Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-27T18:45:01.296Z Has data issue: false hasContentIssue false
  • English
  • Français

EFFICIENT SEMIPARAMETRIC ESTIMATION OF DURATION MODELS WITH UNOBSERVED HETEROGENEITY

Published online by Cambridge University Press:  30 January 2007

Peter Bearse ,
José Canals-Cerdá  and
Paul Rilstone
Peter Bearse
Affiliation:
University of North Carolina at Greensboro
José Canals-Cerdá
Affiliation:
University of Colorado
Paul Rilstone
Affiliation:
York University
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper develops a new semiparametric approach for the estimation of hazard functions in the presence of unobserved heterogeneity. The hazard function is specified parametrically, whereas the distribution of the unobserved heterogeneity is indirectly estimated using the method of kernels. The semiparametric efficiency bounds are derived. The estimator obtains these bounds in large samples.The authors thank Yongmiao Chen, James Heckman, Hidehiko Ichimura, Tony Lancaster, Qi Li, Adrian Pagan, Barry Smith, two anonymous referees, and the co-editor for helpful input. We particularly thank Steven Stern, who prompted us toward this line of research. Any errors are those of the authors. Research funding for Rilstone was provided by the Social Sciences and Humanities Research Council of Canada.

Type
Research Article
Information
Econometric Theory , Volume 23 , Issue 2 , April 2007 , pp. 281 - 308
Copyright
© 2007 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Baker, M. & A. Melino (2000) Duration dependence and nonparametric heterogeneity: A Monte Carlo study. Journal of Econometrics 96, 357–393.Google Scholar
Canals-Cerdá, J. (2003) Pre-Marital Birth, Marriage and Welfare. Working paper, University of Colorado at Boulder.
Elbers, C. & G. Ridder (1982) True and spurious duration dependence: The identifiability of the proportional hazard model. Review of Economic Studies 49, 403–409.Google Scholar
Follmann, D., M. Goldberg, & L. May (1990) Personal characteristics, unemployment insurance, and the duration of unemployment. Journal of Econometrics 45, 351–366.Google Scholar
Gasser, T. & H.G. Muller (1979) Kernel estimation of regression functions. In T. Gasser & M. Rosenblatt (eds.), Smoothing Techniques for Curve Estimation, Lecture Notes in Mathematics 757, pp. 23–68. Springer.
Gritz, R.M. (1993) The impact of training on the frequency and duration of employment. Journal of Econometrics 57, 21–52.Google Scholar
Gurmu, S., P. Rilstone, & S. Stern (1995) Nonparametric Hazard Rate Estimation. Mimeo, Department of Economics, University of Virginia.
Hahn, J. (1994) The efficiency bound of the mixed proportional hazard model. Review of Economic Studies 61, 607–629.Google Scholar
Ham, J. & S. Rea (1987) Unemployment insurance and male unemployment duration in Canada. Journal of Labor Economics 5, 325–353.Google Scholar
Han, A. & J.A. Hausman (1990) Flexible parametric estimation of duration and competing risk models. Journal of Applied Econometrics 5, 1–28.Google Scholar
Heckman, J.J. & B. Singer (1984) A method for reducing the impact of distributional assumptions in econometric models for duration data. Econometrica 52, 271–320.Google Scholar
Heckman, J.J. & B. Singer (1985) Social science duration data. In J.J. Heckman & B. Singer (eds.), Longitudinal Analysis of Labor Market Data, pp. 39–110. Cambridge University Press.
Honoré, B.E. (1990) Simple estimation of a duration model with unobserved heterogeneity. Econometrica 58, 453–474.Google Scholar
Horowitz, J.L. (1996) Semiparametric estimation of a regression model with an unknown transformation of the dependent variable. Econometrica 64, 103–138.Google Scholar
Jurajda, S. (2002) Estimating the effect of unemployment insurance compensation on the labor market histories of displaced workers. Journal of Econometrics 108, 227–252.Google Scholar
Katz, L. & B.D. Meyer (1990) The impact of the potential duration of unemployment benefits on the duration of unemployment. Journal of Public Economics 41, 45–72.Google Scholar
Kennan, J. (1985) The duration of contract strikes in U.S. manufacturing. Journal of Econometrics 28, 5–28.Google Scholar
Kiefer, N. (1988) Economic duration data and hazard functions. Journal of Economic Literature 26, 646–679.Google Scholar
Klein, R.W. & R.H. Spady (1993) An efficient semiparametric estimator for binary response models. Econometrica 61, 387–421.Google Scholar
Lancaster, T. (1979) Econometric methods for the duration of unemployment. Econometrica 47, 939–956.Google Scholar
Lancaster, T. (1990) The Analysis of Transition Data. Cambridge University Press.
Meyer, B.D. (1990) Unemployment insurance and unemployment spells. Econometrica 58, 757–782.Google Scholar
Newey, W.K. (1990) Semiparametric efficiency bounds. Journal of Applied Econometrics 5, 99–135.Google Scholar
Nielsen, J.P., O. Linton, & P.J. Bickel (1998) On a semiparametic survival model with flexible covariate effect. Annals of Statistics 26, 215–241.Google Scholar
Ridder, G. (1990) The non-parametric identification of generalized accelerated failure time models. Review of Economic Studies 57, 167–182.Google Scholar
Ridder, G. & T.M. Woutersen (2003) The singularity of the information matrix of the mixed proportional hazard model. Econometrica 71, 1579–1589.Google Scholar
Trussel, J. & T. Richards (1985) Correcting for unobserved heterogeneity in hazard models: An application of the Heckman–Singer procedure to demographic data. In N. Tuma (ed.), Sociological Methodology, pp. 242–276. Jossey-Bass.
Van der Vaart, A. (1996) Efficient semiparametric estimation in semiparametric mixture models. Annals of Statistics 24, 862–879.Google Scholar