Local Identification In Empirical Games Of Incomplete Information
AbstractThis paper studies identification for a broad class of empirical games in a general functional setting. Global identification results are known for some specific models, for instance in some standard auction models. We use functional formulations to obtain general criteria for local identification. These criteria can be applied to both parametric and nonparametric models, as well as models with asymmetry among players and affiliated private information. A benchmark model is developed where the structural parameters of interest are the distribution of private information and an additional dissociated parameter, such as a parameter of risk aversion. Criteria are derived for some standard auction models, games with exogenous variables, games with randomized strategies, such as mixed strategies, and games with strategic functions that cannot be derived analytically.
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Bibliographic InfoArticle provided by Cambridge University Press in its journal Econometric Theory.
Volume (Year): 26 (2010)
Issue (Month): 06 (December)
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Other versions of this item:
- Florens, Jean-Pierre & Sbaï, Erwann, 2009. "Local Identification in Empirical Games of Incomplete Information," IDEI Working Papers 612, Institut d'Économie Industrielle (IDEI), Toulouse.
- Florens, Jean-Pierre & Sbaï, Erwann, 2009. "Local Identification in Empirical Games of Incomplete Information," TSE Working Papers 10-166, Toulouse School of Economics (TSE).
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C79 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Other
- D44 - Microeconomics - - Market Structure and Pricing - - - Auctions
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- Dunker, Fabian & Florens, Jean-Pierre & Hohage, Thorsten & Johannes, Jan & Mammen, Enno, 2014. "Iterative estimation of solutions to noisy nonlinear operator equations in nonparametric instrumental regression," Journal of Econometrics, Elsevier, vol. 178(P3), pages 444-455.
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