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A Copula Nonlinear Granger Causality

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  • Kim, Jong-Min
  • Lee, Namgil
  • Hwang, Sun Young

Abstract

We propose a new copula nonlinear Granger causality test that is more robust than the current available linear and nonlinear Granger causality tests when there exists an asymmetric and nonlinear directional dependence. To perform the statistical test of the copula nonlinear causality, the Gaussian Copula Marginal Regression (GCMR) model and copula directional dependence (Kim and Hwang, 2017) are employed in this paper. By using GCMR and two-sample permutation test with rank sum statistic for the copula nonlinear Granger causality, we can confirm that the result of the proposed copula nonlinear Granger causality test is a reliable test through the simulated data and real data both for small and large sample sizes.

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  • Kim, Jong-Min & Lee, Namgil & Hwang, Sun Young, 2020. "A Copula Nonlinear Granger Causality," Economic Modelling, Elsevier, vol. 88(C), pages 420-430.
    • Handle: RePEc:eee:ecmode:v:88:y:2020:i:c:p:420-430
    DOI: 10.1016/j.econmod.2019.09.052
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    2. Olatunji A. Shobande & Simplice A. Asongu, 2021. "Has Knowledge Improved Economic Growth? Evidence from Nigeria and South Africa," Working Papers 21/059, European Xtramile Centre of African Studies (EXCAS).
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    5. Roberto Fuentes M. & Irene Crimaldi & Armando Rungi, 2024. "Non-linear dependence and Granger causality: A vine copula approach," Papers 2409.15070, arXiv.org.
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    8. Tie‐Ying Liu & Chien‐Chiang Lee, 2022. "Exchange rate fluctuations and interest rate policy," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3531-3549, July.

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