Testing Conditional Uncorrelatedness
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 t...
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sg-smu-ink.soe_research-13532018-09-03T07:40:24Z Testing Conditional Uncorrelatedness SU, Liangjun ULLAH, Aman 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. 2009-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/354 info:doi/10.1198/jbes.2009.0002 https://ink.library.smu.edu.sg/context/soe_research/article/1353/viewcontent/testing_conditional_uncorrelatedness_afv.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Conditional heteroscedasticity Local polynomial estimator Nonparametric multivariate regression Seemingly unrelated regressions Vector autoregressions Econometrics |
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Conditional heteroscedasticity Local polynomial estimator Nonparametric multivariate regression Seemingly unrelated regressions Vector autoregressions Econometrics SU, Liangjun ULLAH, Aman Testing Conditional Uncorrelatedness |
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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. |
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SU, Liangjun ULLAH, Aman |
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SU, Liangjun ULLAH, Aman |
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SU, Liangjun |
title |
Testing Conditional Uncorrelatedness |
title_short |
Testing Conditional Uncorrelatedness |
title_full |
Testing Conditional Uncorrelatedness |
title_fullStr |
Testing Conditional Uncorrelatedness |
title_full_unstemmed |
Testing Conditional Uncorrelatedness |
title_sort |
testing conditional uncorrelatedness |
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Institutional Knowledge at Singapore Management University |
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2009 |
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https://ink.library.smu.edu.sg/soe_research/354 https://ink.library.smu.edu.sg/context/soe_research/article/1353/viewcontent/testing_conditional_uncorrelatedness_afv.pdf |
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