A Note on Spurious Inference in a Linearly Detrended Vector Autoregression
线性去趋势向量自回归中的伪推断札记
A simulation study is designed to evaluate the sensitivity of inference in a Vector Autoregression in which the variables of interest (GNP, the money stock, the price level, and a short-term interest rate) are treated as trend stationary processes. Using the normal asymptotic theory, the authors find that an artificially generated random walk Granger-causes the genuine variables in the model as often as 60% of the time for a 5% level test. They also observe substantial bias…