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Markov chain Monte Carlo for incomplete information discrete games

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  • Sanjog Misra

Abstract

This paper outlines a Bayesian approach to estimating discrete games of incomplete information. The MCMC routine proposed features two changes to the traditional Metropolis–Hastings algorithm to facilitate the estimation of games. First, we propose a new approach to sample equilibrium probabilities using a probabilistic equilibrium selection rule that allows for the evaluation of the parameter posterior. Second, we propose a differential evolution based MCMC sampler which is capable of handling the unwieldy posterior that only has support on the equilibrium manifold. We also present two applications to demonstrate the feasibility of our proposed methodology. Copyright Springer Science+Business Media, LLC 2013

Suggested Citation

  • Sanjog Misra, 2013. "Markov chain Monte Carlo for incomplete information discrete games," Quantitative Marketing and Economics (QME), Springer, vol. 11(1), pages 117-153, March.
    • Handle: RePEc:kap:qmktec:v:11:y:2013:i:1:p:117-153
    DOI: 10.1007/s11129-012-9128-5
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    14. Paul B. Ellickson & Sanjog Misra, 2008. "Supermarket Pricing Strategies," Marketing Science, INFORMS, vol. 27(5), pages 811-828, 09-10.
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    Cited by:

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    2. Doug J. Chung & Kyoungwon Seo & Reo Song, 2023. "Efficient computation of discrete games: Estimating the effect of Apple on market structure," Production and Operations Management, Production and Operations Management Society, vol. 32(7), pages 2245-2263, July.
    3. Xi Chen & Ralf van der Lans & Michael Trusov, 2021. "Efficient Estimation of Network Games of Incomplete Information: Application to Large Online Social Networks," Management Science, INFORMS, vol. 67(12), pages 7575-7598, December.
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    5. Subramanian Balachander & Bikram Ghosh, 2013. "Bayesian estimation of a simultaneous probit model using error augmentation: An application to multi-buying and churning behavior," Quantitative Marketing and Economics (QME), Springer, vol. 11(4), pages 437-458, December.
    6. Che-Lin Su, 2014. "Estimating discrete-choice games of incomplete information: Simple static examples," Quantitative Marketing and Economics (QME), Springer, vol. 12(2), pages 167-207, June.

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    More about this item

    Keywords

    Discrete games; MCMC; Nested fixed point; Differential evolution; C11; C7; M3; L2;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior

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