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A Specification Test For Nonparametric Instrumental Variable Regression

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Author Info
Patrick Gagliardini (University of Lugano and Swiss Finance Institute)
Olivier Scaillet (University of Geneva, HEC and Swiss Finance Institute)

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Abstract

We 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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Publisher Info
Paper provided by Swiss Finance Institute in its series Swiss Finance Institute Research Paper Series with number 9602.

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Length: 41 pages
Date of creation: Apr 2007
Date of revision:
Handle: RePEc:chf:rpseri:rp0713

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Web page: http://www.SwissFinanceInstitute.ch
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Related research
Keywords: 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: General - - - Estimation
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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