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Semiparametric Modelling and Estimation: A Selective Overview

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  • Dennis Kristensen

    ()
    (Columbia University and CREATES)

Abstract

Semiparametric models are characterized by a finite- and infinite-dimensional (functional) component. As such they allow for added flexibility over fully parametric models, and at the same time estimators of parametric components can be developed that exhibit standard parametric convergence rates. These two features have made semiparametric models and estimators increasingly popular in applied economics. We give a partial overview over the literature on semiparametric modelling and estimation with particular emphasis on semiparametric regression models. The main focus is on developing two-step semiparametric estimators and deriving their asymptotic properties. We do however also briefly discuss sieve-based estimators and semiparametric efficiency.

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Bibliographic Info

Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2009-44.

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Length: 42
Date of creation: 01 Sep 2009
Date of revision:
Handle: RePEc:aah:create:2009-44

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Web page: http://www.econ.au.dk/afn/

Related research

Keywords: efficiency; kernel estimation; regression; semiparametric; sieve; two-step estimation;

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