Discussion Papers In Economics
And Business

Gap of height and education within couple and its
effect on conflict and evaluation about partners:
psychological cost of division of labor within household

Eiji Yamamura
Yoshiro Tsutsui
Discussion Paper 17-35

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANGap of height and education within couple and its
effect on conflict and evaluation about partners:
psychological cost of division of labor within household

Eiji Yamamura
Yoshiro Tsutsui
Discussion Paper 17-35

December 2017

Graduate School of Economics andOsaka School of International Public Policy (OSIPP)
Osaka University, Toyonaka, Osaka 560-0043, JAPANGap of height and education within couple and its
effect on conflict and evaluation about partners:
psychological cost of division of labor within household
Eiji Yamamura
Seinan Gakuin University, Japan

Yoshiro Tsutsui†
Konan University, Japan

ABSTRACTThis paper attempts to investigate how differences of height, education and age within a couple
influence evaluation about partner. Further, this paper explore the effect of differences changed
before and after marriage. For this purpose, monthly web-site surveys were conducted tocollect the individual level data of unmarried persons who having plan to get married withboy/girl friends. Based on the collected data covering the period from March 2012 to March
2015, through the Panel data analysis, we found as; (1) gaps of height and education reduced
quarrel with partner after the marriage. (2) Further, quarrel lowered the evaluation about thepartner. Hence, there is indirect positive effect through quarrel on evaluation about partners. (3)However, after controlling the indirect effect through quarrel, gaps of height and education
lowered the evaluation about partner which is considered as the direct negative effect on theevaluation. (4) considering these results jointly indicated that effect of 1 year difference of
education on the evaluation is equivalent to that of 4.27 cm difference of height. Assuming thatgap of height and education enhanced division of labor within a household, combined results
implied that the division of labor reduce interaction between wife and husband and so avoid thequarrel. This in turn improve evaluation about partner. However, reduction in interaction
between husband and wife increased psychological distance between them, resulting in lowering
the evaluation about the partner. The negative effect of the gap on the evaluation is far larger
than the positive one.
JEL classification: J16; D74;
Keywords: Gap within a couple, Conflict, Evaluation about the partner, Height, Years ofschooling.

*

Corresponding author. Department of Economics, Seinan Gakuin University, 6-2-92 Nishijin, Sawara-ku
Fukuoka 814-8511, Japan.
E-mail address: yamaei@seinan-gu.ac.jp
Tel: +81 92 823 4543; Fax: +81 92 823 2506†

Faculty of Economics, Konan University, 8-9-1 Okamoto, Higashinadaku, Kobe 658-8501
Japan, e-mail tsutsui@center.konan-u.ac.jp

1. Introduction
Single men and women have only limited information about their partner and then makedecision on marriage. At least, married persons judged their partner suitable to themselves and so
get married at the time when they made a decision about marriage. After the marriage, they obtaina greater information about their partner and so possibly change evaluation about the partners.
Here, several questions arise naturally as; what type of couple can improve their relation after
marriage? Does girl make success in the marriage when she get married with boy friends withsimilar characteristics? Do people with different characteristics maintain the harmonious marital
life? These questions about marital quality can be scrutinized by considering how similarity
within a couple affect evaluation about one’s partner after the marriage.
According to the seminal work of Becker (1991), comparative advantage of husband (wife)
leads marital couple to increase household productivity and so economic gains by gender divisionof labor within a household. If one has a comparative advantage in housework, and so is
specialized in housework. In this case, one’s partner becomes full-time breadwinners in the labormarket. Comparative advantage within a couple comes from the difference of schooling years
because schooling years increases human capital, leading to increase marginal product of laborand so wage level in the labor market. Apart from education captured by schooling years,
researcher found that height is positively associated with wage level and so there is heightpremium in the labor market (e.g., Case & Paxson 2008; 2009; Gao & Smyth 2010; Yamamura
et al., 2015). The height premium in the labor market is also found not only for male but also forfemale (Tao 2014). Naturally, gap of schooling years and height within a couple leads to divisionof labor within a household after the marriage. Then, marital quality is expected to be improved
through increase in economic gains by the division of labor.
Once household income level is controlled after the marriage, we can consider effect of thegaps on marital relation from the non-monetary point of view. There is the argument that marital
quality improves when husband and wife plays a similar role and so share works jointly within ahousehold (Simpton & England 1981; Mueller et al., 1979). On the other hand, the classical workof Parsons and Bales (1955) argued that sharing works possibly leads to marital competition,
which decrease marital quality. Hence, even if we control economic gains from marriage, it isunknown whether gaps within a couple influences evaluation about the partner. However, withthe exception of Sohn (2016), few works considered the effect of gaps within a couple on marital
quality. Further, it is difficult to directly observe how married persons consider their partners eventhough researchers used the marital satisfaction to consider marital quality (e.g., Fan, & Lui, 2004;
Chen & Li 2012; Oshio et al., 2013; Minnotte et al. 2015). Further, it is valuable of considering
events which seem to temporary influence the evaluation about partner.
The division of labor becomes far more important after the marriage than before marriage.
Therefore, comparing before and after the marriage is very critical to explore the division of laborwithin a household. We conducted monthly surveys to follow up the same respondents for three
years in order to originally and purposefully constructing the individual level panel data. The
surveys covered the period the pre-marriage and the post-marriage period for the same person.
Hence, the data enables us to comparing the respondent’s evaluation about partner between preand post marriage periods. The data provides the occurrence of quarrel within a couple andevaluation about one’s partner not only in the post-marriage period but also in the pre-marriage
period. Based on the novel data, we have the advantage that we investigated how difference ofschooling years and height within a couple on evaluation about partner change after the marriage
in compare with before the marriage. Major findings are: in compared with the pre-marriage
period, gap within a marital couple reduced the probability of quarrel and then improve theevaluation about partner. However, this positive effect is smaller than the direct negative effect of
the gap on the evaluation. The contribution of this paper is to use the original data to provide thenew evidence on marital relation.
The remainder of this paper is organized as follows; Short review of existing works ispresented in Section 2. Section 3 proposes the testable hypotheses. In Section 4, an overview of1

the data and statistical method are exhibited. In Section 5, we interpret the estimation results anddiscuss its implication. Our conclusions are presented in Section 6.

2. Brief literatures review
Income level of household increases if couple practice division of labor within a household
assuming that there is gap between husband and wife gives marital. Apart from the economic
gains, researchers explored the relation between division of labor and the subjective well-being.
In the United States, men’s happiness level increases if his wife does not work, or if he financiallydepend on his wife (Lee and Ono 2008). This indicates that the height premium of husband leads
to division of labor, increasing the wife’s happiness. On the other hand, according to Oshio et al.
(2013), in China, dual earning is welcome by both husbands and wives. Accordingly, in China,
marital couple relatively prefer an egalitarian division of labor in terms of both market work andhousework, implying that the wife‘s disadvantageous social position is less remarkable. The
outcomes of division of labor within a household is thought to be interpreted in a various way.
Different norm and institutional factor caused the different effect of the division of labor among
countries (Lee and Ono 2008; Oshio et al., 2013).
The externality of the division of labor within the household possibly reduced the positiveeffect of division of labor within a household. Role balance is defined as “the tendency to become
fully engaged in the performance of every role in one’s total role system, to approach every typicalrole and role partner with an attitude of attentiveness and care” (Marks and MacDermid 1996,
421). The role balance-oriented individuals have developed problem-solving skills to deal withconflict (Kashdam & Rottenberg, 2010). In the family, husband’s/wife’s role balance positively
is positively related to their marital satisfaction (Marks et al. 2001). Role balance is thought tomake a contribution to maintain the harmonized interpersonal relations. In the existing works, theheight effect on marriage is explored (e.g., Baten & Murray, 1998; Harper 2000, Herpin 2005,
Belot & Fidrmuc 2010; Manfredini et al. 2013; Sohn 2015a; 2015b; Yamamura & Tsutsui 2017).
However, the effect of height gap with partner on marital relations has not been investigated.

2. Testable Hypotheses
In Figure 1, framework of this paper is illustrated. A lot of existing works found that not only
education level but also some physical characteristics such as height increased earnings (e.g.,
Steckel,1995; Schultz, 2002; Heineck 2005; Dinda et al., 2006; Case & Paxson 2008; 2009; Gao& Smyth 2010; Lundborg et.al., 2014; Yamamura et al., 2015). The comparative advantage
between husband and wife leads to division of labor within a household (Becker1991). To put itin another way, the similar characteristics between them reduces incentives to do division of laborwithin a household. Therefore, in this paper, we assume that the gaps of education and heightcaused the division of labor within a couple. Then, the gaps are treated as proxy for division oflabor between them. As explained in the following section, the data used in this paper includes
the data about occurrence of quarrel with partner. In this paper, the occurrence of quarrel isconsidered to be that of conflict.
Sociologists argued that husband and wife share works jointly within a household, which has
a positive effect on marital quality (Simpton & England 1981; Mueller et al., 1979). However,once “transaction cost” to work together is taken into account, the sharing work is thought to havea negative influence on evaluation about the partner. If husband and wife do and share sameworks together, they need to arrange and coordinate their works. For instance, when husband andwife do house-works, it is important to reach the consensus about how they do it. Disagreement
about it increase time to coordinate each other. Further, quarrel is more likely to occur quarrel
with one’s partner. That is occurrence of quarrel can be considered as “transaction cost” for joining
housework within a marital couple. Therefore, the larger the gaps of education and height reduce
the possibility of quarrel. Further, effect of the gaps become larger because coordination within a2couple become more important especially after the marriage than before the marriage. Here, we
propose the following Hypothesis 1:
Hypothesis 1: Gaps of education and height within a couple are more likely to reduce theprobability of quarrel after the marriage than before the marriage.
Naturally, occurrence of the quarrel with partner is predicted to reduce the evaluation about
one’s partner. As is illustrated as two thin arrows in Figure 1, through channel in which the gaps
reduce the probability of quarrel, the gaps indirectly improve evaluation about one’s partner. Thisis considered as the indirect positive effect of the gaps on evaluation about one’s partner. On theother hand, the gaps leads to division of labor within a couple, which results in reduction in
intimate interaction with partner. In the end, love and passion for one’s partner cooled off.
Accordingly, the gaps reduce the evaluation, which is considered as the direct negative effect of
the gaps on the evaluation about one’s partner. This channel is expressed as thick arrow in Figure
1. In summary, we postulate the following Hypothesis 2:
Hypothesis 2: Gaps of education and height within a couple directly reduce the evaluation about
one’s partner, while the gap indirectly improve the evaluation through its effect on quarrel.

3. Data and methods
3.1. Data
In this paper, we attempt to examine how the gender gap within a couple influence theirrelation before and after the marriage. For this purpose, the targets of the survey were limited tomen and women who planned to get married in the future at the initial time point of the surveys.
Participant ages were between 17 and 51 years. We gathered individual-level panel data covering
all regions of Japan via internet surveys.
To put more concrete, a market research company, INTAGE Communications Inc. has great
experience of conducting academic surveys. So, we commissioned the INTAGE to conduct the
research under the direction of the authors. Relationship within a couple does not so persist andbecause the relation seems to depend on various events in the life. For instance, negative effect ofquarrel with one’s partner is temporary. In order to capture the effect of quarrel, monthly surveys
were carried out for 3 years, from March 2012 to March 2015, a total of 37 surveys during thisperiod. Totally, 1,049 individuals are were included in the first survey. However, during the 3year survey period, other individuals were included. Therefore, in total, 1,855 participants
participated in the survey during the survey period.
Some participants failed to respond and others dropped out of the surveys, giving a response
rate of 60.1%. Finally, the sample size was reduced to 10,492 completed surveys. Questionnaires
included items querying respondent’s individual socioeconomic characteristics such as
educational level, height, age, sex, household income. Information about respondent’s partner’s
educational level, height, age are also obtained. What is more, every month participants wereasked what events had occurred during the previous month such as quarrel during the survey
period. What is more, subjective evaluation about respondent’s partner is also obtained. Using themonthly panel surveys, we can explore how the gaps within a couple on evaluation about one’s
partner changed between before and after the marriage.
Table 1 presents definitions of the variables used in this research and their mean values,
standard deviation, maximum and minimum values. Man value of Quarrel is 0.03, implyingthat probability of occurrence of quarrel within a month is 3 %. The largest gap of height withina couple is 40 cm. The largest gap of schooling year is 9 years. To take an example of 9 years gap,
wife’s final educational background is to graduate from junior high school while husband’s one
is to graduate from university. Average value of married is 0.16. This shows that, during the period
March 2012 to March 2015 (37 months), respondents have been married in 16 % of survey periods.
3That is, in the initial period in March 2012, respondents have only plan to get married. Averagely,
it takes 31.1 months to actually get married. Figure 2 illustrated the distribution of evaluation
about one’s partner. It is clear that marking 6 points are about 48 % and most frequently observed.
This suggests that, respondents tend to evaluate highly their partner.
In Table 2(a), sample is divided into large gap of height with a couple and others. Group oflarge gap of height is defined to be those whose height gap is larger than average gap (13.6 cm).
Further, these groups are further divided into group before married and after married. In thesimilar way, in Table 2(b) sample is divided into large gap of schooling years with a couple andothers. In Table 2(c) sample is divided into large gap of ages with a couple and others. Then themean difference test of evaluation about partner between groups are conducted. Table 2 (a)suggest that, before marriage, mean value for those with large height gap is 5.49 which issignificantly larger than 5.35, mean value of others. After marriage, it is interesting to observethat mean value for those with large height gap reduced to 5.47, while mean value for others
increased to 5.59. The difference is statistically significant. Hence, those with large height gap
more highly evaluate partners than others before marriage, but more others more highly evaluate
after marriage. This tells that role of height gap changed from pre-marriage period to postmarriage period. Turning to gap of schoolings, in Table 2 (b), before marriage, mean value forthose with large gap is 5.40 which is significantly smaller than 5.48 of means of others. This
relation is persistent even after the marriage. What is more, the difference between them increased
to 0.35 after married. In Tables 2(a) and (b), for others, mean values of others significantly
increased from pre-marriage period to post-marriage period while for large gap group, there is not
significant difference between periods. In contrast to Table 2(c), as for gap of ages, mean values
for group with the large gap increased significantly after marriage.

3.2. Methods
To test the hypothesis 1, we firstly explore how effect of the gap within a couple on the conflict
between them changes between before and after the marriage. Here, the quarrel between themwithin a month is used as proxy for conflict. The estimated function takes the following form:
Quarrelit=α1Gap of heightit *Married it +α2Gap of schooling yearsit *Married it+α3Gap of agesit *Married it +α4Gap of heightit +α5Gap of schooling yearsit +α6Gap of agesit+α7 Married it +α8 Incomeit + ki + et+ u it,(1)
where Quarrelit represents occurrence of quarrel with partner within a month for individual i andtime period t, and α represents the marginal effect of independent variables. Key variables arecross term of the gap with partner and dummy for getting married such as Gap of height *Married,Gap of schooling years*Married, Gap of ages *Married. If these variables shows the statisticalsignificance, the gap within a couple changed after the marriage in compare with before themarriage. As argued by Becker (1991), economic gains from division of labor influenced therelation within a couple. Income is included to control for economic gains from division of labor
to avoid the omitted variables bias. Once Income is controlled, we extract non-monetary effect ofdivision of labor and put focus on it. Further, the feature of panel data allow us to control timeinvariant individual fixed effect, ki, and time period effect et. Various factors can be control bythese ki, and et.

To test the hypothesis 2, we decomposed the direct and indirect effect of gap on evaluation
about partner. The estimated function is:
Evaluation it=α1Quarrel it +α2Gap of heightit *Married it +α3Gap of schooling years it *Married it+α4Gap of ages it *Married it +α5Gap of height it +α6 Gap of schooling years it +α7 Gap of ages4

it +α8 Married it +α9 Income it + k i + et+ u it,(2)Here, Evaluation is dependent variable while Quarrel is included to consider the temporary effectof quarrel. Other control variables are equal to function (1). Inclusion of Income as independent
variables enables us to consider the effect of division of labor on the evaluation when income
level is equal for all respondents. After controlling for Quarrel, we can explore the direct effectof the gaps within a couple.
Considering results of Functions (1) and (2), we calculate the indirect effect of the gap on
Evaluation through quarrel.

4. Results and discussion
Table 3 reports the results of estimation where quarrel is the dependent variable. Tables 4 and5 exhibits the results where evaluation about one’s partner is the dependent variable. Table 5
includes quarrel as the set of independent variable. For robustness check, we reports the results
when the time-period dummies are included and those when the dummies are not included. In
these tables, the Random effects model is used for estimations if results of the Hausman test showsthat results of the Random effect model are not systematically different from those of the Fixed
effects model. This is because the Random effect is more efficient than the Fixed effects so that
the Random effects model is preferable (Balitagi 2013). Therefore, we can obtain the results thetime invariant variables such as the gaps of Height, schooling years and ages within a couple. If
the results of Hausman test shows the systematic difference of results between the Random andthe Fixed effects model, the Fixed effects model is preferred. Therefore, results of the fixed effects
model are reported. In this case, the time-invariant variables such as Gap of Height, Gap of
schooling years, Gap of ages are not reported because these effects are completely captured by
the fixed effects.
First, we begin by interpreting the results in Table 3 to test the Hypothesis 1. Cross terms ofgaps within a couple and marriage dummy are key variables. Gap of Height*Married and Gap of
schooling years*Married produced the negative sign and statistically significant in all columns.
This suggests that larger the gaps of height and ages within a couple decrease the occurrence ofquarrel with partner after the marriage in compared with the period before marriage. This isconsistent with the Hypothesis 1. However, concerning Gap of ages*Married, its coefficient is
not statistically significant in any columns and so it does not influence the occurrence of thequarrel. Therefore, role played by gaps of height and education level becomes more influential
than that of ages after the marriage.
Turning to Table 4, with the exception of Gap of Height*Married in column (2), Gap of
Height*Married and Gap of schooling years*Married produced the negative sign and statisticallysignificant. We can interpret it as implying that gap of height and education level reduce theevaluation about one’s partner after the marriage in compared with the period before marriage.
On the other hand, similar to Table 3, Gap of ages*Married, does not indicate statisticalsignificance in any columns. Now let use switch our attention to Table 5 1, coefficient of Quarrel
show the negative sign and statistically significant at the 1 % level in all columns, suggesting that
occurrence quarrel reduce the evaluation about one’s partner. Occurrence of quarrel is considered
to capture the temporary effect on the evaluation, which is in line with intuition. As for crossterms, with the exception of Gap of Height*Married in column (1), Gap of Height*Married andGap of schooling years*Married show the negative sign and its statistical significance. That is,
the results about these variables do not change even when occurrence of quarrel is added to theset of independent variables. So, negative effect of the gaps within a couple on evaluation about
one’s partner is robust in alternative specifications. All in all, combined results of Tables 3-5 tells
1

When quarrel is incorporated into the set of dependent variables, results of random effectabout model without cross terms are not preferable because of result of Hausman test. However,
we cannot obtain the results of the gaps within a couple in the Fixed effects model. Therefore, inTable 5, result of the specification without the cross term is not presented.
5

that the gaps of height and education level reduces the quarrel and in turn improve the evaluation
about one’s partner, which is considered as the indirect positive effect through occurrence ofquarrel. On the other hand, these gaps directly reduces the evaluation, which is considered as the
direct negative effect. These support the Hypothesis 2.
Table 6 summarize the degree of influence of the gaps within a couple. This is calculated basedon results of (6) of Table 3 and (5) of Table 5 because these are results of the full-model. As isshown Table 6(a), the indirect effect of the gap of height on the evaluation is 0.001 while thedirect effect is −0.007. That is, the direct negative effect is 6 times larger than the indirect positiveeffect. Inevitably, total effect of the gap of height is −0.006 on the 7 point scale. According toTable 6(b), the indirect effect of the gap of schooling years on the evaluation is 0.002 while thedirect effect is −0.028. That is, the direct negative effect is 14 times larger than the indirect positiveeffect. Accordingly, total effect of the gap of schooling is −0.026 on the 7 point scale. Considering
Tables 6 (a) and (b) together leads us to suggest that total effect of a year increase in schoolingyear on the evaluation about one’s partner is equivalent total effect of a 4.27 cm increase in height.

5. Conclusion
We tried to tackle with the question about whether husband and wife having a lot in common
improve marital life. In the classical theory of economics, couple with different characteristics
improve their relations by practicing division of labor within a household. On the other hand,couple with similar characteristics is likely to share various works and interact each other toimprove their relations. We used the purposefully collected panel data to examine it.
In this paper, we consider how and the extent to which the gaps of education, height and age inthe couple influence the occurrence of quarrel and evaluation about one’s partner. Key findings
are; (1) gaps of height and education reduced quarrel with partner after the marriage. (2) Further,quarrel lowered the evaluation about the partner. The gaps reduced the occurrence of quarrel,
which in turn improve the evaluation. (3) However, after controlling the indirect effect, the gaps
lowered the evaluation about partner. Reduction in interaction between husband and wife
increased psychological distance between them, resulting in lowering the evaluation about thepartner. Further, effect of 1 year difference of education on the evaluation is equivalent to that of
4.27 cm difference of height. Accordingly, the negative effect of the gap on the evaluation is farlarger than the positive one.
In this paper, on the assumption that gap of height and education between marital couple leads
to division of labor, we argue that the gap reduced evaluation about partner. However, it isunknown about how the gap influences division of labor within a household. So, we should
examine empirically the relation between the gap and the division of labor. Furthermore, it isunknown that the gaps within a couple is related to Happiness level through the evaluation about
one’s partner. Even though the gaps within a couple reduce the evaluation, the gaps possibly
increase happiness level by increasing the economic gains through division of labor. There ispossibility that the positive economic effect by the gaps is larger than the negative effect of low
evaluation about the partner on the happiness. So, we should explore it. These are the remaining
issues to be addressed in the future work.

References
Baltagi, B.H. (2013). Econometric Analysis of Panel data (Fifth edition). Wiley, New York.
Bartley, S.J., Judge, W. & Judge, S. (2007). Antecedents of marital happiness and career. Journalof Business and Public Affairs, 1(1).
Baten, J., & Murray, J.E. (1998). Women’s stature and marriage market in preindustrial Barvaria.
Journal of Family History. 23, 124-135.
6

Becker, G. (1991). A Treatise on the Family. Harvard University Press, Cambridge.
Belot, M., & Fidrmuc, J. (2010). Anthropometry of love: height and gender asymmetries ininterethnic marriages. Economics and Human Biology, 8(3), 361-372.
Case, A. & Paxson, C. (2008). Stature and status: Height, ability and labor market outcomes.
Journal of Political Economy 116(3), 499-532.
Case, A. & Paxson, C. (2009). Making sense of the labor market height premium: Evidence fromthe British household panel survey. Economics Letters 102(3), 174-176.
Chen, L.H., Li, T.S. (2012). Role balance and marital satisfaction in Taiwanese couples: An actorpartner interdependence model approach. Social Indicators Research, 107, 187-199.
Cook, W.L., & Kenny, D.A. (2005). The actor-partner interdependence model: A model ofbidirectional effects in developmental studies. International Journal of Behavioral
Development, 29(2), 101-109.
Cook, W.L., & Snyder, D.K. (2005). Analyzing nonindependent outcomes in couple therapy using
the actor-partner interdependence model. Journal of Family Psychology, 19(1), 133-141.
Dinda S, Gangopadhyay PK, Chattopadhyay BP, Saiyed HN, Pal M., & Bharati P. (2006). Height,
weight and earnings among coalminers in India. Economics & Human Biology, 4, 342–350.
Fan, C. S., & Lui, H.K. (2004). Extramarital affairs, marital satisfaction, and divorce: Evidence
from Hong Kong. Contemporary Economic Policy, 22(4), 442-452.
Gao, W., & Smyth, R. (2010). Health human capital, height and wages in China. Journal of
Development Studies, 46(3), 466-484.
Grossbard, S., & Mukhopadhay, S.(2013). Children, spousal love, and happiness: An economic
analysis. Review of Economics of the Household, 11(3), 447-467.
Hagstrom, P., & Wu, S. (2016). Are pregnant women happier? Racial and ethnic differences in
the relationship between pregnancy and life satisfaction in the United States. Review of
Economics of the Household, 14(3), 507-527.
Harper, B. (2000). Beauty, stature and the labour market: a British cohort study. Oxford Bulletinof Economics and Statistics, 62, 771-800.
Heineck, G. (2005). Up in the skies? The relationship between height and earnings in Germany.
Labour 19(3), 469-489.
Herpin, N. (2005). Love, career, and height in France, 2001. Economics and Human Biology, 3,420-449.
Kashdam, T.B., & Rottenberg, J. (2010). Psychological flexibility as a fundamental aspect ofhealth. Clinical Psychology Review, 30(4), 467-480.
Kenny, D.A., Kashy, D..A., & Cook, W.L. (2006). Dyadic data analysis. New York: Griford Press.
Lee, K.S., Ono, H. (2008)., Specialization and happiness in marriage: A U.S.–Japan comparison.
Social Science Research, 37, 1216–1234.
Liu, R.X., & Chen, Z.Y. (2006). The effects of marital conflict and marital disruption on
depressive affect: A comparison between women in and out of poverty. Social Science andQuarterly, 87(2), 250-271.
Lundborg, P., Nystedt, P., & Rooth, D.O. (2014). The height premium in earnings: The role ofphysical capacity and cognitive and non-cognitive skills. Journal of Human Resources, 149(1),141-161.
Manfredini, M., Breschi, M., Fornasin, A., & Seghieri, C. (2013). Height, socioeconomic status
and marriage in Italy around 1900. Economics and Human Biology, 11(4), 465-473.
Marks, S.R., Huston, T.L., Johnson, E.M., & MacDermid, S.M. (2001). Role balance among whitemarried couplies. Journal of Marriage and the Family, 63(4), 1083-1098.
Marks, S.R., & MacDermid, S.M. (1996).Multiple roles and the self: A theory of role balance.
Journal of Marriage and the Family, 58, 1083-1098.
Massen van den Brink, H., Groot, W. (1994). Labor supply and the welfare costs of maritalconflict. Journal of Economic Psychology, 15(3), 467-486.
Minnotte, K.L., Minotte, M.C., & Bonstrom, J. (2015). Work-family conflicts and maritalsatisfaction among US workers: Does stress amplification matter? Journal of Family andEconomic Issues, 36(1), 21-33.
7

Mueller, C.W., Parcel, T.L., & Pampel, F.C. (1979). The effects of marital-dyad status
inconsistency on women’s support for equal rights. Journal of Marriage and Family 41(4),779-791.
Nemoto, K. (2016). Too Few Women at the Top: The Persistence of Inequality in Japan. Cornell
University Press, London.
Oshio, T., Nozaki, K., & Kobayashi, M. (2013). Division of household labor and maritalsatisfaction in China, Japan and Korea. Journal of Family and Economic Issues, 34(2), 211223.
Parsons, T., & Bales, R.F. (1955). Family, Socialization, and Interaction Process. Free Press; NewYork.
Schultz, T.P. (2002). Wage gains associated with height as a form of health human capital.
American Economic Review 92(2), 349-453.
Simpson, I.H., & England, P. (1981). Conjugal work roles and marital solidarity. Journal of
Family Issues 2(2), 180-204.
Sohn, K. (2015 a). The height premium in Indonesia. Economics and Human Biology, 16, 1-15.
Sohn, K. (2015 b). The value of male height in the marriage market. Economics and Human
Biology, 18, 110-124.
Sohn, K. (2016). Does a taller husband make his wife happier? Personality and Individual
Differences, 91, 14-21.
Steckel, R.H. (1995). Height and the standard of living. Journal of Economic Literature, 33, 19031940.
Tao, H.L. (2014). Height, weight, and entry earnings of female graduates in Taiwan. Economics
and Human Biology 13, 85-98.
Yamamura, E., Smyth, R., & Zhang, Y. (2015). Decomposing the effect of height on income in
China: The role of market and political channels. Economics and Human Biology 19, 62-74.
Yamamura, E., & Tsutsui. (2017). Comparing the role of height of men and women in the marriage
market. Forthcoming in Economics and Human Biology

8Indirect effectQuarrel with partner

Gaps with partner

Evaluation about partner(Division of labor after marriage)
Direct effectFig. 1. Difference of effect of gap with partners between before and after the marriage and its direct and indirect channels.

1

50
40
Percent
20
30
10
0
1

2

3

4

5

6

t

Fig. 2. Distribution of Evaluation about one’s partner.

2

7

Table 1
Basic statistics of variables used in the estimation and the mean values and standard deviations.
Variables
Definition
Evaluation
Question “how do you evaluate your partner?”
There are 7 choices;
1(one cannot be worse as partner) -7(one cannot better as partner)
Quarrel
It takes 1 if respondents have a big quarrel with your partner within amonth, otherwise 1.
Gap of height
Absolute value of (respondent’s height – partner’s height)

Mean
5.46

S.D
1.11

Max
7

Min
1

0.03

0.16

1

0

13.6

7.03

40

0

Gap of schooling
years

Absolute value of (respondent’s schooling years– partner’s schooling
years

1.54

7.03

9

0

Gap of ages

Absolute value of (respondent’s ages– partner’s ages)

5.17

6.51

45

0

IncomeAnnual income (Hundred thousand yens)

41.3

159.5

8000

0

Married

1 if one currently get married, otherwise 0

0.16

0.37

1

0

3

Table 2(a)Mean difference test for the evaluation about partner between those with large gap of height andothers.
Large gap of
OthersDifference ofAbsolute theight(2)−(1)values(1)(2)
Before married (I)
5.49
5.35
−0.13
4.26***
After married (II)

5.47

5.59

Difference of (II)−(I)

−0.02

0.23

Absolute t-values

0.33

5.03***

0.11

2.38**

Note: ** and *** significant at the 5% and 1% levels.

Table 2(b)Mean difference test for the evaluation about partner between those with large gap of schoolingyears and others.
Large gap of
OthersDifference ofAbsolute t-values
schooling years (1)(2)−(1)(2)
Before married (I)
5.40
5.48
0.08
2.48**
After married (II)

5.43

5.69

Difference of (II)−(I)

0.13

0.21

Absolute t-values

0.85

4.79***

0.25

5.25***

Note: ** and *** significant at the 5% and 1% levels.

Table 2(c)Mean difference test for the evaluation about partner between those with large gap of ages andothers.
1

Large gap of ages
(1)

OthersDifference of(2)−(1)

Absolute tvalues

Before married (I)

5.43

(2)
5.43

−0.0010.05

After married (II)

5.61

5.48

−0.13

2.63**

Difference of (II)−(I)

0.18

0.05

Absolute t-values

3.71***

1.37

Note: ** and *** significant at the 5% and 1% levels.

2

Table 3 Determinants of the frequencies of quarrel with one’s partner (Panel model).
(1)
(2)
(3)
(4)
Gap of height−0.003***−0.001**Married(−3.37)(−1.95)
Gap of schooling years−0.009***−0.007***Married(−3.09)(−2.57)
Gap of ages
0.001
*Married(1.13)
Gap of height−0.0001
0.0001(−0.19)(0.24)
Gap of schooling years
0.002
0.004
(1.00)(1.58)
Gap of ages
−0.0004(−0.48)
Income0.050***
0.049***
0.049***
0.049***(5.56)(5.35)(5.46)(5.44)
Married−0.024***0.025−0.037*** −0.035***(−4.41)(1.55)(−3.90)(−3.75)Time-period dummies
No
No
No
No

(5)

(7)
−0.002***(−2.67)0.001(1.13)(6)−0.003***(−3.57)−0.009***(−3.09)0.001(1.15)(8)(9)−0.0007(−0.99)0.048***(5.45)−0.030***(−3.97)
No

0.049***(5.29)
0.043***(2.62)
Yes

0.049***(5.30)
0.019(1.48)
Yes

0.049***(5.29)
0.006(0.72)
Yes

0.048***(5.28)−0.016*(−1.84)Yes−0.008***(−2.84)0.001(0.94)

Hausman-test

P=0.28P=0.09P=0.18P=0.29P=0.49P=0.002

P=0.004

P=0.006

P=0.018

Random effects

Yes

No

Yes

Yes

Yes

No

No

No

No

Observations
9,855
9,855
10,492
9,882
10,733
9,855
10,492
9,882
10,733
Within R-squared
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
Note: Numbers in parentheses are t-statistics calculated using robust standard errors clustered. *, **, and *** indicate significance at the 10%, 5%, and
1% levels. Line of “Random effects” is “Yes”, if the Random effects results are preferred and so reported because Hausman-test does not show
systematic difference of coefficients between Random and the Fixed model. Line of “Random effects” is “No”, if the Random effects results are notpreferred. Constant is included but not reported when the Random effect model is used. Gap of Height, Gap of ages and Gap of ages are cannot bereported because they are completely controlled by the individual fixed effects if the Fixed effects model is used. Coefficient of Income is multiplied by
1000.

1

Table 4.

Determinants of the evaluation about one’s partner (Panel model).
(1)
(2)
(3)
(4)
Gap of height−0.006−0.006**Married(−1.57)(−1.71)
Gap of schooling years−0.028**−0.027***Married(−2.19)(−2.10)Gap of ages
0.005
*Married(0.93)
Gap of height
0.011*
0.013**
0.013**(1.90)(2.09)(2.14)
Gap of schooling years−0.025−0.019−0.019(−1.19)(−0.88)(−0.86)
Gap of ages
−0.008−0.009(−1.17)(−1.30)
Income
0.022
0.019
0.028
0.020
(0.47)(0.40)(0.61)(0.42)
Married−0.035
0.080
0.046
0.015
(−1.28)(1.14)(0.83)(0.40)
Time-period dummies
No
No
No
No

(5)

(7)
−0.007*(−1.84)−0.007(−1.03)0.030(0.63)−0.056(−1.52)No(6)−0.006*(−1.69)−0.027**(−2.13)0.006(1.06)
0.012**(2.12)−0.021(−0.97)−0.002(−0.30)0.020(0.43)
0.143*(1.96)
Yes

0.030(0.65)
0.106*(1.81)
Yes

0.022(0.46)
0.038(0.45)
Yes−0.001(−0.13)0.031(0.66)−0.012(−0.31)
Yes

0.005(0.86)(8)(9)−0.026**(−2.03)0.006(1.10)

0.013**(2.22)−0.019(−0.89)Hausman-test

P=0.24

P=0.63

P=0.60P=0.44

P=0.26

P=0.39P=0.33

P=0.25

P=0.39Random effects

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Observations
6,667
6,667
7,135
6,667
7,166
6,667
7,135
6,667
7,166
Within R-squared
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
Note: Numbers in parentheses are t-statistics calculated using robust standard errors. *, **, and *** indicate significance at the 10%, 5%, and 1% levels.
Line of “Random effects” is “Yes”, if the Random effects results are preferred and so reported because Hausman-test does not show systematicdifference of coefficients between Random and the Fixed model. Line of “Random effects” is “No”, if the Random effects results are not preferred.
Constant is included but not reported. Coefficient of Income is multiplied by 1000.

2

Table 5. Determinants of the evaluation about one’s partner when quarrel is included as independent variable (Panel model).
(1)
(2)
(3)
(4)
(5)
(6)
(7)
Quarrel−0.17***−0.19***−0.16***−0.18***−0.17***−0.20***−0.16***(−3.68)(−4.28)(−3.42)(−4.11)(−3.81)(−4.43)(−3.59)Gap of height−0.006−0.006*−0.007*−0.007**Married(−1.55)(−1.71)(−1.72)(−1.89)Gap of schooling years−0.029**−0.027**−0.028**−0.027***Married(−2.22)(−2.10)(−2.15)(−2.03)
Gap of ages
0.005
−0.0050.006*Married(0.91)(−1.56)(1.11)
Gap of height(8)−0.19***(−4.21)0.006(1.11)

Gap of schooling years
Gap of ages
IncomeTime-period dummies
Hausman-test
Random effects

0.024(0.52)
0.074(1.03)
No
P=0.0007
No

0.034(0.74)
0.035(0.62)
No
P=0.0001
No

0.020(0.48)
0.003(0.08)
No
P=0.0001
No

0.037(0.76)−0.059(−1.56)No
P=0.0001
No

0.025(0.52)
0.146*(1.96)
Yes
P=0.022No

0.036(0.75)
0.113*(1.89)
Yes
P=0.003No

0.025(0.53)
0.080*(1.89)
Yes
P=0.0006
No

0.037(0.76)−0.010(−0.25)Yes
P=0.004
No

Observations
Within R-squared

6,667
0.01

7,135
0.01

6,667
0.01

7,166
0.01

6,667
0.01

7,135
0.01

6,667
0.01

7,166
0.01

MarriedNote: Numbers in parentheses are t-statistics calculated using robust standard errors clustered. *, **, and *** indicate significance at the 10%, 5%, and
1% levels. Line of “Random effects” is “Yes”, if the Random effects results are preferred and so reported because Hausman-test does not show
systematic difference of coefficients between Random and the Fixed model. Line of “Random effects” is “No”, if the Random effects results are notpreferred. Constant is included but not reported when the Random effect model is used. Gap of Height, Gap of ages and Gap of ages are cannot bereported because they are completely controlled by the individual fixed effects if the Fixed effects model is used. Coefficient of Income is multiplied by
1000.
3

Table 6.

(a) Decomposition of gap of height on evaluation about partner.
Difference of effect of height gap between before On quarrel
and after marriage.
Effect of a 1 cm increase in gap of height(A)
Effect of quarrel occurrence on evaluation(B)
Indirect effect of a 1 cm increase in gap of height(C) =(A)*(B)Direct effect of a 1 cm increase in gap of height onevaluation (D)Total effect of a 1 cm increase in gap of height onevaluation (C)+(D)On evaluation−0.003−0.1760.001−0.007−0.006(b) Decomposition of gap of schooling years on evaluation about partner.
Difference of effect of schooling years gap between On quarrel
before and after marriage.

On evaluation−0.009Effect of a 1 year increase in gap of schoolingyears (A)
Effect of quarrel occurrence on evaluation(B)
Indirect effect of a 1 year increase in gap of
schooling years (C) =(A)*(B)Direct effect of a 1 year increase in gap of
schooling years on evaluation (D)Total effect of a 1 year increase in gap of
schooling years on evaluation (C)+(D)−0.1760.002−0.028−0.026

Notes: Values are calculated based on results of (6) of Table 3 and (5) of Table 5.

4