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Unknown Heterogeneity, the EC-EM Algorithm, and the Large T Approximation

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  • El-Gamal, Mahmoud
  • Grether, David

Abstract

We study a panel structure with n subjects/entities being observed over T periods. We consider a class of models for each subject's data generating precess, and allow the unknown heterogeneity. In other words, we do not know many types we have, what the types are, and which subjects belong to each type. We propose a large T approximation to the posterior mode on the unknows through the Estimation/Classification (EC) algorithm of El-Gamal and Grether (1995) which is linear in n,T, and the unknown number of types.
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Suggested Citation

  • El-Gamal, Mahmoud & Grether, David, 1996. "Unknown Heterogeneity, the EC-EM Algorithm, and the Large T Approximation," Working Papers 988, California Institute of Technology, Division of the Humanities and Social Sciences.
    • Handle: RePEc:clt:sswopa:988
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    Cited by:

    1. William Greene, 2001. "Fixed and Random Effects in Nonlinear Models," Working Papers 01-01, New York University, Leonard N. Stern School of Business, Department of Economics.
    2. Isaac C. Rischall, "undated". "The Effect of Migration on Earnings and Welfare Benefit Receipt," Canadian International Labour Network Working Papers 28, McMaster University.
    3. El-Gamal, M.A., 1997. "A Monte Carlo Study of Ec-Estimation in Panel Data Models with Limited Dependent Variables and Heterogeneity," Working papers 9703, Wisconsin Madison - Social Systems.

    More about this item

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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