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In this article, we consider the problem of testing the Granger causality in stationary time series models with non-normal heavy-tailed distributions. We consider a normal mixture model to cover the heavy-tailed distribution, and propose a test statistic based on the partially adaptive estimator proposed by Phillips (1). It is shown that the test statistic asymptotically follows a chi-squared distribution. Simulation results indicate that our test outperforms the conventional test based on thedoi:10.1081/sac-120003341 fatcat:dlow2mmewrernfwca6by6jpziy