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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.

Suggested Citation

  • Dennis Kristensen, 2009. "Semiparametric Modelling and Estimation: A Selective Overview," CREATES Research Papers 2009-44, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2009-44
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    References listed on IDEAS

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    More about this item

    Keywords

    efficiency; kernel estimation; regression; semiparametric; sieve; two-step estimation;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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