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Identification of Lagged Duration Dependence in Multiple Spells Competing Risks Models

Author

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  • Guillaume HORNY

    (Banque de France and UNIVERSITE CATHOLIQUE DE LOUVAIN, Institut de Recherches Economiques et Sociales (IRES))

  • Matteo PICCHIO

    (UNIVERSITE CATHOLIQUE DE LOUVAIN, Institut de Recherches Economiques et Sociales (IRES))

Abstract

We show non-parametric identification of lagged duration dependence in mixed proportional hazard models for duration data, in the presence of competing risks and consecutive spells. We extend the results to the case in which data provide repeated realizations of consecutive spells competing risks structure for each subject

Suggested Citation

  • Guillaume HORNY & Matteo PICCHIO, 2009. "Identification of Lagged Duration Dependence in Multiple Spells Competing Risks Models," LIDAM Discussion Papers IRES 2009001, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    • Handle: RePEc:ctl:louvir:2009001
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    References listed on IDEAS

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    Citations

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    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. Guy Lacroix & Dany Brouillette, 2011. "Assessing the impact of a wage subsidy for single parents on social assistance," Canadian Journal of Economics, Canadian Economics Association, vol. 44(4), pages 1195-1221, November.
    3. Bart Cockx & Stijn Baert, 2015. "Contracting Out Mandatory Counselling and Training for Long-Term Unemployed. Private For-Profit or Non-Profit, or Keep it Public?," CESifo Working Paper Series 5587, CESifo.
    4. Picchio, Matteo, 2012. "Lagged duration dependence in mixed proportional hazard models," Economics Letters, Elsevier, vol. 115(1), pages 108-110.
    5. 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.
    6. Emmanuelle Lavallée & Vincent Vicard, 2013. "National borders matterwhere one draws the lines too," Canadian Journal of Economics, Canadian Economics Association, vol. 46(1), pages 135-153, February.
    7. 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.
    8. 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.
    9. 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.
    10. Rune Lesner, 2015. "Does labor market history matter?," Empirical Economics, Springer, vol. 48(4), pages 1327-1364, June.
    11. Lo, Simon M.S. & Mammen, Enno & Wilke, Ralf A., 2020. "A nested copula duration model for competing risks with multiple spells," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).
    12. Mattia Filomena, 2021. "Unemployment Scarring Effects: A Symposium On Empirical Literature," Working Papers 453, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.

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    More about this item

    Keywords

    Lagged duration dependence; competing risks; MPH models; identification;
    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
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search

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