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Semiparametric Estimation of a Censored Regression Model with an Unknown Transformation of the Dependent Variable by Tue Gørgens; Joel L. Horowitz is a Economics, Econometrics and Finance article available to read on EtoBox.
What is Semiparametric Estimation of a Censored Regression Model with an Unknown Transformation of the Dependent Variable about?
This paper presents a method for estimating the model (1⁄2)"min( X#o, C), where 1⁄2 is a scalar, is an unknown increasing function, X is a vector of explanatory variables, is a vector of unknown parameters, o has unknown cumulative distribution function F, and C is a censoring threshold. It is not assumed that and F belong to known parametric families; they are estimated nonparametrically. This model includes many widely used models as special cases, including the proportional hazards model with unobserved heterogeneity. The paper develops n-consistent, asymptotically normal estimators of and F. Estimators of that are n-consistent and asymptotically normal already exist. The results of Monte Carlo experiments illustrate the finite-sample behavior of the estimators.
Who reads Semiparametric Estimation of a Censored Regression Model with an Unknown Transformation of the Dependent Variable?
It is typically read by researchers, students, and practitioners in Economics, Econometrics and Finance.
- Author
- Tue Gørgens; Joel L. Horowitz
- Publisher
- Elsevier Science; Elsevier ; Elsevier BV (ISSN 0304-4076)
- Published
- 1999
- Language
- EN
- Field
- Economics, Econometrics and Finance (Social Sciences)