Semiparametric Estimation of Censored Transformation Models
AbstractMany widely used models, including proportional hazards models with un- observed heterogeneity, can be written in the form (Y ) = min[ 0 X + U; C], where is an unknown increasing function, the error term U has unknown distribution function and is independent of X, C is a random censoring threshold, and U and C are conditionally independent given X. Thispaper develops new n 1=2 -consistent and asymptotically normal semiparametric esti- mators of and which are easier to use than existing estimators. Moreover, Monte Carlo results suggest that the mean integrated squared error of predic- tions based on the new estimators is lower than for existing estimators.
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Bibliographic InfoPaper provided by New South Wales - School of Economics in its series Papers with number 98-13.
Length: 32 pages
Date of creation: 1998
Date of revision:
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Postal: THE UNIVERSITY OF NEW SOUTH WALES, SCHOOL OF ECONOMICS, P.O.B. 1 KENSINGTON, NEW SOUTH WALES 2033 AUSTRALIA.
Fax: +61)-2- 9313- 6337
Web page: http://www.economics.unsw.edu.au/
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ECONOMETRIC MODELS ; ESTIMATION OF PARAMETERS ; REGRESSION ANALYSIS;
Find related papers by JEL classification:
- 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
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