Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/189707 
Year of Publication: 
2018
Series/Report no.: 
cemmap working paper No. CWP13/18
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
Abstract: 
We study the asymptotic properties of a class of estimators of the structural parameters in dynamic discrete choice games. We consider K-stage policy iteration (PI) estimators, where K denotes the number of policy iterations employed in the estimation. This class nests several estimators proposed in the literature. By considering a "maximum likelihood" criterion function, our estimator becomes the K- ML estimator in Aguirregabiria and Mira (2002, 2007). By considering a "minimum distance" criterion function, it defines a new K-MD estimator, which is an iterative version of the estimators in Pesendorfer and Schmidt-Dengler (2008) and Pakes et al. (2007). First, we establish that the K-ML estimator is consistent and asymptotically normal for any K. This complements findings in Aguirregabiria and Mira (2007), who focus on K = 1 and K large enough to induce convergence of the estimator. Furthermore, we show that the asymptotic variance of the K-ML estimator can exhibit arbitrary patterns as a function K. Second, we establish that the K-MD estimator is consistent and asymptotically normal for any K. [...]
Subjects: 
dynamic discrete choice problems
dynamic games
pseudo maximum likelihood estimator
minimum distance estimator
estimation
asymptotic efficiency
JEL: 
C13
C61
C73
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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