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“Generalized Measures of Correlation for Asymmetry, Nonlinearity, and Beyond”: Some Antecedents on Causality

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  • David E. Allen
  • Michael McAleer

Abstract

This note comments on the generalized measure of correlation (GMC) that was suggested by Zheng, Shi, and Zhang. The GMC concept was partly anticipated in some publications over 100 years earlier by Yule in the Proceedings of the Royal Society, and by Kendall. Other antecedents discussed include work on dependency by Renyi and Doksum and Samarov, together with the Yule–Simpson paradox. The GMC metric partly extends the concept of Granger causality, so that we consider causality, graphical analysis and alternative measures of dependency provided by copulas.

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  • David E. Allen & Michael McAleer, 2022. "“Generalized Measures of Correlation for Asymmetry, Nonlinearity, and Beyond”: Some Antecedents on Causality," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 117(537), pages 214-224, January.
    • Handle: RePEc:taf:jnlasa:v:117:y:2022:i:537:p:214-224
    DOI: 10.1080/01621459.2020.1768101
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    Cited by:

    1. Hrishikesh Vinod, 2023. "Causality Estimation in Panel Data," Fordham Economics Discussion Paper Series dp2023-09er:dp2023-09, Fordham University, Department of Economics.

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