Semiparametric Estimation of Single-Index Transition Intensities
AbstractThis research develops semiparametric kernel-based estimators of state-specific conditional transition intensities, h(y|x), for duration models with right-censoring and/or multiple destinations (competing risks). Both discrete and continuous duration data are considered. The maintained assumption is that h(y|x) depends on x only through an index x'b. In contrast to existing semiparametric estimators, proportional intensities is not assumed. The new estimators are asymptotically normally distributed. The estimator of b is root-n consistent. The estimator of h(y|x) achieves the one-dimensional rate of convergence. Thus the single-index assumption eliminates the "curse of dimensionality". The estimators perform well in Monte Carlo experiments.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Econometric Society in its series Econometric Society World Congress 2000 Contributed Papers with number 0596.
Date of creation: 01 Aug 2000
Date of revision:
Contact details of provider:
Phone: 1 212 998 3820
Fax: 1 212 995 4487
Web page: http://www.econometricsociety.org/pastmeetings.asp
More information through EDIRC
Other versions of this item:
- Gorgens, T., 1999. "Semiparametric Estimation of Single-Index Transition Intensities," Papers 99-25, Carleton - School of Public Administration.
- Tue Gørgens, 1999. "Semiparametric Estimation of Single-Index Transition Intensities," Discussion Papers 99-25, University of Copenhagen. Department of Economics.
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models
- C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
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.:
- Ichimura, H., 1991. "Semiparametric Least Squares (sls) and Weighted SLS Estimation of Single- Index Models," Papers 264, Minnesota - Center for Economic Research.
- Joel L. Horowitz, 1999. "Semiparametric Estimation of a Proportional Hazard Model with Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 67(5), pages 1001-1028, September.
- J. L. HOROWITZ & Wolfgang HÄRDLE, 1994.
"Direct Semiparametric Estimation of Single - Index Models with Discrete Covariates,"
SFB 373 Discussion Papers
1994,36, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Horowitz, Joel & Hardle, Wolfgang, 1994. "Direct Semiparametric Estimation of Single-Index Models With Discrete Covariates," Working Papers 94-22, University of Iowa, Department of Economics.
- Hardle, W.K. & Tsybakov, A.B., 1992.
"How sensitive are average derivatives?,"
1992-8, Tilburg University, Center for Economic Research.
- Hardle, W. & Tsybakov, A., 1991. "How sensitive are average derivates ?," CORE Discussion Papers 1991044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Hardle, W. & Tsybakov, A.B., 1992. "How Sensitive are Average Derivatives?," Papers 9208, Tilburg - Center for Economic Research.
- Klein, R.W. & Spady, R.H., 1991.
"An Efficient Semiparametric Estimator for Binary Response Models,"
70, Bell Communications - Economic Research Group.
- Klein, Roger W & Spady, Richard H, 1993. "An Efficient Semiparametric Estimator for Binary Response Models," Econometrica, Econometric Society, vol. 61(2), pages 387-421, March.
- Pakes, Ariel & Pollard, David, 1989. "Simulation and the Asymptotics of Optimization Estimators," Econometrica, Econometric Society, vol. 57(5), pages 1027-57, September.
- Chunrong Ai, 1997. "A Semiparametric Maximum Likelihood Estimator," Econometrica, Econometric Society, vol. 65(4), pages 933-964, July.
- 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.
- Haerdle,Wolfgang & Stoker,Thomas, 1987. "Investigations smooth multiple regression by the method of average derivatives," Discussion Paper Serie A 107, University of Bonn, Germany.
- Horowitz, J. & Gorgens, T., 1995.
"Semiparametric Estimation of a Censored Regression Model with an Unknown Transformation of the Dependent Variable,"
95-15, University of Iowa, Department of Economics.
- 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.
- Tue Gorgens & Joel L. Horowitz, 1996. "Semiparametric Estimation of a Censored Regression Model with an Unknown Transformation of the Dependent Variable," Econometrics 9603001, EconWPA.
- 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.
- Oliver LINTON, . "Kernel estimation in a nonparametric marker dependent Hazard Model," Statistic und Oekonometrie 9313, Humboldt Universitaet Berlin.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).
If references are entirely missing, you can add them using this form.