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Edgeworth approximations for semiparametric instrumental variable estimators and test statistics

Linton, Oliver (2000) Edgeworth approximations for semiparametric instrumental variable estimators and test statistics. Econometrics; EM/2000/399, EM/00/399. Suntory and Toyota International Centres for Economics and Related Disciplines, London School of Economics and Political Science, London, UK.

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Abstract

We establish the validity of higher order asymptotic expansions to the distribution of a version of the nonlinear semiparametric instrumental variable considered in Newey (1990) as well as to the distribution of a Wald statistic derived from it. We employ local polynomial smoothing with variable bandwidth, which includes local linear, kernel, and [a version of] nearest neighbour estimates as special cases. Our expansions are valid to order n �2є for some 0 < є < ½, where є depends on the smoothness and dimensionality of the data distribution and on the order of the polynomial chosen by the practitioner. We use the expansions to define optimal bandwidth selection methods for both estimation and testing problems and apply our methods to simulated data.

Item Type: Monograph (Discussion Paper)
Official URL: http://sticerd.lse.ac.uk
Additional Information: © 2000 Oliver Linton
Uncontrolled Keywords: Bandwidth selection; Edgeworth approximation; instrumental variables; kernel estimation; local polynomials
Library of Congress subject classification: H Social Sciences > HB Economic Theory
Journal of Economic Literature Classification System: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C14 - Semiparametric and Nonparametric Methods
Sets: Research centres and groups > Financial Markets Group (FMG)
Collections > Economists Online
Departments > Economics
Research centres and groups > Suntory and Toyota International Centres for Economics and Related Disciplines (STICERD)
Rights: http://www.lse.ac.uk/library/rights/LSERO.htm
Identification Number: EM/00/399
URL: http://eprints.lse.ac.uk/2156/

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