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The Power of Cointegration Tests

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Listed author(s):
  • Kremers, Jeroen J M
  • Ericsson, Neil R
  • Dolado, Juan J

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 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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Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics & Statistics.

Volume (Year): 54 (1992)
Issue (Month): 3 (August)
Pages: 325-348

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Handle: RePEc:bla:obuest:v:54:y:1992:i:3:p:325-48
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  1. Johansen, Soren, 1992. "Testing weak exogeneity and the order of cointegration in UK money demand data," Journal of Policy Modeling, Elsevier, vol. 14(3), pages 313-334, June.
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  10. Neil R. Ericsson & Julia Campos & Hong-Anh Tran, 1991. "PC-give and David Hendry's econometric methodology," International Finance Discussion Papers 406, Board of Governors of the Federal Reserve System (U.S.).
  11. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
  12. Sargan, John Denis & Bhargava, Alok, 1983. "Testing Residuals from Least Squares Regression for Being Generated by the Gaussian Random Walk," Econometrica, Econometric Society, vol. 51(1), pages 153-174, January.
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