We introduce aggregate uncertainty into a Rubinstein and Wolinsky (1985)-type dynamic matching and bilateral bargaining model. The market can be either in a high state, where there are more buyers than sellers, or in a low state, where there are more sellers than buyers. Traders do not know the state. They randomly meet each other and bargain by making take-it-or-leave-it offers. The only information transmitted in a meeting is the time a trader spent on the market. There are two kinds of search frictions: time discounting and exogenous exit. We find that as the search frictions vanish, the market discovers the competitive price quickly: the prices offered in equilibrium converge in expectation to the true-state Walrasian price at the rate linear in the total search friction. This rate is the same as it would be if the state were commonly known.
Bibliographical noteWe thank Marco Battaglini (Editor), an anonymous Advisory Editor and three referees for valuable suggestions that have significantly improved this paper. We also gratefully acknowledge helpful comments from seminar and conference participants at Shanghai University of Finance and Economics, the University of Hong Kong, 2013 Asia Meeting of the Econometric Society at National University of Singapore, and Workshop in Memory of Artyom Shneyerov, October 12, 2018.
- Dynamic matching and bargaining
- convergence to perfect competition
- aggregate uncertainty