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Testing conditional symmetry without smoothing

Tao Chen and Gautam Tripathi

Journal of Nonparametric Statistics, 2013, vol. 25, issue 2, 273-313

Abstract: We test the assumption of conditional symmetry used to identify and estimate parameters in regression models with endogenous regressors, without making any distributional assumptions. The Kolmogorov-Smirnov-type statistic we propose is consistent, computationally tractable because it does not require optimisation over an uncountable set, free of any kind of nonparametric smoothing, and can detect n -super-1/2-deviations from the null. Results from a simulation experiment suggest that our test can work very well in moderately sized samples.

Date: 2013
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Working Paper: Testing Conditional Symmetry Without Smoothing (2011) Downloads
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DOI: 10.1080/10485252.2012.752083

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