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Econometrics 2019, 7(1), 16; https://doi.org/10.3390/econometrics7010016

Monte Carlo Inference on Two-Sided Matching Models

1
Department of Economics, Harvard University, Cambridge, MA 02138, USA
2
Department of Economics, University of Haifa, Haifa 3498838, Israel
3
Vancouver School of Economics, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
4
Department of Economics, Seoul National University, Seoul 08826, Korea
*
Author to whom correspondence should be addressed.
Received: 1 October 2018 / Revised: 29 November 2018 / Accepted: 7 March 2019 / Published: 26 March 2019
(This article belongs to the Special Issue Resampling Methods in Econometrics)
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PDF [361 KB, uploaded 26 March 2019]

Abstract

This paper considers two-sided matching models with nontransferable utilities, with one side having homogeneous preferences over the other side. When one observes only one or several large matchings, despite the large number of agents involved, asymptotic inference is difficult because the observed matching involves the preferences of all the agents on both sides in a complex way, and creates a complicated form of cross-sectional dependence across observed matches. When we assume that the observed matching is a consequence of a stable matching mechanism with homogeneous preferences on one side, and the preferences are drawn from a parametric distribution conditional on observables, the large observed matching follows a parametric distribution. This paper shows in such a situation how the method of Monte Carlo inference can be a viable option. Being a finite sample inference method, it does not require independence or local dependence among the observations which are often used to obtain asymptotic validity. Results from a Monte Carlo simulation study are presented and discussed. View Full-Text
Keywords: two-sided matching; monte carlo inference; one-side homogeneous preferences; serial dictatorship mechanism two-sided matching; monte carlo inference; one-side homogeneous preferences; serial dictatorship mechanism
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Kim, T.; Schwartz, J.; Song, K.; Whang, Y.-J. Monte Carlo Inference on Two-Sided Matching Models. Econometrics 2019, 7, 16.

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