One for all and all for one: regression checks with many regressors
AbstractWe develop a novel approach to build checks of parametric regression models when many regressors are present, based on a class of sufficiently rich semiparametric alternatives, namely single-index models. We propose an omnibus test based on the kernel method that performs against a sequence of directional nonparametric alternatives as if there was one regressor only, whatever the number of regressors. This test can be viewed as a smooth version of the integrated conditional moment (ICM) test of Bierens. Qualitative information can be easily incorporated into the procedure to enhance power. In an extensive comparative simulation study, we find that our test is little sensitive to the smoothing parameter and performs well in multidimensional settings. We then apply it to a cross-country growth regression model.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 35779.
Date of creation: 2011
Date of revision:
Dimensionality; Hypothesis testing; Nonparametric methods;
Other versions of this item:
- Pascal Lavergne & Valentin Patilea, 2008. "One for All and All for One:Regression Checks With Many Regressors," Discussion Papers dp08-06, Department of Economics, Simon Fraser University.
- Pascal Lavergne & Valentin Patilea, 2007. "One for All and All for One : Regression Checks with Many Regressors”," Working Papers 2007-12, Centre de Recherche en Economie et Statistique.
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
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