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Sharp identification regions in models with convex predictions: games, individual choice, and incomplete data

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  • Arie Beresteanu

    (Institute for Fiscal Studies and University of Pittsburgh)

  • Ilya Molchanov

    (Institute for Fiscal Studies and University of Bern, Institute of Mathematical Statistics and Actuarial Science)

  • Francesca Molinari

    (Institute for Fiscal Studies and Cornell University)

Abstract

We provide a tractable characterization of the sharp identification region of the parameters ? in a broad class of incomplete econometric models. Models in this class have set-valued predictions that yield a convex set of conditional or unconditional moments for the model variables. In short, we call these models with convex predictions. Examples include static, simultaneous move finite games of complete information in the presence of multiple mixed strategy Nash equilibria; random utility models of multinomial choice in the presence of interval regressors data; and best linear predictors with interval outcome and covariate data. Given a candidate value for ?, we establish that the convex set of moments yielded by the model predictions can be represented as the Aumann expectation of a properly defined random set. The sharp identification region of ?, denoted TI, can then be obtained as the set of minimizers of the distance from a properly specified vector of moments of random variables to this Aumann expectation. We show that algorithms in convex programming can be exploited to efficiently verify whether a candidate ? is in TI. We use examples analyzed in the literature to illustrate the gains in identification and computational tractability afforded by our method. This paper is a revised version of cemmap working paper CWP15/08

Suggested Citation

  • Arie Beresteanu & Ilya Molchanov & Francesca Molinari, 2009. "Sharp identification regions in models with convex predictions: games, individual choice, and incomplete data," CeMMAP working papers CWP27/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:cemmap:27/09
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    File URL: http://cemmap.ifs.org.uk/wps/cwp2709.pdf
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    Cited by:

    1. Marc Henry & Ismael Mourifié, 2013. "Euclidean Revealed Preferences: Testing The Spatial Voting Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(4), pages 650-666, June.
    2. Kline, Brendan & Tamer, Elie, 2012. "Bounds for best response functions in binary games," Journal of Econometrics, Elsevier, vol. 166(1), pages 92-105.
    3. Paul B. Ellickson & Stephanie Houghton & Christopher Timmins, 2010. "Estimating Network Economies in Retail Chains: A Revealed Preference Approach," NBER Working Papers 15832, National Bureau of Economic Research, Inc.
    4. Beresteanu, Arie & Molchanov, Ilya & Molinari, Francesca, 2012. "Partial identification using random set theory," Journal of Econometrics, Elsevier, vol. 166(1), pages 17-32.
    5. Áureo de Paula, 2013. "Econometric Analysis of Games with Multiple Equilibria," Annual Review of Economics, Annual Reviews, vol. 5(1), pages 107-131, May.

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