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Empirical Game Theoretic Models: Computational Issues

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  • Armantier, Olivier
  • Richard, Jean-Francois

Abstract

This paper discusses computational issues raised by a generic solution and estimation methodology applicable to a broad range of empirical game theoretic models with incomplete information. By combining the use of Monte Carlo simulation techniques with that of smooth kernel estimation of empirical distribution functions, the authors develop a numerical algorithm of unparalleled performance and flexibility applicable, in particular, to models for which no operational solutions currently exist. An illustration to a set of procurement data from the French aerospace industry is used to illustrate the operation of this algorithm. Citation Copyright 2000 by Kluwer Academic Publishers.

Suggested Citation

  • Armantier, Olivier & Richard, Jean-Francois, 2000. "Empirical Game Theoretic Models: Computational Issues," Computational Economics, Springer;Society for Computational Economics, vol. 15(1-2), pages 3-24, April.
    • Handle: RePEc:kap:compec:v:15:y:2000:i:1-2:p:3-24
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    Cited by:

    1. Weili Ding & Steven F. Lehrer, 2000. "Using Performance Incentives to Reward the Value Added by Educators: Theory and Evidence from China," Econometric Society World Congress 2000 Contributed Papers 1519, Econometric Society.
    2. Eklöf, Matias, 2003. "Assessing Social Costs of Inefficient Procurement Design," Working Paper Series 2003:12, Uppsala University, Department of Economics.

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