Bayesian Analysis of Entry Games: A Simulated Likelihood Approach Without Simulation Errors

Jinhee Jo and Kyoungwon Seo

Global Economic Review, 2016, vol. 45, issue 3, 294-309

Abstract: This paper provides a practical guide to Bayesian estimation of simultaneous entry games of complete information with heterogeneous firms. Bayesian inference requires computation of the likelihood, which is carried out by simulating unobservables. To avoid errors from finite simulations, we apply Andrieu and Roberts’s [2009. The pseudo-marginal approach for efficient Monte Carlo computations, Annals of Statistics, 37(2), pp. 697–725] pseudo-marginal approach. We rely also on adaptive Markov chain Monte Carlo algorithms that improve computational performance.

Date: 2016
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DOI: 10.1080/1226508X.2016.1211814

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