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Cointegration and Long-Horizon Forecasting

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  • Francis X. Diebold
  • Peter F. Christoffersen

Abstract

Imposing cointegration on a forecasting system, if cointegration is present, is believed to improve long-horizon forecasts. Contrary to this belief, at long horizons nothing is lost by ignoring cointegration when the forecasts are evaluated using standard multivariate forecast accuracy measures. In fact, simple univariate Box-Jenkins forecasts are just as accurate. Our results highlight a potentially important deficiency of standard forecast accuracy measures—they fail to value the maintenance of cointegrating relationships among variables—and we suggest alternatives that explicitly do so.

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Bibliographic Info

Paper provided by International Monetary Fund in its series IMF Working Papers with number 97/61.

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Length: 30
Date of creation: 01 May 1997
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Handle: RePEc:imf:imfwpa:97/61

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References

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  1. Christoffersen, Peter F & Diebold, Francis X, 1996. "Further Results on Forecasting and Model Selection under Asymmetric Loss," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 11(5), pages 561-71, Sept.-Oct.
  2. John Y. Campbell & Robert J. Shiller, 1986. "Cointegration and Tests of Present Value Models," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University 785, Cowles Foundation for Research in Economics, Yale University.
  3. Granger, Clive W J, 1996. "Can We Improve the Perceived Quality of Economic Forecasts?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 11(5), pages 455-73, Sept.-Oct.
  4. Lin, Jin-Lung & Tsay, Ruey S, 1996. "Co-integration Constraint and Forecasting: An Empirical Examination," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 11(5), pages 519-38, Sept.-Oct.
  5. Peter F. Christoffersen & Francis X. Diebold, . "Optimal Prediction Under Asymmetric Loss," CARESS Working Papres, University of Pennsylvania Center for Analytic Research and Economics in the Social Sciences 97-20, University of Pennsylvania Center for Analytic Research and Economics in the Social Sciences.
  6. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers, National Bureau of Economic Research, Inc 0169, National Bureau of Economic Research, Inc.
  7. Wickens, Michael R., 1996. "Interpreting cointegrating vectors and common stochastic trends," Journal of Econometrics, Elsevier, Elsevier, vol. 74(2), pages 255-271, October.
  8. Engle, Robert F. & Yoo, Byung Sam, 1987. "Forecasting and testing in co-integrated systems," Journal of Econometrics, Elsevier, Elsevier, vol. 35(1), pages 143-159, May.
  9. Francis X. Diebold & Jose A. Lopez, 1996. "Forecast Evaluation and Combination," NBER Technical Working Papers, National Bureau of Economic Research, Inc 0192, National Bureau of Economic Research, Inc.
  10. Phillips, P C B, 1991. "Optimal Inference in Cointegrated Systems," Econometrica, Econometric Society, Econometric Society, vol. 59(2), pages 283-306, March.
  11. Clements, M.P. & Hendry, D., 1992. "On the Limitations of Comparing Mean Square Forecast Errors," Economics Series Working Papers, University of Oxford, Department of Economics 99138, University of Oxford, Department of Economics.
  12. Horvath, Michael T.K. & Watson, Mark W., 1995. "Testing for Cointegration When Some of the Cointegrating Vectors are Prespecified," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 11(05), pages 984-1014, October.
  13. Eric Zivot, 1996. "The Power of Single Equation Tests for Cointegration when the Cointegrating Vector is Prespecified," Econometrics, EconWPA 9612001, EconWPA.
  14. Hoffman, Dennis L & Rasche, Robert H, 1996. "Assessing Forecast Performance in a Cointegrated System," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 11(5), pages 495-517, Sept.-Oct.
  15. Clements, M.P. & Hendry, D.F., 1992. "Forecasting in Cointegrated Systems," Economics Series Working Papers, University of Oxford, Department of Economics 99139, University of Oxford, Department of Economics.
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