Learning in the Marriage Market: The Economics of Dating
Yair Antler, Daniel Bird, Daniel Fershtman*
Last modified: 2022-04-17
Abstract
We develop a dynamic model of two-sided matching with search and learning frictions. Agents engage in a search for a potential partner and, upon meeting, may gradually acquire information about their compatibility as a couple, a process we refer to as dating. Dating is mutually exclusive and, as such, introduces a tradeoff between becoming better informed about one’s compatibility with a potential partner and meeting other, more promising, potential partners. We derive a closed-form solution for the unique steady-state equilibrium when agents are ex-ante homogeneous, and characterize it when they are vertically heterogeneous. In the steady state, agents date for longer than is socially optimal, an inefficiency that is alleviated by a small degree of asymmetry in dating costs between partners. Furthermore, block segregation fails, yet matching is assortative – in a probabilistic sense we refer to as single-crossing in marriage probabilities. Motivated by recent advances in matching technologies in decentralized markets, we study the effects of improvements in search and learning technologies and show that they differ qualitatively.