Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors
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.
Clark, Todd E., Michael W. McCracken, and Elmar Mertens. 2017. “Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors” Federal Reserve Bank of Cleveland, Working Paper No. 17-15. https://doi.org/10.26509/frbc-wp-201715