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The Power of Cointegration Tests

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Author Info

  • 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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Bibliographic Info

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: 325-48

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Handle: RePEc:bla:obuest:v:54:y:1992:i:3:p:325-48

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References

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  1. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
  2. Sargan, J D, 1980. "Some Tests of Dynamic Specification for a Single Equation," Econometrica, Econometric Society, vol. 48(4), pages 879-97, May.
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  4. Hendry, David F & Mizon, Grayham E, 1978. "Serial Correlation as a Convenient Simplification, not a Nuisance: A Comment on a Study of the Demand for Money by the Bank of England," Economic Journal, Royal Economic Society, vol. 88(351), pages 549-63, September.
  5. Nymoen, Ragnar, 1992. "Finnish manufacturing wages 1960-1987: Real-wage flexibility and hysteresis," Journal of Policy Modeling, Elsevier, vol. 14(4), pages 429-451, August.
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  8. Banerjee, Anindya, et al, 1986. "Exploring Equilibrium Relationships in Econometrics through Static Models: Some Monte Carlo Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 48(3), pages 253-77, August.
  9. James G. MacKinnon, 1990. "Critical Values for Cointegration Tests," Working Papers 1227, Queen's University, Department of Economics.
  10. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
  11. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-72, June.
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  13. Johansen, Soren, 1992. "Cointegration in partial systems and the efficiency of single-equation analysis," Journal of Econometrics, Elsevier, vol. 52(3), pages 389-402, June.
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  15. Davidson, James E H, et al, 1978. "Econometric Modelling of the Aggregate Time-Series Relationship between Consumers' Expenditure and Income in the United Kingdom," Economic Journal, Royal Economic Society, vol. 88(352), pages 661-92, December.
  16. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-80, November.
  17. Johansen, S., 1991. "Testing Weak Exogeneity and the Order of Cointegration in UK Money Demand Data," Papers 78, Helsinki - Department of Economics.
  18. Kremers, Jeroen J. M., 1989. "U.S. Federal indebtedness and the conduct of fiscal policy," Journal of Monetary Economics, Elsevier, vol. 23(2), pages 219-238, March.
  19. Julia Campos & Neil R. Ericsson, 1988. "Econometric modeling of consumers' expenditure in Venezuela," International Finance Discussion Papers 325, Board of Governors of the Federal Reserve System (U.S.).
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