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Local Identification in Empirical Games of Incomplete Information

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  • Florens, Jean-Pierre
  • Sbaï, Erwann

Abstract

This 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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File URL: http://idei.fr/doc/wp/2009/wp_idei_612.pdf
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Bibliographic Info

Paper provided by Institut d'Économie Industrielle (IDEI), Toulouse in its series IDEI Working Papers with number 612.

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Date of creation: Jul 2009
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Publication status: Published in Econometric Theory, vol.�26, n°6, 2010, p.�1638-1662.
Handle: RePEc:ide:wpaper:22796

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Cited by:
  1. 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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