A Genetic Algorithm for the Structural Estimation of Games with Multiple Equilibria
AbstractThis 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.
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Bibliographic InfoPaper provided by Boston University - Department of Economics in its series Boston University - Department of Economics - Working Papers Series with number WP2005-001.
Length: 48 pages
Date of creation: Jan 2005
Date of revision:
Empirical games; Maximum likelihood estimation; Multiple equilibria; Genetic algorithms;
Other versions of this item:
- Victor Aguirregabiria & Pedro Mira, 2005. "A Genetic Algorithm for the Structural Estimation of Games with Multiple Equilibria," Econometrics 0502017, EconWPA.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-03-18 (All new papers)
- NEP-CMP-2006-03-18 (Computational Economics)
- NEP-ECM-2006-03-18 (Econometrics)
- NEP-GTH-2006-03-18 (Game Theory)
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