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Faculty of Economics

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Linton, O. and Gozalo, P.

Testing conditional independence restrictions

Econometric Reviews

Vol. 33(5-6) pp. 523-552 (2013)

Abstract: We propose a nonparametric test of the hypothesis of conditional independence between variables of interest based on a generalization of the empirical distribution function. This hypothesis is of interest both for model specification purposes, parametric and semiparametric, and for non-model based testing of economic hypotheses. We allow for both discrete variables and estimated parameters. The asymptotic null distribution of the test statistic is a functional of a Gaussian process. A bootstrap procedure is proposed for calculating the critical values. Our test has power against alternatives at distance n^(−1/2) from the null; this result holding independently of dimension. Monte Carlo simulations provide evidence on size and power.

JEL Codes: C12, C14, C15, C52

Author links: Oliver Linton  

Publisher's Link: http://www.tandfonline.com/doi/full/10.1080/07474938.2013.825135#.UjjUXcbEOGM



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