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Lagged Duration Dependence in Mixed Proportional Hazard Models

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  • M. PICCHIO

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Abstract

We study the non-parametric identification of a mixed proportional hazard model with lagged duration dependence when data provide multiple outcomes per individual or stratum. We show that the information conveyed by the within strata variation can be exploited to non-parametrically identify lagged duration dependence in more general models than in the literature.

Suggested Citation

  • M. Picchio, 2011. "Lagged Duration Dependence in Mixed Proportional Hazard Models," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 11/747, Ghent University, Faculty of Economics and Business Administration.
  • Handle: RePEc:rug:rugwps:11/747
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    References listed on IDEAS

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    1. 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.
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    3. Bart Cockx & Matteo Picchio, 2012. "Are Short-lived Jobs Stepping Stones to Long-Lasting Jobs?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(5), pages 646-675, October.
    4. Frederiksen, Anders & Honore, Bo E. & Hu, Luojia, 2007. "Discrete time duration models with group-level heterogeneity," Journal of Econometrics, Elsevier, vol. 141(2), pages 1014-1043, December.
    5. Maarten Lindeboom & Marcel Kerkhofs, 2000. "Multistate Models For Clustered Duration Data - An Application To Workplace Effects On Individual Sickness Absenteeism," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 668-684, November.
    6. Patrick Arni & Rafael Lalive & Jan C. Van Ours, 2013. "How Effective Are Unemployment Benefit Sanctions? Looking Beyond Unemployment Exit," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(7), pages 1153-1178, November.
    7. 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.
    8. Arni, Patrick & Lalive, Rafael & van Ours, Jan C, 2009. "How Effective Are Unemployment Benefit Sanctions?," CEPR Discussion Papers 7541, C.E.P.R. Discussion Papers.
    9. 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.
    10. Melino, Angelo & Sueyoshi, Glenn T., 1990. "A simple approach to the identifiability of the proportional hazards model," Economics Letters, Elsevier, vol. 33(1), pages 63-68, May.
    11. Ridder, Geert & Tunali, Insan, 1999. "Stratified partial likelihood estimation," Journal of Econometrics, Elsevier, vol. 92(2), pages 193-232, October.
    12. Frijters, Paul, 2002. "The non-parametric identification of lagged duration dependence," Economics Letters, Elsevier, vol. 75(3), pages 289-292, May.
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    14. 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.
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    Cited by:

    1. 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.
    2. Rune Lesner, 2015. "Does labor market history matter?," Empirical Economics, Springer, vol. 48(4), pages 1327-1364, June.

    More about this item

    Keywords

    lagged duration dependence; mixed proportional hazard models; identification; multiple spells; parallel data.;

    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

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