Simulation Based Estimation of Discrete Sequential Move Games of Perfect Information

Yafeng Wang () and Brett Graham

MPRA Paper from University Library of Munich, Germany

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.

Keywords: Game-Theoretic Econometric Models; Sequential-Move Game; Method of Simulated Moments; Importance Sampling; Conditional Moment Restrictions. (search for similar items in EconPapers)
JEL-codes: C01 C13 C35 C72 (search for similar items in EconPapers)
Date: 2010-07-08
New Economics Papers: this item is included in nep-ecm and nep-gth
References: Add references at CitEc
Citations:

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/23153/1/MPRA_paper_23153.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/23398/1/MPRA_paper_23398.pdf revised version (application/pdf)
https://mpra.ub.uni-muenchen.de/69281/1/MPRA_paper_69281.pdf revised version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:23153

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().