June 1992

The Power of Cointegration Tests

Jeroen J.M. Kremers, Neil R. Ericsson, and Juan J. Dolado

Abstract:

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 non-standard 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.

PDF: Full Paper

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Last Update: March 05, 2021