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Simulation Based Estimation of Discrete Sequential Move Games of Perfect Information

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  • Wang, Yafeng
  • Graham, Brett

Abstract

We propose simulation based estimation for discrete sequential move games of perfect information which relies on the simulated moments and importance sampling. We use importance sampling techniques not only to reduce computational burden and simulation error, but also to overcome non-smoothness problems. The model is identified with only weak scale and location normalizations, monte Carlo evidence demonstrates that the estimator can perform well in moderately-sized samples.

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File URL: http://mpra.ub.uni-muenchen.de/23153/
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File URL: http://mpra.ub.uni-muenchen.de/23398/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 23153.

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Date of creation: 08 Jul 2010
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Handle: RePEc:pra:mprapa:23153

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Related research

Keywords: Game-Theoretic Econometric Models; Sequential-Move Game; Method of Simulated Moments; Importance Sampling; Conditional Moment Restrictions.;

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  17. Yuichi Kitamura & Gautam Tripathi & Hyungtaik Ahn, 2001. "Empirical Likelihood-Based Inference in Conditional Moment Restriction Models," CIRJE F-Series CIRJE-F-124, CIRJE, Faculty of Economics, University of Tokyo.
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