Tests of Independence in Separable Econometric Models
AbstractA 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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Bibliographic InfoPaper provided by Yale School of Management in its series Yale School of Management Working Papers with number ysm329.
Date of creation: 28 Jul 2004
Date of revision:
Cramer-von Mises Distance; Empirical Independence Processes; Random Utility Models; Semir;
Other versions of this item:
- Donald J. Brown & Marten H. Wegkamp, 2003. "Tests of Independence in Separable Econometric Models," Cowles Foundation Discussion Papers 1395, Cowles Foundation for Research in Economics, Yale University.
- 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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- 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.
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