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Estimation of Heterogeneous Treatment Effects on Hazard Rates

Author

Listed:
  • Gaure, Simen

    (Ragnar Frisch Centre for Economic Research)

  • Røed, Knut

    (Ragnar Frisch Centre for Economic Research)

  • van den Berg, Gerard J.

    (University of Groningen)

  • Zhang, Tao

    (Ragnar Frisch Centre for Economic Research)

Abstract
Consider a setting where a treatment that starts at some point during a spell (e.g. in unemployment) may impact on the hazard rate of the spell duration, and where the impact may be heterogeneous across subjects. We provide Monte Carlo evidence on the feasibility of estimating the distribution of treatment effects from duration data with selectivity, by means of a nonparametric maximum likelihood estimator with unrestricted numbers of mass points for the heterogeneity distribution. We find that specifying the treatment effect as homogenous may yield misleading average results if the true effects are heterogeneous, even when the sorting into treatment is appropriately accounted for. Specifying the treatment effect as a random coefficient allows for precise estimation of informative average treatment effects including the program’s overall impact on the mean duration.

Suggested Citation

  • Gaure, Simen & Røed, Knut & van den Berg, Gerard J. & Zhang, Tao, 2010. "Estimation of Heterogeneous Treatment Effects on Hazard Rates," IZA Discussion Papers 4794, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp4794
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    File URL: https://docs.iza.org/dp4794.pdf
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    References listed on IDEAS

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    1. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College," NBER Working Papers 9546, National Bureau of Economic Research, Inc.
    2. Carneiro, Pedro & Hansen, Karsten T. & Heckman, James J., 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," IZA Discussion Papers 767, Institute of Labor Economics (IZA).
    3. Bruno Crépon & Marc Ferracci & Grégory Jolivet & Gerard J. van den Berg, 2009. "Active Labor Market Policy Effects in a Dynamic Setting," Journal of the European Economic Association, MIT Press, vol. 7(2-3), pages 595-605, 04-05.
    4. Pedro Carneiro & Karsten T. Hansen & James J. Heckman, 2003. "2001 Lawrence R. Klein Lecture Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 361-422, May.
    5. Fredriksson, Peter & Johansson, Per, 2008. "Dynamic Treatment Assignment," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 435-445.
    6. Abbring, Jaap H & van den Berg, Gerard J, 2005. "Social experiments and intrumental variables with duration outcomes," Working Paper Series 2005:11, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    7. Jaap H. Abbring & Gerard J. van den Berg, 2004. "Analyzing the effect of dynamically assigned treatments using duration models, binary treatment models, and panel data models," Empirical Economics, Springer, vol. 29(1), pages 5-20, January.
    8. Michael Rosholm & Michael Svarer, 2008. "The Threat Effect of Active Labour Market Programmes," Scandinavian Journal of Economics, Wiley Blackwell, vol. 110(2), pages 385-401, June.
    9. Jaap H. Abbring & Gerard J. van den Berg, 2003. "The Nonparametric Identification of Treatment Effects in Duration Models," Econometrica, Econometric Society, vol. 71(5), pages 1491-1517, September.
    10. 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.
    11. Knut Røed & Oddbjørn Raaum, 2006. "Do Labour Market Programmes Speed up the Return to Work?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(5), pages 541-568, October.
    12. Baker, Michael & Melino, Angelo, 2000. "Duration dependence and nonparametric heterogeneity: A Monte Carlo study," Journal of Econometrics, Elsevier, vol. 96(2), pages 357-393, June.
    13. Aakvik, Arild & Heckman, James J. & Vytlacil, Edward J., 2005. "Estimating treatment effects for discrete outcomes when responses to treatment vary: an application to Norwegian vocational rehabilitation programs," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 15-51.
    14. Richardson, Katarina & van den Berg, Gerard J, 2008. "Duration dependence versus unobserved heterogeneity in treatment effects: Swedish labor market training and the transition rate to employment," Working Paper Series 2008:7, IFAU - Institute for Evaluation of Labour Market and Education Policy.
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    Cited by:

    1. Aderonke Osikominu, 2013. "Quick Job Entry or Long-Term Human Capital Development? The Dynamic Effects of Alternative Training Schemes," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(1), pages 313-342.

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    More about this item

    Keywords

    duration analysis; unobserved heterogeneity; program evaluation; nonparametric estimation; Monte Carlo simulation; timing of events; random effects;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • 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
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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