Testing Additivity in Generalized Nonparametric Regression Models

Oliver Linton and Pedro Gozalo
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Pedro Gozalo: Brown University

No 1106, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: We propose a nonparametric test of conditional independence based on the empirical distribution function. The asymptotic null distribution is a mixture of chi-squares. A bootstrap procedure is proposed for calculating the critical values. Our test has power against alternatives at distance n^{-1/2} from the null. Monte Carlo simulations provide evidence on size and power. We apply the test to the Boston housing dataset.

Keywords: Conditional independence; empirical distribution; independence; nonparametric; smooth bootstrap; test (search for similar items in EconPapers)
JEL-codes: C12 C14 C15 C52 (search for similar items in EconPapers)
Pages: 37 pages
Date: 1995-06
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Citations: View citations in EconPapers (1)

Published in Journal of Econometrics (1999), 104: 1-48

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Working Paper: Testing Additivity in Generalized Nonparametric Regression Models (1996)
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