The Review of Economics and Statistics Vol. 102 No. 1 2020

Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors

Todd E. Clark¹; Michael W. McCracken²; Elmar Mertens³

¹ Federal Reserve Bank of Cleveland · ² Federal Reserve Bank of St. Louis · ³ Deutsche Bundesbank

Abstract

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 simple variance approaches, our stochastic volatility model improves the accuracy of uncertainty measures for survey forecasts.

DOI

10.1162/rest_a_00809

Volume

102

Issue

1

Pages

17-33

Language

en

Sources

openalex crossref

Cite

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