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Tests of Independence in Separable Econometric Models: Theory and Application

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Author Info
Donald J. Brown () (Economic Growth Center, Yale University)
Rahul Deb () (Yale University)
Marten H. Wegkamp () (Florida State 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. As an application, we stimulate estimation of a random quasilinear utility function, where we apply our tests of independence.

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File URL: http://www.econ.yale.edu/growth_pdf/cdp946.pdf
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Publisher Info
Paper provided by Economic Growth Center, Yale University in its series Working Papers with number 946.

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Length: 26 pages
Date of creation: Oct 2006
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Handle: RePEc:egc:wpaper:946

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Related research
Keywords: Cramér-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
C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing

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References listed on IDEAS
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  1. Donald J. Brown & Caterina Calsamiglia, 2005. "The Nonparametric Approach to Applied Welfare Analysis," Cowles Foundation Discussion Papers 1507, Cowles Foundation, Yale University. [Downloadable!]
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  2. Brown, Bryan W, 1983. "The Identification Problem in Systems Nonlinear in the Variables," Econometrica, Econometric Society, vol. 51(1), pages 175-96, January. [Downloadable!] (restricted)
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