Preliminary And Incomplete – Please Do Not Circulate or Cite Without Authors ’ Permission

This paper uses a novel data set obtained from a major online dating service to draw inferences on mate preferences and ultimately the match outcomes of the site users. The data set contains detailed information on the demographic and socioeconomic attributes of the users, as well as information on their religion, political inclination, etc. A measure of the physical attractiveness of the site members was obtained from looks ratings of their posted photographs, which we obtained in a laboratory setting. The data set contains a detailed record of all online activities of the users. In particular, we know which profiles a user browses, to whom a user sends an e-mail to, and which e-mails he or she replies to. We also have limited information on the contents of the exchanged e-mails; for example, we know whether any contact information was exchanged. A drawback of the data set is that we do not observe any “offline ” activities. We first compare the reported demographic characteristics of site users to the characteristics of the population-at-large, and do not find large differences. We then use regression analysis to investigate how user attributes are related to “outcomes”, for example the rate at which a user is approached by potential mates. We provide some conditions under which the results of these “outcome regressions ” can be interpreted as preference estimates. Our empirical results indicate that both men and women care strongly about the physical appearance of their potential mates. While women’s choices depend strongly on the income and education of men, there is much less evidence for the reverse. The site members “discriminate ” strongly against members of a different ethnicity, and this effect is stronger for women than for men. Finally, we provide some preliminary evidence on observed “matches ” among the site members, and compare these matches to the predictions from a simple matching model. ∗We thank Babur De los Santos, Chris Olivola, and Tim Miller for their excellent research assistance