Add to ORKGA 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
In this paper we introduce a general method for estimating semiparametrically the different compon...
This article develops nonparametric tests of independence between two stochastic processes satisfyin...
Three simple and explicit procedures for testing the independence of two multi-dimensional random va...
A common stochastic restriction in econometric models separable in the latent variables is the assum...
A common stochastic restriction in econometric models separable in the latent variables is the assum...
Three simple and explicit procedures for testing the independence of two multi-dimensional random va...
It is common to assume in empirical research that observables and unobservables are additively sepa...
There are several tests for testing independence of two variables, but a shortage of tests that can ...
Consider the nonparametric regression model Y = m(X) + E, where the function m is smooth, but unknow...
The detection of dependence structures within a set of random variables provides a valuable basis fo...
Limit theorems as well as other well-known results in probability and statistics are often based on ...
AbstractA nonparametric test of the mutual independence between many numerical random vectors is pro...
In this paper we propose a new procedure for testing independence of random variables, which is base...
New statistics are proposed for testing the hypothesis that arbitrary random variables are mutually ...
We propose a new class of nonparametric tests for the supposition of independence between two contin...
In this paper we introduce a general method for estimating semiparametrically the different compon...
This article develops nonparametric tests of independence between two stochastic processes satisfyin...
Three simple and explicit procedures for testing the independence of two multi-dimensional random va...
A common stochastic restriction in econometric models separable in the latent variables is the assum...
A common stochastic restriction in econometric models separable in the latent variables is the assum...
Three simple and explicit procedures for testing the independence of two multi-dimensional random va...
It is common to assume in empirical research that observables and unobservables are additively sepa...
There are several tests for testing independence of two variables, but a shortage of tests that can ...
Consider the nonparametric regression model Y = m(X) + E, where the function m is smooth, but unknow...
The detection of dependence structures within a set of random variables provides a valuable basis fo...
Limit theorems as well as other well-known results in probability and statistics are often based on ...
AbstractA nonparametric test of the mutual independence between many numerical random vectors is pro...
In this paper we propose a new procedure for testing independence of random variables, which is base...
New statistics are proposed for testing the hypothesis that arbitrary random variables are mutually ...
We propose a new class of nonparametric tests for the supposition of independence between two contin...
In this paper we introduce a general method for estimating semiparametrically the different compon...
This article develops nonparametric tests of independence between two stochastic processes satisfyin...
Three simple and explicit procedures for testing the independence of two multi-dimensional random va...