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A Simple GMM Estimator for the Semi-Parametric Mixed Proportional Hazard Model

Author

Listed:
  • Bijwaard, Govert

    (NIDI - Netherlands Interdisciplinary Demographic Institute)

  • Ridder, Geert

    (University of Southern California)

Abstract
Ridder and Woutersen (2003) have shown that under a weak condition on the baseline hazard there exist root-N consistent estimators of the parameters in a semiparametric Mixed Proportional Hazard model with a parametric baseline hazard and unspecified distribution of the unobserved heterogeneity. We extend the Linear Rank Estimator (LRE) of Tsiatis (1990) and Robins and Tsiatis (1991) to this class of models. The optimal LRE is a two-step estimator. We propose a simple first-step estimator that is close to optimal if there is no unobserved heterogeneity. The efficiency gain associated with the optimal LRE increases with the degree of unobserved heterogeneity.

Suggested Citation

  • Bijwaard, Govert & Ridder, Geert, 2009. "A Simple GMM Estimator for the Semi-Parametric Mixed Proportional Hazard Model," IZA Discussion Papers 4543, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp4543
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. van den Berg, Gerard. J. & Janys, Lena & Mammen, Enno & Nielsen, Jens Perch, 2021. "A general semiparametric approach to inference with marker-dependent hazard rate models," Journal of Econometrics, Elsevier, vol. 221(1), pages 43-67.
    2. 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.
    3. Janys, Lena, 2017. "A General Semiparametric Approach to Inference with Marker-Dependent Hazard Rate Models," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168077, Verein für Socialpolitik / German Economic Association.
    4. 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.
    5. 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.
    6. Govert Bijwaard & Christian Schluter, 2016. "Interdependent Hazards, Local Interactions, and the Return Decision of Recent Migrants," RF Berlin - CReAM Discussion Paper Series 1620, Rockwool Foundation Berlin (RF Berlin) - Centre for Research and Analysis of Migration (CReAM).

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    More about this item

    Keywords

    counting process; linear rank estimation; mixed proportional hazard;
    All these keywords.

    JEL classification:

    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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