A NONPARAMETRIC TEST FOR EQUALITY OF DISTRIBUTIONS WITH MIXED CATEGORICAL AND CONTINUOUS DATA

Qi Li, Esfandiar Maasoumi () and Jeffrey Scott Racine ()
Authors registered in the RePEc Author Service: Esfandiar Maasoumi and Esfandiar Maasoumi ()

Emory Economics from Department of Economics, Emory University (Atlanta)

Abstract: In this paper we consider the problem of testing for equality of two density or two conditional density functions de ned over mixed discrete and continuous variables. We smooth both the discrete and continuous variables, with the smoothing parameters chosen via least-squares cross- validation. The test statistics are shown to have (asymptotic) normal null distributions. However, we advocate the use of bootstrap methods in order to better approximate their null distribution in nite-sample settings. Simulations show that the proposed tests have better power than both conventional frequency-based tests and smoothing tests based on ad hoc smoothing parameter selection, while a demonstrative empirical application to the joint distribution of earnings and educational attainment underscores the utility of the proposed approach in mixed data settings.

New Economics Papers: this item is included in nep-ecm
Date: 2008-10
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Related works:
Journal Article: A nonparametric test for equality of distributions with mixed categorical and continuous data (2009)
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Persistent link: http://EconPapers.repec.org/RePEc:emo:wp2003:0805

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