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Nonparametric Estimation and Hypothesis Testing in Econometric Models

  • Conference paper
Semiparametric and Nonparametric Econometrics

Part of the book series: Studies in Empirical Economics ((STUDEMP))

Abstract

In this paper we systematically review and develop nonparametric estimation and testing techniques in the context of econometric models. The results are discussed under the settings of regression model and kernel estimation, although as indicated in the paper these results can go through for other econometric models and for the nearest neighbor estimation. A nontechnical survey of the asymptotic properties of kernel regression estimation is also presented. The technique described in the paper are useful for the empirical analysis of the economic relations whose true functional forms are usually unknown.

I thank I. Ahmad, A. Bera, A. Pagan, C. Robinson, A. Zellner, and the participants of the workshops at the Universities of Chicago, Northern Illinois, Stanford, Riverside and Santa Barbara, for their comments on the subject matter of this paper. The work on this paper was done when the author was a vising scholar at the Stanford University. The SSHRC research grant and research facilities at the Stanford University are gratefully acknowledged.

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Authors and Affiliations

  1. Department of Economics, University of Western Ontario, London, Ontario, N6A 5C2, Canada

    Aman Ullah

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  1. Aman Ullah
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Editors and Affiliations

  1. Department of Economics, University of Western Ontario, London, Ontario, N6A 5C2, Canada

    Aman Ullah

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© 1989 Physica-Verlag Heidelberg

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Ullah, A. (1989). Nonparametric Estimation and Hypothesis Testing in Econometric Models. In: Ullah, A. (eds) Semiparametric and Nonparametric Econometrics. Studies in Empirical Economics. Physica-Verlag HD. https://doi.org/10.1007/978-3-642-51848-5_7

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  • DOI: https://doi.org/10.1007/978-3-642-51848-5_7

  • Publisher Name: Physica-Verlag HD

  • Print ISBN: 978-3-642-51850-8

  • Online ISBN: 978-3-642-51848-5

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