Estimating dynamic discrete-choice games of incomplete information

Dynamic Games with Incomplete Information

Identification and Estimation of Continuous Time Dynamic Discrete Choice Games

We consider the theoretical and econometric properties of a recently proposed class of continuous time dynamic games with discrete choices. This class of models has computationally-desirable properties and includes widely-used entry, exit, and investment games that underlie many applications in empirical industrial organization. First, we provide more general conditions for existence of equilib...

Pursuit-Evasion Games with incomplete information in discrete time

Pursuit-Evasion Games (in discrete time) are stochastic games with nonnegative daily payoffs, with the final payoff being the cumulative sum of payoffs during the game. We show that such games admit a value even in the presence of incomplete information and that this value is uniform, i.e. there are ǫ-optimal strategies for both players that are ǫ-optimal in any long enough prefix of the game. ...

Markov Chain Monte Carlo for Incomplete Information Discrete Games

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 ...

Estimating Discrete Games

T paper provides a critical review of the methods for estimating static discrete games and their relevance for quantitative marketing. We discuss the various modeling approaches, alternative assumptions, and relevant trade-offs involved in taking these empirical methods to data. We consider games of both complete and incomplete information, examine the primary methods for dealing with the coher...