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Circumventing multiple integration: A comparison of GMM and SML estimators for the panel probit model

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  • Inkmann, Joachim

Abstract

The paper compares two approaches to the estimation of panel probit models: the Generalized Method of Moments (GMM) and the Simulated Maximum Likelihood (SML) technique. Both have in common that they circumvent multiple integrations of joint density functions without the need to impose restrictive variance-covariance specifications on the error term distribution. Particular attention is paid to a three-stage GMM estimator based on nonparametric estimation of optimal instruments. A Monte Carlo study reveals slight efficiency gains from SML when the underlying model is correctly specified. GMM turns out to be more robust than SML when heteroskedasticity over time is ignored as well as in the presence of multiplicative heteroskedasticity. An application to the product innovation activities of German manufacturing firms is presented.

Suggested Citation

  • Inkmann, Joachim, 1997. "Circumventing multiple integration: A comparison of GMM and SML estimators for the panel probit model," Discussion Papers, Series II 339, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".
    • Handle: RePEc:zbw:kondp2:339
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    References listed on IDEAS

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    1. Haggeney, Isabelle & Fitzenberger, Bernd & Ernst, Michaela, 1998. "Wer ist noch Mitglied in den Gewerkschaften? Eine Panelanalyse für Westdeutschland," ZEW Discussion Papers 98-11, ZEW - Leibniz Centre for European Economic Research.

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    More about this item

    Keywords

    panel probit model; conditional moment restrictions; optimal instruments; k-nearest neighbor estimation; GHK simulator; heteroskedasticity;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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