Exploring the Use of a Nonparametrically Generated Instrumetal Variable in the Estimation of a Linear Parametric Equation
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.
|Date of creation:||Jan 2005|
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- Buckley, Neil J. & Denton, Frank T. & Leslie Robb, A. & Spencer, Byron G., 2004.
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- 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," Quantitative Studies in Economics and Population Research Reports 381, McMaster University.
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- Newey, W.K., 1989. "Efficient Instrumental Variables Estimation Of Nonlinear Models," Papers 341, Princeton, Department of Economics - Econometric Research Program.
- 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. Full references (including those not matched with items on IDEAS)
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