The Reversal of the Gender Gap in Education and Its Consequences for Family Life

Bavel, Jan Van; Schwartz, Christine R.; Esteve, Albert

doi:10.1146/annurev-soc-073117-041215

Cited by 174 publications

(166 citation statements)

References 138 publications

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“…Conversely, older and highly educated women were most likely to face shortages of marital partners. This finding was consistent with other related empirical evidence that sex‐ratio imbalances increase with women's age and that the gender reversal in educational attainment has upended traditional patterns of educational hypergamy among American women (see Lichter & Qian, ; Van Bavel et al, ). Race also placed constraints on marital opportunities.…”

Section: Resultssupporting

confidence: 91%

“…High rates of incarceration and substantial out‐marriage to White women, especially among Black men, have also left many minority women without marital partners (Crowder & Tolnay, ). The fact that women's educational levels now exceed men's (Buchmann & DiPrete, ; Van Bavel, Schwartz, & Esteve, ) further implies that young women—by necessity—are less financially dependent on husbands than in the past and that educational hypogamy has become more commonplace (Breen & Salazar, ; Qian, ). Young women seemingly face shortages of demographically similar men to marry.…”

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confidence: 99%

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Mismatches in the Marriage Market

Lichter

Price

Swigert

2019

J of Marriage and Family

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Objective This article provides an assessment of whether unmarried women currently face demographic shortages of marital partners in the U.S. marriage market. Background One explanation for the declines in marriage is the putative shortage of economically attractive partners for unmarried women to marry. Previous studies provide mixed results but are usually focused narrowly on sex ratio imbalances rather than identifying shortages on the multiple socioeconomic characteristics that typically sort women and men into marriages. Methods This study identifies recent marriages from the 2008 to 2012 and 2013 to 2017 cumulative 5‐year files of the American Community Survey. Data imputation methods provide estimates of the sociodemographic characteristics of unmarried women's potential (or synthetic) spouses who resemble the husbands of otherwise comparable married women. These estimates are compared with the actual distribution of unmarried men at the national, state, and local area levels to identify marriage market imbalances. Results These synthetic husbands have an average income that is about 58% higher than the actual unmarried men that are currently available to unmarried women. They also are 30% more likely to be employed (90% vs. 70%) and 19% more likely to have a college degree (30% vs. 25%). Racial and ethnic minorities, especially Black women, face serious shortages of potential marital partners, as do low socioeconomic status and high socioeconomic status unmarried women, both at the national and subnational levels. Conclusions This study reveals large deficits in the supply of potential male spouses. One implication is that the unmarried may remain unmarried or marry less well‐suited partners.

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Section: Resultssupporting

confidence: 91%

mentioning

confidence: 99%

Mismatches in the Marriage Market

Lichter

Price

Swigert

2019

J of Marriage and Family

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“…the stigma of a woman marrying “down” will differ if a wife has 5 years of school and her husband zero compared with 5 years and her husband 10). Conventions are also likely to vary across time; when the educational composition of a population changes, the social meaning of a given credential shifts (Frye & Lopus, ), and gender roles and family forms are transformed (Caldwell, ; van Bavel et al, ). In this way, a population's educational composition indirectly impacts its propensity or aversion toward a given assortative mating outcome, as individuals—in response to social conventions—pair more (or less) often than would be expected based solely on the marginal distributions of husbands' and wives' characteristics.…”

Section: Educational Expansion and The Prevalence Of Hypergamy Hypogmentioning

confidence: 99%

“…Around the world, scholars have documented a longstanding cultural preference for unions in which husbands are at least as educated as wives and a corresponding opposition toward female status-dominant relationships (Basu, 1998;Hitsch, Hortaçsu, & Ariely, 2010;Tichenor, 2005; for a review, see van Bavel et al, 2018). In the United States and Europe, this distaste for hypogamy appears to have weakened over time: Marriages in which women have higher status are no longer more likely to dissolve (Schwartz & Han, 2014), and attitudinal surveys show a growing acceptance of hypogamy (Esteve et al, 2016).…”

Section: Educational Assortative Mating Propensitiesmentioning

confidence: 99%

Intramarital Status Differences Across Africa's Educational Expansion

Lopus

Frye

2019

J of Marriage and Family

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Objective: This article documents how intramarital differences in educational status vary across Africa's heterogeneous educational expansion, which has encompassed an enormous breadth of educational opportunities during the past 50 years. Background: Educational expansion influences intramarital status differences both by altering the educational composition of men and women and by reconfiguring the social conventions associated with a given educational context. Status differentials between marital partners can influence spousal well‐being and, in the aggregate, determine the extent to which marriage provides a pathway to upward social mobility. Method: Using Demographic and Health Survey data representing 32 sub‐Saharan African countries and 5 decades of birth cohorts, the article examines the prevalence and propensity of educational pairings as a function of educational access (the percentage of a cohort who ever attended school) and wife's education level. Results: Educational expansion created gendered changes in educational compositions of married individuals, which led to increased prevalence of hypergamy (wives who married “up”) in most countries. Educational expansion has also led hypogamous marriages to become less of a social aberration: in lower education contexts (but less so in higher education contexts), conventions lead women to “marry down” at far lower rates than would be expected based on the sex‐specific compositions of husbands and wives. Conclusion: Educational attainment remains a central determinant of social positioning in African society. However, as schooling expands across the continent, social conventions regarding educational status are playing a weakening role in determining who marries whom.

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“…André Grow, Jan van Bavel and colleagues have been working for the past several years on the reversal of the gender gap in education and its implications for female hypergamy, using agent-based simulation models (van Bavel, 2012;Grow & van Bavel, 2015;van Bavel, Schwartz & Esteve, 2018). Their simulations are sophisticated, taking into account homophily (in terms of age and education level), general desirability of the potential partner (represented as earnings prospects), the possibility of divorce and repartnering, mortality, the structuring role of the educational system, etc.…”

Section: Research Using Simulationmentioning

confidence: 99%

Partner choice and parameter estimates: modelling the effect of preferences

Halpin¹

2019

Preprint

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Assortative mating, the process through which people interactively choose each other as spouses, is a complex, consequential and informative phenomenon. 1 It has important consequences for the structure of society, for inequality and integration, and it tells a lot about social structures, patterns of interactions and preferences. However, it is a complex process, and while tempting it is problematic to read preferences directly from the empirical outcomes. The mapping of preferences to outcomes in a process subject to constraints is not straightforward. Outcomes are constrained in complex ways, not least the gendered distribution of the characteristics of interest, the competition among peers for alters with the desired characteristics, and the fact that alters are agents with preferences too. Additionally, the fact that the process is dynamic, where the context changes continually, not only because of external historical reasons, but also endogenously, as the distribution of single people changes as others marry.Research on assortative mating has a long history of looking at the data, usually tables of spouse pairs classified by the characteristic of interest, and making inferences about the data generating processes in terms of homogamy preference, competition for desirable characteristics, female hypergamy preference, or relative desirability of different characteristics leading to status exchange. Earlier work tends to read directly from patterns in the tables, or simple summaries. But loglinear modelling of these tables, predominant in the literature since the 1980s, is markedly superior, by controlling for the marginal distributions and correlated characteristics. For instance, raw data may show lots of women marrying up, but loglinear analysis may correctly detect that this is explained entirely by a gendered distribution where men are higher on average.The research question that motivates this research is whether loglinear models of tables of achieved marriages correctly capture evidence of underlying preferences, such as homophily, competition, female hypergamy, or relative ranking of attributes in the context of status exchange. This is partly a question about loglinear models, but more fundamentally it concerns the extent to which the theoretical mechanisms leave detectable evidence in the resulting data, the tables of spouse pairs usually used in analysis.

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The Reversal of the Gender Gap in Education and Its Consequences for Family Life

Cited by 174 publications

References 138 publications

Mismatches in the Marriage Market

Mismatches in the Marriage Market

Intramarital Status Differences Across Africa's Educational Expansion

Partner choice and parameter estimates: modelling the effect of preferences

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