Federal Reserve Bank of Cleveland
Working Papers (New Series)
Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors
We estimate uncertainty measures for point forecasts obtained from survey data, pooling information embedded in observed forecast errors for different forecast horizons. To track time-varying uncertainty in the associated forecast errors, we derive a multiple-horizon specification of stochastic volatility. We apply our method to forecasts for various macroeconomic variables from the Survey of Professional Forecasters. Compared to constant variance approaches, our stochastic volatility model improves the accuracy of uncertainty measures for survey forecasts. Our method can also be applied to other surveys like the Blue Chip Consensus, or the Federal Open Market Committee’s Summary of Economic Projections.
Cite this item
Todd E. Clark & Michael W. McCracken & Elmar Mertens, Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors, Federal Reserve Bank of Cleveland, Working Papers (New Series) 171501, 01 Sep 2017, revised 08 May 2018.
Note: This paper is a revision of Working Paper 17-15 published in September of 2017.
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
Keywords: Stochastic volatility; survey forecasts; fan charts
This item with handle RePEc:fip:fedcwq:171501
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