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Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors

Todd Clark, Michael McCracken () and Elmar Mertens ()

No 2017-26, Working Papers from Federal Reserve Bank of St. Louis

Abstract: We develop uncertainty measures for point forecasts from surveys such as the Survey of Professional Forecasters, Blue Chip, or the Federal Open Market Committee's Summary of Economic Projections. At a given point of time, these surveys provide forecasts for macroeconomic variables at multiple horizons. To track time-varying uncertainty in the associated forecast errors, we derive a multiple-horizon specification of stochastic volatility. Compared to constant-variance approaches, our stochastic-volatility model improves the accuracy of uncertainty measures for survey forecasts.

Keywords: Stochastic volatility; survey forecasts; prediction (search for similar items in EconPapers)
JEL-codes: C32 C53 E47 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-for, nep-mac, nep-mon, nep-ore and nep-rmg
Date: 2017-08-28
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Related works:
Working Paper: Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors (2018) Downloads
Working Paper: Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors (2018) Downloads
Working Paper: Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors (2017) Downloads
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DOI: 10.20955/wp.2017.026

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