Chunrong Ai , Li-Hsien Sun , Zheng Zhang , Liping Zhu
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Testing unconditional and conditional independence via mutual information
Testing independence has garnered increasing attention in the econometric and statistical literature. Many tests have been proposed, most of which are inconsistent against all departures from independence. Few of those tests, though consistent, suffer a significant loss of local power. This study proposes a mutual information test for testing independence. The proposed test is simple to implement and, with a slight loss of local power, is consistent against all departures from independence. The key driving factor is that we estimate the density ratio directly. This value is constant in a state of independence. This is in contrast with related studies that estimate the joint and marginal density functions to form the density ratio. A small-scale simulation study indicates that the proposed test outperforms the existing alternatives in various dependence structures.
期刊介绍:
The Journal of Econometrics serves as an outlet for important, high quality, new research in both theoretical and applied econometrics. The scope of the Journal includes papers dealing with identification, estimation, testing, decision, and prediction issues encountered in economic research. Classical Bayesian statistics, and machine learning methods, are decidedly within the range of the Journal''s interests. The Annals of Econometrics is a supplement to the Journal of Econometrics.