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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/9760

Title: Estimation of a semiparametric transformation model
Authors: LINTON, O.
Issue Date: 2008
Citation: ANNALS OF STATISTICS, 36(2). p. 686-718
Abstract: This paper proposes consistent estimators for transformation parameters in semiparametric models. The problem is to find the optimal transformation into the space of models with a predetermined regression structure like additive or multiplicative separability. We give results for the estimation of the transformation when the rest of the model is estimated non- or semi-parametrically and fulfills some consistency conditions. We propose two methods for the estimation of the transformation parameter maximizing a profile likelihood function or minimizing the mean squared distance from independence. First the problem of identification of such models is discussed. We then state asymptotic results for a general class of nonparametric estimators. Finally, we give some particular examples of nonparametric estimators of transformed separable models. The small sample performance is studied in several simulations.
Notes: [Linton, Oliver] London Sch Econ, Dept Econ, London WC2A 2AE, England. [Sperlich, Stefan] Univ Gottingen, Inst Stat & Okonometrie, D-37073 Gottingen, Germany. [Van Keilegom, Ingrid] Univ Catholique Louvain, Inst Stat, B-1348 Louvain, Belgium.
URI: http://hdl.handle.net/1942/9760
DOI: 10.1214/009053607000000848
ISI #: 000254502700008
ISSN: 0090-5364
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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