Cointegration and Long-Horizon Forecasting

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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