Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors

• 成果类型: Article
• 署名作者: Clark, Todd E.; McCracken, Michael W.; Mertens, Elmar
• 署名单位: Federal Reserve System - USA; Federal Reserve Bank - Cleveland; Federal Reserve System - USA; Federal Reserve Bank - St. Louis; Deutsche Bundesbank
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/rest_a_00809
• 发表日期: 2020-03
• 页码: 17-33
• 关键词: stochastic volatility; density forecasts; us inflation

摘要

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.