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Estimating a Semi-Parametric Duration Model without Specifying Heterogeneity

  • Tiemen Woutersen
  • Jerry Hausman

This paper presents a new estimator for the mixed proportional hazard model that allows for a nonparametric baseline hazard and time-varying regressors. In particular, this paper allows for discrete measurement of the durations as happens often in practice. The integrated baseline hazard and all parameters are estimated at regular rate,square root of N , where N is the number of individuals. A hazard model is a natural framework for time-varying regressors if a flow or a transition probability depends on a regressor that changes with time since a hazard model avoids the curse of dimensionality that would arise from interacting the regressors at each point in time with one another.

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Paper provided by The Johns Hopkins University,Department of Economics in its series Economics Working Paper Archive with number 525.

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Date of creation: Aug 2005
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Handle: RePEc:jhu:papers:525
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  1. Michael Baker & Angelo Melino, 1999. "Duration Dependence and Nonparametric Heterogeneity: A Monte Carlo Study," Working Papers melino-99-01, University of Toronto, Department of Economics.
  2. Joel L. Horowitz, 1999. "Semiparametric Estimation of a Proportional Hazard Model with Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 67(5), pages 1001-1028, September.
  3. Han, Aaron & Hausman, Jerry A, 1990. "Flexible Parametric Estimation of Duration and Competing Risk Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(1), pages 1-28, January-M.
  4. Geert Ridder & Tiemen Woutersen, 2002. "The Singularity of the Information Matrix of the Mixed Proportional Hazard Model," UWO Department of Economics Working Papers 20026, University of Western Ontario, Department of Economics.
  5. Gorgens, Tue & Horowitz, Joel L., 1999. "Semiparametric estimation of a censored regression model with an unknown transformation of the dependent variable," Journal of Econometrics, Elsevier, vol. 90(2), pages 155-191, June.
  6. Songnian Chen, 2002. "Rank Estimation of Transformation Models," Econometrica, Econometric Society, vol. 70(4), pages 1683-1697, July.
  7. Heckman, James J. & Lalonde, Robert J. & Smith, Jeffrey A., 1999. "The economics and econometrics of active labor market programs," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 31, pages 1865-2097 Elsevier.
  8. 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.
  9. Newey, W.K., 1989. "Uniform Convergence In Probability And Stochastic Equicontinuity," Papers 342, Princeton, Department of Economics - Econometric Research Program.
  10. Hausman, Jerry A & Wise, David A, 1979. "Attrition Bias in Experimental and Panel Data: The Gary Income Maintenance Experiment," Econometrica, Econometric Society, vol. 47(2), pages 455-73, March.
  11. Bruce D. Meyer, 1988. "Unemployment Insurance And Unemployment Spells," NBER Working Papers 2546, National Bureau of Economic Research, Inc.
  12. Heckman, James J, 1991. "Identifying the Hand of the Past: Distinguishing State Dependence from Heterogeneity," American Economic Review, American Economic Association, vol. 81(2), pages 75-79, May.
  13. Horowitz, Joel L, 1996. "Semiparametric Estimation of a Regression Model with an Unknown Transformation of the Dependent Variable," Econometrica, Econometric Society, vol. 64(1), pages 103-37, January.
  14. Van den Berg, Gerard J., 2000. "Duration Models: Specification, Identification, and Multiple Durations," MPRA Paper 9446, University Library of Munich, Germany.
  15. J. A. Hausman, 1976. "Specification Tests in Econometrics," Working papers 185, Massachusetts Institute of Technology (MIT), Department of Economics.
  16. Abrevaya, Jason, 1999. "Computation of the maximum rank correlation estimator," Economics Letters, Elsevier, vol. 62(3), pages 279-285, March.
  17. J. A. Hausman & W. E. Taylor, 1980. "Panel Data and Unobservable Individual Effects," Working papers 255, Massachusetts Institute of Technology (MIT), Department of Economics.
  18. Geert Ridder, 1990. "The Non-Parametric Identification of Generalized Accelerated Failure-Time Models," Review of Economic Studies, Oxford University Press, vol. 57(2), pages 167-181.
  19. Lancaster, Tony, 1979. "Econometric Methods for the Duration of Unemployment," Econometrica, Econometric Society, vol. 47(4), pages 939-56, July.
  20. Chris Elbers & Geert Ridder, 1982. "True and Spurious Duration Dependence: The Identifiability of the Proportional Hazard Model," Review of Economic Studies, Oxford University Press, vol. 49(3), pages 403-409.
  21. Jinyong Hahn, 1994. "The Efficiency Bound of the Mixed Proportional Hazard Model," Review of Economic Studies, Oxford University Press, vol. 61(4), pages 607-629.
  22. Honore, Bo E, 1990. "Simple Estimation of a Duration Model with Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 58(2), pages 453-73, March.
  23. Han, Aaron K., 1987. "Non-parametric analysis of a generalized regression model : The maximum rank correlation estimator," Journal of Econometrics, Elsevier, vol. 35(2-3), pages 303-316, July.
  24. Ham, John C & LaLonde, Robert J, 1996. "The Effect of Sample Selection and Initial Conditions in Duration Models: Evidence from Experimental Data on Training," Econometrica, Econometric Society, vol. 64(1), pages 175-205, January.
  25. Sherman, Robert P, 1993. "The Limiting Distribution of the Maximum Rank Correlation Estimator," Econometrica, Econometric Society, vol. 61(1), pages 123-37, January.
  26. Bo E. Honoré, 1993. "Identification Results for Duration Models with Multiple Spells," Review of Economic Studies, Oxford University Press, vol. 60(1), pages 241-246.
  27. Horowitz, Joel L., 2001. "The Bootstrap," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 52, pages 3159-3228 Elsevier.
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