Panel Data Research Center at Keio University
DISCUSSION PAPER SERIES
DP2017-006
December, 2017

Impact of a Wife's Employment on her Husband's Retirement Decision:
Evidence from Japanese Longitudinal Data
Tadashi Sakai*
Akihito Toda**
Atsuhiro Yamada***【Abstract】
Based on a large longitudinal data set on Japanese middle-aged and older individuals, this study
investigates whether women’s labor force participation affects their husbands’ retirement decisions.
Employing a simple fixed-effects model, we found a significant positive effect of wives’ labor force
participation on husbands’ retirement decisions, which seems to imply that a husband’s leisure iscomplementary to that of his wife. However, when employing the instrumental variable fixed-effects
model, which assumes joint decision-making by the husband and wife, we found no significant
effect of the wife’s employment on her husband’s retirement decision, regardless of employment
type.

* Faculty of Economics, Hosei University** Recruit Works Institute*** Faculty of Economics, Keio University

Panel Data Research Center at Keio University
Keio University

Impact of a Wife’s Employment on her Husband's Retirement Decision:
Evidence from Japanese Longitudinal Data

Tadashi Sakai+, Akihito Toda++, and Atsuhiro Yamada+++December, 2017

Abstract
Based on a large longitudinal data set on Japanese middle-aged and older individuals, this study
investigates whether women’s labor force participation affects their husbands’ retirement decisions.
Employing a simple fixed-effects model, we found a significant positive effect of wives’ labor force
participation on husbands’ retirement decisions, which seems to imply that a husband’s leisure iscomplementary to that of his wife. However, when employing the instrumental variable fixed-effects
model, which assumes joint decision-making by the husband and wife, we found no significant effectof the wife’s employment on her husband’s retirement decision, regardless of employment type.
Keywords: Retirement; Middle-aged person; Interdependence
JEL Classification Numbers: J14; J22; J26

I. Introduction
The Japanese government is facing a steady decline in the labor force associated with an aging
population, and is consequently tasked with the urgent need to raise the labor force participation rateof older individuals. What has come to be known is the fact that in many industrialized countries, labor
force participation of older women has driven, not curbed, their husbands’ labor force participation,+

Hosei University, Machida-shi, Tokyo, Japan.
Recruit Works Institute, Chuo-ku, Tokyo, Japan.
+++
Keio University, Minato-ku, Tokyo, Japan.
++

which implies that a husband’s leisure is complementary to his wife’s. According to Schirle (2008),
husbands’ responses to increases in their wives’ labor force participation can account for one-fourth,
one-half, and one-third of the increase in the recent labor force participation of older men in the UnitedStates, Canada, and the United Kingdom, respectively. In contrast to those countries, the extent towhich the wife’s labor force participation determines her husband’s retirement is not yet known forJapan. Figure 1, which corresponds to Figure 1 of Schirle (2008), shows a gradual rise in the labor
force participation rate of Japanese women aged between 55 and 64 years, and a high, stableparticipation rate of Japanese men in the same age range. Almost the same patterns are found for men
and women between the ages of 60 and 64 years. If complementarity of leisure between a husband
and wife plays a key role in the retirement decision, the upward trend of Japanese women’s labor
participation will lead to higher participation by the older men. In contrast, if the income effect isimportant, the rise in the Japanese women’s labor participation rate will serve as a disincentive forolder men to work. The goal of this study is to determine the effect that is dominant in the husband’s
retirement decision, using the largest longitudinal dataset on Japanese middle-aged and older
individuals.
Interdependencies between husband and wife have long been considered a central issue in the
study of labor supply. Theoretically, as remarked above, it is ambiguous whether the spouse’s
employment would encourage or discourage the other spouse’s employment. An impediment to a
precise estimate of the impact is that the husband and wife may jointly make decisions about working,possibly causing a bias in the result of estimation by reduced form equation in which the spouse’slabor supply is treated exogenously. To avoid the bias, several studies exploit exogenous variations inthe spouse’s labor supply, which are generated by legal changes such as regulations on the workweek
and tax reform (Goux et al., 2014; Gelber, 2014). In our analysis, we use health status, the existenceof care need in the household, and pensionable ages as the instrumental variables (IVs) for the spouse’s

2

labor force participation1.
At retirement age, individuals may be more responsive to their spouse’s work-or-leisure choice.
Several studies found a positive correlation between the husband and wife’s retirement decision (Blau,
1998; Gustman and Steinmeir, 2000). Further evidence implicates asymmetric complementarities ofleisure, that is, men are very responsive to their wives’ employment, while women are not as
responsive to their husbands’ employment (Coile, 2004). Our study contributes to the understandingof the interdependencies between Japanese middle-aged and elderly married couples’ work decisions.
To the best of our knowledge, ours is the only study to xplore such interdependencies by using large
longitudinal dataset on Japanese middle-aged and older individuals, and the IV technique.
We found significant positive effects of the wife’s labor force participation on her husband’s
participation when employing the simple fixed-effects model, which seems to imply that the husband’s
leisure is complementary to his wife’s. When the IV fixed-effects model is employed, however, theeffect of the wife’s employment on the husband’s employment is not significant regardless of
employment type and firm size.
The remainder of this paper is organized in the following manner. Section II presents themethodology used to examine the impact of the wife’s employment on her husband’s retirement
decision. Section III describes the dataset used in the analysis. Section IV provides the results of
estimation. Section V concludes.

II. Empirical Model
To examine the interdependencies in spousal labor supply, we estimate the following IV fixedeffects model:
1

Yamada and Sakai (2016), whose study is based on the same dataset as the present analysis, find
only women are less likely to have a job when they have a frail parent. Fukahori et al. (2015) alsofind that the incidence of a frail individual in the household has a larger impact on women’s
employment than on men’s employment.
3

LHit  LWit  X itH   vt  ui  
HWwhere, by Lit and Lit , we denote the employment status for year t for ith husband and ith wife ,respectively, and whereLit  1 indicates that the individual is employed. LWit is an endogenous

variable for which we exploit wife’s health condition, the existence of care need in the household, andthe pensionable ages as IVs. The health status of the wife consists of three dummy variables thatindicate health status is “very good,” “good,” and “fair,” respectively. The existence of care need in
the household is a dummy variable that equals one if the respondent is living with a family member
who needs care. Two pensionable ages are used as IVs: pensionable age for basic pension andpensionable age for second-tier pension, both of which have been raised since 2000s according to theHschedule. The variable X it includes variables regarding age, health condition, homeownership, theamount of deposits and housing loan of the husband.
We conduct the IV fixed-effects model at the expense of abandoning nonlinear specification todeal with unobserved heterogeneity2. We compare the result of the IV fixed-effects model with theresult of the simple fixed-effects model so as to distinguish the role of IVs. Standard errors are
clustered by individual, as including fixed effects is not enough for controlling for all the within-cluster
correlation of the error (Cameron and Miller, 2015).

III. Data
The data used to estimate the model described in Section II come from the Longitudinal Survey ofMiddle-aged and Elderly Persons (LSMEP), a nationally representative sample of middle-aged andelderly individuals who were aged between 55 and 59 years at the end of October of 2005. LSMEP is

2

Following Schirle (2008), we also estimated the recursive bivariate probit model for a nonlinear
specification to confirm the robustness of our results, and found almost the same result as that of theIV fixed-effects model, though these are not shown in this paper.
4the largest longitudinal survey of middle-aged and elderly individuals in Japan, and has been
conducted annually by the Japanese Ministry of Labour, Health and Welfare since 2005. This survey
included 34,240 respondents in the initial year, and approximately 70% of those respondents remainedin the survey as of 2012. The survey provides a rich set of information about the respondents’ family
background, health status, employment status, and financial situations. Since our main interest is a
spouse’s employment status, we picked up households with both husband and wife as respondents andmatched their information to create sub-samples of couples. This matched sub-sample isapproximately 40% of the whole sample. Although our base estimation relies on the first eight waves,the IV estimates are based only on the fourth through the eighth waves as the question on whether
there is a fragile individual in the household starts with the fourth wave. The descriptive statistics ofthe dataset for our estimation are shown in Table 1.

IV. Results
The estimation results of the fixed-effects model are presented in Table 2. In column (1), which shows
the result of the estimation based on all couples, we find that the coefficient of the wife’s employment
is positive and statistically significant. This result seems to imply that a husband’s and wife’s leisure
are complementary to each other. It is also found that middle-aged and elderly men are more prone towork if they are healthier, if they do not own houses, and if they are in the middle of paying back theirhousing loans.
We also estimated the models on the basis of the sample respondents whose age is over 60 years(column (2) in Table 2), since a focus of the present study is to investigate whether elderly men remainin the labor market beyond the mandatory retirement age3. In this case, too, positive and statisticallysignificant coefficient of the wife’s employment was observed.

3

Japanese firms are prohibited from setting the mandatory retirement age below 60 years old.
5

The result of the estimation based on couples where the wife is older than the husband is presented
in Column (3) of Table 2. Among those couples where the wife enters the retirement process ahead of
the husband, the wife’s employment status is considered to be more exogenous for the husband’s
retirement decision. We found that the coefficient of the wife’s employment is positive, but
insignificant in this case.
Japanese wives often quit their jobs upon marriage and continue to be housewives in the years that
follow. In such cases, the husband may not consider his wife’s employment status in making his
retirement decision. Hence, we re-estimate the same model limiting the sample to those husbands
whose wives are employed at the age of 59, so as to capture the decision-making of those who maychange the timing of their retirement depending on their wives’ employment. The results are presented
in column (4) of Table 2, where it is observed that the coefficient of the wife’s employment issignificantly positive, and much larger than the case of all couples.
To capture the fact that there is a substantial difference in the retirement process between
employees and self-employed workers, we divide the sample by the husband’s employment type atage of 59 (columns (5) and (6) in Table 2)4. Column (5) shows the result of estimation conducted ona sub-sample that consists of husbands who were regular workers at the age of 59 and whose wife hada job at the age of 59, whereas the result of estimation based on the sub-sample of those husbands who
were self-employed at the age of 59 is shown in column (6). In both columns, we found a significant
positive effect from the wife’s employment.
The estimation results of the IV fixed-effects model are presented in Table 3, in which each column
corresponds to each specification of Table 2. We find that the IVs are not weak in most of thespecifications. However, the results mark a sharp contrast with the results shown in Table 2 as we find

4

Usui et al. (2015) found that Japanese workers in salaried jobs gradually move to part-time workor retire after beginning to receive pension benefits, while self-employed workers neither retire nor
reduce their working hours after beginning to receive pension benefits.
6

that all the estimated coefficients on the wife’s employment from the IV fixed-effects model are
insignificant5.
Although not shown in Table 3, we also estimated the IV fixed-effects model on two additional
sub-samples: the first, where husbands were non-regular workers at the age of 59, and the second,
where husbands were employed as non-regular workers in a company with less than 300 workers.
Those who consist of the above sub-samples are considered to have the relative freedom of choosing
the timing of retirement. Even among them, however, we found no significant coefficient on wife’s
employment6.

V. Conclusion
From the results of the IV estimations, we found that a Japanese worker’s retirement decision is
independent of the spouse’s employment. This result was in contrast with the results from theestimations that treat the spouse’s employment as exogenous. The finding based on the IV model isrobust regardless of employment type and firm size, and reveals that husband and wife indeed makedecisions about retirement jointly. Although the findings are inconsistent with similar existing studies
in Europe and the United States, in which complementarity of leisure between a husband and wife has
been found, our findings may imply that, in Japan, factors such as mandatory retirement age, post
retirement employment, and health may be more important conditions that affect retirement timing.

5

Assuming that husbands who were self-employed at the age of 59 rarely receive benefit of secondtier pension, the pensionable age for second-tier pension as an IV is excluded from the first-stage
equation for the estimation of column (6) in Table 3.
6
We also found that even in the sample where husbands work in firms that do not have a mandatory
retirement age, the estimated coefficient on the wife’s employment is insignificant.
7

Acknowledgement
This work was supported by Health Labour Sciences Research Grant（厚生労働科学研究費補助金（政策科学総合研究事業（政策科学推進研究事業））「就業状態の変化と積極的労働市場政策に関する研究」（H26-政策-一般-003，研究代表：慶應義塾大学・山本勲）. We are permitted to use theLongitudinal Survey of Middle-aged and Elderly Persons by Ministry of Health, Labour and Welfare
under Article 33 of the Statistics Act. We would like to thank Yoshio Higuchi and Isamu Yamamoto
for their helpful comments. We take full responsibility for any remaining errors.

8References
Blau, D., (1998) “Labor Force Dynamics of Older Married Couples,” Journal of Labor Economics
16(3): 595-629.
Cameron, C., and D. MIller (2015) “A Practitioner's Guide to Cluster-Robust Inference,” Journal of
Human Resources 50(2): 317-372.
Coile, C., (2004) “Retirement incentives and couples’ retirement decisions,” B.E. Journal of Economic
Analysis & Policy 4(1): 1–30.
Fukahori, R., Sakai, T., and K. Sato (2015) “The Effects of Incidence of Care Needs in Households on
Employment, Subjective Health, and Life Satisfaction among Middle-aged Family Members,”
Scottish Journal of Political Economy, 62(5):518-545.
Gelber, A., (2014) “Taxation and the Earnings of Husbands and Wives: Evidence from Sweden,”
Review of Economics and Statistics 96(2): 287-305.
Goux, D., Maurin, E., and B. Petrongolo (2014) “Worktime Regulations and Spousal Labor Supply,”
American Economic Review 104(1): 252-76.
Gustman, A., and T. Steinmeier (2000) “Retirement in Dual-Career Families: A Structural Model,”Journal of Labor Economics 18(3): 503-545.
Schirle, T., (2008) “Why Have the Labor Force Participation Rates of Older Men Increased since theMid-1990s?” Journal of Labor Economics Vol. 26, No. 4, pp. 549-594.
Yamada, A., and T. Sakai (2016) “Labor Supply and Income Reduction of Middle- and Old-Aged
People in Japan with a Parent in Need of Long-Term Care” Economic Analysis 191: 183-212 (inJapanese).
Usui, E., Shimizutani, S., and T. Oshio (2016) “Are Japanese Men of Pensionable Age Underemployedor Overemployed?” Japanese Economic Review 67(2): 150–168.

9

Figure 1. Participation rates of individuals aged 55–64, by sex
0.90

0.80
Men(55-64)
Women(55-64)
Men(60-64)
Women(60-64)

0.70

0.60

0.50

0.40

0.30
1973

1977

1981

1985

1989

1993

1997

2001

2005

2009

Source: Statistics Bureau of Japan, Labour Force Survey

2013

Table 1. Descriptive Statistics
N. of Obs.
62,28962,28962,28962,28962,28962,28962,28962,28936,53362,28962,28962,28962,28962,28962,289Husband is having a job
Health condition of husband: Very good
Good
Fair
Living in a privately owned house
In the middle of paying back a housing loan
Amount of deposits (ten-thousand yen)
Non-answer to question on amount of deposits
Living with persons who need care
Wife is having a job
Health condition of wife:
Very goodGood
Fair
Wife's age is over pensionable age for basic pension
Wife's age is over pensionable age for second-tier pension

11

Mean
0.878
0.064
0.318
0.424
0.912
0.309
887.550
0.330
0.091
0.630
0.052
0.305
0.453
0.114
0.244

Std. Dev.
0.327
0.244
0.466
0.494
0.284
0.462
1,621.514
0.470
0.287
0.483
0.222
0.460
0.498
0.317
0.429

Min
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0

Max
1
1
1
1
1
1
47,000
1
1
1
1
1
1
1
1

Table 2 Effects of Wife's Employment on Husband's Retirement: Fixed-effects Model (Linear Probability Model)
(1)
(2)
(3)
(4)
(5)
(6)
Husbands whose wives were
employed at the age of 59
Husbands Husbands
who were who wereType of couple:
selfregular
Husbands
workers at employed
Husbands who are
the age of at the age
younger
aged 60
of 59
59
All
and older their wives
Wife is having a job
0.023*** 0.025***0.010
0.046*** 0.038*** 0.055***(0.004)(0.007)(0.008)(0.004)(0.007)(0.006)
Husband's health condition: Very good
0.008
0.021*
0.018
0.010-0.0180.023***(0.006)(0.012)(0.014)(0.007)(0.012)(0.009)Good
0.020*** 0.026*** 0.024*** 0.017***-0.0050.019***(0.004)(0.008)(0.009)(0.005)(0.008)(0.006)Fair
0.025*** 0.030*** 0.030*** 0.024***0.003
0.017***(0.004)(0.007)(0.008)(0.004)(0.007)(0.005)
Living in a privately owned house-0.049*** -0.054**
0.021-0.029**-0.012-0.019(0.010)(0.022)(0.023)(0.012)(0.022)(0.015)In the middle of paying back a housing loan
0.034***
0.012
0.032*** 0.033*** 0.029***-0.011*(0.004)(0.010)(0.010)(0.005)(0.008)(0.006)
Amount of deposits (ten-thousand yen)
-0.000*** -0.000** -0.000*** -0.000*** -0.000***-0.000(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)Non-answer to question on amount of deposits-0.004-0.0050.015*-0.006-0.006-0.005(0.004)(0.008)(0.008)(0.004)(0.007)(0.005)Constant
0.868*** 0.621*** 0.943*** 0.842*** 0.605*** 0.881***(0.015)(0.025)(0.042)(0.018)(0.076)(0.055)Observations
62,28926,492
9,379
43,382
17,796
9,509
R-squared
0.101
0.077
0.066
0.089
0.166
0.045
Number of id
9,076
6,676
1,382
6,228
2,329
1,273
Note:
The dependent variable is a dichotomous variable which indicates one if a husband is having a job.
12
All models include dummy variables for husband's age and survey year as independent variables.
Cluster-robust standard errors are in parentheses. *** p<0.01, ** p<0.05, * p<0.1.

Table 3 Effects of Wife's Employment on Husband's Retirement: IV Fixed-effects Model (Linear Probability Model)
(1)
(2)
(3)
(4)
(5)
(6)
Husbands whose wives were
employed at the age of 59
Husbands Husbands
who were who wereType of couple:
selfregular
Husbands
workers at employed
Husbands who are
the age of at the age
aged 60
younger
of 59
59
All
and older their wives
Wife is having a job-0.014-0.069-0.233-0.0220.033
0.047(0.077)(0.105)(0.161)(0.069)(0.103)(0.127)
Husband's health condition: Very good
0.013
0.033**
0.021
0.013-0.0090.024*(0.010)(0.014)(0.021)(0.011)(0.019)(0.014)
Good
0.022*** 0.035***
0.027*
0.015**
0.003
0.018(0.007)(0.009)(0.016)(0.007)(0.013)(0.012)
Fair
0.025*** 0.034***
0.027*
0.022***
0.008
0.018*(0.006)(0.008)(0.014)(0.007)(0.011)(0.010)
Living in a privately owned house-0.041**-0.0350.035-0.033-0.008-0.032(0.020)(0.031)(0.059)(0.026)(0.046)(0.054)In the middle of paying back a housing loan
0.029***
0.014
0.043** 0.033*** 0.050***-0.018(0.009)(0.014)(0.021)(0.010)(0.017)(0.014)
Amount of deposits (ten-thousand yen)
-0.000*** -0.000** -0.000** -0.000*** -0.000**-0.000(0.000)(0.000)(0.000)(0.000)(0.000)(0.000)Non-answer to question on amount of deposits-0.005-0.0090.031**-0.005-0.006-0.002(0.006)(0.009)(0.013)(0.007)(0.012)(0.008)Observations
R-squared
Cragg-Donald Wald F stat.
Hansen J stat.
Number of id

36,3390.069
27.716
11.684**
7,814

22,8030.058
16.7389.607*
5,781

5,434-0.013
5.900
2.026
1,175

25,4200.055
29.8559.083
5,464

10,8420.109
15.93310.771*
2,256

5,711
0.039
3.505
6.055
1,227

Note:
The dependent variable is a dichotomous variable which indicates one
13 if a husband is having a job.
All models include dummy variables for husband's age and survey year as independent variables. Columns (2)-(6) are the results of
estimations which rely on 4th-8th waves.
Cluster-robust standard errors are in parentheses. *** p<0.01, ** p<0.05, * p<0.1.