A Method for Testing the Independence of Two Time Series That Accounts for a Potential Pattern in the Cross-Correlation Function

Abstract The Haugh (1976) test for independence employs the univariate residual cross-correlation function. However, it ignores information about a possible pattern in successive cross-correlation coefficients. An asymptotic test is developed that incorporates this information and includes the Haugh test as a special case. A Monte Carlo study indicates that the proposed test is more powerful than the Haugh s and regression F tests for certain models. Two empirical examples are presented showing the simplicity of applying this test and its ability to recognize relationships that the Haugh test may fail to detect.

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