The Effects of Detrending in Granger Causality Tests
用美国季度数据研究去趋势处理对格兰杰因果检验的影响，发现去趋势会削弱或消除因果关系，而不去趋势则可能引入或增强因果关系，提示需要更稳健的因果检验方法。
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.