Discussion Papers In Economics
And BusinessSpousal gaps in age and identity, and their impact
on the allocation of housework
Eiji Yamamura
Yoshiro Tsutsui

Discussion Paper 18-29

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANSpousal gaps in age and identity, and their impact
on the allocation of housework
Eiji Yamamura
Yoshiro Tsutsui

Discussion Paper 18-29

October 2018

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANSpousal gaps in age and identity, and their impact on the allocation of housework
Eiji Yamamura ∗Seinan Gakuin University, Japan
Yoshiro Tsutsui †Konan University, Japan
ABSTRACTThis study investigates how spousal age gaps influence the allocation of housework
between husbands and wives. Further, we consider the identity formed as a result of
respondents’ family backgrounds by specifically exploring the effects of the age gaps
between the respondents’ parents.
We initially collect an individual-level panel dataset covering the periods before andafter marriage, by monthly surveys of unmarried persons in the initial period prior to
marriage, then the three-year period that follows. After controlling for individual- andtime period-fixed effects, the key findings are as follows: (1) after marriage, women older
than their husbands tend to become burdened with a larger amount of housework, and the
spousal gap effect increases as the marriage duration increases; (2) women with mothers
older than their fathers tend to assume a larger allocation of the housework as the marriage
duration increases; and (3) the age gap hardly affects the men’s allocation of housework,
although men with a full-time working mother at age 15 assume a larger allocation ofhousework as the marriage duration increases.

JEL classification: J12; J16; D13
Keywords: Spousal age gaps; housework allocation; intra-household bargaining∗

Department of Economics, Seinan Gakuin University, 6-2-92 Nishijin, Sawara-ku, Fukuoka,
814-8511, Japan, yamaei@seinan-gu.ac.jp†
Faculty of Economics, Konan University, 8-9-1 Okamoto, Higashinada-ku, Kobe, Hyogo, 6580079, Japan, tsutsui@center.konan-u.ac.jp
11. Introduction
The allocation of housework between spouses is increasingly important in considering
how the spousal relationship influences economic efficiency in the labor market. The
bargaining model assumes that such characteristics as education, weight, and age—which
are highly valued in marriage markets—influence an individual’s intra-householdbargaining power (e.g., Oreffice and Quintana-Domeque, 2012; Grossbard andMukhopadhyay, 2017). The differences in an individual’s characteristics relative to theirspouse’s generate differences in bargaining power within a couple, and consequently
influence the partner-selection process as well as the household specialization after
marriage. 1 For instance, economic researchers have constructed theoretical models basedon assumption that men prefer younger women (e.g., Siow, 1998; Diaz-Gimenez andGiolito, 2013) 2. Accordingly, a couple’s age difference is a key factor in decision-making
about marriage and marital life. 3 In the real world, the number of “toy boy” marital
couples—in which the female partner is at least five years older than her male partner—
have substantially increased since the 1970s in the United States and United Kindom.
Coles and Francesconi (2011) attempted to explain this phenomenon by considering amechanism in which a wife older than her husband earns more to compensate for the
younger husband’s disutility; these authors assumed that men and women both preferyounger spouses. 4
1

However, gender differences in such developed countries as Japan have gradually disappearedin the marriage market (Yamamura and Tsutsui, 2017).
2
Fecundity declines more rapidly for women than men, which results in the genders’ differencein preferences regarding the age differences within a couple (Diaz-Gimenez and Giolito, 2013).
3
Booth and Kee (2009) examined the spousal age gap’s effects on fertility, although this gap
hardly had an influence.
4
Bloemen and Stancanelli (2015) used French data to discover that larger spousal age
differences are positively associated with couples in which only the wife works, but negatively
with dual-earner households, in which the wife out-earns the husband.
2

Researchers disagree about the optimal spousal age gap to maximize marital gains.
The gains from marriage become the largest in older husband-younger wife pairs, which
parallels the positive “traditional family” perspective (Bergstrom and Bagnoli, 1993). In
contrast, other studies report that similarly aged couples experience the largest marital
gains (Choo and Siow, 2006; Mansour and McKinnish, 2014). Analyses incorporating
online and speed-dating data provided evidence that both men and women prefer partners
similar in age (Belot and Francesconi, 2013). Further, Groot and van den Brink (2002)
proposed two different hypotheses about the reasons for marriage—the financial supportand social equality hypotheses—which focus on the fact that the husband is typicallyolder and more educated than his wife. The authors use panel data from the Netherlands
to demonstrate that this tendency is explained by the financial support hypothesis.
Gender identity theory explains gender differences in the allocation of time between
spouses if other things are equal (Akerlof and Kranton, 2000). 5 This is partially why
women are less likely than men to be full-time workers, even when her labor quality ishigh enough to work full-time. According to Bertrand et al. (2015), for couples in which
the wife’s potential income is likely to exceed the husband’s, the wife is less likely to bein the labor force, and earns less than her potential income even if she does work. Further,
the wife spends more time on housework than her husband even in couples in which thewife earns more. Empirical analyses have revealed that women are inclined to spend moretime on typically “female” tasks, such as cooking and cleaning (e.g., Hersch, 2009;
Hersch and Stratton, 2002). 6 Regarding gender identity formation, children learn fromtheir parents to form their world views and social value, while individual preferences aretransmitted in communities through families (Bisin and Verdier, 2001; Bisin et al., 2004).
Booth and Kee (2009) investigate the family-specific “cultural transmission” to find thatthe size of the woman’s family of origin is positively associated with complete fertility inher destination family. Moreover, men with working mothers tend to prefer working
wives (Kawaguchi and Miyazaki, 2009), and thus, the wives of men with working

5

Existing works use data from Western countries—such as the United Kingdom (Booth and
Van Ours, 2008), Australia (Booth and Van Ours, 2009) and the Netherlands (Booth and Van
Ours, 2013)—to empirically test the identity theory and investigate gender differences in therelationship between part-time work and subjective well-being.
6
However, in such developed countries as Japan, gender differences have graduallydisappeared from the marriage market (Yamamura and Tsutsui, 2017).
3

mothers are significantly more likely to work (Fernandez et al., 2004). In the pre-marriage
period, family characteristics also influence the selection of a marital partner; individuals
marry partners who share the same cultural and social backgrounds (Bisin and Verdier,
2000).
This paper essentially assumes that both genders value a degree of youth in themarriage market, which therefore increases an individual’s intra-household bargaining
power. 7 Further, we added an identity factor to examine how the spousal age gap impacts
the allocation of housework between husband and wife. Further, we also consider theidentity formed as a result of the family background by exploring the effects of thedifferences in age between the respondent’s parents. This analysis involves initiallycollecting an individual-level panel dataset throughout Japan, and covering the periods
before and after marriage through monthly surveys of unmarried persons in the initialperiod, then tracking them for three years after. Compared with existing works (e.g.,
Booth and Van Ours, 2008; 2009; 2013; Grossbard et al., 2014; Grossbard andMukhopadhyay, 2017), our original data is advantageous, as it enables us to collectinformation about the allocation of housework and the timing of such events as marriage,
cohabitation, pregnancy, and childbirth. Additionally, frequent surveys in this short period
are less likely to suffer from changes in other factors. We also obtain data about the
respondent’s characteristics as well as those of his or her partner to use information
regarding couple and their parents. This novel data allows us to consider the gender
identity’s role and how the difference in age within a couple influences their allocation ofhousework.
This paper’s major findings are as follows: After marriage, women older than theirpartners tend to burden with a larger amount of housework, and the age gap’s effectincreases as the marriage duration increases. Additionally, the age gap between the
respondents’ mother and father also caused female respondents to increase their allocationof housework; this effect also increases as the marriage duration increases. This paper
contributes to current literature by providing evidence that women are primarily affected

7

In a study of obesity and its effect on the labor market (Oreffice and Quintana-Domeque,2012; Grossbard and Mukhopadhyay, 2017), it was found that female thinness is valued in
marriage markets, which increases her intra-marriage bargaining power (Vaillant and Wolff,2011).
4

by a couple’s age gap and the identity formed by learning from one’s parents.
The remainder of this paper is organized as follows: Section 2 proposes testable
hypotheses, while Section 3 explains the data and the empirical method used. Section 4
presents the estimation results and their interpretation, and Section 5 concludes.

2. Hypotheses

Household decision-making is likely to be determined by joint decision-making, andin instances of partners’ conflicting preferences, the outcome might depend on thepartner’s bargaining power. This power is partially determined by the couple’s differencesin characteristics. For instance, younger people are more valuable in the marriage market,
which increases his or her bargaining power relative to his or her spouse (Coles andFrancesconi, 2011). A mechanism seems to exist in that the older person is likely toassume a larger allocation of housework to compensate for their disutility toward the
younger spouse. Thus, we propose the following Hypothesis 1:
Hypothesis 1: Individuals older than their spouses have weaker bargaining power,
leading them to assume a larger allocation of housework.

However, the spousal age gap’s effects depend on gender identity. According to
Akerlof and Kranton (2000, p.747), “the husband loses [his] identity when he doeshousework and when his wife earns more than half the household income. Equality ofutility is restored when the wife undertakes more housework than her husband.”In

contrast, the wife loses her identity when she does not do housework and earn more thanhusband. Therefore, the age gap’s effect on the amount of housework differs between
genders. Hence, we propose the following Hypothesis 2:
Hypothesis 2: The age gap has a larger effect on women than men regarding theallocation of housework.

Further, the difference in bargaining power between the spouses’ parents possibly
formed their children’s identity about the allocation of housework within a couple. If
Hypothesis 1 and Hypothesis 2 hold true, a woman with a mother older than her father
has grown up in a family in which her mother assumes a larger amount of housework than
5

families with a mother younger than the father. If so, the woman will follow her motherand assume a larger amount of housework than other women. Accordingly, we propose
the following Hypothesis 3:
Hypothesis 3: A woman with a mother older than her father tends to assume a larger
amount of housework.

The spousal age gap seems to be a key factor in selecting a partner, which
subsequently influences the allocation of housework even if bargaining power does notexist. If so, the allocation of housework might be determined before marriage. Existing
works argue that couples who marry with imperfect information can change the benefitsof marriage, as any benefits could not be predicted at the time of the marriage (Becker,
Landes, and Michael, 1977; Weiss and Willis, 1997). Therefore, this imperfect
information might cause the marital couple to make decisions about the allocation ofhousework through intra-household bargaining. As we consider it crucial to identify theage gap’s effects, the primary problem is as follows: If women married to younger
husbands initially burden them with a greater allocation of housework, does this larger
allocation of housework persist, increase, or decrease over the duration of the marriage?
If the allocation of housework does not change, this is not the outcome of intra-householdbargaining. Thus, Hypothesis 4 is proposed:
Hypothesis 4: The effects of the spousal age gap increases as the marital duration
increases.

3. Methods and Data

3.1. Data
We collected our data through Internet surveys to realize our project objectives;
specifically, we commissioned INTAGE Communications Inc., a Japanese market
research company with sufficient experience in conducting academic Internet surveys.
INTAGE conducted the Internet surveys under the direction of the research team,primarily composed of researchers from Osaka University. The relationship within acouple is likely to change, and depends on various life events, such as marriage or having
a child. We aimed to scrutinize these effects by monthly surveys, which pursued the same6

people planning to get married in the near future to their current significant other.
Specifically, monthly Internet surveys were conducted from March 2012 to March 2015,
or a total of 37 waves during this period, and these surveys gathered individual-level panel
data covering all regions of Japan. As some individuals from the initial survey dropped
out of the sample during the three-year survey period, we added new individuals annually
to keep sample size large enough to conduct a statistical estimation; the response rate wasapproximately 60%.
This paper examines how the spousal age gap influences the allocation of housework,and how this effect changes before and after marriage. Spouses are less likely to live
together before marriage, and thus, partners are less likely to influence the allocation ofand time spent on housework. Cohabitation substantially forms a household, even if they
are not yet married. Accordingly, we considered marriage and cohabitation to be athreshold to change their allocation of housework. Therefore, the surveys’ targets werelimited to men and women who have been unmarried or were not cohabitating at the timeof the initial survey, and have since married or cohabitated during the studied period.
Naturally, older individuals were not included; participants’ ages ranged between 17 and51 years.
The questionnaires included various items querying the respondents’ individual
socioeconomic characteristics, such as whether the couple lived together, their marital
status, education, age, sex, household income, mother’s work status when the respondent
was 15 years old, housework hours, and the allocation of housework. Further, we also
obtained detailed characteristics about his or her partner at the initial survey—although
we did not directly ask the partner—including the respondent partner’s education, age,and parents’ ages. We then used the survey panel data to explore how the age gaps withina couple impact time allocation, both before and after a marriage. The sample used forour estimation consists of 300 individuals who frequently appeared in surveys at different
time points. Further, a sample size of over 5,800 was used for the estimations, as this data
set allows us to conduct a fixed-effects analysis to identify within-marriage changes in
the allocation of household work over time; this contrasts a cross-sectional analysis thatcompares recently married couples to those with a longer marital duration. A substantial
advantage of our data is that it enables us to ascertain whether the allocation of housework
within a couple evolves differently over the duration of the marriage for differently aged7

couples compared to similarly aged couples.
Figure 1 illustrates how the observations changed, both before and after a marriage or
cohabitation. 8 The zero on the horizontal line indicates the time point at which
respondents got married or began to cohabitate with their partner. If respondents began
cohabitating before marriage, we define zero as the point at which cohabitation began,even if the couple is not yet married. Positive values are the months after the marriage or
cohabitation, while the negative values are the months before it. This demonstrates thatthe observations after marriage (or cohabitation) are larger than before it, although thenumber of the samples before is considered large enough to compare the situations before
and after.
Table 1 presents the definitions of the variables used in this research and their meanvalues for the questionnaire respondents, but not their spouses. We can observe from
Table 1 that the spousal age gap reveals positive and negative values for men and women,
respectively. This seems to reflect that older men tend to marry younger women. Let us
consider the age-gap distribution within a couple, as illustrated in Figure 2. The
respondent’s partner is the same for the studied period in the sample, and thus, the gaps
do not change during the period. A zero indicates that the age values are the same withina couple. Figure 2 demonstrates that the percentages of couples with no age gap are higher
than the other groups for both genders. However, the age difference between men andwomen is not symmetrical, with a higher percentage of men than women that are older
than their partners.
Table 1 also reveals the age gaps regarding the respondents’ and partners’ parents,
which implies that the father is older than the mother. These indicate that the husbands’
ages are greater than the wives’, which is generally observed in existing works (e.g.,
Grossbard et al., 2014; Lee and McKinnish, 2018). Regarding the respondent parents’ age
gaps, the gap in the men’s sample is measured by the equation “(father’s age – mother’sage),” while the gap in the women’s sample is measured by “(mother’s age – father’sage).” This is because we aim to explore the effects from parents with the same gender as
the respondent and the latter’s relationship to the different gendered parent to consider

8

This includes observations not used for the regression estimation, as some independent
variables are not obtained.
8

how the respondent’s gender identity formed. Specifically, in the men’s sample, we
compare the age gap (his age – his wife’s age) with his parents’ age gap (his father’s age– his mother’s age). In the women’s sample, we compare the age gap (her age – herhusband’s age) with her parents’ age gap (her mother’s age – her father’s age). The parents’
gap demonstrates the positive and negative values for the men’s and women’s samples,
respectively. The partner parents’ gaps also suggest the same results. Collectively, thisindicates that the fathers are older than the mothers. Therefore, the respondents inherited
their spousal age gap patterns from their parents.
The questionnaire also asks about the respondents’ hours spent on housework.
Additionally, seven specific items query the allocation of housework hours between
spouses. We can use this data to estimate the housework hours of respondent husbands
and wives, although we do not ask how housework hours are allocated to specifichousework activities. Aside from questions regarding housework hours, we also ask about
the allocation of specific housework within a household—divided into “respondent’s
share,” “partner’s share,” and “others’ share” categories—to obtain information regarding
the respondent’s share of seven housework categories. 9 We aggregate this information to
calculate the respondent’s share of total housework, although we exclude childcare fromour definition of “housework” because the couples in our sample did not have children
before marriage or cohabitation. 10

Table 1 indicates women spent on average 135.7 minutes on housework per day, or
more than twice as long as men. The housework allocation indicates that women areburdened with 71% of the housework, while men only assume approximately 39%.
Figure 3 illustrates the average housework time in the sample period, while Figure 4
indicates the allocation (%) of housework. The horizontal line is defined the same as in
Figure 1. We consider that the sample size is not large enough to suggest unbiased results
when observations are less than 20 in each time period. Thus, we restricted the time period9The seven categories are “cooking,” “clear the dishes from the table,” “cleaning andsweeping,” “washing,” shopping,” “taking out the garbage,” and “childcare.”10
Grossbard et al. (2014) also exclude childcare from our definition of “housework” because
previous works have reported that parents found spending time with their children moreenjoyable than other kinds of housework (Kahneman et al., 2004; Kahneman and Krueger,2006).
9to those that contain more than 20 observations to illustrate Figures 3 and 4. A cursory
examination of Figure 3 suggests that women’s housework time is consistently longer
than men’s, even in the pre-marriage period. However, the gap distinctly widened after
marriage or cohabitation, as women’s housework time remarkably increased while men’shousework time increased slightly as time passed. Regarding Figure 4, the housework
allocation gap between men and women widened over time, similar to Figure 3. However,the former differs from Figure 3, in that the share of housework at the initial time point isalmost same between partners. The women’s allocation of housework then increased after
marriage, while men’s decreased over the course of time. Our interpretation reveals that
although men’s time spent on housework increased, women spent predominantly moretime than men; thus, men’s allocation of housework decreased. Collectively, a division oflabor within a household can be observed after marriage (or cohabitation). Ourinterpretation in Figures 3 and 4 illustrates that before marriage or cohabitation, men who
have lived alone tend to do housework for themselves; thus, the allocation increased eventhough they have not spent substantial time on housework.
Individuals learn much from their parents in their childhood, and are consequently
influenced by the marital relationship between their parents. For instance, their parents
can impact their selection of a marital partner. As we have observed in Table 1,
respondents’ and their partners’ fathers are older than their mothers, on average. We moreclosely examine this by confirming the correlation between the parents’ and respondents’
spousal age gaps. Table 2 indicates that the respondents’ spousal age gap is positively
correlated with their and their partner’s parents’ age gap. Therefore, the selection of amarital partner seems to be influenced by the couple’s parents, who provide a spousal
model for their children that inevitably influences the child’s selection of marital partner
later in life. Consequently, similar spousal relationships occur. Further, a noteworthy,
positive correlation can be observed between the respondent parents’ age gap and that of
their partner. This indicates that respondents select partners with similar family
backgrounds, reflected in the spousal age gap; thus, the marital couple shares an identity
formed through their parents’ marital relationship.
We then confirm the inference that older spouses can compensate for their disutility
by assuming a larger allocation of housework. Table 3 compares the housework time
before and after the marriage, according to groups divided by the spousal differences in10

age. The upper part of the panel illustrates the men’s sample, which indicates that
respondents have spent a longer time on housework after marriage than before marriage
in all groups. Further, in the group with men older than their wives, the men spent 29
minutes longer on housework after the marriage than before. The differences are 13 and3 minutes for the same age groups and groups in which the husband is younger than his
wife, respectively. Hence, a larger difference in housework hours can be observed as
men’s ages are relatively higher than their wives’. The same tendency is also observed
for the women’s sample in the lower part of the panel. However, the women’s level oftime is remarkably longer than the men’s. Additionally, the difference in time between
the periods for women is remarkably longer than for men.
Similarly, Table 4 compares the allocation of housework, although it differs from
Table 3 in that the former notes a lower allocation of housework for men after marriage
than before. However, the difference decreases if the man is relatively older than his wife,
which implies that men relatively older than their wives are more likely to carry theburden of housework after marriage. Alternatively, women assume a larger burden ofhousework after marriage than before. The increase in the wife’s allocation is 16% for thegroup of women older than their husbands, which is a larger share than in other groups.
Collectively, the observations of Tables 3 and 4 are consistent with the inferences statedin Hypotheses 1 and 2.
We then scrutinize how marriage changes housework time and allocation bydecomposing this into the outcomes of partner selections and intra-household bargaining.
The following section introduces a simple methodological framework to meet thisobjective.

3.2. Methods

We test our hypotheses by exploring how the spousal age gaps among respondents
and their parents impact hours of housework. The estimated function takes the following
form:Houseworkit=α1Gap of agei *Married it+α2Gap of agesi*Marital duration it +α3Marital duration it
11

+α7Parents’ gap of ages i *Married it+α8Parents’ gap of agesi* Marital duration it+α9Partner’s parents’ gap of agesi*Married it+α10 Partner’s parents’ gap of agesi*
Marital durationit++α11 Working motheri*Married it+α12 Working motheri*Marital
durationit+ Xit + ki + et+ u it,

where Houseworkit represents the minutes of housework per day (or the allocation ofhousework) for respondent i and time period t, and α represents the independent variables’
marginal effect. The panel data feature allows us to control for the time-invariant,individual-fixed effect ki, and the time period effect et, while u it, is the error term.
As described in Table 1, these gaps are calculated as the “(respondent’s age – theirpartner’s age).” As proxies for bargaining power, we use the age differences between
partners, expressed as Gap of age (Booth and Kee, 2009). The spousal age gap’s effects
can be decomposed into the partner selection and bargaining effects. The key variables
are the cross-terms of the spousal age gaps and a dummy for getting married (orcohabitation): Gap of ages*Married. This effect represents the partner selection effect,
rather than the bargaining effect captured by Gap of ages*duration; specifically, younger
men tend to marry girlfriends who tend to assume a larger burden of housework tocompensate for his disutility. Older women who prefer housework as part of their gender
identity might marry boyfriends who prefer she assume housework responsibilities tocompensate for his disutility in having an older wife. Namely, the partner selection effectis possibly reflected in how the spousal gap influences the housework allocation between
husband and wife. Thus, it is necessary to decompose the spousal age gap’s effect into thepartner selection effect before marriage and the intra-household bargaining effect after
marriage.
In more recent work using panel data from Australia, Lee and McKinnish (2018)decomposed the spousal age gap’s effect into its impact on satisfaction levels at the timeof marriage and the changes in satisfaction over the duration of marriage. They discoveredthat individuals tended to be more satisfied with younger spouses at the time of marriage,
and less satisfied with those who were older. As time passed, marital satisfaction
decreased more in differently aged couples than those who were similarly aged (Lee and12McKinnish, 2018). 11 We follow Lee and McKinnish’s (2018) specification by including
Gap of ages*Marital duration, an interaction term. Thus, the Gap of ages*Marital
duration can be interpreted as capturing the effects of intra-household bargaining throughmarital life after controlling for the partner selection effect by Gap of ages*Married.
These interaction terms are anticipated to be positive based on Hypotheses 1 and 4, while
Hypothesis 2 leads us to predict that women exhibit a greater coefficient than men women
exhibit a greater coefficient than men.
The relationships between parents possibly form the child’s view (or preference) about
the division of labor within a household. This can consequently influence the child’s time
allocation within a household after the child marries in adulthood. We thus obtain suchvariables as the respondent parents’ and partner parents’ spousal age gaps. As describedin Table 1, these gaps are the “(father’s or mother’s) value – the (mother’s or father’s)value when the respondent is (male or female),” respectively. Booth and Kee (2009)
revealed that a woman’s fertility depends on the size of her family of origin, as well asthat of her husband’s. This indicates that decision-making within a household is
influenced by the spouse’s origin-family characteristics through a family-specific culturaltransmission. Therefore, we must also examine the effect of partner parents’ age gaps.
Hence, in the same way that the spousal age gap’s interaction term was created, Parents(partner’s parents) gap of ages*Marital duration and Parents (partner’s parents) gap of
ages*Marriage are included to consider the effect of identities inherited from parents.
Hypotheses 3 and 4 lead us to predict that these interaction terms have a positive sign for
women.
Aside from parents’ age gaps, we follow existing works (e.g., Fernandez et al., 2004;
Kawaguchi and Miyazaki, 2009) to anticipate the mother’s work status will determine
preferences and perspectives about the allocation of time within a household. We interpret
this effect as forming gender identity, and test this effect by including Working mother*Marital duration and Working mother*Marriage. Mothers who work full-time during
one’s childhood are thought to spend less time on housework; if so, the woman will
decrease her allocation of housework, while the man will increase it. These interaction

11

Sohn (2016) found that women with taller husbands experienced happiness after marriage,
but these effects declined as time passed.
13

terms for the working mother are predicted to have negative and positive signs for females
and males, respectively.
One critical issue involves controlling for bias, and instrumental variables (IVs) aretraditionally used to control it. However, it is difficult to discover valid IVs, as we havealready controlled for individual-fixed effects, and most potential IVs are captured by
fixed effects. 12 Thus, we attempted to disentangle the intra-household bargaining andpartner selection effects as noted above.
Various other factors can be controlled by a vector of control variables Xit , including
dummies for employment status, the number of children, and the respondent’s or partner’s
period of pregnancy. These control variables are included in all specifications, although
their results are not presented in Tables 5 to 8.

4. Results and Interpretation
Tables 5 to 8 illustrate the fixed effects’ estimation results based on the men’s andwomen’s samples, respectively. Tables 5 and 6 provide the results when housework hours
are the dependent variable, while Tables 7 and 8 exhibit results for the allocation ofhousework as the dependent variable. Respondents’ ages across the generation gap arethought to influence the results; therefore, robust standard errors are clustered by age.
We can observe from Table 5—based on the male sample—that the interaction terms
for Gap of ages*Married indicate a negative sign for most results. However, not allcolumns exhibit statistical significance. For example, no statistical significance can beobserved for the interaction terms for the parents’ age gap. In our interpretation, the male’s
gender identity plays a key role, as this can discourage men to assume the burden ofhousework (Akerlof and Kranton, 2000). This identity is considered as neutralizing males’
motivation to do housework to compensate for his wife’s disutility from having an older
husband. We should carefully focus on the possibility that household activities can beoutsourced (Burda et al., 2008), although we cannot further examine this due to data
limitations. If this is the case, men might earn more to employ a maid or order housework
12

Lee and McKinnish (2018) controlled for a similar bias from mate selection by attempting toconduct IV estimations, but could not discover any valid IVs. Grossbard and Mukhopadhyay(2017) used panel data to conduct IV estimations, but could not use the IV method whencontrolling for fixed effects because the IVs are time-invariant.
14

services instead of the wives assuming the burden of housework. In contrast, thecoefficients for Working mother*Marital duration and Working mother*Married indicate
positive signs. Columns 4 to 6 in Table 5 reveal Working mother*Marital duration is
statistically significant, suggesting that husbands who had full-time working mothers inchildhood tend to increase their housework hours to support their wives as a consequenceof intra-household bargaining.
Concerning the control variables, the coefficient of Children produces significant,positive signs in all columns, which indicates that the emergence of children will leadhusbands to increase their housework hours.
Regarding the results of Table 6, and consistent with the female gender (Akerlof andKranton, 2000; Booth and Van Ours, 2009), Married exhibits a positive, significant signin all columns, implying that marriage (or cohabitation) leads women to increase theirhousework hours. Further, the Gap of ages*Married and Gap of ages*Marital duration
demonstrate positive signs in all results; Gap of ages*Married is positive and statisticallysignificant at the 1% level in all columns, while Gap of ages*Marital duration is not
significant in any columns. This indicates that the age gap does not influence intrahousehold bargaining, although a partner-selection effect can be observed. No statisticalsignificance can be observed in any results concerning the interaction terms for theparents’ age gaps.
We now focus on the results of housework allocation in Tables 7 and 8. The results ofTable 7, which include the male sample, are nearly similar to those in Table 5. Specifically,
the spousal age gap does not influence men’s housework hours or the allocation ofhousework. Further, Married reveals a negative, significant sign in all columns, whichreflects a decreased allocation of housework after marriage. The age gap between
respondents’ mother and father has no influence on the allocation of housework. These
results do not support Hypotheses 1, 2 and 4. Alternatively, the coefficients of Working
mother*Marital duration and Working mother*Marriage exhibit positive signs. Columns
4 and 6 in Table 7 indicate that Working mother*Marital duration is statisticallysignificant; therefore, men are influenced by their mothers’ work status in childhood toshare the housework with his wife after marriage. This parallels existing works(Fernandez et al., 2004; Kawaguchi and Miyazaki, 2009).
We can observe in Table 8 that the Gap of ages*Married and Gap of ages*Marital
15

duration are positive and statistically significant in most cases. The spousal age gap leads
women to increase their allocation of housework through both the partner selection andintra-household bargaining effects. One compelling observation is that Parents Gap of
ages*Marital duration exhibits a positive sign and statistical significance, while Parents
Gap of ages*Marriage indicates a positive sign, but no statistical significance. These
imply that respondents’ parental age gaps lead women to increase their allocation ofhousework through intra-household bargaining, but not through their partner selection.
We assume here that the wife older than her husband assumes a larger allocation ofhousework to compensate for her husband’s disutility. This situation contributes toforming her daughter’s identity to assume more housework as a consequence of
bargaining with a younger husband. These results support Hypotheses 1 to 4. Consistent
with our prediction, the coefficients of Working mother*Marital duration and Working
mother*Marriage exhibit negative signs, although these are not statistically significant.
Hence, working mothers had no substantial impact on their daughters’ decreased
housework allocation. One possible interpretation is that women’s gender identity toprefer housework is sufficiently large to neutralize the effects of the mother’s work status.
In considering Tables 5 to 8, it can be posited that the mother’s work status influencessons’ housework allocation after marriage, but not daughters’.
Collectively, the results from Tables 5 to 8 support Hypotheses 1 to 4, proposed in
Section 2. Our observations thus far allow us to derive the following conclusions: younger
husbands experience disutility in their marriages to older wives, but compensate for thisby assuming a larger allocation of his wife’s housework as a consequence of intrahousehold bargaining. In contrast, gender identities lead wives with older husbands tocompensate for her disutility by his larger earnings. Unfortunately, we cannot analyze
spouses’ earnings, as our dataset only includes the family’s total earnings. Further,individual gender identities form through learning from parents’ lifestyles, and thus, thespousal age gap has long-term effects not only on the couple’s allocation of housework,
but also on their children’s allocation of housework after marriage.

5. Conclusion

Various works have studied how spousal age gaps relate to the allocation of housework.
16However, research thus far has failed to scrutinize the effects of parents’ age gaps.
Individuals are fundamentally influenced by their parents’ lifestyles, and form their own
identities to determine their decision-making in various situations later in life. First, we
use a novel dataset to compare the effects of spousal gaps between genders by considering
gender identity. Further, we consider how parent characteristics, such as the parents’ age
gap and mother’s work status, play a role in forming this identity, thus influencing theallocation of housework between spouses. One innovation in this paper involves its
investigation of the intergenerational transmission and allocation of housework between
the genders.
We originally collected individual-level data through monthly Internet surveys for 37
months. At the initial survey point, respondents were unmarried with the intent to marry
their partner in the near future. We then tracked the same individuals after their marriage
occurred to consider how the allocation of housework changed.
After controlling for individual- and time period-fixed effects, our key findings are as
follows: (1) Women older than their partners tend to assume a larger amount of housework
than in the pre-marriage period, and the spousal gap effect increases as the marriage
duration increases. (2) Women with mothers older than their fathers tend to assume alarger allocation of housework as the marriage duration increases, (3) the age gap hardly
affects men’s allocation of housework, while men who had full-time working mothers at
age 15 assume a larger allocation of housework as the marital duration increases.
This implies that for women, the spousal age gap influences not only the selection ofa mate, but also the allocation of housework as a result of intra-household bargaining. We
tested our hypotheses by first assuming that mothers older than fathers, as well as fatherswith full-time working wives, assume a larger amount of housework. Regarding women,
their identities that form from their parents’ age gap only influenced the allocation ofhousework as an outcome of bargaining. Alternatively, men’s identities as formed throughhaving a working mother lead to his assuming a larger amount of housework.
This paper cannot directly address an endogeneity bias in partner selection, partially
due to data limitations; however, valid instrumental variables should be used to control
this. Otherwise, a quasi-experimental setting should be used to scrutinize the age-gap
effects. These are remaining issues to be addressed in future studies.
17References

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20

250
200
Observations
100
150
50
0
-40

-20
0
20
Timing of marriage or cohabitation
Man

40

Woman

Fig. 1. Difference of observations according to the timing of marriage or cohabitation.
Note: On the horizontal line, marriage or cohabitation (the latter, if one is not yet
married) begins at t = 0. The numbers on the x-axis indicate the months before and after
the marriage event.

21

Woman0

10Percent

20

30

Man

-30

-20

-10

0

10

20

30

-30

-20

-10

0

10

20

30

Fig. 2. Distribution of the age differences between respondents and their partners.

22

200
150
Minutes
100
50
-10

0
10
Timing of marriage or cohabitation
Man

20

Woman

Fig. 3. Dynamic effect of marriage or cohabitation on housework hours (the minutes forhousework in a weekday).
Note: On the horizontal line, marriage or cohabitation (the latter, if one is not yet
married) begins at t = 0.

23

80
70
Percentage
60
50
40
-10

0
10
Timing of marriage or cohabitation
Man

20

Woman

Fig. 4. Rate of allocation for housework within a household (percentage of housework).

24

Table 1. Basic statistics of variables used in the estimation and mean values for males and females
Variables
Definition
Housework hours
Respondent’s housework minutes per day

Males
59.7

Females
135.7

Allocationof housework
Marital duration

Respondent’s share of housework within a household (%).

38.8

71.0

Months passed after the marriage or cohabitation

9.46

7.68

Age

Ages

33.3

30.4

Gap of ages

(Respondent’s age – Partner’s age)

3.57

−1.31

Parents’ age gap

Respondent father’s (or mother’s) age – Respondent mother’s (father’s) age

2.77

−3.03

Partner parents’ age Partner father’s (or mother’s) age – Partner mother’s (or father’s) age
gap
Working mother
This assumes a value of one if the respondent’s mother worked when the respondent
was 15 years old, and zero otherwise.
Married
A value of one of the respondent is currently married or cohabitating with one’s
partner, and zero otherwise.

2.53

−1.79

0.31

0.32

0.82

0.80

Pregnancy period

A value of one if the respondent (or partner) is pregnant, and zero otherwise.

0.10

0.09

Children

Number of children

0.24

0.07

Notes: The parents’ age gap is calculated by the “father’s age − mother’s age” when the respondent is male, while this is the “mother’s age− father’s age” when the respondent is woman. We use information about the respondent’s share of six housework categories (“cooking,”“clearing dishes from the table,” “cleaning and sweeping,” “washing,” “shopping,” and “taking out the garbage”) to calculate therespondents’ share of housework as a whole.
23

Table 2. Correlation matrix between the spousal and parental age gaps

Age gap withpartner

Age Gap with
Partner

Parents’ Age Gap

Partner Parents’
Age Gap1

0.24***

0.34***

1

0.46***

Parents’ age gap
Partner parents’ agegap

1

Note: The parents’ age gap is calculated as the “(father’s age − mother’s age)” when the
respondent is male, while this is calculated as the “(mother’s age − father’s age)” when
the respondent is female. *** indicates significance at the 1% level.

24

Table 3. Comparison of housework hours across groups

Men’s Sample
Age>Partner’s Age

Before(a) marriage or
cohabitation
(a)
50

After
(b)marriage or
cohabitation(b)
79

Difference(b) – (a)29

Age=Partner’s Age

36

49

13

Age<Partner’s Age

44

47

3

Age > Partner’s Age

74

161

87

Age = Partner’s Age

63

137

74

Age < Partner’s Age

92

142

50

Women’s Sample

Note: The numerals here are the minutes per day.

25

Table 4. Comparison of housework allocations across groups
Men’s Sample

Age > Partner’s Age

Before Marriage or
Cohabitation(a)46

After Marriage or
Cohabitation(b)
45

Difference(b) – (a)−1Age = Partner’s Age

51

43

−8

Age < Partner’s Age

63

35

− 18

Women’s Sample
Age > Partner’s Age

61

77

16

Age = Partner’s Age

64

69

5

Age < Partner’s Age

61

71

10

Note: The numerals here are percentages (%).

26

Table 5. Determinants of housework hours (fixed-effects model): Men’s sample
(1)
(2)
(3)
(4)
(5)
(6)
Gap of Age
−0.42
−0.33
−0.36
−0.45
−0.39
−0.42
*Married(−0.51)(−0.42)(−0.44)(−0.54)(−0.48)(−0.49)Gap of Age
0.01
0.01
0.01
* Marital duration(0.41)(0.42)(0.48)
Married
2.51
2.97
3.78
2.04
2.31
4.33
(0.58)(0.66)(0.96)(0.51)(0.55)(1.23)
Marital duration
−0.27
−0.27
−0.42
(−0.98)(−0.92)(−1.36)
Parents’ EffectParents’ age gap
0.67
0.79
1.24
1.36
* Married(0.56)(0.73)(1.06)(1.27)
Partner parents’ age gap 0.44
0.61
0.35
0.76
* Married(0.70)(1.32)(0.58)(1.59)
Parents’ age gap−0.07** −0.07****Marital duration(−2.41)(−2.77)
Partner parents’ age gap
−0.01
−0.03
* Marital duration(−0.30)(−1.65)Working mother
7.41
6.55
8.54
4.61
4.08
4.82
*Married(0.88)(0.77)(1.01)(0.54)(0.47)(0.57)
Working mother
0.45**
0.44**
0.49*** Marital duration(2.47)(2.47)(2.58)
Control
Pregnancy period
4.42
4.26
4.64
3.62
3.73
4.51
(1.35)(1.32)(1.42)(1.06)(1.13)(1.34)
Children
13.2***
12.1*** 13.4*** 12.1*** 11.4***
13.0***(3.72)(3.69)(3.76)(3.04)(3.12)(3.24)
Ages
−4.41
−4.35
−4.33
−4.24
−4.19
−4.19
(−1.67)(−1.59)(−1.64)(−1.61)(−1.55)(−1.55)Observations
2879
2923
2885
2879
2923
2885
Number of Individuals
155
158
156
155
158
156
R-square
0.03
0.03
0.03
0.03
0.03
0.03
Note: The married-cohabitating, time period, job status, and individual dummies areincluded in all estimations, although their results are not reported. The numbers inparentheses are t-values, based on robust standard errors clustered by age. *, **, and*** indicate significance at the 10%, 5%, and 1% levels, respectively.

27

Table 6. Determinants of housework hours (fixed-effects model): Women’s sample
(1)
(2)
(3)
(4)
(5)
(6)
Gap of Age
2.56***
2.99*** 2.50*** 2.37*** 2.36*** 2.39****Married(3.32)(4.06)(3.31)(3.04)(2.77)(3.19)
Gap of Age
0.01
0.07
0.01
* Marital duration(0.28)(0.94)(0.29)
Married109.5*** 105.9*** 98.4*** 102.9*** 98.9*** 96.8***(7.02)(6.90)(8.32)(7.53)(6.94)(8.88)
Marital duration
−0.46
−0.61
−1.51**(−0.39)(−0.51)(−2.30)Parents’ EffectParents’ age gap
3.28
3.90
1.95
2.67
* Married(1.26)(1.66)(0.84)(1.18)
Partner parents’ age gap 1.80
2.06
1.76
1.84
* Married(0.52)(0.60)(0.54)(0.56)
Parents’ age gap
0.16
0.13
*Marital duration(0.93)(0.76)
Partner parents’ age gap
0.01
0.01
* Marital duration(0.08)(0.20)
Working mother
−2.85
1.16
5.33
−8.80
−6.60
−4.09
*Married(−0.16)(0.06)(0.30)(−0.47)(−0.35)(−0.21)
Working mother
0.57
0.74
1.09
* Marital duration(0.62)(0.90)(1.54)
Control
Pregnancy period
14.3*
8.91
12.4
17.7**
11.3
14.9*(1.75)(1.14)(1.46)(2.38)(1.54)(1.75)
Children
41.1*
44.9**
40.5*
45.0**
47.1**
43.1**(1.91)(2.15)(1.81)(2.24)(2.41)(2.01)
Ages
1.13
−1.32
1.24
1.39
−0.92
1.51
(0.18)(−0.19)(0.20)(0.23)(−0.13)(0.25)
Observations
2579
2745
2579
2579
2745
2579
Number of Individuals
163
175
163
163
175
163
R-square
0.27
0.28
0.27
0.27
0.28
0.27
Note: The married-cohabitating, time period, job status, and individual dummies areincluded in all estimations, although their results are not reported. The numbers inparentheses are t-values, based on robust standard errors clustered by age. *, **, and*** indicate significance at the 10%, 5%, and 1% levels, respectively.

28

Table 7. Determinants of housework allocation (fixed-effects model): Men’s sample
(1)
(2)
(3)
(4)
(5)
(6)
Gap of Age
−0.08
−0.01
−0.09
−0.43
0.02
−0.06
*Married(−0.21)(−0.01)(−0.22)(−0.11)(0.06)(−0.25)
Gap of Age−0.001−0.001−0.001* Marital duration(−0.13)(−0.12)(−0.05)
Married−15.7*** −14.9*** −15.7*** −16.5*** −15.9*** −16.0***(−3.57)(−3.65)(−3.94)(−2.87)(−2.98)(−2.94)
Marital duration
−0.23
−0.24
−0.30
(−0.43)(−0.43)(−0.57)
Parents’ EffectParents’ age gap
0.05
0.17
0.30
0.42
* Married(0.12)(0.40)(0.63)(0.91)
Partner parents’ age gap 0.45
0.49
0.39
0.53
* Married(0.68)(0.78)(0.62)(0.85)
Parents’ age gap
−0.03
−0.03
*Marital duration(−1.59)(−1.69)Partner parents’ age gap
−0.01
−0.01
* Marital duration(−0.06)(−0.63)
Working mother
8.33*
7.50
8.53*
7.29
6.58
7.10
*Married(1.84)(1.56)(1.87)(1.62)(1.41)(1.54)
Working mother
0.19*
0.19
0.21*
* Marital duration(1.75)(1.64)(1.93)
Control
Pregnancy period
2.88
2.57
2.95
2.49
2.28
2.84
(1.48)(1.35)(1.49)(1.29)(1.21)(1.43)
Children
4.06**
3.88**
4.09**
3.86**
3.81**
4.20**(2.45)(2.51)(2.50)(2.43)(2.57)(2.55)
Ages−3.26** −3.25** −3.24** −3.14** −3.12** −3.14**(−2.66)(−2.74)(−2.68)(−2.49)(−2.54)(−2.47)
Observations
2881
2925
2887
2881
2925
2887
Number of Individuals
155
158
156
155
158
156
R-square
0.06
0.06
0.06
0.06
0.06
0.06
Note: The married-cohabitating, time period, job status, and individual dummies areincluded in all estimations, although their results are not reported. The numbers inparentheses are t-values, based on robust standard errors clustered by age. *, **, and*** indicate significance at the 10%, 5%, and 1% levels, respectively.

29

Table 8. Determinants of housework allocation (fixed-effects model): Women’s sample
(1)
(2)
(3)
(4)
(5)
(6)
Gap of Age
0.40***
0.57**
0.38*** 0.30**
0.40*
0.30***Married(2.87)(2.72)(2.88)(2.19)(1.95)(2.10)
Gap of Age
0.01*
0.02*** 0.01
* Marital duration(1.88)(2.72)(1.52)
Married13.9***
13.0*** 11.7***
10.8*** 10.0*** 10.2***(7.39)(7.47)(5.58)(5.30)(5.02)(4.50)
Marital duration
0.12
0.13
−0.22
(0.62)(0.73)(−0.99)Parents’ EffectParents’ age gap
0.64
0.74**
0.26
0.46* Married(1.47)(2.16)(0.58)(1.21)
Partner parents’ age gap 0.77***
0.82*** 0.92**
0.91*** Married(3.11)(3.48)(2.01)(2.05)
Parents’ age gap
0.06*** 0.04***Marital duration(2.91)(2.46)
Partner parents’ age gap
−0.02
−0.01
* Marital duration(−0.49)(−0.42)Working mother
−2.21
−1.65
−0.61
−0.01
−0.01
0.68
*Married(−0.73)(−0.69)(−0.23)(−0.00)(−0.00)(0.18)
Working mother
−0.38
−0.31
−0.20
* Marital duration(−1.69)(−1.46)(−1.04)Control
Pregnancy period−5.02*** −5.50*** −5.38*** −4.49*** −5.35*** −5.32***(−3.74)(−4.87)(−3.40)(−3.11)(−4.68)(−3.23)
Children
−1.45
−0.50
−1.67
−0.79
−0.54
−1.41
(−1.02)(−0.32)(−1.18)(−0.50)(−0.34)(−0.83)
Ages
0.32
−0.10
0.05
0.13
0.03
0.16
(0.02)(−0.07)(0.03)(0.08)(0.02)(0.09)
Observations
2581
2747
2581
2581
2747
2581
Number of Individuals
163
175
163
163
175
163
R-square
0.06
0.07
0.06
0.06
0.07
0.06
Note: The married-cohabitating, time period, job status, and individual dummies areincluded in all estimations, although their results are not reported. The numbers inparentheses are t-values, based on robust standard errors clustered by age. *, **, and*** indicate significance at the 10%, 5%, and 1% levels, respectively.

30