A Genetic Algorithm for the Structural Estimation of Games with Multiple Equilibria
New Mathematics and Natural Computation, Vol. 1, Number 2, 295-303.
18 Pages Posted: 4 Mar 2005 Last revised: 30 Oct 2016
Date Written: July 1, 2005
This paper proposes an algorithm to obtain maximum likelihood estimates of structural parameters in discrete games with multiple equilibria. The method combines a genetic algorithm (GA) with a pseudo maximum likelihood (PML) procedure. The GA searches efficiently over the huge space of possible combinations of equilibria in the data. The PML procedure avoids the repeated computation of equilibria for each trial value of the parameters of interest. To test the ability of this method to get maximum likelihood estimates, we present a Monte Carlo experiment in the context of a game of price competition and collusion.
Keywords: Empirical games, Maximum likelihood estimation, Multiple equilibria, Genetic algorithms
JEL Classification: C13, C35
Suggested Citation: Suggested Citation