{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T23:17:20Z","timestamp":1785799040472,"version":"3.56.0"},"reference-count":45,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2024,5,14]],"date-time":"2024-05-14T00:00:00Z","timestamp":1715644800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,3,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>We propose a new sequential Efficient Pseudo-Likelihood (k-EPL) estimator for dynamic discrete choice games of incomplete information. k-EPL considers the joint behaviour of multiple players simultaneously, as opposed to individual responses to other agents\u2019 equilibrium play. This, in addition to reframing the problem from conditional choice probability (CCP) space to value function space, yields a computationally tractable, stable, and efficient estimator. We 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. Furthermore, we show the sequence achieves higher-order equivalence to the finite-sample maximum-likelihood estimator with iteration and that 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\u2019s 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. We apply the estimator to analyse competition in the U.S. wholesale club industry.<\/jats:p>","DOI":"10.1093\/restud\/rdae050","type":"journal-article","created":{"date-parts":[[2024,5,14]],"date-time":"2024-05-14T16:40:35Z","timestamp":1715704835000},"page":"981-1021","source":"Crossref","is-referenced-by-count":3,"title":["Efficient and Convergent Sequential Pseudo-Likelihood Estimation of Dynamic Discrete Games"],"prefix":"10.1093","volume":"92","author":[{"given":"Adam","family":"Dearing","sequence":"first","affiliation":[{"name":"\u00a0\u00a0S.C. Johnson Graduate School of Management, S.C. Johnson College of Business, Cornell University and NBER ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jason R","family":"Blevins","sequence":"additional","affiliation":[{"name":"Department of Economics, The Ohio State University ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,5,14]]},"reference":[{"key":"2025030619564747400_rdae050-B1","doi-asserted-by":"crossref","first-page":"1223","DOI":"10.3982\/QE1735","article-title":"Imposing Equilibrium Restrictions in the Estimation of Dynamic Discrete Games","volume":"12","author":"Aguirregabiria","year":"2021","journal-title":"Quantitative Economics"},{"key":"2025030619564747400_rdae050-B2","doi-asserted-by":"crossref","first-page":"1519","DOI":"10.1111\/1468-0262.00340","article-title":"Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision 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