A common stochastic restriction in econometric models separable in the latent variablesis 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
Keywords: Cramér-von Mises distance, Empirical independence processes, Random utility models, Semiparametric econometric models, Specification test of independence
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.
Keywords: Cramer–von Mises distance, Empirical independence processes, Random utility models, Semiparametric econometric models, Specification test of independence
In this paper we introduce a family of minimum distance from independence estimators, suggested by Manski’s minimum mean square from independence estimator. We establish strong consistency, asymptotic normality and consistency of resampling estimates of the distribution and variance of these estimators. For Manski’s estimator we derive both strong consistency and asymptotic normality.