Modeling time-varying uncertainty of multiple-horizon forecast errors

Todd E. Clark, Michael W. McCracken and Elmar Mertens

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

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Year of publication:	August 31, 2017 ; This draft: August 31, 2017
Authors:	Clark, Todd E. ; McCracken, Michael W. ; Mertens, Elmar
Publisher:	St. Louis, MO : Federal Reserve Bank of St. Louis, Research Division
Subject:	Wirtschaftsprognose \| Economic forecast \| Prognoseverfahren \| Forecasting model \| Stochastische Volatilität \| Stochastic volatility \| Risiko \| Risk \| USA \| United States