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A Monte Carlo study on non-parametric estimation of duration models with unobserved heterogeneity

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  • Zhang, Tao

    (The Ragnar Frisch Centre for Economic Research)

Abstract

We conduct extensive Monte Carlo experiments on non-parametric estimations of duration models with unknown duration dependence and unknown mixing distribution for unobserved heterogeneity. We propose a full non-parametric maximum likelihood approach, based on time-varying lagged explanatory covariates from observational data. By utilising this data-based identification source, we find that both duration dependence and unobserved heterogeneity can be reliably estimated. Our Monte Carlo evidences show that variation in time-varying lagged explanatory variables contributes to the identification of both duration dependence and unobserved heterogeneity, especially when sample sizes are limited. For limited sample sizes, maximum penalised likelihood with information criteria seems to produce more accurate estimators than pure maximum likelihood. Our approach can be easily extended to multivariate competing risks model with dependent unobserved heterogeneities.

Suggested Citation

  • Zhang, Tao, 2003. "A Monte Carlo study on non-parametric estimation of duration models with unobserved heterogeneity," Memorandum 25/2003, Oslo University, Department of Economics.
    • Handle: RePEc:hhs:osloec:2003_025
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    File URL: http://www.sv.uio.no/econ/english/research/unpublished-works/working-papers/pdf-files/2003/Memo-25-2003.pdf
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    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. Brinch,C., 2000. "Identification of structural duration dependence and unobserved heterogeneity with time-varying," Memorandum 20/2000, Oslo University, Department of Economics.
    3. Kiefer, Nicholas M, 1988. "Economic Duration Data and Hazard Functions," Journal of Economic Literature, American Economic Association, vol. 26(2), pages 646-679, June.
    4. Rafael Lalive & Jan C. van Ours & Josef Zweimueller, "undated". "The Impact of Active Labor Market Programs on the Duration of Unemployment," IEW - Working Papers 041, Institute for Empirical Research in Economics - University of Zurich.
    5. McCall, Brian P., 1996. "The Identifiability of the Mixed Proportional Hazards Model with Time-Varying Coefficients," Econometric Theory, Cambridge University Press, vol. 12(4), pages 733-738, October.
    6. Gaure, Simen & Røed, Knut, 2003. "How Tight is the Labour Market? A Micro-Based Macro Indicator," Memorandum 09/2003, Oslo University, Department of Economics.
    7. Huh, Keun & Sickles, Robin C, 1994. "Estimation of the Duration Model by Nonparametric Maximum Likelihood, Maximum Penalized Likelihood, and Probability Simulators," The Review of Economics and Statistics, MIT Press, vol. 76(4), pages 683-694, November.
    8. repec:cup:etheor:v:12:y:1996:i:4:p:733-38 is not listed on IDEAS
    9. 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.
    10. 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.
    11. Lancaster, Tony, 1985. "Generalised residuals and heterogeneous duration models : With applications to the Weilbull model," Journal of Econometrics, Elsevier, vol. 28(1), pages 155-169, April.
    12. McCall, B.P., 1992. "The Identifiability of the Mixed non-Proportional Hazards Models," Papers 92-16, Minnesota - Industrial Relations Center.
    13. Joel L. Horowitz, 1999. "Semiparametric Estimation of a Proportional Hazard Model with Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 67(5), pages 1001-1028, September.
    14. McCall, B.P., 1992. "The Non-parametric Identifiability of a Competing Risks Model with Regressors," Papers 92-01, Minnesota - Industrial Relations Center.
    15. Knut Roed & Tao Zhang, 2003. "Does Unemployment Compensation Affect Unemployment Duration?," Economic Journal, Royal Economic Society, vol. 113(484), pages 190-206, January.
    16. Richardson, Katarina & van den Berg, Gerard J., 2002. "The effect of vocational employment training on the individual transition rate from unemployment to work," Working Paper Series 2002:8, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    17. Lancaster, Tony, 1979. "Econometric Methods for the Duration of Unemployment," Econometrica, Econometric Society, vol. 47(4), pages 939-956, July.
    18. 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.
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    Cited by:

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    2. Nicoletti, Cheti & Rondinelli, Concetta, 2006. "The (mis)specification of discrete time duration models with unobserved heterogenity: a Monte Carlo study," ISER Working Paper Series 2006-53, Institute for Social and Economic Research.
    3. 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.
    4. Gaure, Simen & Roed, Knut & Zhang, Tao, 2007. "Time and causality: A Monte Carlo assessment of the timing-of-events approach," Journal of Econometrics, Elsevier, vol. 141(2), pages 1159-1195, December.
    5. Ott Toomet, 2005. "Does an increase in unemployment income lead to longer unemployment spells? Evidence using Danish unemployment assistance data," Economics Working Papers 2005-07, Department of Economics and Business Economics, Aarhus University.
    6. Ortiz-Villajos, José M. & Sotoca, Sonia, 2018. "Innovation and business survival: A long-term approach," Research Policy, Elsevier, vol. 47(8), pages 1418-1436.
    7. Pål Børing, 2015. "The effects of firms’ R&D and innovation activities on their survival: a competing risks analysis," Empirical Economics, Springer, vol. 49(3), pages 1045-1069, November.
    8. Pål Børing, 2010. "Gamma Unobserved Heterogeneity and Duration Bias," Econometric Reviews, Taylor & Francis Journals, vol. 29(1), pages 1-19.
    9. 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.

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    More about this item

    Keywords

    duration dependence; unobserved heterogeneity; non-parametric estimation; Monte Carlo study; time-varying covariates;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

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