We propose a nonparametric test for conditional uncorrelatedness in multiple-equation models such as seemingly unrelated regressions (SURs), multivariate volatility models, and vector autoregressions (VARs). Under the null hypothesis of conditional uncorrelatedness, the test statistic converges to the standard normal distribution asymptotically. We also study the local power property of the test. Simulation shows that the test behaves quite well in finite samples.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000268506400002&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701EconomicsSocial Sciences, Mathematical MethodsStatistics & Pr...
This paper proposes a nonparametric test for parametric conditional distributions of dynamic models....
Statistical tools to detect nonlinear relationship between variables are commonly needed in various ...
This paper proposes a nonparametric test for conditional independence that is easy to implement, yet...
We propose a nonparametric test for conditional uncorrelatedness in multiple-equation models such as...
Conditional independence is of interest for testing unconfoundedness assumptions in causal inference...
Financial support from the Natural Sciences and Engineering Research Council of Canada and from the...
Conditional local independence is an asymmetric independence relation among continuous time stochast...
We propose a characteristic function based test for conditional independence, which is applicable in...
<p>Statistical inference on conditional dependence is essential in many fields including genetic ass...
The concept of causality is naturally defined in terms of conditional distribution, however almost a...
96 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997.This thesis presents a test st...
In this paper, we propose a new diagnostic test for residual cross-section uncorrelatedness (CU) in ...
This paper proposes a nonparametric test of conditional independence based on the notion that two co...
Many statistical techniques devoted to stationary time series analysis assume a constant conditional...
This paper proposes a simple consistent nonparametric test of multivariate conditional symmetry base...
This paper proposes a nonparametric test for parametric conditional distributions of dynamic models....
Statistical tools to detect nonlinear relationship between variables are commonly needed in various ...
This paper proposes a nonparametric test for conditional independence that is easy to implement, yet...
We propose a nonparametric test for conditional uncorrelatedness in multiple-equation models such as...
Conditional independence is of interest for testing unconfoundedness assumptions in causal inference...
Financial support from the Natural Sciences and Engineering Research Council of Canada and from the...
Conditional local independence is an asymmetric independence relation among continuous time stochast...
We propose a characteristic function based test for conditional independence, which is applicable in...
<p>Statistical inference on conditional dependence is essential in many fields including genetic ass...
The concept of causality is naturally defined in terms of conditional distribution, however almost a...
96 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1997.This thesis presents a test st...
In this paper, we propose a new diagnostic test for residual cross-section uncorrelatedness (CU) in ...
This paper proposes a nonparametric test of conditional independence based on the notion that two co...
Many statistical techniques devoted to stationary time series analysis assume a constant conditional...
This paper proposes a simple consistent nonparametric test of multivariate conditional symmetry base...
This paper proposes a nonparametric test for parametric conditional distributions of dynamic models....
Statistical tools to detect nonlinear relationship between variables are commonly needed in various ...
This paper proposes a nonparametric test for conditional independence that is easy to implement, yet...