STRATEGY AND BUSINESS ECONOMICS


Efficient and Convergent Sequential Pseudo-Likelihood Estimation of Dynamic Discrete Games


ADAM DEARING ASSISTANT PROFESSOR


Samuel Curtis Johnson Graduate School of Management


Cornell SC Johnson College of Business Cornell University


Review of Economic Studies, 92, 2, March 2025 LINK TO PAPER


Co-authors • Adam Dearing


Assistant Professor, Samuel Curtis Johnson Graduate School of


Management, Cornell SC Johnson College of Business, Cornell University • Jason R. Blevins, Te Ohio State University, Columbus, OH


Summary Te authors propose a new sequential Efficient Pseudo-Likelihood (k-EPL)


estimator for dynamic discrete choice games of incomplete information. k-EPL considers the joint behavior of multiple players simultaneously, as opposed to individual responses to other agents’ equilibrium play. Tis yields a computa- tionally tractable, stable, and efficient estimator, in addition to reframing the problem from conditional choice probability (CCP) space to value function space.


Te authors show that each iteration in the k-EPL sequence is consistent and asymptotically efficient, so the first-order asymptotic properties do not vary across iterations. Te sequence achieves higher-order equivalence to the finite-sample maximum-likelihood estimator with iteration, and the sequence of estimators converges almost surely to the maximum-likelihood estimator at a nearly superlinear rate when the data are generated by any regular Markov perfect equilibrium, including equilibria that lead to inconsistency of other sequential estimators. When utility is linear in parameters, k-EPL iterations are computationally simple, only requiring that the researcher solve linear systems of equations to generate pseudo-regressors which are used in a static logit/probit regression. Monte Carlo simulations demonstrate the theoretical results and show k-EPL’s good performance in finite samples in both small- and large-scale games, even when the game admits spurious equilibria in addition to one that generated the data. Te authors also apply the estimator to analyze competition in the U.S. wholesale club industry.


CONTENTS TO MAIN


| RESEARCH WITH IMPACT: CORNELL SC JOHNSON COLLEGE OF BUSINESS • 2025 EDITION


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