Matching and Searching Online
Using data on user attributes and interactions from an online dating site, mate preferences are estimated, and the Gale-Shapley algorithm is used to predict stable matches. The predicted matches are similar to the actual matches achieved by the dating site, and the actual matches are approximately efficient. Out-of-sample predictions of offline matches, i.e., marriages, exhibit assortative mating patterns similar to those observed in actual marriages. Thus, mate preferences, without resort to search frictions, can generate sorting in marriages. However, we underpredict some of the correlation patterns; search frictions may play a role in explaining the discrepancy.
Ali Hortasçu is a professor in economics at the University of Chicago, where he is also director of graduate studies and the co-director of graduate admissions. He is a co-editor of the RAND Journal of Economics and the associate editor of the American Economic Review. He conducts research in auctions, industrial organizations, and search and matching models.
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