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Semiparametric estimation of a censored regression model with an unknown transformation of the dependent variable

  • Gorgens, Tue
  • Horowitz, Joel L.

In this paper we develo psemiparametric estimators of L and y in the model L(Y) = min[b›X + U,C], where Y is a nonnegative dependent variable, X is a vector of explanatory variables, U is an unobserved random "error" term with unknown distribution function y, C is a random censoring variable, b is an unknown parameter vector, and L is an unknown strictly increasing function. This model includes as a special case the censored proportional hazards model with unobserved heterogeneity. Estimators of L and y already exist for the case where either L or y belongs to a known finite-dimensional parametric family, and methods for estimating b exist for the general case. In this paper we propose estimators of L and y which do not assume that L and y belong to known parametric families. We obtain their asymptotic distributions and investigate the small sample properties of the estimators by Monte Carlo simulation.

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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 90 (1999)
Issue (Month): 2 (June)
Pages: 155-191

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Handle: RePEc:eee:econom:v:90:y:1999:i:2:p:155-191
Contact details of provider: Web page: http://www.elsevier.com/locate/jeconom

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  1. 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.
  2. Tue Gorgens & Joel L. Horowitz, 1996. "Semiparametric Estimation of a Censored Regression Model with an Unknown Transformation of the Dependent Variable," Econometrics 9603001, EconWPA.
  3. 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.
  4. Kennan, John & Wilson, Robert, 1989. "Strategic Bargaining Models and Interpretation of Strike Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(S), pages S87-130, Supplemen.
  5. 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.
  6. Bruce D. Meyer, 1988. "Unemployment Insurance And Unemployment Spells," NBER Working Papers 2546, National Bureau of Economic Research, Inc.
  7. Powell, James L & Stock, James H & Stoker, Thomas M, 1989. "Semiparametric Estimation of Index Coefficients," Econometrica, Econometric Society, vol. 57(6), pages 1403-30, November.
  8. Pakes, Ariel & Pollard, David, 1989. "Simulation and the Asymptotics of Optimization Estimators," Econometrica, Econometric Society, vol. 57(5), pages 1027-57, September.
  9. Kiefer, Nicholas M, 1988. "Economic Duration Data and Hazard Functions," Journal of Economic Literature, American Economic Association, vol. 26(2), pages 646-79, June.
  10. Haerdle,Wolfgang & Stoker,Thomas, 1987. "Investigations smooth multiple regression by the method of average derivatives," Discussion Paper Serie A 107, University of Bonn, Germany.
  11. Ichimura, H., 1991. "Semiparametric Least Squares (sls) and Weighted SLS Estimation of Single- Index Models," Papers 264, Minnesota - Center for Economic Research.
  12. 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.
  13. Sherman, Robert P, 1993. "The Limiting Distribution of the Maximum Rank Correlation Estimator," Econometrica, Econometric Society, vol. 61(1), pages 123-37, January.
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