Sharp identification regions in games
Abstract
We study identification in static, simultaneous move finite games of complete information, where the presence of multiple Nash equilibria may lead to partial identification of the model parameters. The identification regions for these parameters proposed in the related literature are known not to be sharp. Using the theory of random sets, we show that the sharp identification region can be obtained as the set of minimizers of the distance from the conditional distribution of game's outcomes given covariates, to the conditional Aumann expectation given covariates of a properly defined random set. This is the random set of probability distributions over action profiles given profit shifters implied by mixed strategy Nash equilibria. The sharp identification region can be approximated arbitrarily accurately through a finite number of moment inequalities based on the support function of the conditional Aumann expectation. When only pure strategy Nash equilibria are played, the sharp identification region is exactly determined by a finite number of moment inequalities. We discuss how our results can be extended to other solution concepts, such as for example correlated equilibrium or rationality and rationalizability. We show that calculating the sharp identification region using our characterization is computationally feasible. We also provide a simple algorithm which finds the set of inequalities that need to be checked in order to insure sharpness. We use examples analyzed in the literature to illustrate the gains in identification afforded by our method.Download Info
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Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number CWP15/08.Length:
Date of creation: Jun 2008
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Handle: RePEc:ifs:cemmap:15/08
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Related research
Keywords: Identification; Random Sets; Aumann Expectation; Support Function; Capacity Functional; Normal Form Games; Inequality Constraints.;Find related papers by JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-08-21 (All new papers)
- NEP-ECM-2008-08-21 (Econometrics)
- NEP-GTH-2008-08-21 (Game Theory)
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Arie Beresteanu, 2009.
"Sharp Identification Regions in Models with Convex Predictions: Games, Individual Choice, and Incomplete Data,"
Working Papers
428, University of Pittsburgh, Department of Economics, revised Sep 2010.
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- Giorgio Topa & Elizabeth Setren & Meta Brown, 2011. "Do Referrals Lead to Better Matches? Evidence from a Firm's Employee," 2011 Meeting Papers 711, Society for Economic Dynamics.
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"Inference for Parameters Defined by Moment Inequalities: A Recommended Moment Selection Procedure,"
Cowles Foundation Discussion Papers
1676, Cowles Foundation for Research in Economics, Yale University.
- Donald W.K. Andrews & Panle Jia, 2008. "Inference for Parameters Defined by Moment Inequalities: A Recommended Moment Selection Procedure," Cowles Foundation Discussion Papers 1676R, Cowles Foundation for Research in Economics, Yale University, revised Aug 2011.
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"Market Structure and Multiple Equilibria in Airline Markets,"
2004 Meeting Papers
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Quantitative Economics,
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Discussion Papers Series, Department of Economics, Tufts University
0739, Department of Economics, Tufts University.
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"Sharp Bounds in the Binary Roy Model,"
CIRJE F-Series
CIRJE-F-835, CIRJE, Faculty of Economics, University of Tokyo.
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