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Convenient estimators for the panel probit model

  • Bertschek, Irene
  • Lechner, Michael

The paper shows that several estimators for the panel probit model suggested in the literature belong to a common class of GMM estimators. They are relatively easy to compute because they are based on conditional moment restrictions involving univariate moments of the binary dependent variable only. Applying nonparametric methods we discuss an estimator that is optimal in this class. A Monte Carlo study shows that a particular variant of this estimator has good small sample properties and that the efficiency loss compared to maximum likelihood is small. An application to the product innovation decisions of German firms reveals the expected efficiency gains.

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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 87 (1998)
Issue (Month): 2 (September)
Pages: 329-371

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Handle: RePEc:eee:econom:v:87:y:1998:i:2:p:329-371
Contact details of provider: Web page: http://www.elsevier.com/locate/jeconom

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  1. Chamberlain, Gary, 1980. "Analysis of Covariance with Qualitative Data," Review of Economic Studies, Wiley Blackwell, vol. 47(1), pages 225-38, January.
  2. Bertschek, Irene, 1995. "Product and Process Innovation as a Response to Increasing Import and Foreign Direct Investment," Journal of Industrial Economics, Wiley Blackwell, vol. 43(4), pages 341-57, December.
  3. Newey, Whitney K, 1990. "Efficient Instrumental Variables Estimation of Nonlinear Models," Econometrica, Econometric Society, vol. 58(4), pages 809-37, July.
  4. Marc Nerlove, 1968. "Further Evidence on the Estimation of Dynamic Economic Relations from a Time Series of Cross-Sections," Cowles Foundation Discussion Papers 257, Cowles Foundation for Research in Economics, Yale University.
  5. 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 761-64, May.
  6. Chamberlain, Gary, 1987. "Asymptotic efficiency in estimation with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 34(3), pages 305-334, March.
  7. Robinson, P M, 1987. "Asymptotically Efficient Estimation in the Presence of Heteroskedasticity of Unknown Form," Econometrica, Econometric Society, vol. 55(4), pages 875-91, July.
  8. Guilkey, David K. & Murphy, James L., 1993. "Estimation and testing in the random effects probit model," Journal of Econometrics, Elsevier, vol. 59(3), pages 301-317, October.
  9. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  10. 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.
  11. 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.
  12. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
  13. Robinson, Peter M, 1982. "On the Asymptotic Properties of Estimators of Models Containing Limited Dependent Variables," Econometrica, Econometric Society, vol. 50(1), pages 27-41, January.
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