American Economic Review Vol. 100 No. 1 2010

Matching and Sorting in Online Dating

Günter J. Hitsch¹; Ali Hortaçsu²; Dan Ariely³

¹ Booth School of Business, University of Chicago, 5807 S. Woodlawn Ave., Chicago, IL 60637. · ² Department of Economics, University of Chicago, 1126 E. 59th Street, Chicago, IL 60637. · ³ Fuqua School of Business, Duke University, 1 Towerview Drive, Durham, NC 27708.

Abstract

Using data on user attributes and interactions from an online dating site, we estimate mate preferences, and use the Gale-Shapley algorithm 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.

DOI

10.1257/aer.100.1.130

Volume

100

Issue

1

Pages

130-163

Language

en

Sources

openalex crossref bibtex:phds-export.bib

Cite

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