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The Effects of Detrending in Granger Causality Tests
Authors:Heejoon Kang
Affiliation:Graduate School of Business, Indiana University , Bloomington , Indiana , 47405
Abstract:Nonstationary time series are frequently detrended in empirical investigations by regressing the series on time or a function of time. The effects of the detrending on the tests for causal relationships in the sense of Granger are investigated using quarterly U.S. data. The causal relationships between nominal or real GNP and M1, inferred from the Granger–Sims tests, are shown to depend very much on, among other factors, whether or not series are detrended. Detrending tends to remove or weaken causal relationships, and conversely, failure to detrend tends to introduce or enhance causal relationships. The study suggests that we need a more robust test or a better definition of causality.
Keywords:Nonstationarity  ARIMA analysis  Granger–Sims tests
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