Misspecification Testing in a Class of Conditional Distributional Models

Christoph Rothe and Dominik Wied

No 6364, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: We propose a specification test for a wide range of parametric models for the conditional distribution function of an outcome variable given a vector of covariates. The test is based on the Cramer-von Mises distance between an unrestricted estimate of the joint distribution function of the data, and a restricted estimate that imposes the structure implied by the model. The procedure is straightforward to implement, is consistent against fixed alternatives, has non-trivial power against local deviations of order n^-1/2 from the null hypothesis, and does not require the choice of smoothing parameters. In an empirical application, we use our test to study the validity of various models for the conditional distribution of wages in the US.

Keywords: bootstrap; location-scale model; distributional regression; quantile regression; Cramer-von Mises distance; wage distribution (search for similar items in EconPapers)
JEL-codes: C12 C14 C31 C52 J31 (search for similar items in EconPapers)
Pages: 38 pages
Date: 2012-02
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (7)

Published - published in: Journal of the American Statistical Association, 2013, 108 (501), 314-324

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Journal Article: Misspecification Testing in a Class of Conditional Distributional Models (2013)
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