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

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Author Info
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.

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Publisher Info
Paper provided by Oslo University, Department of Economics in its series Memorandum with number 25/2003.

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Length: 89 pages
Date of creation: 01 Dec 2003
Date of revision:
Handle: RePEc:hhs:osloec:2003_025

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Postal: Department of Economics, University of Oslo, P.O Box 1095 Blindern, N-0317 Oslo, Norway
Phone: 22 85 51 27
Fax: 22 85 50 35
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Web page: http://www.oekonomi.uio.no/indexe.html
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Related research
Keywords: duration dependence; unobserved heterogeneity; non-parametric estimation; Monte Carlo study; time-varying covariates;

Other versions of this item:

Find related papers by JEL classification:
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. 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 Labour Market Policy Evaluation. [Downloadable!]
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  3. 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 683-94, November. [Downloadable!] (restricted)
  4. repec:cup:etheor:v:12:y:1996:i:4:p:733-38 is not listed on IDEAS
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  6. Kiefer, Nicholas M, 1988. "Economic Duration Data and Hazard Functions," Journal of Economic Literature, American Economic Association, vol. 26(2), pages 646-79, June. [Downloadable!] (restricted)
  7. Elbers, Chris & Ridder, Geert, 1982. "True and Spurious Duration Dependence: The Identifiability of the Proportional Hazard Model," Review of Economic Studies, Blackwell Publishing, vol. 49(3), pages 403-09, July. [Downloadable!] (restricted)
  8. Joel L. Horowitz, 1999. "Semiparametric Estimation of a Proportional Hazard Model with Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 67(5), pages 1001-1028, September.
  9. Lancaster, Tony, 1979. "Econometric Methods for the Duration of Unemployment," Econometrica, Econometric Society, vol. 47(4), pages 939-56, July. [Downloadable!] (restricted)
  10. McCall, B.P., 1992. "The Non-parametric Identifiability of a Competing Risks Model with Regressors," Papers 92-01, Minnesota - Industrial Relations Center.
  11. Jaap H. Abbring & Gerard J. van den Berg, 2000. "The Non-Parametric Identification of the Mixed Proportional Hazards Competing Risks Model," Tinbergen Institute Discussion Papers 00-066/3, Tinbergen Institute. [Downloadable!]
  12. Rafael Lalive & Jan C. van Ours & Josef Zweimueller, . "The Impact of Active Labor Market Programs on the Duration of Unemployment," IEW - Working Papers iewwp041, Institute for Empirical Research in Economics - IEW. [Downloadable!]
  13. Abbring, Jaap H & van den Berg, Gerard J, 2007. "The Unobserved Heterogeneity Distribution in Duration Analysis," CEPR Discussion Papers 6219, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
    Other versions:
  14. McCall, Brian P., 1996. "The Identifiability of the Mixed Proportional Hazards Model with Time-Varying Coefficients," Econometric Theory, Cambridge University Press, vol. 12(04), pages 733-738, October. [Downloadable!]
  15. 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. [Downloadable!] (restricted)
    Other versions:
  16. Knut Roed & Tao Zhang, 2003. "Does Unemployment Compensation Affect Unemployment Duration?," Economic Journal, Royal Economic Society, vol. 113(484), pages 190-206, January. [Downloadable!] (restricted)
  17. McCall, B.P., 1992. "The Identifiability of the Mixed non-Proportional Hazards Models," Papers 92-16, Minnesota - Industrial Relations Center.
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  1. repec:ese:iserwp: is not listed on IDEAS
  2. 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. [Downloadable!]
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