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Semiparametric estimation of a panel data proportional hazards model with fixed effects

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  • Joel L. Horowitz
  • Sokbae (Simon) Lee

Abstract

This paper considers a panel duration model that has a proportional hazards specificationwith fixed effects. The paper shows how to estimate the baseline and integratedbaseline hazard functions without assuming that they belong to known, finitedimensionalfamilies of functions. Existing estimators assume that the baseline hazardfunction belongs to a known parametric family. Therefore, the estimators presented hereare more general than existing ones. This paper also presents a method for estimatingthe parametric part of the proportional hazards model with dependent right censoring,under which the partial likelihood estimator is inconsistent. The paper presents someMonte Carlo evidence on the small sample performance of the new estimators.

Suggested Citation

  • Joel L. Horowitz & Sokbae (Simon) Lee, 2002. "Semiparametric estimation of a panel data proportional hazards model with fixed effects," CeMMAP working papers 21/02, Institute for Fiscal Studies.
    • Handle: RePEc:azt:cemmap:21/02
    DOI: 10.1920/wp.cem.2002.2102
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    References listed on IDEAS

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    1. Jinyong Hahn, 1994. "The Efficiency Bound of the Mixed Proportional Hazard Model," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 607-629.
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    7. Joel L. Horowitz, 1999. "Semiparametric Estimation of a Proportional Hazard Model with Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 67(5), pages 1001-1028, September.
    8. Powell, James L & Stock, James H & Stoker, Thomas M, 1989. "Semiparametric Estimation of Index Coefficients," Econometrica, Econometric Society, vol. 57(6), pages 1403-1430, November.
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    10. Tiemen Woutersen, 2000. "Estimators for Panel Duration Data with Endogenous Censoring and Endogenous Regressors," Econometric Society World Congress 2000 Contributed Papers 1581, Econometric Society.
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    12. Horowitz, Joel L, 1996. "Semiparametric Estimation of a Regression Model with an Unknown Transformation of the Dependent Variable," Econometrica, Econometric Society, vol. 64(1), pages 103-137, January.
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