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The (mis)specification of discrete duration models with unobserved heterogeneity: A Monte Carlo study

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  • Nicoletti, Cheti
  • Rondinelli, Concetta

Abstract

Empirical researchers usually prefer statistical models that can be easily estimated with the help of commonly available software packages. Sequential binary models with or without normal random effects are an example of such models that can be adopted to estimate discrete duration models with unobserved heterogeneity. But an easy-to-implement estimation may incur a cost. In this paper we conduct a Monte Carlo simulation to evaluate the consequences of omitting or misspecifying the unobserved heterogeneity distribution in single-spell discrete duration models.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:econom:v:159:y:2010:i:1:p:1-13
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    References listed on IDEAS

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    1. Meyer, Bruce D, 1990. "Unemployment Insurance and Unemployment Spells," Econometrica, Econometric Society, vol. 58(4), pages 757-782, July.
    2. Sueyoshi, Glenn T, 1995. "A Class of Binary Response Models for Grouped Duration Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(4), pages 411-431, Oct.-Dec..
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, May.
    4. Jenkins, Stephen P, 1995. "Easy Estimation Methods for Discrete-Time Duration Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 57(1), pages 129-138, February.
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    8. Narendranathan, W & Stewart, Mark B, 1993. "How Does the Benefit Effect Vary as Unemployment Spells Lengthen?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(4), pages 361-381, Oct.-Dec..
    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.
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    11. 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.
    12. 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.
    13. Robert A. Moffitt & Peter Gottschalk, 2002. "Trends in the Transitory Variance of Earnings in the United States," Economic Journal, Royal Economic Society, vol. 112(478), pages 68-73, March.
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    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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