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Exploring the Use of a Nonparametrically Generated Instrumetal Variable in the Estimation of a Linear Parametric Equation

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  • Frank T. Denton

Abstract

The use of a nonparametrically generated instrumental variable in estimating a single-equation linear parametric model is explored, using kernel and other smoothing functions. The method, termed IVOS (Instrumental Variables Obtained by Smoothing), is applied in the estimation of measurement error and endogenous regressor models. Asymptotic and small-sample properties are investigated by simulation, using artificial data sets. IVOS is easy to apply and the simulation results exhibit good statistical properties. It can be used in situations in which standard IV cannot because suitable instruments are not available.

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File URL: http://socserv.mcmaster.ca/sedap/p/sedap124.pdf
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Bibliographic Info

Paper provided by McMaster University in its series Social and Economic Dimensions of an Aging Population Research Papers with number 124.

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Length: 36 pages
Date of creation: Jan 2005
Date of revision:
Handle: RePEc:mcm:sedapp:124

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Keywords: single equation models; nonparametric; instrumental variables;

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  1. Newey, W.K., 1989. "Efficient Instrumental Variables Estimation Of Nonlinear Models," Papers 341, Princeton, Department of Economics - Econometric Research Program.
  2. Yatchew,Adonis, 2003. "Semiparametric Regression for the Applied Econometrician," Cambridge Books, Cambridge University Press, number 9780521012263, December.
  3. Neil J. Buckley & Frank T. Denton & A. Leslie Robb & Byron G. Spencer, 2003. "The Transition from Good to Poor Health: An Econometric Study of the Older Population," Social and Economic Dimensions of an Aging Population Research Papers 94, McMaster University.
  4. James H. Stock & Francesco Trebbi, 2003. "Retrospectives: Who Invented Instrumental Variable Regression?," Journal of Economic Perspectives, American Economic Association, vol. 17(3), pages 177-194, Summer.
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