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Almost Consistent Estimation of Panel Probit Models with 'Small' Fixed Effects

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  • Lechner, Michael
  • Laisney, François

Abstract

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.

Suggested Citation

  • Lechner, Michael & Laisney, François, 2002. "Almost Consistent Estimation of Panel Probit Models with 'Small' Fixed Effects," ZEW Discussion Papers 02-64, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  • Handle: RePEc:zbw:zewdip:547
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    References listed on IDEAS

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    1. Avery, Robert B & Hansen, Lars Peter & Hotz, V Joseph, 1983. "Multiperiod Probit Models and Orthogonality Condition Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 24(1), pages 21-35, February.
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    3. Myoung-jae Lee, 1999. "A Root-N Consistent Semiparametric Estimator for Related-Effect Binary Response Panel Data," Econometrica, Econometric Society, vol. 67(2), pages 427-434, March.
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    5. Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics,in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier.
    6. Newey, W.K., 1991. "The Asymptotic Variance of Semiparametric Estimators," Working papers 583, Massachusetts Institute of Technology (MIT), Department of Economics.
    7. Butler, J S & Moffitt, Robert, 1982. "A Computationally Efficient Quadrature Procedure for the One-Factor Multinomial Probit Model," Econometrica, Econometric Society, vol. 50(3), pages 761-764, May.
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    12. Manski, Charles F, 1987. "Semiparametric Analysis of Random Effects Linear Models from Binary Panel Data," Econometrica, Econometric Society, vol. 55(2), pages 357-362, March.
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    Cited by:

    1. Justina A.V. Fischer, 2005. "Do Institutions of Direct Democracy Tame the Leviathan? Swiss Evidence on the Structure of Expenditure for Public Education," CESifo Working Paper Series 1628, CESifo Group Munich.
    2. Michael Lechner & Stefan Lollivier & Thierry Magnac, 2005. "Parametric Binary Choice Models," University of St. Gallen Department of Economics working paper series 2005 2005-23, Department of Economics, University of St. Gallen.

    More about this item

    Keywords

    Panel data; binary choice model; generalised method of moments; fixed effects;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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