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Rank Estimators For A Transformation Model

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Author Info
Asparouhova, Elena
Golanski, Robert
Kasprzyk, Krzysztof
Sherman, Robert P.
Asparouhov, Tihomir
Abstract

We establish [square root]n-consistency and asymptotic normality of Han s (1987a, Journal of Econometrics 35, 191 209) estimator of the parameters characterizing the transformation function in a semiparametric transformation model. We verify a Vapnik Cervonenkis (VC) condition for the parameterizations of Box and Cox (1964, Journal of the Royal Statistical Society, Series B 34, 187 200) and Bickel and Doksum (1981, Journal of the American Statistical Association 76, 296 311). The verification establishes the VC property for a class of sets generated by a nonlinear function of the transformation parameters. We also introduce a new class of rank estimators for these parameters. These estimators require only O(n2 logn) computations to evaluate the criterion function, compared to O(n4) computations for Han s estimator. We prove that these estimators are also [square root]n-consistent and asymptotically normal. A simulation study compares two of the new estimators to Han s estimator, the fully parametric estimator of Bickel and Doksum (1981), and the nonlinear two-stage least squares estimator of Amemiya and Powell (1981, Journal of Econometrics 17, 351 381).

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Publisher Info
Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 18 (2002)
Issue (Month): 05 (October)
Pages: 1099-1120
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Handle: RePEc:cup:etheor:v:18:y:2002:i:05:p:1099-1120_18

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  1. Subbotin, Viktor, 2007. "Asymptotic and bootstrap properties of rank regressions," MPRA Paper 9030, University Library of Munich, Germany, revised 20 Mar 2008. [Downloadable!]
  2. Subbotin, Viktor, 2008. "Essays on the econometric theory of rank regressions," MPRA Paper 14086, University Library of Munich, Germany. [Downloadable!]
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