The Power of Cointegration Tests
A cointegration test statistic based upon estimation of an error-correction model can be approximately normally distributed when no cointegration is present. By contrast, the equivalent Dickey-Fuller statistic applied to residuals from a static relationship has a nonstandard asymptotic distribution. When cointegration exists, the error-correction test generally is more powerful than the Dickey-Fuller test. These differences arise because the latter imposes a possibly invalid common factor restriction. The issue is general and has ramifications for system-based cointegration tests. Monte Carlo analysis and an empirical study of U.K. money demand demonstrate the differences in power. Copyright 1992 by Blackwell Publishing Ltd
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Volume (Year): 54 (1992)
Issue (Month): 3 (August)
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