Cointegration and Long-Horizon Forecasting

30 Pages Posted: 22 Jan 1998

See all articles by Peter Christoffersen

Peter Christoffersen

University of Toronto - Rotman School of Management; Copenhagen Business School; Aarhus University - CREATES

Francis X. Diebold

University of Pennsylvania - Department of Economics; National Bureau of Economic Research (NBER)

Multiple version iconThere are 3 versions of this paper

Date Written: May 1997

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 mutivariate 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 tht explicitly do so.

JEL Classification: C32, C53

Suggested Citation

Christoffersen, Peter and Diebold, Francis X., Cointegration and Long-Horizon Forecasting (May 1997). IMF Working Paper No. 97/61. Available at SSRN: https://ssrn.com/abstract=54985 or http://dx.doi.org/10.2139/ssrn.54985

Peter Christoffersen (Contact Author)

University of Toronto - Rotman School of Management ( email )

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Francis X. Diebold

University of Pennsylvania - Department of Economics ( email )

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