Cointegration and Long-Horizon Forecasting
AbstractThe authors consider the forecasting of cointegrated variables and they show that, at long horizons, nothing is lost by ignoring cointegration when forecasts are evaluated using standard multivariate forecast accuracy measures. In fact, simple univariate Box-Jenkins forecasts are just as accurate. The authors' results highlight a potentially important deficiency of standard forecast accuracy measures--they fail to value the maintenance of cointegrating relationships among variables--and the authors suggest alternatives that explicitly do so.
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Bibliographic InfoArticle provided by American Statistical Association in its journal Journal of Business and Economic Statistics.
Volume (Year): 16 (1998)
Issue (Month): 4 (October)
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Other versions of this item:
- Peter F. Christoffersen & Francis X. Diebold, 1997. "Cointegration and Long-Horizon Forecasting," NBER Technical Working Papers 0217, National Bureau of Economic Research, Inc.
- Francis X. Diebold & Peter F. Christoffersen, 1997. "Cointegration and Long-Horizon Forecasting," IMF Working Papers 97/61, International Monetary Fund.
- Peter F. Christoffersen & Francis X. Diebold, 1997. "Cointegration and long-horizon forecasting," Working Papers 97-14, Federal Reserve Bank of Philadelphia.
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
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