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Tests of Independence in Separable Econometric Models: Theory and Application

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

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File URL: http://cowles.econ.yale.edu/P/cd/d13b/d1395-r.pdf
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Bibliographic Info

Paper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 1395R.

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Length: 26 pages
Date of creation: Jan 2003
Date of revision: Oct 2006
Handle: RePEc:cwl:cwldpp:1395r

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Postal: Yale University, Box 208281, New Haven, CT 06520-8281 USA
Phone: (203) 432-3702
Fax: (203) 432-6167
Web page: http://cowles.econ.yale.edu/
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Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA

Related research

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

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  1. Rosa L. Matzkin, 2008. "Identification in Nonparametric Simultaneous Equations Models," Econometrica, Econometric Society, vol. 76(5), pages 945-978, 09.
  2. Donald Brown & Caterina Calsamiglia, 2007. "The Nonparametric Approach to Applied Welfare Analysis," Economic Theory, Springer, vol. 31(1), pages 183-188, April.
  3. Roehrig, Charles S, 1988. "Conditions for Identification in Nonparametric and Parametic Models," Econometrica, Econometric Society, vol. 56(2), pages 433-47, March.
  4. repec:cup:cbooks:9780521496032 is not listed on IDEAS
  5. Brown, Bryan W, 1983. "The Identification Problem in Systems Nonlinear in the Variables," Econometrica, Econometric Society, vol. 51(1), pages 175-96, January.
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Cited by:
  1. Du, Zaichao, 2014. "Testing for serial independence of panel errors," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 248-261.

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