Next Article in Journal
Measures of Dispersion and Serial Dependence in Categorical Time Series
Next Article in Special Issue
Optimal Multi-Step-Ahead Prediction of ARCH/GARCH Models and NoVaS Transformation
Previous Article in Journal
On the Convergence Rate of the SCAD-Penalized Empirical Likelihood Estimator
Previous Article in Special Issue
Indirect Inference: Which Moments to Match?

Monte Carlo Inference on Two-Sided Matching Models

Department of Economics, Harvard University, Cambridge, MA 02138, USA
Department of Economics, University of Haifa, Haifa 3498838, Israel
Vancouver School of Economics, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
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)
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
MDPI and ACS Style

Kim, T.; Schwartz, J.; Song, K.; Whang, Y.-J. Monte Carlo Inference on Two-Sided Matching Models. Econometrics 2019, 7, 16.

AMA Style

Kim T, Schwartz J, Song K, Whang Y-J. Monte Carlo Inference on Two-Sided Matching Models. Econometrics. 2019; 7(1):16.

Chicago/Turabian Style

Kim, Taehoon, Jacob Schwartz, Kyungchul Song, and Yoon-Jae Whang. 2019. "Monte Carlo Inference on Two-Sided Matching Models" Econometrics 7, no. 1: 16.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop