Cointegration and Long-Horizon Forecasting /

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...

詳細記述

書誌詳細
第一著者: Diebold, Francis
その他の著者: Christoffersen, Peter
フォーマット: 雑誌
言語:English
出版事項: Washington, D.C. : International Monetary Fund, 1997.
シリーズ:IMF Working Papers; Working Paper ; No. 1997/061
主題:
オンライン・アクセス:Full text available on IMF
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245 1 0 |a Cointegration and Long-Horizon Forecasting /  |c Francis Diebold, Peter Christoffersen. 
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300 |a 1 online resource (30 pages) 
490 1 |a IMF Working Papers 
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500 |a <strong>On-Campus Access:</strong> No User ID or Password Required 
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520 3 |a 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. 
538 |a Mode of access: Internet 
650 7 |a Dynamic Quantile Regressions  |2 imf 
650 7 |a Dynamic Treatment Effect Models  |2 imf 
650 7 |a Mover Accent  |2 imf 
650 7 |a Time-Series Models  |2 imf 
650 7 |a WP  |2 imf 
700 1 |a Christoffersen, Peter. 
830 0 |a IMF Working Papers; Working Paper ;  |v No. 1997/061 
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