This paper considers a panel duration model that has a proportional hazards specification with fixed effects. The paper shows how to estimate the baseline and integrated baseline hazard functions without assuming that they belong to known, finitedimensional families of functions. Existing estimators assume that the baseline hazard function belongs to a known parametric family. Therefore, the estimators presented here are more general than existing ones. This paper also presents a method for estimating the parametric part of the proportional hazards model with dependent right censoring, under which the partial likelihood estimator is inconsistent. The paper presents some Monte Carlo evidence on the small sample performance of the new estimators.
Authors
![Sokbae "Simon" Lee](/sites/default/files/styles/square_desktop/public/2022-07/Simon%20Lee.jpg?itok=J8PnQSbc)
Research Fellow Columbia University
Sokbae is an IFS Research Fellow and a Professor at Columbia University, with an interest in Econometrics, Applied Microeconomics and Statistics.
![Person graphic](/sites/default/files/styles/square_desktop/public/2022-06/IFS-person-graphic.png?itok=hWCtTSrz)
Northwestern University
Working Paper details
- DOI
- 10.1920/wp.cem.2002.2102
- Publisher
- IFS
Suggested citation
Horowitz, J and Lee, S. (2002). Semiparametric estimation of a panel data proportional hazards model with fixed effects. London: IFS. Available at: https://ifs.org.uk/publications/semiparametric-estimation-panel-data-proportional-hazards-model-fixed-effects (accessed: 30 June 2024).
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