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Tests of Independence in Separable Econometric Models

Author

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  • Donald J. Brown

    () (Yale University, Cowles Foundation)

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.

Suggested Citation

  • Donald J. Brown, 2004. "Tests of Independence in Separable Econometric Models," Yale School of Management Working Papers ysm329, Yale School of Management.
  • Handle: RePEc:ysm:somwrk:ysm329
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    Cited by:

    1. Donald J. Brown & Caterina Calsamiglia, 2003. "Rationalizing and Curve-Fitting Demand Data with Quasilinear Utilities," Cowles Foundation Discussion Papers 1399R, Cowles Foundation for Research in Economics, Yale University, revised Jul 2004.

    More about this item

    Keywords

    Cramer-von Mises Distance; Empirical Independence Processes; Random Utility Models; Semir;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

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