Discussion Paper Series

University of Tokyo

Institute of Social Science
Panel Survey
東京大学社会科学研究所 パネル調査プロジェクト
ディスカッションペーパーシリーズ

Is Online Mate Selection Linked to More
Egalitarian Marriages in Japan?
Gina Potarca（University of Liverpool）
Hiroshi Ishida（University of Tokyo）

October 2023
No.169東京大学社会科学研究所
INSTITUTE OF SOCIAL SCIENCE UNIVERSITY OF TOKYOInstitute of Social Sciences
University of Tokyo
Panel Survey Project Discussion Paper Series No. 169
October 2023

Is Online Mate Selection Linked to More Egalitarian Marriages in Japan?
Gina Potarca(University of Liverpool)andHiroshi Ishida(University of Tokyo)
Abstract
Objective: This study explores how online matchmaking in Japan, an emergent way of
meeting potential partners substituting for declining traditional structures of mateselection and potentially reinventing courtship rules, could aid the shift towards lessgendered marital unions.
Background: In Japan, persistent norms in favor of the male breadwinner model currently
co-exist with calls for more gender-egalitarian unions and a rising demand for women’s
income-earning capacity.
Method: Based on a sample of 2,941 married couples from the Japanese Life Course
Panel Surveys (2007-2016), we examine the probability of engaging in an egalitariandivision of housework, while also accounting for observed selection into internet dating
via entropy balancing methods.
Results: Results show that compared to marriages formed elsewhere, marriages initiatedonline reported more equal sharing, but only when the wife was university-educated.
Conclusions: Online dating enlarges the field of possibilities, allows for a moregender-disruptive courtship, and affords women, typically in undersupply, a structuralmating advantage, which leads to a better negotiation of gender in the dating phase and,as results show, later in marriage.
Implications: Considering recent trends of declining marriage, this study highlights theimportance of digital innovations in partner search technology in assisting Japanese
adults, especially highly educated women, in making more egalitarian union choices.

Acknowledgements
Acknowledgements: This study benefited from the support of an Ambizione grant from the
Swiss National Science Foundation (grant number: PZ00P1_174197). This research was also
supported by an KAKENHI Grant-in-Aid for Specially Promoted Research (Grant Numbers
JP25000001 and JP18H05204) and Scientific Research (S) (Grant Numbers JP18103003 andJP22223005) from the Japan Society for the Promotion of Science. The research support in
conducting the Japanese Life Course Panel Surveys (JLPS) was obtained from the Instituteof Social Science, University of Tokyo, and The Outsourcing, Inc. The Research Ethics
Review Board at the Institute of Social Science, University of Tokyo, approved the JLPS
study. The permission to use JLPS data is obtained from the Management Committee of theJapanese Life Course Panel Surveys.
0INTRODUCTION
Japan is undergoing significant demographic transformations in the area of marriage,
with increasing numbers of people marrying late, marrying less, or retreating from romantic
and sexual relationships altogether (Raymo et al., 2015). Japan’s late singlehood rate has
been recently identified as one of the highest in East Asia (Esteve et al., 2020). Explanations
for these trends include a persistent demand for high-earning male partners (Yamada, 2017)
in a context of increased precarious employment among men (Piotrowski et al., 2015), butalso high opportunity costs of marriage and childbearing for women, who still
disproportionately bear the burden of childrearing and domestic work (Kan & Hertog, 2017).
Some studies also point out growing discrepancies between men and women in terms ofwhat they expect from a partnership, with women more often demanding more egalitarian
relationships (Piotrowski et al., 2019; Yu & Hertog, 2018), or placing more emphasis on
emotional compatibility in unions than men (Dalton & Dales, 2016). Despite thesemismatches, marriage remains highly desirable among Japanese adults (Miwa, 2019).
Although a decline in marriage intentions has been recently observed in the 2021 Japanese
National Fertility Survey (compared to the one collected in 2015), the decrease is minimal,
with less than a five-percentage point drop; the majority (over 80%) of never-married
individuals aged 18-34, including both men and women, still express a desire to get married(National Institute of Population and Social Security Research, 2022). Some argue, in fact,that recent trends are not necessarily driven by an intentional retreat from marriage, butrather by “an unplanned drifting into singlehood” due to limited access to partner options(Raymo et al. 2021, 69).
On the backdrop of these marriage market shortages, the decline of previous
structures of mate selection (i.e., family, work), and rising individual preferences towards aless rigid dating culture (Beck et al., 2014), recent years have witnessed the onset of the
konkatsu (i.e., spouse hunting) culture (Castro-Vazquez 2016; Dalton and Dales 2016; Miwa
and Tanaka 2020) and a general increase in more liberalized marriage markets. The
popularity of formal matchmaking services (e.g., through miai parties, where people withstrong intentions of getting married can meet potential partners), or more informal group
dating (gokon) options, reflects the shift from family-driven and work-related mate selection
to more individualistic and agentic ways of searching for partners (Yang, 2017). Online
matchmaking sites represent one modality to have emerged within the burgeoning industryof partner hunting in recent years (Farrer & Gavin, 2009; Yu & Hertog, 2018). Digital dating
is an important means of searching for partners particularly for singles with reduced time
availability or, some argue, limited communication skills (Nemoto et al., 2013). Though we
do not yet notice the massive take-up seen in the West, as for instance, in the U.S. (Rosenfeld
et al. 2019), recent survey data indicates that internet dating accounts for 13.6% of recent
marriages in Japan. In Western contexts, research has already identified the impact of online
mate search and selection on various outcomes, such as timing of marriage, the marriage gap
or assortative mating (Potarca, 2021; Rosenfeld, 2017; Thomas, 2020). For Japan, researchso far has looked at the online dating records and partner preferences of users enrolled on amatchmaking agency (Yu & Hertog, 2018), but no attention has yet been given to how
digital mate selection may support the transition towards a more modern dating culture andmore gender-progressive marital practices. Given that Japanese families are now undergoinga transitional phase from gender-traditional towards gender-egalitarian arrangements(Esping-Andersen & Billari, 2015; Fukuda et al., 2020), the Internet may be an arena where
gender innovation plays out the most (Beck et al., 2014), as recently seen in a study using1German data (Potarca & Hook, 2023). This may occur as a result of a more liberal space ofinteraction, structural conditions of anonymity, a wider dating pool and male-biased sex
ratios (i.e., more men than women), leading to more progressive courtship dynamics and amore assertive expression of preferences, particularly for women with a high level of
education. It can be expected that, compared to women with less education, those with auniversity degree take better advantage of online dating options to more freely revert
hierarchy and power in gender relations and create better suited unions, as seen in Germany
and Switzerland (Potarca 2020, 2021).
In the context of women’s increasing levels of education (Hannum et al., 2019;
Ishida, 2022; Kojima, 2013; Nakamura, 2022), and overall changes in the landscape of
marriage, the current study investigates how online dating marriage markets shape thedivision of housework among married couples in Japan. We specifically examine theprobability of equally sharing time spent performing routine household tasks (e.g., preparing
meals, doing laundry, cleaning, grocery shopping). Using random effects logistic regression
models and data on 2,941 married respondents from the Japanese Life Course Panel Surveys,
we first scrutinize whether couples established via the internet have more egalitarianpractices of dividing household labor compared to couples formed offline, while also
accounting for observed selection into online dating via entropy balancing weights. To
examine if this effect is universal to modern intentional dating or only relevant to online
matchmaking, we divide the offline category into two groups and compare couples that met
through online dating to both those who met in conventional ways (i.e., labelled as “offline
traditional”), and through offline matchmaking (i.e., grouping together both the formal miai
parties and encounters facilitated by marriage agencies, and the informal gokon
matchmaking options). Finally, we examine whether patterns differs by wife’s level of
education. In particular, we assess whether the association between online matching and theegalitarian division of housework is more conspicuous among highly educated women.
This study makes several contributions. First, by examining whether online dating
challenges or perpetuates traditional expressions of gender within marriage in Japan, thisstudy adds to current scholarship aiming to understand contemporary partnering in a country
paradoxically showcasing both stability and progress (Raymo et al., 2021). Second, as
Dalton and Dales (2016) remark, the patterns observed on online dating platforms, typicallyless constrained by social control, can reveal how masculinity and femininity are currently
being (re-)constructed within marriage and families in Japan. The results of this study would
then also inform contemporary patterns occurring in other East Asian countries undergoingcomparable demographic transitions (Yu & Hara, 2020). Lastly, in the context of
below-replacement fertility, a rapidly aging society, and anticipated labor shortages, adding
to our understanding of how marriage is experienced by highly educated women, an
expanding demographic group, is of utmost importance (Brinton and Oh 2019). This study
hence tackles the important and timely issue of gender enactment in the realm of marriage
and family in a rarely examined non-Western context.
THEORETICAL BACKGROUND
Division of Unpaid Labor
Similar to other East Asian countries, Japan has long encouraged a traditional
patriarchal family model (Krumbein, 2021; Raymo et al., 2015, 2021). Although the malebreadwinner model is increasingly unattainable for many men, Japan’s enduring pro-workconservatism and adherence to gender essentialist norms (Brinton & Lee, 2016) result in2

individuals being rigidly assigned and expected to fulfill specific marital roles based on theirgender: men as breadwinners, women as homemakers and caretakers. Japanese men arehence still expected to fully commit to a full-time job (Matsuda, 2019) while women’s
economic contribution to the household mostly takes the form of a secondary wage (Brinton
et al., 2021). Even when encouraged to pursue employment, women are expected to exit thelabor market upon marriage and motherhood (Raymo & Lim, 2011), and take up
responsibility for both housework and childcare tasks (Kan & Hertog, 2017). Overall,
progress towards narrowing gender gaps in both paid and unpaid work has been stagnant,mirroring the situation in Western countries (Kan et al., 2022).
Though some changes in expectations and behaviors are happening, such as men
returning home from workplace earlier (Fuwa, 2020), becoming more involved in parenting(Ishii-Kuntz, 2021), or greater priority given to emotional compatibility (rather than justfinancial security) in unions (Dalton & Dales, 2016), these are not yet substantial orpervasive (Piotrowski et al., 2019). Furthermore, change in individual preferences towards amore progressive division of labor has not been accompanied by change in family-related
policies or workplaces (Fuwa, 2020; Piotrowski et al., 2015). Men are not only still reluctant
to embrace an egalitarian division of household labor (Piotrowski et al., 2019), but their longhours and after-hour engagements (Fuwa, 2019; Kato et al., 2018) leave little space forhousework contributions. In addition to this, housework is rarely outsourced, even in
high-income households (Kolpashnikova & Koike, 2021). In comparative terms, Japan, as
well as Korea, parallel Southern European welfare regimes, as they heavily rely on family
for care support, which hinders women's participation in the workforce (Kan et al., 2022).
The Online Partner Market in JapanThe recent rise in partner search technology, such as dating websites, phone apps or
online social networks, however, may have ushered in certain partnering and genderinnovations. Traditionally, partner selection in Japan was intermediated by family (Matsuda,2019) or work (Nemoto et al., 2013). Given the gradual failure of these traditional marriage
markets (Raymo et al. 2021; Uchikoshi and Raymo 2021), the internet, as a more efficientand modern dating market, one that provides a wider set of opportunities, easy access ormobility (Finkel et al., 2012), had great potential to displace them, as it did in several
Western contexts (e.g., U.S., Switzerland). Why the internet has not yet taken off as leading
marriage market in Japan (Miwa & Tanaka, 2020), in the same way as it has in the West,may have to do with several reasons, including online dating not yet being viewed as reliable
as traditional intermediaries (Dalton & Dales, 2016), its lingering stigma, and people still
holding preconceived notions about the type of singles that resort to digital partner search,and the type of sexual behaviors harbored online (Mantell, 2018).
Nevertheless, some point out that internet dating did reach a fair level of popularity inJapan as well (Yu & Hertog, 2018), and that seeking partners online is representative of achanging culture of dating, the transition towards more agentic, individualized personal
choices, and a diversification of intimate needs (Endo 2018, Yang 2017). The decline intraditional marriage markets left no choice to modern-day singles but to seek alternative
spaces of interaction and partner selection, which, in the case of digital partner markets, alsopresent a different set of rules and a different ecological structure. In addition to facilitating
anonymized encounters with potential partners, allowing singles who work and have no timeto search for partners to easily access a large and diverse pool of eligible candidates, theinternet has the advantage of also minimizing the social costs of interaction (Farrer & Gavin,2009), which is often cumbersome for young Japanese adults with poor communication3

skills (Nemoto et al., 2013) and limited inter-gender offline interactions (Endo, 2018). But
especially by allowing for more personalized choices, that do not necessarily conform withtraditional social scripts (Murai, 2018), digital mate selection may have an impact on
increasing gender equity in the division of household labor, and assist women in better
realizing gender-progressive partner preferences. Internet matchmaking may facilitate theformation of more degendered marriages through several potential mechanisms.
First, dating websites and apps typically attract more men than women (e.g., Potarca,
2020; Skopek et al., 2011). The oversupply of men in digital partner markets may have to dowith overall gender digital divides (e.g., men are more likely to have access to and better use
digital technologies), but also the experience of dating online itself, which poses more risksof harassment and bothersome contact for women than men (Anderson et al., 2020). Morefavorable sex ratios online, however, may grant women more power in interactions with men
and encourage a more assertive expression of preferences. According to Guttentag andSecord’s (1983) theory of imbalanced sex ratios, which is similar to demographic/
macrostructural opportunity theory (South & Trent, 1988) and marriage squeeze theory(Akers, 1967), unequal sex ratios have an impact on the distribution of power between men
and women. For example, when there is an undersupply of women in online spaces, it cancreate a tilt in the gender power balance, giving women an advantage in the negotiation ofrelationships both at the outset and later in marriage. Conversely, men in oversupply may bemotivated to actively engage in these negotiations. Empirical research has indeed
demonstrated a connection between imbalanced sex ratios and the bargaining of fertility
goals (Ogasawara & Komura, 2021) or division of household responsibilities among couples(Stauder & Röhlke, 2022).
Second, the anonymity, reduced intrusion from family and friends and increased
privacy offered by online platforms can foster a greater inclination, particularly among
women, for risk-taking and self-affirming in interactions with men. While there is evidenceof online replication of gendered ways of relating between men and women, such as men
predominantly initiating first contact (Dinh et al., 2022), we contend that internet dating also
provides opportunities for deviations from such traditional scripts. Several qualitative studies,for instance, reveal that women perceive greater empowerment and agency in theircommunication with men as the primary advantages of using digital partner search tools
compared to conventional non-digital methods of selecting partners (Cooper & Sportolari,
1997; Dwyer et al., 2020; Lawson & Leck, 2006). Since engaging in moregender-progressive courtship dynamics influences the enactment of gender later in marriage(Lamont, 2020), we believe that the internet may help women set up relationships where
they can more successfully communicate and assert preferences, both in the courtship phaseand later, during negotiations of housework in marriage.
We therefore put forward our first hypothesis, claiming that online-formed couples are
more likely to report a gender egalitarian division of housework than couples formed offline,
either in traditional ways or via offline dating services such as gokon, miai parties ormarriage agencies (Hypothesis 1). Though matchmaking through gokon and miai events also
represents a non-conventional way of selecting partners, they provide a less dense and lesswide dating pool (e.g., gokon parties often involve friends of friends) than online dating.
More importantly, they do not remove the direct interference of third parties (as friends often
mediate miai and gokon meetings) and subsequent social pressures to conform to traditional
courtship rules. Meeting someone through a marriage agency can emulate some of thespecificities of online dating (e.g., matching with potential partners from outside one’s social
circle, less meddling of family and friends). It cannot, however, provide key affordances4such as anonymity or a greater sense of agency over the selection process, which foster
greater ease and willingness to innovate and assert non-conventional preferences.
Selection into Internet Matching
We also anticipate that several selection processes may partially explain why
couples that formed online might be more egalitarian than those formed elsewhere. First,
online dating typically appeals to singles who were previously married and those who arechildless (Robnett & Feliciano, 2011; Sautter et al., 2010). As earlier mentioned, it may alsointerest those with a selectively progressive gender role orientation (Dwyer et al., 2020) and
who resort to internet dating services to better meet their demand for more egalitarian
partners. Given that these profile characteristics are strong predictors of more equal sharingof housework tasks (Greenstein, 1996; Kleider, 2015; Yavorsky et al., 2015), we need toadjust for this potential covariate imbalance.
Furthermore, one’s age, education, employment status, and the area in which singles
reside (e.g., urban versus rural, center versus periphery) may impact access to mating
opportunities and ultimate partner search strategy (Potârcă & Mills, 2015; Sautter et al.,2010; Yu & Hara, 2020), but also speak of social and normative influences on how
individuals approach gender issues in general and the division of household labor inparticular (Coltrane, 2000; Kolpashnikova & Koike, 2021; Stauder & Röhlke, 2022). Finally,
health difficulties and limited size of one’s social network may also motivate both thedecision (or necessity) to date online and the way couples share housework tasks (Podor &Halliday, 2012; Rözer et al., 2018). Nevertheless, even though selection on observablesocio-demographic, residential and attitudinal characteristics may contribute to anticipatedonline dating effects, we also expect the association between meeting online and housework
to still be significant after adjusting for differences between couples formed through internet
dating and couples formed using offline methods (Hypothesis 2).
Wife’s Educational Level
Finally, we argue that the online dating effect may be particularly visible among
married couples in which the wife is high-level educated (Hypothesis 3). Owing to thefemale educational expansion, the stock of eligible Japanese women with university
education in the marriage market has been progressively increasing in recent decades(Nakamura, 2022; Yoshida, 2010). In the past, given the persistence of the male breadwinnermodel (Piotrowski et al., 2020) and a preference for unions in which men hold theeducational advantage, i.e., female hypergamy (Matsuda, 2019), high-educated women used
to face poor marriage prospects (Raymo & Iwasawa, 2005). Recent evidence, however, haspointed out the reversal of the previously negative educational gradient in marriage forwomen in Japan (Fukuda et al., 2020; Miwa, 2022; Uchikoshi & Raymo, 2021).
Nevertheless, when it comes to the division of housework, better education does notnecessarily guarantee better outcomes. A recent comparative study, for instance, showed thathigher levels of education were associated with fewer hours of housework for married
women in the U.S. and Taiwan, but not in Japan (Kolpashnikova and Koike 2021). Stillsubject to strong gender conditioning in offline spaces of interactions, progressively minded
women with high-level training may therefore feel compelled to seek out alternative partner
markets (i.e., online) to experience couplehood on different terms and establish unions inwhich the male partner potentially contributes more to domestic tasks. The internet may thus
assist highly educated women in better realizing gender-progressive partner preferences.
Using data from Germany, Potarca (2021) showed that university-educated women who used5

online dating increased their chances of marrying, partly as a result of better matching on
egalitarian gender attitudes. For Switzerland, it was also found that highly educated women
were more likely to match up with lower educated men if they met on dating apps (Potarca2020). These findings showcase online dating as an arena where well-educated womenmanage to a noticeable extent to subvert normative ways of partnering. Beyond selection
effects, however, women with a university degree may be better skilled than the lesseducated at communicating online and setting up more egalitarian relationship dynamics thatwould ultimately lead to a more equal split of domestic work. In short, the third hypothesis
predicts that the online dating effect of promoting an egalitarian division of housework ismore conspicuous among highly educated women.
METHODSData
We use the Japanese Life Course Panel Surveys of the Youth sample (JLPS-Y) and of
the Middle-aged sample (JLPS-M), which are ongoing annual nationally representative panel
surveys conducted by the Institute of Social Science at the University of Tokyo. The surveys
started in 2007 with a joint sample of 4,800 individuals aged between 20–34 years (JLPS-Y)
and 35–40 years (JLPS-M), respectively. A supplement of 963 respondents was added as of
the fifth wave in 2011. The response rate for the first wave was 34.5% for the JLPS-Y and40.4% for the JLPS-M, and then ranged from 76.0% to 80.7% for the JLPS-Y and from
79.0% to 88.0% for the JLPS-M, respectively, in subsequent waves. The response rate for the
first wave of JLPS-Y is fairly low, and though a report looking at sample composition indeed
revealed an overrepresentation of the highly educated, the extent of the bias was deemed
trivial (Miwa, 2008). In both surveys, participants were asked about work, family,socioeconomic status, attitudes, and values. Those who were in a partnership/ marriage werealso asked about where they met their partner/ spouse. This study uses ten waves of data
(2007-2016) that are publicly available. After eliminating respondents who are unpartnered
and those in non-marital unions, those in marriages formed before 1995 (i.e., thepost-Internet dating age), cases with missing information, the final analytical sample
consisted of 2,689 married respondents with 12,022 observation points.
Measures
Dependent Variable
Time spent doing household labor is evaluated via the question: “How often do you
perform the following activities? Prepare meals; Do laundry; House cleaning; Grocery
shopping. Respondents could provide answers ranging from: 1) Everyday; 2) 5-6 days per
week; 3) 3-4 days per week; 4) 1-2 days per week; 5) 1-3 days per month; 6) Almost never.
First, given that these items were not included in wave 2 (2008) and wave 4 (2010), we
copied answers from previous waves in most cases, and when that was unavailable, fromfollow-up waves. Second, similar to Geist (2005), we used information from these variables
and partners’ gender to create three-category indicators distinguishing between 1) the female
partner spending more time; 2) both partners spending equal time (e.g., they both spend
three-four days per week on such tasks); and 3) the male partner spending more time on a
specific household labor task. Second, we computed an average score based on all four typesof activities, which ranges from 0 to 2. Third, given the left skewed distribution of scores(e.g., 63.1% of respondents have 0 as average score) and an insufficient number of cases for
all values across each meeting context sub-group (e.g., there are only 6 observations that6

have an average score of 2 for online-formed marriages), we created a binary indicator
where value 1 (a progressive or egalitarian division of household labor) includes cases where
the average score was equal or higher than 0.75, meaning that there are at least three
activities that are equally shared.
Independent Variables
To assess the meeting context of couples, we rely on a measure asking: “How did
you first meet your spouse?”. Respondents could provide multiple answers from thefollowing list: 1) Introduced by parent/sibling; 2) Introduced by relative other thanparent/sibling; 3) Introduced by friend/acquaintance/childhood friend; 4) Introduced bycolleague or boss at work; 5) Met at work; 6) Through school classes, groups, and activities;7) Through a part-time job; 8) Through a hobby class; 9) Through a group dating party(gōkon); 10) Through a meeting arranged for finding potential partners (miai, or an arranged
marriage); 11) Through a party that is arranged to meet somebody for potential partners(miai party); 12) Met via the Internet or cellular phone; 13) Met on a street in town or during
a trip; 14) Through a marriage consultation service or marriage agency; 15) Other. Givensample limitations, we recoded the measure into a three-category variable, distinguishing
between 1) meeting in conventional, nondigital ways (i.e., “offline traditional”) in general (n= 2,599 respondents); 2) meeting through a group dating party (n = 244), a miai party (n =91) or the less frequent cases (n = 41) of meeting through a marriage agency (i.e, “offline
dating services”); and 3) meeting through online dating services (n = 133). We removed thefew cases of overlap between the last two categories, e.g., couples that met both online andthrough a group dating party.
When investigating the selectivity of couples that formed in non-conventional ways
(as described in the Analysis section), we rely on a series of covariates that may have
impacted both the probability of being part of an online-formed marriage and an egalitarian
distribution of household labor. This includes respondent’s gender, age, marital duration (inyears), wife’s and husbands’ education, the presence of resident children, previous marital
experience, living in an urban environment, residing in the Kanto region (living in Japan’s
political and economic urban center, which includes the capital of Tokyo, seen as proxy ofless traditional views on family in general, but also as exposure to presumably larger local
partner markets), satisfaction with friends (an indicator of social network strength), healthstatus (which, when precarious, could influence the decision to invest in online partner
search rather than look offline), and exposure to egalitarian gender values early on. For thelatter, instead of using an indicator of respondent’s current gender attitudes, which would
entail a high risk of endogeneity, we rely on a measure pertaining to a period prior to
marriage, more specifically respondents’ exposure to how gender was enacted in their familyof origin early on. Here, we use information from items asking respondents if, when they
were 15 years old (when they graduated middle school), their fathers took part inhousekeeping but relied on their mother for childrearing, they took part in childrearing but
not housekeeping, or they took part in both housekeeping and childrearing. We synthesized
the answers from both items to create a binary indicator of father’s participation inhousework (irrespective of their involvement in childcare).
For both partners’ education, we distinguish between graduates of: 1) middle/ highschool education; 2) vocational school/ junior college education; or 3) university or higher.
Similar to Raymo and Iwasawa (2005), we adopted the conventional approach of combining
junior college graduates and vocational school graduates into one category. To assess
whether the couple had any resident children, we use information that was directly provided
in waves 2007, 2012-2016, and indirectly from household roosters in remaining waves.
7

Information on previous marital experience (i.e., whether the respondent was divorced or
widowed) was taken from the marital status variable. Acting as proxy for social network
density, satisfaction with friends was measured via a question asking respondents to rate howsatisfied they were of their relationships with friends on a scale containing the following five
options: 1) satisfied, 2) somewhat satisfied, 3) neither satisfied nor dissatisfied, 4) somewhat
unsatisfied to 5) unsatisfied. To deal with sample size limitations and a reduced number ofcases within certain categories for online-formed couples, we recoded the variable on athree-point scale, grouping the first two answers in a single ‘satisfied’ category and the last
two answers in a single ‘unsatisfied’ category, while retaining the neutral middle point.
Health status is measured via the question “How do you generally feel about your healthcondition?”, with the following possible answers: 1) excellent, 2) good, 3) average, 4) notvery good, and 5) poor. As with the previous variable, we recoded health status on athree-point scale as follows: 1) good health, 2) average, 3) poor health.
In addition to accounting for the selectivity of online dating via entropy balancing
weights (as explained in the next section), the main analyses of equal sharing of housework
includes several basic controls, such as respondent’s gender, division of paid work (seebelow for details), subjective standard of living (based on a question measured on a 5-point
scale: “How do you evaluate your household’s current standard of living?”, which we
recoded to differentiate between 1) poor, 2) average, and 3) wealthy), and partners’
educational pairing. To measure the division of paid work, we used information on bothspouses’ employment status and distinguished between: 1) male breadwinner households(where the husband was full-time employed or self-employed and the wife was either
working part-time or not at all); and 0) all other arrangements, largely comprised of dual
earner couples (in which both spouses are either full-time employed or self-employed), thefewer cases of female breadwinner households (where the husband was either working
part-time, was unemployed or other, and the wife was full-time employed or self-employed)
and other cases. Given the modest sample size of marriages that started online, we could notoperationalize the division of paid work in greater detail. Partners’ educational pairing wasconstructed based on both spouses’ education, distinguishing between: 1) hypergamy (themale partner is better educated), 2) homogamy (partners have a similar level of education),and 3) hypogamy (the female partner is better educated). Here, we employed a measure ofcouples’ relative education, rather than solely considering the husband's education, topartially gauge the distribution of (economic) power within the marital relationship. Our
assumption is that wives who possess an educational advantage tend to earn more, enablingthem to implement a less conventional division of domestic chores.
ANALYSIS
The first analytical step is to check and adjust for differences in observed characteristics
between respondents who met their partner through online dating and those who met theirspouse in offline traditional ways or offline dating services. Our aim is to minimize the riskof significant differences in the likelihood of equal sharing of housework being attributable
to underlying differences (i.e., selection bias) in the characteristics of respondents who met
their partner in various ways rather than to the direct effect of meeting context itself. To
achieve this goal, we use entropy balancing (EB) (Hainmueller 2012), a multivariate
matching technique that reweights the two control groups (i.e., couples that met offline intraditional ways and couples that met via offline dating services) to match the covariate
distribution of the treatment group (i.e., couples that met online). As opposed to reweighting
8

based on propensity scores, which requires a time-consuming iterative process of selecting
covariates, weighting, and balance checking, EB directly estimates weights based on apre-specified set of balance constraints. Especially when dealing with modest-size samples,
as is the case in our study, EB also allows us to avoid trimming outliers, such as observations
for long duration partnerships, typically over-represented among couples who met in
non-digital ways. Using the ebalance command (Hainmueller & Xu, 2013) in Stata 17(StataCorp, 2021), we generate weights under the constraint of balance in the mean andvariance of all variables across the three groups.
The second step in our analysis was the estimation of random-effects logistic
regression models using Stata’s melogit command. These models allowed us to test whether
the probability of having an egalitarian division of housework varies across meeting context
and have the advantage of accounting for the nesting of observations within individuals. We
first estimated a pre- and post-weighting model for the full sample, and then by wife’s
education given that the online dating effect – for brevity, used hereafter to denote theassociation between meeting online and the division of housework, and by no means as
indicator of causality – may uniquely affect the allocation of housework of women withdifferent education. The specification of the models took the following mathematical form:,
where pij is the probability of respondent i in wave j to experience an egalitarian division ofhousehold labor, modelled as a logistic function of meeting context. β0 is the intercept. β1
represents the difference in experiences of equal sharing for couples that met through offline
dating services or internet dating versus the reference category of having met via offline
traditional contexts, adjusted for time-varying controls (vector Xij )with coefficient vectorβ_2), and time-constant controls (vector Zi with coefficient vector β3). The specification
finally includes a between-individual (uj) error term. We also considered fixed-effects
models, which would have had the advantage of accounting for potential unobserved fixed
traits, but we did not have sufficient variation in our main independent variable, with very
few changes in treatment (i.e., type of meeting context).
RESULTS
Entropy Balancing
To explore differences in observed characteristics between couples formed offline,
in conventional ways versus online-formed unions, Figure 1 (Panel A) plots standardized
differences in means for each covariate. Focusing on unadjusted values, particularly thosegreater than ±0.2, we see that observations for couples who met their partner online(hereafter, for brevity: online observations) were more often associated with shorter marriage
duration, younger age, previous marital experience, and dissatisfaction with friendships.
Additional differences that were, however, not large also revealed online observations
additionally linked to less exposure to progressive gender values (i.e., respondents were lesslikely to have seen their father involved in housework when they were 15 years old),
residence in an urban environment or in the Kanto region, but differences compared tooffline observations were not large. Figure 1 (Panel A) also shows that, after weighting,differences shrank to zero, indicating that covariate balance was achieved. Figure 1 (PanelB) further inspect the selectivity of couples who met online compared to those who met via
offline dating services, with similar findings.
9

Descriptive Statistics
We begin by presenting weighted descriptive statistics of dependent and independent
variables for the total sample, by meeting context (Table 1A). Married couples who met
through online dating in Japan were slightly more likely to report an egalitarian division ofhousework than couples who met in traditional ways, though, overall, the proportion ofequal sharing of housework was small (i.e., not surpassing 16% in either category).
When looking at results by wife’s educational level (Table 1B) we see that this contrast
was particularly notable among couples where the wife was university-educated. Moreprecisely, when the wife was highly trained, 27.9% of couples reported equal sharing if they
met online, compared to only 15.8% if they met offline in traditional ways or 18.2% if they
met through offline meeting services. None of these differences, however, were statisticallysignificant. Table 1A and 1B finally indicated that among couples that met online, there wasan over-representation of educationally hypogamous couples, especially among couple
where the wife was highly educated.
Multivariate Results
We next turn to multivariable analyses to test our first hypothesis stating thatmarried couples who met online are more likely to have an egalitarian division of routine
household labor than other couples. Table 2 shows results from a set of random-effects
logistic regression models predicting an equal split of housework. We estimate a first modelon unweighted data and a second one on weighted data to assess the extent to which
selection on observed variables explains the anticipated positive effect of internet dating on
equal sharing (Hypothesis 2). We run these analyses for the full sample and then by wife’s
education separately to test our third hypothesis, which predicted that the online effect would
be particularly visible among couples where the wife was highly educated.
First, unadjusted results for the full sample indicate that married couples who met
online were 1.74 (=exp[0.55]) times more likely to show equal sharing of housework thancouples who met offline, in traditional settings (p < .10), confirming Hypothesis 1.
Accounting for observed selection into internet dating, however, reduced the meeting online
effect by 44.8% (= (1-(0.31/0.55)) and rendered it non-significant. This lends support to
Hypothesis 2, which predicted that the selectivity of online daters would explain part of thepositive online dating effect.
Results stratified by wife’s education further validate Hypothesis 3, by showing aparticularly stronger online matchmaking effect among couples in which the wife wasuniversity trained. More specifically, online-formed couples in which the wife was highly
educated were 3.67 (=exp[1.30]) times more likely to have an egalitarian division ofhousework than couples who met offline in conventional ways (p < .05). For couples inwhich the wife was not university-educated, results were inconclusive: a small and negative
meeting online effect for unions in which the female partner had high school or less; positive
but non-significant for unions in which the wife graduated vocational school or juniorcollege only. Even after accounting for various factors that may have selected individuals
into internet dating, couples that met online and where the wife was university educatedwere 2.54 (=exp[0.93]) times more likely to report equal sharing of housework tasks (p< .05). As opposed to the general sample, for these couples, controlling for observed
selection attenuated the online dating effect to a lower extent (i.e., by 28.4% =(1–(0.93/1.30)]), and the coefficient retained statistical significance. Finally, the effect ofmeeting via offline dating services rather than via offline traditional methods was small and10

nonsignificant across all three educational groups.
Supplementary Analyses
We also ran two secondary analyses. First, though we did not directly hypothesize
on how meeting online may impact the educational gap in the division of housework, we
aimed to also see whether digital spaces of partner selection generate a higher education
dividend of reduced time spent on housework for women in Japan, as seen in other contexts(Kolpashnikova & Koike, 2021). As opposed to the main objective of the paper, which is to
examine the association between online dating and the division of housework among couples
with varying levels of the wife's education, this analysis shifts its focus to explore thedifferences in housework allocation among women with different educational backgrounds
across meeting contexts. Since previous analyses were stratified by wife’s education in order
to examine online dating effects and the contribution of selection factors for eacheducational group separately, to directly assess educational effects across meeting contexts,
we ran an additional analysis on the full sample including an interaction between wife’s
education and meeting context. Figure A1 in the Appendix graphs predicted probabilities of
equal sharing based on this model. Results indicate that among couples who met offline,
couples where the wife was university educated were not statistically different from couples
where the wife was less educated in terms of how gender-imbalanced their division ofhousework was; among couples formed within the more liberal bounds of digital partner
markets, wife’s university education was associated with a significantly more egalitariandivision of housework compared to the lowest level of education (p < .10).
Second, to investigate how the association between online dating and a moreegalitarian split of housework for couples in which the wife is highly educated varies acrossdifferent categories of couple’s division of paid work and in so doing verify whether theeffect applies to women with high education and working full-time, we constructed avariable distinguishing between male breadwinner arrangements in which the wife worked
part-time, male breadwinner couples in which the wife is not working at all, and the rest,
labelled ‘modern’ (largely comprised of dual earner couples). As previously mentioned,
sample limitations did not allow us to also distinguish between, for instance, dual earners
and female breadwinner households. Predicted probabilities based on a model that includes
an interaction between meeting context and the division of paid work are plotted in Figure
A2. Results show that the meeting online effect only pertains to male breadwinner couples inwhich the female partner works part-time, with no effect seen among either more traditionalarrangements (i.e., in which the wife is not engaged in any form of employment) or more
modern ones. We also notice that the probability of equal sharing among male breadwinnercouples where the wife is working part-time is almost at the same level as that amongmodern couples. In other words, online matching allows women working part-time toachieve the same level of equal sharing of housework as women working full-time.
DISCUSSION
Japan’s work and family landscape currently inhabits a transitional space (Fukuda etal., 2020), where long-standing cultural norms prescribing traditional marriage andmale-breadwinner arrangements paradoxically co-exist with an undeniable rise ingender-egalitarian preferences and an increasing demand for women’s education andincome-earning capacity (Brinton et al., 2021). Alongside these trends, there have also beenstark changes in partner selection processes, including a decline in previous structures of11matchmaking (e.g., family, workplace) and a concomitant rise in the marriage hunting
industry (Castro-Vazquez, 2016; Dalton & Dales, 2016). This study aimed to examine thelink between these two trends by looking at the role that internet matchmaking options mightplay in facilitating de-gendered marital practices. Compared to other modern go-between
options such as miai parties, marriage agencies or gokon gatherings, which often still involvethe intermediation of family and friends, online dating not only enlarges the field of
possibilities, but also provides conditions of anonymity, limited interference by third parties,
and, in the case of women, who are often under-represented on these platforms, a structuralmating advantage. Given these particularities, we argue that digital spaces of interaction may
allow for a subversion of gender during the dating phase (e.g., women more often claiming
power and expressing preferences in interactions with men), which, similar to patterns
recently observed for Germany (Potarca & Hook, 2023), may set relationships on course formore gender-egalitarian marriages later on (Lamont, 2020).
To test this claim, we selected a sample of married couples from the Japanese Life
Course Panel Surveys. Based on ten waves of data (2007-2016), we performed random
effects logistic regression analyses that model the probability of engaging in equal sharing ofhousework tasks, while also accounting for observed selection into internet dating via EB
weighting. Results first indicated that married couples who met online generally had a moreegalitarian division of housework than couples who met in either traditional ways or throughother modern but non-digital matchmaking options. The results were marginally significant,and the association was partly offset when controlling for the socio-demographic, residential
and attitudinal selectivity of online daters. Results stratified by wife’s education, however,revealed that, if the female partner was highly educated, the online dating effect was more
prominent and more robust. Marriages that started online and where the wife wasuniversity-trained were significantly more likely to report an egalitarian allocation ofhousework compared to other marriages, and the effect was robust beyond any selectivity
based on observed characteristics. Further investigations of the four components comprising
our index of egalitarian sharing indicate that online-formed couples who adopt an equal
division of domestic work tend to show notable changes in the contributions made by malepartners. Specifically, there is a marked increase in male involvement when it comes to tasks
such as meal preparation and grocery shopping. Additionally, we observe an upturn in maleparticipation for typically less desirable tasks like house cleaning and laundry, while asignificant proportion of couples opt for an equal sharing of these chores.
Though not yet mirroring the large-scale popularity witnessed in contexts such as
the U.S. (Rosenfeld et al., 2019), digital partner selection emerging as significant component
in the Japanese dating culture in recent years does seem to fulfill its promise of facilitating acertain degree of change, especially with regards to gender (Beck et al., 2014), and for ademographic group currently on the rise (i.e., university-educated women). The fact that
digital modern dating options create space for change to occur, which is not also visible
among couples that met through non-digital modern matchmaking options (e.g., gokon, miai
parties, marriage agencies), confirms that the affordances of digital media (e.g., lessinterference by third parties, anonymity, a multitude of options) make a significant differencein the process of seeking out more egalitarian partnerships.
The online effect particularly noticeable for marriages in which the wife was
high-level education suggests that, to leverage the advantages of online partner selection andbe able to establish more egalitarian dynamics in marriage, Japanese women have to possess
human capital and some economic resources. Finding a significant online effect among
women working part-time but not among already more egalitarian women in dual earner12couples (i.e., the majority in the ‘modern couple’ category), as additional analyses revealed,
indicates the following: first, already advantaged groups engage in similar negotiations bothoffline and online, and any affordance conveyed by the internet adds little to increasing
egalitarianism in the division of housework; second, women holding part-time rather thanfull-time employment affords economic power that is not too threatening, but sufficientenough to bargain gender in online interactions with men. In alternative social spaces such as
digital partner markets, having higher education and some employment is seemingly valued(Brinton et al., 2021) and allows women to somewhat dismantle the ‘professional housewife’
script rigid societal norms still assign them to. These semi-traditional couple arrangements
initiated in the online space (i.e., 1.5 male breadwinner couples with a more egalitariandivision of housework) also allow full-time working men to step away from the role of soleprovider of financial security and make contributions to domestic work. As men’s mate valuechanges alongside that of women’s, especially in the context of increasing difficulty among
men to gain regular employment (Piotrowski et al., 2015), our findings signal a relevant shift
in patterns that may be observed in the years to come.
We nevertheless acknowledge that our study comes with certain limitations. Firstand foremost, when computing EB weights, we were not able to observe the characteristics
of online daters pre-marriage. We tried to overcome this issue by including time-constantmeasures or indicators of selectivity pertaining to an earlier stage in life (e.g., father’s
involvement in housework at age 15 as proxy for pre-marriage gender values that the
respondents were exposed to) whenever possible. Nevertheless, we cannot entirely rule out
the risk of endogeneity or the potential bias of not accounting for unobserved time-variant
traits. Second, the content and size of the data did not allow for a more detailed examinationof specific digital dating options or looking at interactions with other factors (e.g., the online
effect for university-educated women who are at the same time breadwinners or better
educated than their partner).
Despite these limitations, the results presented here already provide a glimpse into
the potential that digital instruments of mate selection have to facilitate change in Japan’s
partnership culture. Similar to research using European data (e.g., Potarca 2021), results also
indicate that the internet provides women with university education an advantage that they
otherwise would not possess. For this particular group, online dating offers the tools andaccess to different types of communication and wider dating pools, which open up
possibilities for different types of gender dynamics during courtship, that potentiallyreverberate into a more egalitarian manifestation of gender during marriage. This study adds
to previous research (e.g., Potarca 2020; Thomas 2020) by indicating that technologicalinnovations in the process of mate selection play a significant part in demographictransitions, and allow for more individualized and more diversified personal choices(Castells, 2009), even in staunchly traditional contexts. Finally and related, our study
suggests that in Japan’s case and in line with Ogburn’s (1922) cultural lag hypothesis,
significant cultural change in marriage and family patterns is more likely to take off whenchanges in economic and technological conditions, including transformations in partner
search and selection technology, occur.

13

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18

FIGURE 1. Standardized Differences in Means between Couples Formed via Online Dating
Services vs. Offline Traditional (a) or Offline Dating Services (b) for Selected
Covariates, Before and After Entropy Balancing.
Note: Positive (negative) values indicate that the mean for online-formed couples is higher(lower) than for offline-formed couples.

19

TABLE 1A. Weighted sample descriptive statistics (percentages), by meeting context – total
sample.
OfflineOffline dating

Online dating

traditional

services

services

Egalitarian division of housework

11.3

13.3

15.5

Female respondent
Male breadwinner couple
Household living standard
Poor
Average
WealthyPartners’ educational pairing
Hypergamy
Homogamy
Hypogamy

53.7
67.7

53.7
62.9

53.7
70.6

18.6
62.1
19.3

18.4
61.7
19.9

19.7
58.8
21.5

37.7
44.9
17.4

36.0
48.7
15.3

40.2
36.4†
23.4†

15,780
2,600

1,800
371

673
133

N (observations)
N (couples)
Note: † p < 0.10.

20TABLE 1B. Weighted sample descriptive statistics (percentages), by meeting context –stratified by wife’s educational level.
A. Wife’s education: High school or less

OfflineOffline dating

Online dating

traditional

services

services

Egalitarian division of housework

9.6

10.7

6.2

Female respondent
Male breadwinner couple
Household living standard
Poor
Average
WealthyPartners’ educational pairing
Hypergamy
Homogamy

53.4
74.9

55.6
74.2

63.9
84.6

25.4
59.4
15.2

26.2
61.7
12.1

21.9
60.8
17.3

50.5
49.5

47.4
52.6

61.9
38.1

N (observations)
N (couples)

4,725
789

462
93

260
49

Egalitarian division of housework

10.8

13.3

18.3

Female respondent
Male breadwinner couple
Household living standard
Poor
Average
WealthyPartners’ educational pairing
Hypergamy
Homogamy
Hypogamy

55.2
66.3

48.2
58.8

47.2
61.6

16.0
65.9
18.1

16.3
64.3
19.4

24.3
54.9†
20.8

43.0
26.7
30.3

42.0
28.3
29.8

38.7
22.9
38.4

N (observations)
N (couples)

6,933
1,110

945
189

284
55

Egalitarian division of housework

15.8

18.2

27.9

Female respondent
Male breadwinner couple
Household living standard
Poor
Average
WealthyPartners’ educational pairing
Homogamy
Hypogamy

51.0
56.2

61.9
49.2

48.1
62.0

10.4
59.3

7.1
56.2

4.7
63.6

30.3
75.9
24.1

36.7
85.8
14.2

31.8
62.0*
38.0*

N (observations)
N (couples)

4,122
692

393
89

129
28

B. Wife’s education: Vocational school/ junior college

C. Wife’s education: University or higher

Note: † p < 0.10; * p < .05.

21

TABLE 2. Results from unweighted and weighted random-effects logistic regression models predicting equal sharing of housework among
married couples in Japan, stratified by wife’s educational level

Total Sample

Wife’s education:
High school or lessWife’s education:
Vocational school/ juniorcollege

Wife’s education:
University or higher

Unweighted

Weighted

Unweighted

Weighted

Unweighted

Weighted

Unweighted

Weighted

0.06

0.10

–0.19

0.11

0.12

0.06

0.34

0.19

(0.20)(0.16)(0.39)(0.31)(0.30)(0.23)(0.37)(0.24)

0.55†

0.31

–0.26

–0.29

0.74

0.38

1.30*

0.93*

(0.31)(0.23)(0.61)(0.43)(0.46)(0.33)(0.63)(0.40)–1.07***–0.75***–1.06***–0.47–0.88***–0.53*–1.33***–1.49***(0.14)(0.17)(0.26)(0.30)(0.22)(0.26)(0.24)(0.30)–1.78***–1.51***–1.15***–1.06***–2.02***–1.60***–2.00***–1.95***(0.11)(0.16)(0.19)(0.27)(0.17)(0.22)(0.20)(0.37)–0.19–0.40*–0.29–0.72**

–0.12

–0.34

–0.33

–0.05

(0.12)(0.19)(0.20)(0.27)(0.18)(0.29)(0.27)(0.40)

–0.02

–0.30

0.05

–0.75*

–0.05

–0.53

–0.23

0.07

(0.15)(0.22)(0.28)(0.38)(0.24)(0.37)(0.30)(0.39)

Meeting context (ref.: offline traditional)
Offline dating services

Online dating services

Female respondent

Male breadwinner couple

Household living standard (ref.: poor)
Average

Wealthy22

Partners’

educational

pairing(ref.:

hypergamy)
Homogamy

Hypogamy

0.86***

0.59**

0.76**

0.72*

0.59*

–0.08

(0.16)(0.19)(0.26)(0.29)(0.28)(0.31)

0.54**

0.67**

0.47†

0.48

23

Ref.

Ref.

–0.63*–0.45

Supplementary Analyses

FIGURE A1. Predicted Probabilities of Equal Sharing of Housework, by Wife’s Educational
Level and Meeting Context.
Notes: Based on an unweighted random-effects logistic regression model including an interaction between
meeting context and wife’s education, controlling for respondent’s gender, whether male breadwinnercouple, household living standard, and partners’ educational pairing. The star indicates probabilities
significantly different compared to the “offline traditional” category: † p < .10.

24

FIGURE A2. Predicted Probabilities of Equal Sharing of Housework among Couples inwhich the Wife Is Highly Educated, by the Division of Paid Work and Meeting Context.
Notes: PT = part-time, NW= not working. Based on an unweighted random-effects logistic regression model
including an interaction between meeting context and the division of paid work, controlling for respondent’s
gender, household living standard, and partners’ educational pairing. The stars indicate probabilities
significantly different compared to the “offline traditional” category: † p < .10; * p < .05.

25

東京大学社会科学研究所パネル調査プロジェクトについて
労働市場の構造変動、急激な少子高齢化、グローバル化の進展などにともない、日本社会における就業、結婚、家族、教育、意識、ライフスタイルのあり方は大きく変化を遂げようとしている。これからの日本社会がどのような方向に進むのかを考える上で、現在生じている変化がどのような原因によるものなのか、あるいはどこが変化してどこが変化していないのかを明確にすることはきわめて重要である。
本プロジェクトは、こうした問題をパネル調査の手法を用いることによって、実証的に解明することを研究課題とするものである。このため社会科学研究所では、若年パネル調
査、壮年パネル調査、高卒パネル調査、中学生親子パネル調査の４つのパネル調査を実施している。

本プロジェクトの推進にあたり、以下の資金提供を受けた。記して感謝したい。

文部科学省・独立行政法人日本学術振興会科学研究費補助金
基盤研究 S：2006 年度～2009 年度、2010 年度～2014 年度 基盤研究 C：2013 年度～
2016 年度 特別推進研究：2015 年度～2017 年度 若手研究 A：2015 年度～2018 年度
基盤研究 B：2016 年度～2020 年度 特別推進研究：2018 年度～2024 年度
厚生労働科学研究費補助金
政策科学推進研究：2004 年度～2006 年度
奨学寄付金
株式会社アウトソーシング（代表取締役社長・土井春彦、本社・静岡市）：2006 年度
～2008 年度

東京大学社会科学研究所パネル調査プロジェクト
ディスカッションペーパーシリーズについて
東京大学社会科学研究所パネル調査プロジェクトディスカッションペーパーシリーズは、
東京大学社会科学研究所におけるパネル調査プロジェクト関連の研究成果を、速報性を重視し暫定的にまとめたものである。

東京⼤学社会科学研究所 パネル調査プロジェクト
http://ssjda.iss.u-tokyo.ac.jp/panel/