Tests of Independence in Separable Econometric Models: Theory and Application

Donald Brown (), Rahul Deb and Marten H. Wegkamp
Additional contact information
Marten H. Wegkamp: Dept. of Statistics, Florida State University

No 1395R, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

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. As an application, we simulate estimation of a random quasilinear utility function, where we apply our tests of independence.

Keywords: Cramer–von Mises distance; Empirical independence processes; Random utility models; Semiparametric econometric models; Specification test of independence (search for similar items in EconPapers)
JEL-codes: C12 C13 C14 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2003-01, Revised 2006-10
New Economics Papers: this item is included in nep-ecm and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Related works:
Working Paper: Tests of Independence in Separable Econometric Models: Theory and Application (2007)
Working Paper: Tests of Independence in Separable Econometric Models: Theory and Application (2006)
Working Paper: Tests of Independence in Separable Econometric Models: Theory and Application (2006)
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