Identification and Estimation in Many‐to‐One Two‐Sided Matching Without Transfers

Author:

He YingHua1,Sinha Shruti2,Sun Xiaoting3

Affiliation:

1. Department of Economics, Rice University

2. Toulouse School of Economics, University of Toulouse Capitole

3. Department of Economics, Simon Fraser University

Abstract

In a setting of many‐to‐one two‐sided matching with nontransferable utilities, for example, college admissions, we study conditions under which preferences of both sides are identified with data on one single market. Regardless of whether the market is centralized or decentralized, assuming that the observed matching is stable, we show nonparametric identification of preferences of both sides under certain exclusion restrictions. To take our results to the data, we use Monte Carlo simulations to evaluate different estimators, including the ones that are directly constructed from the identification. We find that a parametric Bayesian approach with a Gibbs sampler works well in realistically sized problems. Finally, we illustrate our methodology in decentralized admissions to public and private schools in Chile and conduct a counterfactual analysis of an affirmative action policy.

Funder

Agence Nationale de la Recherche

Publisher

The Econometric Society

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