer workers in Europe, the work hours by Japanese should converge tothe level of comparable Europeans, with other factors being equal. By estimating θ, we assessthe degree of convergence of hours worked as a result of the group interaction effects. In theestimation, we assume that the degree of convergence is a cubic function of the number ofyears since the workers moved to Europe and a linear function of other group interaction
variables.
r

As for the reference level of hours worked, we use three types of h i , estimated asfollows:
1
 hk
N Li kLi

r1

hi 

where ˆLi is an estimate from hk  Zk Li  k , k  Li ,r2
hi  hˆi  Z iˆk

r3

hi 

where Li  UK, Germany , k  1,, NLi ,1

hl where JM (i)  {l  1,...,NLi | Zl  Zi  dM (i)},# J M (i) lJ M (i )where NL is the number of observations for locally hired managers in country Li= {UK,Germany} where worker i is working, JM(i) is the set of indices for the matches for worker ithat are at least as close as the Mth match, #JM(i) is the number of elements of JM(i), and dM(i)is the distance of the Mth-closest characteristic.
r1

The first reference hours worked, hi , is the sample average of log hours worked byr2

locally hired UK (German) managers if worker i is working in the UK (Germany). Second, hi

indicates the counterfactual hours worked by worker i, derived on the assumption that worker

i is a locally hired manager. More specifically, we first estimate the hours-worked regressions
hk = ZkδL + νk by using the observations of locally hired UK (German) managers k. By using
the estimates ˆL , we next derive the predicted hours of worker i by substituting his/herir3

individual characteristics Zi into Z iˆLi . Third, hi is the nearest neighborhood-matching
estimate of counterfactual hours worked. We first collect locally hired UK (German)
managers whose individual characteristics Zi are close to those of worker i. Then, taking thesample average of similar workers, we derive the counterfactual hours worked for worker i.
Regarding individual characteristics to estimate second and third reference hours, we usedtenure at the current firm, years of experience, age, occupation, whether exempt from theovertime regulation, main business (industry) of the firm, number of regular employees at the16workplace, marital status, and number of children living with the respondents, which are
queried to both Japanese and non Japanese respondents.
Tables 6(1) to 6(3) summarize the estimation results of equation (4) on annual hours
r1

r2

r3

worked when hi , hi , or hi is used as the reference hours worked. All the tables show thatthe degree of convergence to the reference level is significantly affected by the groupinteraction variables: the number of years since the transfer to Europe has a nonlinear effecton the degree of convergence, while the proportion of work time spent with non-Japanese
staff and clients (peer effects) has a positive effect.
On the basis of the estimation results of Table 6(3), we plot in Figure 3 the estimateddegrees of convergence θ for different values of group interaction variables to see how thegroup interaction effects evolve. It is shown in Figure 3 that hours worked converge only to alevel in the range of 15 to 40 percent of the reference hours worked when the number of years
since the transfer to Europe is less than one. However, hours worked converge to a level inthe range of 35 to 60 percent of the reference after the first year and remained relatively thesame for the next several years. When the number of years since the transfer to Europe
exceeds five, the hours worked converge to 55 to 80 percent of the reference level. Thispattern of work hour change implies that with more time spent in Europe, Japanese workers
seem to adjust more to European ways of working. However, our results indicate thatneighbor and peer worker influences do not affect Japanese working habits linearly, but rather
non-monotonically. The reason for the large convergence after five years is not clear.
According to a survey conducted by the Japan Institute for Labour Policy and Training
among Japanese workers who worked outside Japan (JILPT [2008]), those transferred toEuropean countries stay 4.5 years on average (standard deviation = 1.3). This implies that
almost half of the workers return to Japan within five years. If this is the case, the chances offurther staying in Europe become 50 percent after four years in Europe, which might serve as
the threshold period for a change in work habits. One interpretation is that the non-monotone
convergence after the fifth year in our analysis may reflect this change for those who staylonger than the expected period.
We shall also emphasize that the degree of convergence is affected by the proportionof work time spent with non-Japanese staff and clients. For those who spend 80 percent of
their work time with non-Japanese staff and clients, the degree of convergence becomes17

nearly 80 percent of the reference hours within five years. It remains about a half of thereference level for those who spend only 40 percent of their time with non-Japanese workers.
This finding stresses the importance of interaction with local colleagues and clients as afactor contributing to group interaction effects.

V. Robustness check and interpretations(1) Robustness check
In this section, we check whether the group interaction effect described in Section IV can still
be observed even after adjusting for the several institutional changes and individual
heterogeneity.
First, we adjust for the difference in the number of national holidays. In Japan, there
are fifteen national holidays per year, while the UK and Germany have only eight and tendays, respectively. Therefore, the increase in the days of paid leave taken after the workers
move to Europe might be offset by the decrease in the number of national holidays. To takethis into account, we recalculate the annual work hours of each subject, adjusting the national
holidays of the country where the person actually works. The estimation result, using
equation (3), is shown in Table 7. Cases (1) and (2) in the table show the results when theleft-hand side variables are the annual hours worked ignoring the difference in national
holidays (case (1) is the same result shown in Table 3). Although the result obtained in case(3) in Table 7 is not significant, case (4) suggest that even after taking into account thedifferences in national holidays, the group interaction effect can be still observed for Japanese
workers transferred to Europe especially for those who interact with locally hired staffs.
Second, we adjust for the institutional changes that occurred to a large number ofJapanese respondents after moving to Europe: sick leave. In Japan, workers are expected totake sick leave as part of their annual entitlement of paid leave. According to our survey,
however, almost 60 percent of respondents answered that they no longer need to take sickleave from the annual entitlement as long as they work in Europe. Cases (5) and (6) are theresults adjusted for institutional changes with regard to sick leave, indicating that the groupinteraction effect still holds after the adjustment.
Third, we incorporate three variables to control for individual heterogeneity in order18

to take account of the possible selection bias that might influence the results obtained above:(a) the total number of years the person lived overseas since starting work (excluding thenumber of years since his/her moving to Europe at the time of the survey), (b) age group
dummies, and (c) motivation for promotion. In our survey, some respondents answered that
this was not their first stint working abroad. We check whether such overseas experience inthe past might influence the group interaction effect. In addition, we also consider the
possible difference in the adjustment by age. One may think that if preference toward leisure
is different among ages the adjustment of hours worked may differ by age even with the sameenvironmental changes. We also take into account whether differences in one’s motivation for
promotion (individual preferences) will affect the order of the group interaction effect.
Specifically, we ask the respondents, “How concerned are you about lack of career
progression or colleagues being promoted ahead of you?” and respondents are asked tochoose from four choices: highly concerned, fairly concerned, not very concerned, and not at
all concerned. We take 1 when a respondent chooses highly concerned for the answer in order
to see whether differences in the aggressiveness toward promotion would affect one’s
behavior.
Table 8 shows the results based on these three variables. As can be seen from thetable, even after controlling for individual heterogeneity, the findings shown in Section IV
still hold.

(2) Interpretations
The above estimation results tell us that the number of hours worked by Japanese workers
declined significantly after moving to Europe from the influence of peer working behavior.
Then, why are Japanese workers affected by their peer workers? While explaining
complementarities in hours worked in Section II, we considered two possible channels
through which other people’s work hours may influence one’s choice of labor supply. One is
the technical channel, typical of team production. When a person’s job involves team work,
production is not possible if his/her coworkers leave office early. In such a case, the person
has to reduce the work time even if he/she does not want to. Another is the mental channel; aperson may feel lonely or a sense of isolation when he/she spends long hours alone at theworkplace while coworkers and friends enjoy leisure time. In addition, the person may feel19

ashamed to be considered a clumsy worker, always the last to leave office. Therefore, bothcases urge the person to speed up his/her work. Which was the channel through which theJapanese workers in our study were more likely to be influenced? Our estimates in Table 5
suggest that the Japanese workers’ sentiments toward work had changed after moving toEurope. We also confirmed that our estimation results in Tables 3, 4, and 6 do not changeeven when we control for a dummy variable that takes 1 if a worker answered that “my job
mostly involves team working.” Both evidences suggest the importance of the mental channel.
In addition, the following episodes obtained during the manager interviews also endorse therelevance of the mental channel.
During the interviews with Japanese managers working in the UK or Germany,
many of them described several common features of European ways of working quite
different from Japanese. One feature is the attitude toward risk taking. Many Japanesemanagers mentioned that in European workplaces people who occasionally produce great
results are highly estimated even if they have made some mistakes or errors (merit system).
On the other hand, they note that the typical attitude in workplaces in Japan is such thatpeople who make few mistakes or errors are highly valued even if they have not produced
any great results (demerit system). Furthermore, they mentioned that such merit-based system
in European workplaces induces workers to take risks, and consequently decisions are likely
to be made quite promptly. In addition, even though their own performance assessment does
not change after moving to Europe, many managers feel that this attitude at the workplace
influences their own way of thinking and attitudes toward taking risks to some extent. This
expedites their own decision making after moving to Europe.
Another feature concerns work efficiency. Many managers point out that theJapanese tend to pursue 100 percent quality in every task, while Europeans are more likely tothink about cost effectiveness. For example, one manager mentioned that “Japanese sales
representatives prepare five to ten patterns of presentation materials before visiting a client.
This is to get ready for any type of inquiry that may occur from a client. This practice isactually appreciated by many clients, but employees have to take quite an amount of time toprepare them, which consequently leads them to work long hours. On the other hand, frommy casual observation, locally hired sales representatives seem to prepare just a very simple
presentation material beforehand, get information of clients’ needs during meetings, and20respond to the client’s needs only when they are required. It seems that the latter style saves a
lot of time.” Another manager said, “To make 80 percent of quality in your work you only
need to take 20 percent of your energy, but to further raise the quality from 80 to 100 percent,you need to spend 80 percent of energy. In Japan, all tasks are implicitly required to get donewith 100 percent quality—even internal meeting materials just for inside staff. I think it isvery inefficient to take a long time to make internal materials look nicer, and I believe many
people also feel the same way, but people just chicken out from changing such culture. I
would say this quality-seeking attitude in Japanese firms is one of the major reasons forJapanese to work long hours.”
Lastly, let us present the result from the following survey question to Japanese
workers: “Assuming that your work hours were flexible, do you think you would increase,decrease, or keep your work hours the same given your current hourly rate of pay?”
According to our data, only 10 percent of workers who reduced their actual hours worked
after moving to Europe answered that he/she wants to increase work hours. The several
episodes and results presented above show that the mental channel seems to be the dominant
path that influenced and changed the work habits of Japanese workers.

VI. Conclusion
This paper uses information on Japanese workers who were transferred to European branchesof the same global companies to determine how hours worked would be affected when an
individual was moved from a country where most people work long hours (Japan) tocountries where people work relatively shorter hours (the UK and Germany), holding otherthings constant. Our findings imply that group interaction effects are of paramountimportance in determining one’s labor supply, suggesting another feature that may explain the
cross-country differences of work hours besides tax distortions or differences in preferencesamong nationalities.
Since this paper focuses on hours worked, our findings cannot exactly determine
whether a decrease in one’s work hours after moving to Europe is the outcome of positive or
negative externalities. If a worker’s incentive to shirk is stronger when his/her coworkers
shirk more, a decrease in hours worked can be simply considered as a negative outcome of21

the productivity decline. However, since the workers we focus on are mostly middle- tosenior-level managers in a more or less successful career track, such shirking behavior isunlikely. Instead, we interpret the decrease in hours worked after the workers moved toEurope as an increase in their per hour productivity due to the influence of colleagues (locally
hired managers) who work more efficiently in less time, as described in Section V. The factthat the base productivity per hour is much higher in the UK and Germany than in Japansupports this interpretation (OECD [2008]).18
It would be interesting to see how the work hours of those who have been influenced
by European ways would change after they move back to Japan, where more than 20 percent
of prime-age full-time male workers work more than 60 hours a week. It would also beinteresting to see how one’s behavior would be affected in the opposite case—when a worker
is shifted from a short-hour to a long-hour equilibrium environment. Furthermore, one would
like to know if the same group interaction effects can be observed in workers of othernationalities, since Japanese are sometime considered to be a nation prone to collective action.
These are areas for further study.

Appendix. Insights from manager interviews
Prior to the above survey, we conducted interviews with fourteen Japanese managers who
worked in eleven global Japanese firms operating either in the UK or Germany: six firms in
manufacturing sector and five firms in the service sector (three firms in finance or insurance,
one in wholesale, and one in information and telecommunications). Each interview took
about 1.5 to 2 hours. The following is an overview of the common issues we heard from theinterviews.

Transfer system and HRM
In general, the transfers to overseas branches are assigned by the personnel department19 at
18

Blanchard (2004) suggests in the US over the period 1970 to 2000, GDP per hour
increased by 43 percent whereas in France, over the same period, GDP per hour increased by
80 percent, indicating a much higher rate of growth in productivity per hour in European
countries than in the US.
19
In general, the personnel department in Japanese firms has a great deal of power andinfluence compared with that of western firms. Regarding the general practices of the22headquarters in Japan, and therefore workers are less likely to move of their own choices.20
Although the length of appointment depends on each firm’s personnel policy, most of the
managers answered the average is about three to five years. There are some workers who aretransferred from one country to another other than Japan, but most of workers are transferredfrom Japan and are transferred back after several years.
Since the transfers are not made by workers’ wish but assigned by the firm,transferred workers are guaranteed the same conditions, including salary, managerial
practices, and paid leave as if they stayed in Japan. Specifically, firms basically assure thoseworkers the same level of annual after-tax net income, which indicates that we do notnecessarily have to consider the differences in salary, tax rates, and other social insurance
system between Japan and the UK/Germany.21 Similarly, the managerial practices and otherlabor conditions (such as the number of paid leave given to workers) are essentially the samewith the workers in Japan. Thus, we do not basically take account of the differences in HRM
system before and after the transfer to the UK/Germany. Regarding performance assessment,
however, many firms employ a dual system in European branches; each worker’s
performance is first assessed and reported to the personnel office at the headquarters by
his/her boss in the same establishment, and the final assessment is made by the personnel
office. In order to take account for the possible changes at the first-tier assessment practices
by bosses in the European branches, we employ information that denotes whether practices of
performance assessment at workplace have changed after moving to Europe in the analysis
below. Detailed description is stated in Section III (2).

personnel department in Japan, see Jacoby (2005). He points out that the number of people
working in the personnel department of Japanese firms per 100 employees is, on average,
almost double that of American firms.
20This is the typical practice, established in the 1960s and 1970s, for Japanese firms. Initially,
the practice of transferring workers without their consent was started during the economic
downturn by relocating workers from a bad-performing section/department/establishment to agood-performing one to adjust personnel costs and avoid redundancy. Furthermore, in orderto relocate workers from one place to another efficiently, many firms gradually adopted suchpractices on a routine basis. By the mid-1980s, such practices came to be endorsed by theSupreme Court (July 14, 1986), which decreed against an employee who was dismissed froma firm for refusing the firm’s command to move establishments and ruled the dismissal
effective.
21Even if there were some changes in net income after being transferred to Europe (such asadditional oversea allowances), we assume that the income effects on hours worked are
negligible since our main focus is workers in managerial levels.
23

Workload, miscellaneous job characteristics, and business cycle
Hours worked would differ if the worker’s workload itself changed after moving to Europe.
In fact, some managers mentioned that their workload had increased compared to theirprevious position in Japan, while others stated it had decreased. We control for such changes
in the workload in our analysis.
Besides workload, many managers mentioned one factor that had increased
significantly after moving to Europe: discretionary power. The major reason for gaining
discretionary power seems to be related to the size of the establishment. Since discretionary
power has a lot to do with the speed of decision making, and therefore strongly related tohours worked, we also control for this factor in our analysis.
Furthermore, many Japanese managers mentioned that in Japan, when making animportant decision or starting a new project, workers tend to spend quite a lot of time forin-advance negotiations behind the scenes, talking to many colleagues or superiors to reach aconsensus or to get approvals. This practice is called nemawashi in Japanese, and we regard
this as a sort of coordination cost for a firm that would result in long work hours. In
interviews, many managers state that the nemawashi cost has decreased after moving toEurope. Thus, we also control for this change in our analysis.
In addition, most Japanese managers stated that they were exempt from overtime
regulations in Japan and it does not change even after moving to Europe. Thus, for mostworkers, the differences in working hour regulations such as maximum work hours or
overtime premium would not affect their way of working. However, some workers in our
survey were promoted as managers after moving to Europe, and therefore became exempt
from work hour regulations such as the EU Working Time Directive. On the other hand, someworkers were not exempt from the regulations both before and after moving to Europe, andthus would be affected by the difference in work hour regulations between Japan and theUK/Germany. Regarding these workers, we control for the changes in the status of
exemptions from working hour regulations in the analysis.
Lastly, many managers mentioned that work hours have recently decreased significantly withthe financial crisis of 2008. This implies that the observed decline in hours worked in Figure
1 might have been brought about by the aggregate shocks from the financial crisis of 2008.
24

Although we control for the change in workload after moving to Europe, we also explicitly
account for the effect of business cycles on hours worked by Japanese managers. This is doneby using the difference-in-differences analysis in Section IV.

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26

Table 1 Descriptive statistics
Mean

Std. Dev.

Min

Max

Weekly hours worked in EU

50.48

8.59

35.00

90.00

Weekly hours worked in Japan

55.78

9.64

35.00

90.00

-9.89

17.79

-71.91

58.78

Annual hours worked in EU

2480.45439.091677.434602.86

Annual hours worked in Japan

2777.66

490.711755.00

4566.86

Hours worked and paid leave taken

Changes in hours worked (%)-11.2818.57-80.5958.78

Paid leave taken in EU (days)

15.20

7.34

0.00

42.00

Paid leave taken in Japan (days)

11.78

6.74

0.00

40.00

3.41

6.33

-15.0030.00

Presenteeism (Increased or no change =1)

0.05

0.21

0.00

1.00

Priority of client (Increased or no change =1)

0.78

0.42

0.00

1.00

Number of years since moving to Europe

2.15

1.40

0.00

5.00

Number of non-Japanese local friends (More than 10 people=1)

0.29

0.46

0.00

1.00

Proportion of work time with non-Japanese

0.52

0.19

0.00

0.98

Workload (Increased=1, no change =0, decreased=-1)

-0.02

0.80

-1.00

1.00

Discretionary power (1, 0, -1)

0.73

0.57

-1.00

1.00

Element of team working (1, 0, -1)

-0.06

0.79

-1.00

1.00

Clarity of job description (1, 0, -1)

0.02

0.77

-1.00

1.00

Performance accessment (work overtime is valued highly: 1, 0, -1)

-0.51

0.55

-1.00

1.00

∆(Coordination cost inside a firm (number of persons laying
groundwork; nemawashi))

-1.21

2.75

-15.00

5.00

Specialist/ Technical

0.14

0.35

0.00

1.00

Management

0.58

0.49

0.00

1.00

Clerical

0.08

0.27

0.00

1.00

Sales/Marketing

0.13

0.33

0.00

1.00

Sales representative (sales calls, etc.)

0.04

0.21

0.00

1.00

Services and others

0.02

0.13

0.00

1.00

0.87

0.33

0.00

1.00

Changes in hours worked (%)

Difference in paid leave taken (days)
Attiude toward work

Group interaction /peer /neighborhood variables

Job and HRM characteristiscs

Occupation dummies

Manager dummy
Work hour regulation dummies
Exempt both in Japan and the EU

0.75

0.43

0.00

1.00

Non-exempt both in Japan and the EU

0.12

0.33

0.00

1.00

Now exempt in the EU

0.13

0.34

0.00

1.00

Notes: Japanese respondents. Although 344 respondents were selected, only those who
answered all questions were considered for the analysis of weekly hours worked.
27

Table 2 Difference-in-difference estimation of group interaction effects
(1)

(2)

(3)

(4)

(5)

(6)

-0.084** -0.070** -0.058*-0.066** 0.002

0.012(0.014)(0.021)(0.038)Group interaction /peer /neighborhood variables
EU Movers (from Japan to EU =1)(0.019)EU Movers x Number of years since moving
to Europe(0.025)(0.035)-0.007-0.005(0.010)(0.010)

Number of non-Japanese local friends(More than 10 people=1)-0.014-0.010(0.023)(0.023)

Proportion of work time with non-Japanese(0, 0.1, 0.2, … , 0.9 or 1.0)

-0.138*-0.134*(0.058)(0.057)-0.032-0.032

Year dummies-0.033

2005
2006
2007
2008

(0.024)(0.024)(0.025)(0.025)(0.025)

0.002

0.004

0.002

0.003

0.004

(0.024)(0.024)(0.024)(0.024)(0.024)-0.018-0.015-0.018-0.018-0.016(0.025)(0.026)(0.025)(0.025)(0.026)-0.045-0.042-0.045-0.043-0.041(0.029)(0.029)(0.029)(0.030)-0.062*-0.060+-0.063*-0.062*-0.060+(0.031)(0.032)(0.031)(0.031)(0.032)-0.067*-0.067*-0.067*-0.067*-0.067*(0.031)(0.031)(0.031)(0.031)(0.031)-0.008+

0.005

0.007

0.005

0.005

0.007

(0.004)(0.007)(0.007)(0.007)(0.007)(0.007)

0.135

0.151

0.152

0.152

0.159

0.160

2010

R-squared-0.033(0.029)2009

Number of years after transfer-0.032

Notes: The sample size is 1,139. Occupation dummies are included. Numbers inparentheses are robust standard errors. +, *, and ** indicate statistical significanceat 10%, 5%, and 1 %, respectively.

28

Table 3 Group interaction effects on weekly hours worked
Dependent variable = ∆(Log weekly hours worked)
(1)

(2)

(3)

(4)

(5)

-0.079**-0.041+-0.034-0.0390.004(0.024)(0.024)(0.025)(0.024)(0.037)

Group interaction /peer /neighborhood variables
Constant term

-0.003

Number of years since moving to Europe(0.007)-0.007

Number of non-Japanese local friends(More than 10 people=1)(0.020)-0.090+

Proportion of work time with non-Japanese(0, 0.1, 0.2, … , 0.9 or 1.0)

(0.053)

Job and HRM characteristics
Workload (Increased=1, no change =0, decreased=1)0.101**

0.103**

0.103**

0.103**

0.101**(0.015)(0.014)(0.014)(0.014)(0.014)Discretionary power (Increased=1, no change =0,
decreased=-1)-0.003-0.004-0.004-0.004-0.007(0.019)(0.019)(0.019)(0.019)(0.019)Element of team working (Increased=1, no change=0, decreased=-1)-0.010-0.010-0.010-0.010-0.009(0.013)(0.013)(0.013)(0.013)(0.013)Clarity of job description (Increased=1, no change=0, decreased=-1)-0.028*-0.027+-0.027+-0.027+-0.026+(0.014)(0.014)(0.014)(0.014)(0.014)

Performance assessment (work overtime is valued
highly: Increased=1, no change =0, decreased=-1)

0.039*

0.041*

0.041*

0.041*

0.036+(0.019)(0.019)(0.019)(0.019)(0.019)∆(Coordination cost inside a firm (number of persons
laying groundwork; nemawashi))

0.007+

0.007+

0.007+

0.007+

0.007*(0.004)(0.004)(0.004)(0.004)(0.004)∆(Occupation and manager dummies)

yes

yes

yes

yes

yes

-0.070*-0.070*-0.070*-0.067*(0.034)(0.034)(0.034)(0.034)(0.033)-0.041-0.034-0.034-0.035-0.030(0.029)(0.029)(0.029)(0.029)(0.029)-0.001

0.006

0.006

0.007

0.005

(0.027)(0.027)(0.027)(0.027)(0.027)

0.023

0.023

0.023

0.023

0.026

(0.025)(0.024)(0.025)(0.025)(0.025)

0.023

0.022

0.021

0.022

0.026

(0.020)(0.020)(0.020)(0.020)(0.020)Estimated year-specific effects

no

yes

yes

yes

yes

R-squared

0.295

0.308

0.309

0.309

0.317

Work hour regulation dummies (base=exempt both in Japan and the EU)
Non-exempt in both Japan and the EU
Now exempt in the EU-0.067+

FamilyLiving with spouse
Living with child
Region (Germany=1, UK=0)

Notes: The sample size is 252. The numbers in parentheses are robust standard errors.
+, *, and ** indicate statistical significance at 10%, 5%, and 1 %, respectively.
29

Table 4 Group interaction effects on annual hours worked and paid leave
Dependent variable∆(days of paid leave taken)∆(Log annual hours worked)
(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

Group interaction /peer /neighborhood variables
Constant term

-0.052*-0.040-0.048+0.008

2.398*

1.333

1.880+-1.070(0.025)(0.027)(0.025)(0.038)(1.064)(1.147)(1.099)(1.335)

Number of years since moving toEurope-0.006

0.681**(0.007)(0.216)-0.017

Number of non-Japanese local
friends (M ore than 10 people=1)

1.897*(0.021)(0.880)-0.122*

Proportion of work time with nonJapanese (0, 0.1, 0.2, … , 0.9 or 1.0)

6.840**(0.055)(1.793)

Job and HRM characteristics

yes

yes

yes

yes

yes

yes

yes

yes

Work hour regulation

yes

yes

yes

yes

yes

yes

yes

yes

Family

yes

yes

yes

yes

yes

yes

yes

yes

Region

yes

yes

yes

yes

yes

yes

yes

yes

Estimated year specific effects

yes

yes

yes

yes

no

no

no

no

0.328

0.329

0.329

0.342

0.123

0.147

0.140

0.165

R-squared

Notes: The sample size is 251 for columns (1)–(4) and 302 for columns (5)–(8). The
numbers in parentheses are robust standard errors. +, *, and ** indicate statisticalsignificance at 10%, 5%, and 1 %, respectively.

30

Table 5 Group interaction effects on work attitudes
Dependent variable
Presenteeism (Increased or no change =1)
(1)

(2)

(3)

Priority of client (Increased or no change =1)
(5)

(6)

(7)

Group interaction /peer /neighborhood variables
Number of years since moving toEurope-0.006*0.009(0.003)(0.016)-0.013

Number of non-Japanese local
friends (M ore than 10 people=1)-0.063(0.010)(0.055)0.019

Proportion of work time with nonJapanese (0, 0.1, 0.2, … , 0.9 or 1.0)

-0.254*(0.028)(0.125)

Job and HRM characteristics

yes

yes

yes

yes

yes

yes

Work hour regulation

yes

yes

yes

yes

yes

yes

Family

yes

yes

yes

yes

yes

yes

Region

yes

yes

yes

yes

yes

yes

Notes: The sample size is 303. The numbers are marginal effects from probit estimates.
The numbers in parentheses are robust standard errors. +, *, and ** indicate
statistical significance at 10%, 5%, and 1 %, respectively. Presenteeism takes 1 if a
respondent answered “yes” to the question “If other people are still in the office, is
it difficult to leave?” and 0 otherwise. Priority of client takes 1 if a respondent
answered “yes” to the question “Even if it was unreasonable, would you rearrange
things at the office to respond to an important client’s urgent request?” and 0
otherwise.

31

Table 6 Adjustment of annual hours worked due to neighborhood effects(1) Reference hours worked = average hours worked by local managers
Dependent variable = ∆(Log annual hours worked)
(1)

(2)

(3)

(4)

0.227+

0.212+-0.054-0.049(0.115)(0.114)(0.134)(0.134)

0.462**

0.451**

0.506**

0.499**(0.175)(0.172)(0.168)(0.166)-0.229**-0.228**-0.257**-0.255**(0.086)(0.084)(0.082)(0.081)0.032**

0.032**

0.036**

0.036**(0.012)(0.011)(0.011)(0.011)ϴϴ0ϴ 1 (Number of years since moving to Europe)2ϴ 2 (Number of years since moving to Europe )3ϴ 3 (Number of years since moving to Europe )ϴ 4 (Number of non-Japanese local friends)

0.090

0.042

(0.072)(0.069)

ϴ 5 (Proportion of work time with non-Japanese)
Job characteristics, Work hour regulations
R-squared

0.549**

0.527**(0.158)(0.159)

yes

yes

yes

yes

0.492

0.495

0.517

0.518

(2) Reference hours worked = counterfactual hours worked
Dependent variable = ∆(Log annual hours worked)
(1)

(2)

(3)

(4)

0.122

0.111

-0.128-0.119(0.104)(0.102)(0.115)(0.114)0.404**

0.381*

0.448**

0.429**(0.152)(0.148)(0.143)(0.140)-0.181*-0.176*-0.210**-0.204**(0.073)(0.070)(0.070)(0.068)0.024*

0.024*

0.028**

0.027**(0.010)(0.009)(0.009)(0.009)ϴϴ0ϴ 1 (Number of years since moving to Europe)2ϴ 2 (Number of years since moving to Europe )3ϴ 3 (Number of years since moving to Europe )ϴ 4 (Number of non-Japanese local friends)

0.115+

0.077(0.063)(0.058)ϴ 5 (Proportion of work time with non-Japanese)
Job characteristics, Work hour regulations
R-squared

32

0.498**

0.465**(0.136)(0.135)

yes

yes

yes

yes

0.451

0.457

0.481

0.484

(3) Reference hours worked = matched hours worked
Dependent variable = ∆(Log annual hours worked)
(1)

(2)

(3)

(4)

0.160+

0.148-0.090-0.086(0.097)(0.094)(0.113)(0.112)0.376*

0.362*

0.379**

0.370**(0.148)(0.144)(0.143)(0.142)-0.175*-0.173*-0.184**-0.183**(0.073)(0.071)(0.070)(0.069)0.024*

0.024*

0.025*

0.025**(0.010)(0.010)(0.010)(0.010)ϴϴ0ϴ 1 (Number of years since moving to Europe)2ϴ 2 (Number of years since moving to Europe )3ϴ 3 (Number of years since moving to Europe )ϴ 4 (Number of non-Japanese local friends)

0.097

0.057

(0.067)(0.062)

ϴ 5 (Proportion of work time with non-Japanese)
Job characteristics, Work hour regulations
R-squared

0.564**

0.540**(0.148)(0.148)

yes

yes

yes

yes

0.457

0.461

0.492

0.493

Notes: The sample size is 251. The numbers in parentheses are robust standard errors.
*, **, and *** indicate statistical significance at 10%, 5%, and 1 %, respectively.

33

Table 7 Robustness check: Accounting for institutional changes
Dependent variable : ∆(Log annual hours worked)
Base
(1)

National holiday(2)

Sick leave

(3)

(4)

(5)

(6)

-0.052* 0.017-0.0230.047-0.054* 0.021(0.025)(0.025)(0.038)(0.026)

Peer/neighborhood variables
Constant term

(0.038)(0.038)

Number of years after moving toEurope-0.004-0.004-0.004(0.007)(0.007)(0.007)

Number of non-Japanese local
friends (M ore than 10 people=1)-0.013-0.013-0.012(0.021)(0.021)(0.021)

Proportion of work time with nonJapanese (0, 0.1, 0.2, … , 0.9 or 1.0)

-0.116*-0.118*-0.126*(0.055)(0.055)(0.056)

Job and HRM characteristics

yes

yes

yes

yes

yes

yes

Estimated year specific effects

yes

yes

yes

yes

yes

yes

R-squared

0.328

0.344

0.328

0.344

0.328

0.346

Notes: 1. The sample size is 251.
2. The numbers in parentheses are robust standard errors.
3. *, **, and *** indicate statistical significance at 10%, 5%, and 1 %, respectively.

34

Table 8 Robustness check: Accounting for heterogeneity
Dependent variable : ∆(Log annual hours worked)
oversea exp.
age dummy
career progression(1)
Peer/neighborhood variables
Constant term
Number of years after moving toEuropex (cross term)
Number of non-Japanese local
friends (M ore than 10 people=1)
x (cross term)
Proportion of work time with nonJapanese (0, 0.1, 0.2, … , 0.9 or 1.0)
x (cross term)
Number of years in total lived
overseas since starting work

(2)

(3)

-0.051* 0.009(0.025) (0.040)-0.004(0.008)-0.000(0.003)-0.000(0.022)-0.013(0.008)-0.111+(0.060)-0.001(0.027)-0.0020.003(0.004) (0.014)-0.049+ 0.005(0.026) (0.045)
0.002(0.008)-0.024(0.015)-0.015(0.026)-0.003(0.046)-0.112+(0.068)-0.031(0.117)-0.025(0.023)Age dummy (under 40=1)

(4)

yes
yes
0.328

yes
yes
0.350

yes
yes
0.331

yes
yes
0.355

Notes: 1. The sample size is 251.
2. The numbers in parentheses are robust standard errors.
3. *, **, and *** indicate statistical significance at 10%, 5%, and 1 %, respectively.

35

(6)

-0.055*(0.026)0.019(0.041)-0.006(0.007)0.031(0.032)-0.017(0.021)0.070(0.081)-0.110+(0.057)-0.143(0.213)0.049(0.036)
yes
yes
0.332

0.031
(0.102)
yes
yes
0.353

0.032
(0.066)

Sentiment of career progression(highly concerned=1)
Job and HRM characteristics
Estimated year specific effects
R-squared(5)

Figure 1 Hours worked and amount of paid leaves taken before and after moving to Europe

Weekly hours worked in EU
60
80

100

(1) Weekly hours worked

40

45 degree line

40

60
80
Weekly hours worked in Japan

100

0Paid leave taken in EU (in days)
10
20
30

40

(2) Amount of paid leaves taken

0

10

20
30
Paid leave taken in Japan (in days)

36

40

5000

(3) Annual hours worked

1000

Annual hours worked in EU
2000
3000
4000

45 degree line

1000

2000

3000
4000
Annual hours worked in Japan

5000

Notes: The size of the circles indicates the frequency. The curve is a 45-degree line.

37

weekly hours worked
40
60
80

100

Figure 2 Distributions of weekly hours worked across countries and nationalities

J before

J afterEU

J beforeUK

J afterEU

Germany

Notes: The lower, middle, and upper line in the boxes indicate the 25th,
50th, and 75th percentile, respectively. The dots indicate outliers.

Figure 3 Adjustment of annual hours worked over time (evolution of the estimated ϴ)ϴ
0.9

Proportion = 0.8

Proportion=0.6

Proportion=0.4

0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
0

1

2
3
Number of years since moving to Europe

38

45