Matching and Sorting in Online Dating

48 Pages Posted: 30 Mar 2008

See all articles by Günter J. Hitsch

Günter J. Hitsch

University of Chicago - Booth School of Business

Ali Hortacsu

University of Chicago - Department of Economics; National Bureau of Economic Research (NBER)

Dan Ariely

Duke University - Fuqua School of Business

Date Written: March 1, 2008

Abstract

This paper studies the economics of match formation using a novel data set obtained from a major online dating service. Using detailed information on the users' attributes and interactions, we estimate a model of mate preferences. Based on the estimated preferences, we use the Gale-Shapley algorithm to predict the stable matches among the users of the dating site. Comparing the predicted and observed matching patterns, we find that the Gale-Shapley model explains the matches achieved by the online dating market well, and that the matches are approximately efficient (within the class of stable matches). We then explore whether the estimated mate preferences, in conjunction with the Gale-Shapley algorithm, can explain the matching patterns in offline, real-world marriages. We find that we can predict assortative mating patterns that are similar to those observed in marriages. As the Gale-Shapley algorithm predicts match outcomes in the absence of search costs, we conclude that mate preferences, not search frictions, explain much of the strong degree of sorting along various attributes in marriages.

Keywords: matching, market design, Gale-Shapley, marriage, sorting

JEL Classification: C78, D02, D78, J12

Suggested Citation

Hitsch, Guenter J. and Hortacsu, Ali and Ariely, Dan, Matching and Sorting in Online Dating (March 1, 2008). Available at SSRN: https://ssrn.com/abstract=1113243 or http://dx.doi.org/10.2139/ssrn.1113243

Guenter J. Hitsch (Contact Author)

University of Chicago - Booth School of Business ( email )

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Ali Hortacsu

University of Chicago - Department of Economics ( email )

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National Bureau of Economic Research (NBER)

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Dan Ariely

Duke University - Fuqua School of Business ( email )

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