Testing unconditional and conditional independence via mutual information

Chunrong Ai, Li Hsien Sun, Zheng Zhang, Liping Zhu

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
JournalJournal of Econometrics
StateAccepted/In press - 2022


  • Convex optimization
  • Density ratio
  • Independence test
  • Mutual information


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