A Specification Test For Nonparametric Instrumental Variable Regression
AbstractWe consider testing for correct specification of a nonparametric instrumental variable regression. In this ill-posed inverse problem setting, the test statistic is based on the empirical minimum distance criterion corresponding to the conditional moment restriction evaluated with a Tikhonov Regularized estimator of the functional parameter. Its asymptotic distribution is normal under the null hypothesis, and a consistent bootstrap is available to get simulation based critical values. We explore the finite sample behavior with Monte Carlo experiments. Finally, we provide an empirical application for an estimated Engel curve.
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Bibliographic InfoPaper provided by Swiss Finance Institute in its series Swiss Finance Institute Research Paper Series with number 9602.
Length: 41 pages
Date of creation: Apr 2007
Date of revision:
Specification Test; Nonparametric Regression; Instrumental Variables; Minimum Distance; Tikhonov Regularization; Ill-posed Inverse Problems; Generalized Method of Moments; Bootstrap; Engel Curve;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
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- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
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- Breunig, Christoph, 2012. "Goodness-of-fit tests based on series estimators in nonparametric instrumental regression," Working Papers 12-13, University of Mannheim, Department of Economics.
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