The family is not a static institution. In recent decades, marriage rates have fallen, divorce rates have risen, and the defining characteristics of marriage have changed. The economic approach to the family seeks to explain these trends by reference to models that can also explain how and why families form. Gary Becker’s (1981) Treatise on the Family proposed a theory based on “production complementarities,” in which husband and wife specialize in the market and domestic spheres, respectively. Production complementarities also arise in the production and rearing of one’s own children. However, production complementarities—at least as initially described—are decreasingly central to modern family life. Increased longevity and declining fertility mean that most of one’s adult life is spent without one’s own children in the household. Also, the rise in marital formation at older ages, including remarriage, means that many families form with no intention of producing children. Moreover, increases in female labor force participation suggest that household specialization has either declined or, at least taken on a different meaning. These changes have come about as what is produced in the home has been dramatically altered both by the emergence of labor-saving technology in the home and by the development of service industries that allow much of what was once provided by specialized homemakers to be purchased in the market. The availabil

/pdf/marriage-and-divorce-changes-and-their-driving-forces-2ad25osaye.pdf

Marriage and Divorce: Changes and their Driving Forces

We present a model in which investment in schooling generates two kinds of returns: the labor-market return, resulting from higher wages and a marriagemarket return, defined as the impact of schooling on the marital surplus share one can extract. Men and women may have different incentives to invest in schooling because of different market wages or household roles. This asymmetry can yield a mixed equilibrium with some educated individuals marrying uneducated spouses. When the labor-market returns to schooling rises, home production demands less time and the traditional spousal labor division norms weaken, more women may invest in schooling than men.

/pdf/investment-in-schooling-and-the-marriage-market-3wh7s0emdz.pdf

Investment in Schooling and the Marriage Market

Testosterone and financial risk preferences

The old boy (and girl) network: Social network formation on university campuses

In paradigms in which participants state their ideal romantic-partner preferences or examine vignettes and photographs, men value physical attractiveness more than women do, and women value earning prospects more than men do. Yet it remains unclear if these preferences remain sex differentiated in predicting desire for real-life potential partners (i.e., individuals whom one has actually met). In the present study, the authors explored this possibility using speed dating and longitudinal follow-up procedures. Replicating previous research, participants exhibited traditional sex differences when stating the importance of physical attractiveness and earning prospects in an ideal partner and ideal speed date. However, data revealed no sex differences in the associations between participants' romantic interest in real-life potential partners (met during and outside of speed dating) and the attractiveness and earning prospects of those partners. Furthermore, participants' ideal preferences, assessed before the speed-dating event, failed to predict what inspired their actual desire at the event. Results are discussed within the context of R. E. Nisbett and T. D. Wilson's (1977) seminal article: Even regarding such a consequential aspect of mental life as romantic-partner preferences, people may lack introspective awareness of what influences their judgments and behavior.

Sex differences in mate preferences revisited: Do people know what they initially desire in a romantic partner?

This paper uses a novel data set obtained from an online dating service to draw inferences on mate preferences and to investigate the role played by these preferences in determining match outcomes and sorting patterns. The empirical analysis is based on a detailed record of the site users' attributes and their partner search, which allows us to estimate a rich preference specification that takes into account a large number of partner characteristics. Our revealed preference estimates complement many previous studies that are based on survey methods. In addition, we provide evidence on mate preferences that people might not truthfully reveal in a survey, in particular regarding race preferences. In order to examine the quantitative importance of the estimated preferences in the formation of matches, we simulate match outcomes using the Gale-Shapley algorithm and examine the resulting correlations in mate attributes. The Gale-Shapley algorithm predicts the online sorting patterns well. Therefore, the match outcomes in this online dating market appear to be approximately efficient in the Gale-Shapley sense. Using the Gale-Shapley algorithm, we also find that we can predict sorting patterns in actual marriages if we exclude the unobservable utility component in our preference specification when simulating match outcomes. One possible explanation for this finding suggests that search frictions play a role in the formation of marriages.

/pdf/what-makes-you-click-mate-preferences-and-matching-outcomes-58w6jbla8s.pdf

What Makes You Click? Mate Preferences and Matching Outcomes in Online Dating

This paper discusses the role of agents’ beliefs and their implications for the economic modeling of their behavior, in particular, their behavior over time. The paper also discusses the corresponding planning problems facing both firms and consumers in their current decision making. After a general discussion of the consumer and firm problem, we discuss recent examples of some of the emerging empirical literature on dynamic choice behavior in marketing.

/pdf/measuring-long-run-marketing-effects-and-their-implications-qnas05z30q.pdf

Measuring long-run marketing effects and their implications for long-run marketing decisions

What Makes You Click? An Empirical Analysis of Online Dating

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What Makes You Click? Mate Preferences and Matching Outcomes in Online Dating

Measuring long-run marketing effects and their implications for long-run marketing decisions

What Makes You Click? An Empirical Analysis of Online Dating