Publication Type
Journal Article
Version
acceptedVersion
Publication Date
3-2009
Abstract
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.
Keywords
Conditional heteroscedasticity, Local polynomial estimator, Nonparametric multivariate regression, Seemingly unrelated regressions, Vector autoregressions
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Business and Economic Statistics
Volume
27
Issue
1
First Page
18
Last Page
29
ISSN
0735-0015
Identifier
10.1198/jbes.2009.0002
Publisher
Taylor and Francis
Citation
SU, Liangjun and ULLAH, Aman.
Testing Conditional Uncorrelatedness. (2009). Journal of Business and Economic Statistics. 27, (1), 18-29.
Available at: https://ink.library.smu.edu.sg/soe_research/354
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1198/jbes.2009.0002