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


  • Joel L. Horowitz

    () (Institute for Fiscal Studies and Northwestern University)

  • Sokbae Lee

    () (Institute for Fiscal Studies and Columbia University and IFS)


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.

Suggested Citation

  • Joel L. Horowitz & Sokbae Lee, 2002. "Semiparametric estimation of a panel data proportional hazards model with fixed effects," CeMMAP working papers CWP21/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  • Handle: RePEc:ifs:cemmap:21/02

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    References listed on IDEAS

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    2. Gorgens, Tue & Horowitz, Joel L., 1999. "Semiparametric estimation of a censored regression model with an unknown transformation of the dependent variable," Journal of Econometrics, Elsevier, vol. 90(2), pages 155-191, June.
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    Cited by:

    1. I. Sebastian Buhai & Coen N. Teulings, 2014. "Tenure Profiles and Efficient Separation in a Stochastic Productivity Model," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 245-258, April.
    2. Horowitz, Joel L., 2004. "Semiparametric models," Papers 2004,17, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
    3. Rachel Griffith & Sokbae Lee & John Van Reenen, 2011. "Is distance dying at last? Falling home bias in fixed‐effects models of patent citations," Quantitative Economics, Econometric Society, vol. 2(2), pages 211-249, July.
    4. Sokbae Lee, 2006. "Identification of a competing risks model with unknown transformations of latent failure times," Biometrika, Biometrika Trust, vol. 93(4), pages 996-1002, December.
    5. Griffith, Rachel & Lee, Sokbae & Straathof, Bas, 2017. "Recombinant innovation and the boundaries of the firm," International Journal of Industrial Organization, Elsevier, vol. 50(C), pages 34-56.
    6. Khan, Shakeeb & Tamer, Elie, 2007. "Partial rank estimation of duration models with general forms of censoring," Journal of Econometrics, Elsevier, vol. 136(1), pages 251-280, January.
    7. Light, Audrey & Omori, Yoshiaki, 2012. "Fixed effects maximum likelihood estimation of a flexibly parametric proportional hazard model with an application to job exits," Economics Letters, Elsevier, vol. 116(2), pages 236-239.
    8. Tue Gørgens & Dean Hyslop, 2016. "The specification of dynamic discrete-time two-state panel data models," Working Papers 16_01, Motu Economic and Public Policy Research.
    9. Wolter, James Lewis, 2016. "Kernel estimation of hazard functions when observations have dependent and common covariates," Journal of Econometrics, Elsevier, vol. 193(1), pages 1-16.
    10. Hausman, Jerry A. & Woutersen, Tiemen, 2014. "Estimating a semi-parametric duration model without specifying heterogeneity," Journal of Econometrics, Elsevier, vol. 178(P1), pages 114-131.
    11. repec:eee:jeborg:v:137:y:2017:i:c:p:113-131 is not listed on IDEAS
    12. Garibaldi, Pietro & Pacelli, Lia, 2008. "Do larger severance payments increase individual job duration?," Labour Economics, Elsevier, vol. 15(2), pages 215-245, April.
    13. James Wolter, 2015. "Kernel Estimation Of Hazard Functions When Observations Have Dependent and Common Covariates," Economics Series Working Papers 761, University of Oxford, Department of Economics.
    14. Bo E. Honoré & Aureo de Paula, 2009. ""Interdependent Durations" Third Version," PIER Working Paper Archive 09-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Feb 2008.
    15. Bo E. Honor & Áureo De Paula, 2010. "Interdependent Durations," Review of Economic Studies, Oxford University Press, vol. 77(3), pages 1138-1163.
    16. Whited, Toni M., 2006. "External finance constraints and the intertemporal pattern of intermittent investment," Journal of Financial Economics, Elsevier, vol. 81(3), pages 467-502, September.
    17. He, Bang-Qiang & Hong, Xing-Jian & Fan, Guo-Liang, 2017. "Block empirical likelihood for partially linear panel data models with fixed effects," Statistics & Probability Letters, Elsevier, vol. 123(C), pages 128-138.
    18. Bo E. Honore & Aureo de Paula, 2007. "Interdependent Durations, Second Version," PIER Working Paper Archive 08-044, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Nov 2008.

    More about this item

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

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