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Forecast-error-based estimation of forecast uncertainty when the horizon is increased

Malte Knüppel

No 40/2014, Discussion Papers from Deutsche Bundesbank

Abstract: Recently, several institutions have increased their forecast horizons, and many institutions rely on their past forecast errors to estimate measures of forecast uncertainty. This work addresses the question how the latter estimation can be accomplished if there are only very few errors available for the new forecast horizons. It extends upon the results of Knüppel (2014) in order to relax the condition on the data structure required for the SUR estimator to be independent from unknown quantities. It turns out that the SUR estimator of forecast uncertainty tends to deliver large efficiency gains compared to the OLS estimator (i.e. the sample mean of the squared forecast errors) in the case of increased forecast horizons. The SUR estimator is applied to the forecast errors of the Bank of England and the FOMC.

Keywords: multi-step-ahead forecasts; forecast error variance; SUR (search for similar items in EconPapers)
JEL-codes: C13 C32 C53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-for
Date: 2014
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Related works:
Journal Article: Forecast-error-based estimation of forecast uncertainty when the horizon is increased (2018) Downloads
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