Cointegration and Long-Horizon Forecasting

Author/Editor:

Francis X. Diebold ; Peter F. Christoffersen

Publication Date:

May 1, 1997

Electronic Access:

Free Download. Use the free Adobe Acrobat Reader to view this PDF file

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.

Series:

Working Paper No. 1997/061

Subject:

Economic forecasting Vector autoregression

English

Publication Date:

May 1, 1997

ISBN/ISSN:

9781451848137/1018-5941

Stock No:

WPIEA0611997

Pages:

30

Please address any questions about this title to publications@imf.org