Tests of Independence in Separable Econometric Models: Theory and Application
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.
|Date of creation:||Jan 2003|
|Date of revision:||Dec 2007|
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- Donald J. Brown & Caterina Calsamiglia, 2005.
"The Nonparametric Approach to Applied Welfare Analysis,"
Cowles Foundation Discussion Papers
1507, Cowles Foundation for Research in Economics, Yale University.
- Donald Brown & Caterina Calsamiglia, 2007. "The Nonparametric Approach to Applied Welfare Analysis," Economic Theory, Springer, vol. 31(1), pages 183-188, April.
- Brown, Bryan W, 1983. "The Identification Problem in Systems Nonlinear in the Variables," Econometrica, Econometric Society, vol. 51(1), pages 175-96, January.
- repec:cup:cbooks:9780521496032 is not listed on IDEAS
- Roehrig, Charles S, 1988. "Conditions for Identification in Nonparametric and Parametic Models," Econometrica, Econometric Society, vol. 56(2), pages 433-47, March.
- Rosa L. Matzkin, 2008. "Identification in Nonparametric Simultaneous Equations Models," Econometrica, Econometric Society, vol. 76(5), pages 945-978, 09.
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