One for All and All for One:Regression Checks With Many Regressors

Pascal Lavergne and Valentin Patilea
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Valentin Patilea: CREST-ENSAI and IRMAR-INSA

Discussion Papers from Department of Economics, Simon Fraser University

Abstract: We develop a novel approach to build checks of parametric regression models when many regressors are present, based on a class of rich enough 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 in the procedure to enhance power. Our test is little sensitive to the smoothing parameter and performs better than several known lack-of-fit tests in multidimensional settings, as illustrated by extensive simulations and an application to a cross-country growth regression.

Keywords: Dimensionality; Hypothesis testing; Nonparametric methods (search for similar items in EconPapers)
JEL-codes: C12 C52 (search for similar items in EconPapers)
Pages: 28
Date: 2008-11
New Economics Papers: this item is included in nep-ecm
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Related works:
Journal Article: One for All and All for One: Regression Checks With Many Regressors (2011)
Working Paper: One for all and all for one: regression checks with many regressors (2011)
Working Paper: One for All and All for One: Regression Checks with Many Regressors" (2007)
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