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Non‐parametric identification of the mixed proportional hazards model with interval‐censored durations


  • Christian N. Brinch


This note presents identication results for the mixed proportional hazards model when duration data are interval-censored. Earlier positive results on identication under intervalcensoring require both parametric specication on how covariates enter the hazard functions and assumptions of unbounded support for covariates. New results provided here show how one can dispense with both of these assumptions. The mixed proportional hazards model is non-parametrically identied with interval-censored duration data, provided covariates have support on an open set and the hazard function is a non-constant continuous function of covariates.
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Suggested Citation

  • Christian N. Brinch, 2011. "Non‐parametric identification of the mixed proportional hazards model with interval‐censored durations," Econometrics Journal, Royal Economic Society, vol. 14(2), pages 343-350, July.
  • Handle: RePEc:ect:emjrnl:v:14:y:2011:i:2:p:343-350

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    References listed on IDEAS

    1. Sueyoshi, Glenn T, 1995. "A Class of Binary Response Models for Grouped Duration Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(4), pages 411-431, Oct.-Dec..
    2. J. Heckman & B. Singer, 1984. "The Identifiability of the Proportional Hazard Model," Review of Economic Studies, Oxford University Press, vol. 51(2), pages 231-241.
    3. Knut Røed & Tao Zhang, 2002. "A note on the Weibull distribution and time aggregation bias," Applied Economics Letters, Taylor & Francis Journals, vol. 9(7), pages 469-472.
    4. van den Berg, Gerard J & van Ours, Jan C, 1994. "Unemployment Dynamics and Duration Dependence in France, the Netherlands and the United Kingdom," Economic Journal, Royal Economic Society, vol. 104(423), pages 432-443, March.
    5. Christian N. Brinch, 2008. "Non-parametric Identification of the Mixed Hazards Model with Interval-Censored Durations," Discussion Papers 539, Statistics Norway, Research Department.
    6. 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.
    7. Han, Aaron & Hausman, Jerry A, 1990. "Flexible Parametric Estimation of Duration and Competing Risk Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(1), pages 1-28, January-M.
    8. Berg, G.J. & Ours, J.C., 1993. "Unemployment dynamics and duration dependence in France, the Netherlands and the UK," Serie Research Memoranda 0038, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    9. Jaap H. Abbring & Gerard J. van den Berg, 2003. "The identifiability of the mixed proportional hazards competing risks model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(3), pages 701-710.
    10. McCall, Brian P, 1994. "Testing the Proportional Hazards Assumption in the Presence of Unmeasured Heterogeneity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(3), pages 321-334, July-Sept.
    11. Brinch, Christian N., 2007. "Nonparametric Identification Of The Mixed Hazards Model With Time-Varying Covariates," Econometric Theory, Cambridge University Press, vol. 23(02), pages 349-354, April.
    12. Chris Elbers & Geert Ridder, 1982. "True and Spurious Duration Dependence: The Identifiability of the Proportional Hazard Model," Review of Economic Studies, Oxford University Press, vol. 49(3), pages 403-409.
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    Cited by:

    1. Paolo Lucchino & Dr Richard Dorsett, 2013. "Young people's labour market transitions: the role of early experiences," National Institute of Economic and Social Research (NIESR) Discussion Papers 419, National Institute of Economic and Social Research.
    2. James Kau & Donald Keenan & Constantine Lyubimov, 2014. "First Mortgages, Second Mortgages, and Their Default," The Journal of Real Estate Finance and Economics, Springer, vol. 48(4), pages 561-588, May.

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    JEL classification:

    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies


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