IDEAS home Printed from https://ideas.repec.org/p/ssb/dispap/539.html
   My bibliography  Save this paper

Non-parametric Identification of the Mixed Hazards Model with Interval-Censored Durations

Author

Listed:

Abstract

Econometric duration data are typically interval-censored, that is, not directly observed, but observed to fall within a known interval. Known non-parametric identification results for duration models with unobserved heterogeneity rely crucially on exact observation of durations at a continuous scale. Here, it is established that the mixed hazards model is non-parametrically identified through covariates that vary over time within durations as well as between observations when durations are interval-censored. The results hold for the mixed proportional hazards model as a special case.

Suggested Citation

  • Christian N. Brinch, 2008. "Non-parametric Identification of the Mixed Hazards Model with Interval-Censored Durations," Discussion Papers 539, Statistics Norway, Research Department.
  • Handle: RePEc:ssb:dispap:539
    as

    Download full text from publisher

    File URL: https://www.ssb.no/a/publikasjoner/pdf/DP/dp539.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Heckman, James & Singer, Burton, 1984. "A Method for Minimizing the Impact of Distributional Assumptions in Econometric Models for Duration Data," Econometrica, Econometric Society, vol. 52(2), pages 271-320, March.
    2. Matzkin, Rosa L., 1986. "Restrictions of economic theory in nonparametric methods," Handbook of Econometrics,in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 42, pages 2523-2558 Elsevier.
    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. Carling, Kenneth & Edin, Per-Anders & Harkman, Anders & Holmlund, Bertil, 1996. "Unemployment duration, unemployment benefits, and labor market programs in Sweden," Journal of Public Economics, Elsevier, vol. 59(3), pages 313-334, March.
    5. Geert Ridder, 1990. "The Non-Parametric Identification of Generalized Accelerated Failure-Time Models," Review of Economic Studies, Oxford University Press, vol. 57(2), pages 167-181.
    6. Heckman, James J. & Navarro, Salvador, 2007. "Dynamic discrete choice and dynamic treatment effects," Journal of Econometrics, Elsevier, vol. 136(2), pages 341-396, February.
    7. 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.
    8. Bergstrom, R & Edin, P-A, 1992. "Time Aggregation and the Distributional Shape of Unemployment Duration," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(1), pages 5-30, Jan.-Marc.
    9. 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.
    10. Sueyoshi, Glenn T., 1992. "Semiparametric proportional hazards estimation of competing risks models with time-varying covariates," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 25-58.
    11. 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.
    12. 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.
    13. 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.
    14. Roger W. Klein & Robert P. Sherman, 2002. "Shift Restrictions and Semiparametric Estimation in Ordered Response Models," Econometrica, Econometric Society, vol. 70(2), pages 663-691, March.
    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. 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.
    17. 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.
    18. Bierens, Herman J., 2008. "Semi-Nonparametric Interval-Censored Mixed Proportional Hazard Models: Identification And Consistency Results," Econometric Theory, Cambridge University Press, vol. 24(03), pages 749-794, June.
    19. Knut Roed & Tao Zhang, 2003. "Does Unemployment Compensation Affect Unemployment Duration?," Economic Journal, Royal Economic Society, vol. 113(484), pages 190-206, January.
    20. Klein, Roger W & Spady, Richard H, 1993. "An Efficient Semiparametric Estimator for Binary Response Models," Econometrica, Econometric Society, vol. 61(2), pages 387-421, March.
    21. Arulampalam, Wiji & Stewart, Mark B, 1995. "The Determinants of Individual Unemployment Durations in an Era of High Unemployment," Economic Journal, Royal Economic Society, vol. 105(429), pages 321-332, March.
    22. 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.
    23. 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.
    24. 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.
    25. Bearse, Peter & Canals-Cerd , Jos & Rilstone, Paul, 2007. "Efficient Semiparametric Estimation Of Duration Models With Unobserved Heterogeneity," Econometric Theory, Cambridge University Press, vol. 23(02), pages 281-308, April.
    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. 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.

    More about this item

    Keywords

    duration analysis; interval-censoring; non-parametric identification;

    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:539. See general information about how to correct material in RePEc.

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

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.