A Note on Spurious Inference in a Linearly Detrended Vector Autoregression
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 when other persistent stochastic processes are included in the autoregressions. The number of rejections are two to five times greater than if the variables are not linearly detrended prior to analysis. Copyright 1991 by MIT Press.
Volume (Year): 73 (1991)
Issue (Month): 3 (August)
|Contact details of provider:|| Web page: http://mitpress.mit.edu/journals/|
|Order Information:||Web: http://mitpress.mit.edu/journal-home.tcl?issn=00346535|
When requesting a correction, please mention this item's handle: RePEc:tpr:restat:v:73:y:1991:i:3:p:568-71. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Kristin Waites)
If references are entirely missing, you can add them using this form.