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...

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Bibliografski detalji
Glavni autor: Diebold, Francis
Daljnji autori: Christoffersen, Peter
Format: Žurnal
Jezik:English
Izdano: Washington, D.C. : International Monetary Fund, 1997.
Serija:IMF Working Papers; Working Paper ; No. 1997/061
Teme:
Online pristup:Full text available on IMF
Opis
Sažetak: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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Opis:1 online resource (30 pages)
Format:Mode of access: Internet
ISSN:1018-5941
Pristup:Electronic access restricted to authorized BRAC University faculty, staff and students