We propose four different GMM estimators that allow almost consistent estimation of the structural parameters of panel probit models with fixed effects for the case of small T and large N. The moments used are derived for each period from a first order approximation of the mean of the dependent variable conditional on explanatory variables and on the fixed effect. The estimators differ w.r.t. the choice of instruments and whether they use trimming to reduce the bias or not. In a Monte Carlo study we compare these estimators with pooled probit and conditional logit estimators for different DGPs. The results show that the proposed estimators outperform these competitors in several situations.
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Find related papers by JEL classification: C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
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Lechner, Michael & Lollivier, Stefan & Magnac, Thierry, 2005.
"Parametric Binary Choice Models,"
IDEI Working Papers
398, Institut d'Économie Industrielle (IDEI), Toulouse.
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