Cointegration and Long-Horizon Forecasting

By Francis X. Diebold, Peter F. Christoffersen

May 1, 1997

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Francis X. Diebold, and Peter F. Christoffersen Cointegration and Long-Horizon Forecasting, (USA: International Monetary Fund, 1997) accessed November 21, 2024

Disclaimer: This Working Paper should not be reported as representing the views of the IMF.The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate

Summary

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.

Subject: Economic forecasting, Vector autoregression

Keywords: Mover accent, WP

Publication Details

Pages:

30
Volume:

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DOI:

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Issue:

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Series:

Working Paper No. 1997/061
Stock No:

WPIEA0611997
ISBN:

9781451848137
ISSN:

1018-5941

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