A Copula Nonlinear Granger Causality
  • Kim, Jong-Min
  • Lee, Namgil
  • Hwang, Sun Young
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초록

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.

키워드

CopulaGranger causalityDirectional dependencePermutation testBETA REGRESSIONGUIDELINES
제목
A Copula Nonlinear Granger Causality
저자
Kim, Jong-MinLee, NamgilHwang, Sun Young
DOI
10.1016/j.econmod.2019.09.052
발행일
2020-06
유형
Article
저널명
Economic Modelling
88
페이지
420 ~ 430