IDEAS home Printed from https://ideas.repec.org/p/ssb/dispap/600.html
   My bibliography  Save this paper

Non-parametric identication of the mixed proportional hazards model with interval-censored durations

Author

Listed:

Abstract

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.

Suggested Citation

  • Christian N. Brinch, 2009. "Non-parametric identication of the mixed proportional hazards model with interval-censored durations," Discussion Papers 600, Statistics Norway, Research Department.
  • Handle: RePEc:ssb:dispap:600
    as

    Download full text from publisher

    File URL: https://www.ssb.no/a/publikasjoner/pdf/DP/dp600.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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, August.
    3. 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..
    4. R. A. Kortram & A. C. M. van Rooij & A. J. Lenstra & G. Ridder, 1995. "Constructive identification of the mixed proportional hazards model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 49(3), pages 269-281, November.
    5. Geert Ridder, 1990. "The Non-Parametric Identification of Generalized Accelerated Failure-Time Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 57(2), pages 167-181.
    6. J. Heckman & B. Singer, 1984. "The Identifiability of the Proportional Hazard Model," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 51(2), pages 231-241.
    7. Van den Berg, Gerard J., 2001. "Duration models: specification, identification and multiple durations," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 55, pages 3381-3460, Elsevier.
    8. 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.
    9. 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.
    10. 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.
    11. Christian N. Brinch, 2008. "Non-parametric Identification of the Mixed Hazards Model with Interval-Censored Durations," Discussion Papers 539, Statistics Norway, Research Department.
    12. 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.
    13. 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.
    14. Brinch, Christian N., 2007. "Nonparametric Identification Of The Mixed Hazards Model With Time-Varying Covariates," Econometric Theory, Cambridge University Press, vol. 23(2), pages 349-354, April.
    15. Christopher J. Flinn & James J. Heckman, 1982. "Models for the Analysis of Labor Force Dynamics," NBER Working Papers 0857, National Bureau of Economic Research, Inc.
    16. Chris Elbers & Geert Ridder, 1982. "True and Spurious Duration Dependence: The Identifiability of the Proportional Hazard Model," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 49(3), pages 403-409.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dorsett, Richard & Lucchino, Paolo, 2018. "Young people's labour market transitions: The role of early experiences," Labour Economics, Elsevier, vol. 54(C), pages 29-46.
    2. Bonev, Petyo, 2020. "Nonparametric identification in nonseparable duration models with unobserved heterogeneity," Economics Working Paper Series 2005, University of St. Gallen, School of Economics and Political Science.
    3. Dorsett, Richard & Lucchino, Paolo, 2018. "Young people's labour market transitions: The role of early experiences," Labour Economics, Elsevier, vol. 54(C), pages 29-46.
    4. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Christian N. Brinch, 2008. "Non-parametric Identification of the Mixed Hazards Model with Interval-Censored Durations," Discussion Papers 539, Statistics Norway, Research Department.
    2. Gaure, Simen & Roed, Knut & Zhang, Tao, 2007. "Time and causality: A Monte Carlo assessment of the timing-of-events approach," Journal of Econometrics, Elsevier, vol. 141(2), pages 1159-1195, December.
    3. Bonev, Petyo, 2020. "Nonparametric identification in nonseparable duration models with unobserved heterogeneity," Economics Working Paper Series 2005, University of St. Gallen, School of Economics and Political Science.
    4. Jaap H. Abbring, 0000. "Mixed Hitting-Time Models," Tinbergen Institute Discussion Papers 07-057/3, Tinbergen Institute, revised 11 Aug 2009.
    5. 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.
    6. Bart Cockx & Muriel Dejemeppe, 2005. "Duration dependence in the exit rate out of unemployment in Belgium. Is it true or spurious?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(1), pages 1-23, January.
    7. Brinch, Christian N., 2007. "Nonparametric Identification Of The Mixed Hazards Model With Time-Varying Covariates," Econometric Theory, Cambridge University Press, vol. 23(2), pages 349-354, April.
    8. Effraimidis, Georgios, 2016. "Nonparametric Identification of a Time-Varying Frailty Model," DaCHE discussion papers 2016:6, University of Southern Denmark, Dache - Danish Centre for Health Economics.
    9. Horny, Guillaume & Picchio, Matteo, 2010. "Identification of lagged duration dependence in multiple-spell competing risks models," Economics Letters, Elsevier, vol. 106(3), pages 241-243, March.
    10. Van den Berg, Gerard J., 2001. "Duration models: specification, identification and multiple durations," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 55, pages 3381-3460, Elsevier.
    11. Jaap H. Abbring, 2012. "Mixed Hitting‐Time Models," Econometrica, Econometric Society, vol. 80(2), pages 783-819, March.
    12. Florens, Jean-Pierre & Fougère, Denis & Mouchart, Michel, 2007. "Duration Models and Point Processes," IZA Discussion Papers 2971, Institute of Labor Economics (IZA).
    13. Bart Cockx & Matteo Picchio, 2013. "Scarring effects of remaining unemployed for long-term unemployed school-leavers," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(4), pages 951-980, October.
    14. Abbring, Jaap H. & van den Berg, Gerard J. & van Ours, Jan C., 2002. "The anatomy of unemployment dynamics," European Economic Review, Elsevier, vol. 46(10), pages 1785-1824, December.
    15. Nicoletti, Cheti & Rondinelli, Concetta, 2010. "The (mis)specification of discrete duration models with unobserved heterogeneity: A Monte Carlo study," Journal of Econometrics, Elsevier, vol. 159(1), pages 1-13, November.
    16. Ruixuan Liu, 2020. "A competing risks model with time‐varying heterogeneity and simultaneous failure," Quantitative Economics, Econometric Society, vol. 11(2), pages 535-577, May.
    17. Jaap Abbring & Gerard Van Den Berg, 2005. "Social experiments and instrumental variables with duration outcomes," IFS Working Papers W05/19, Institute for Fiscal Studies.
    18. Guido Imbens & Lisa Lynch, 2006. "Re-employment probabilities over the business cycle," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 5(2), pages 111-134, August.
    19. Botosaru, Irene, 2020. "Nonparametric analysis of a duration model with stochastic unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 217(1), pages 112-139.
    20. Jaap H. Abbring, 2010. "Identification of Dynamic Discrete Choice Models," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 367-394, September.

    More about this item

    Keywords

    duration analysis; interval-censoring; non-parametric identication;
    All these keywords.

    JEL classification:

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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ssb:dispap:600. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: L Maasø (email available below). General contact details of provider: https://edirc.repec.org/data/ssbgvno.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.