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Tests of Independence in Separable Econometric Models

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Author Info
Donald J. Brown () (Cowles Foundation, Yale University)
Marten H. Wegkamp (Yale University)

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Abstract

A common stochastic restriction in econometric models separable in the latent variables is the assumption of stochastic independence between the unobserved and observed exogenous variables. Both simple and composite tests of this assumption are derived from properties of independence empirical processes and the consistency of these tests is established.

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File URL: http://cowles.econ.yale.edu/P/cd/d13b/d1395.pdf
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Publisher Info
Paper provided by Cowles Foundation, Yale University in its series Cowles Foundation Discussion Papers with number 1395.

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Length: 19 pages
Date of creation: Jan 2003
Date of revision:
Handle: RePEc:cwl:cwldpp:1395

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Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA

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Related research
Keywords: Cramer-von Mises distance; Empirical independence processes; Random utility models; Semiparametric econometric models; Specification test of independence;

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Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods

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  1. Donald J. Brown & Caterina Calsamiglia, 2003. "Rationalizing and Curve-Fitting Demand Data with Quasilinear Utilities," Cowles Foundation Discussion Papers 1399R, Cowles Foundation, Yale University, revised Jul 2004. [Downloadable!]
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This page was last updated on 2009-12-14.

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