IDEAS home Printed from https://ideas.repec.org/p/tse/wpaper/25316.html
   My bibliography  Save this paper

A Duration Model with Dynamic Unobserved Heterogeneity

Author

Listed:
  • Botosaru, Irene

Abstract

The paper considers a new class of duration models in which unobserved heterogeneity changes with time. The class addresses two main questions: How does the exit probability from a state vary when unobserved heterogeneity evolves through time? And do changes in unobserved heterogeneity have a timing effect? We show the non- and semi-parametric identification of the new class by solving a nonlinear integral equation with unknown kernel. Both the function of observed covariates and the mean of the distribution of unobserved heterogeneity are nonparametrically identified. Identifying timing effects and the distribution of unobserved heterogeneity requires stronger assumptions on either one of the two. An extension to the case when unobserved heterogeneity is a function of observed covariates is also identified. We show that sieve maximum likelihood estimators are consistent and present Monte Carlo simulations for both correct specification and misspecification. The paper also presents an empirical model of unemployment duration in which individuals exit unemployment when total accumulated losses due to unemployment cross over a self-imposed spending limit.

Suggested Citation

  • Botosaru, Irene, 2011. "A Duration Model with Dynamic Unobserved Heterogeneity," TSE Working Papers 11-262, Toulouse School of Economics (TSE), revised Nov 2013.
  • Handle: RePEc:tse:wpaper:25316
    as

    Download full text from publisher

    File URL: http://www.tse-fr.eu/sites/default/files/medias/doc/wp/etrie/dh_version2.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bound, John & Stinebrickner, Todd & Waidmann, Timothy, 2010. "Health, economic resources and the work decisions of older men," Journal of Econometrics, Elsevier, vol. 156(1), pages 106-129, May.
    2. Bent Jesper Christensen & Malene Kallestrup‐Lamb, 2012. "The Impact Of Health Changes On Labor Supply: Evidence From Merged Data On Individual Objective Medical Diagnosis Codes And Early Retirement Behavior," Health Economics, John Wiley & Sons, Ltd., vol. 21(S1), pages 56-100, June.
    3. Eduardo A. Haddad & Jaime Bonet & Geoffrey J. D. Hewings, 2023. "Introduction and Overview," Advances in Spatial Science, in: Eduardo A. Haddad & Jaime Bonet & Geoffrey J. D. Hewings (ed.), The Colombian Economy and Its Regional Structural Challenges, chapter 0, pages 1-16, Springer.
    4. Ariga, Kenn & Ohkusa, Yasushi & Brunello, Giorgio, 1999. "Fast track: is it in the genes? The promotion policy of a large Japanese firm," Journal of Economic Behavior & Organization, Elsevier, vol. 38(4), pages 385-402, April.
    5. James J. Heckman & Christopher R. Taber, 1994. "Econometric Mixture Models and More General Models for Unobservables in Duration Analysis," NBER Technical Working Papers 0157, National Bureau of Economic Research, Inc.
    6. Aalen, Odd O. & Hjort, Nils Lid, 2002. "Frailty models that yield proportional hazards," Statistics & Probability Letters, Elsevier, vol. 58(4), pages 335-342, July.
    7. Y. Kebir, 1991. "On hazard rate processes," Naval Research Logistics (NRL), John Wiley & Sons, vol. 38(6), pages 865-876, December.
    8. Heckman, James J. & Singer, Burton, 1984. "Econometric duration analysis," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 63-132.
    9. 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. 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.
    2. 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.
    3. Nathalie Gimenes & Emmanuel Guerre, 2019. "Nonparametric identification of an interdependent value model with buyer covariates from first-price auction bids," Papers 1910.10646, arXiv.org.

    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. Botosaru, Irene, 2020. "Nonparametric analysis of a duration model with stochastic unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 217(1), pages 112-139.
    2. Jaap H. Abbring & Gerard J. Van Den Berg, 2007. "The unobserved heterogeneity distribution in duration analysis," Biometrika, Biometrika Trust, vol. 94(1), pages 87-99.
    3. 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.
    4. 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.
    5. Peng, Yingwei & Zhang, Jiajia, 2008. "Identifiability of a mixture cure frailty model," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2604-2608, November.
    6. Dorsett, Richard, 2014. "The effect of temporary in-work support on employment retention: Evidence from a field experiment," Labour Economics, Elsevier, vol. 31(C), pages 61-71.
    7. Jaap H. Abbring, 0000. "Mixed Hitting-Time Models," Tinbergen Institute Discussion Papers 07-057/3, Tinbergen Institute, revised 11 Aug 2009.
    8. Jaap H. Abbring & Gerard J. van den Berg, 2000. "The Non-Parametric Identification of the Mixed Proportional Hazards Competing Risks Model," Tinbergen Institute Discussion Papers 00-066/3, Tinbergen Institute.
    9. Bijwaard, Govert, 2011. "Unobserved Heterogeneity in Multiple-Spell Multiple-States Duration Models," IZA Discussion Papers 5748, Institute of Labor Economics (IZA).
    10. Wienke, Andreas & Kuss, Oliver, 2009. "Random effects Weibull regression model for occupational lifetime," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1249-1250, August.
    11. Berg, G.J. & Ours, J.C., 1994. "Eyeball tests for state dependence and unobserved heterogeneity in aggregate unemployment duration data," Serie Research Memoranda 0009, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    12. Wiji Narendranathan & Mark B. Stewart, 1993. "Modelling the Probability of Leaving Unemployment: Competing Risks Models with Flexible Base‐Line Hazards," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 42(1), pages 63-83, March.
    13. Ott-Siim Toomet, 2005. "Does an Increase in Unemployment Income Lead to Longer Unemployment Spells? Evidence Using Danish Unemployment Assistance Data," Bank of Estonia Working Papers 2005-09, Bank of Estonia, revised 10 Oct 2005.
    14. Govert Bijwaard, 2014. "Multistate event history analysis with frailty," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 30(58), pages 1591-1620.
    15. John C. Ham & Xianghong Li & Lara Shore-Sheppard, 2009. "Seam Bias, Multiple-State, Multiple-Spell Duration Models and the Employment Dynamics of Disadvantaged Women," NBER Working Papers 15151, National Bureau of Economic Research, Inc.
    16. 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.
    17. Hie Ahn & James Hamilton, 2016. "Heterogeneity and Unemployment Dynamics," Working Papers id:11130, eSocialSciences.
    18. J. Cao, "undated". "Welfare recipiency and welfare recidivism: An analysis of the NLSY data," Institute for Research on Poverty Discussion Papers 1081-96, University of Wisconsin Institute for Research on Poverty.
    19. 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.
    20. Bijwaard Govert E. & Ridder Geert & Woutersen Tiemen, 2013. "A Simple GMM Estimator for the Semiparametric Mixed Proportional Hazard Model," Journal of Econometric Methods, De Gruyter, vol. 2(1), pages 1-23, July.

    More about this item

    Keywords

    duration analysis; Levy process; dynamic unobserved heterogeneity; identification; mixture;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • 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:tse:wpaper:25316. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/tsetofr.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.