Uncertainty measures from partially rounded probabilistic forecast surveys
Alexander Glas and
No 427, Working Papers from University of Milano-Bicocca, Department of Economics
Although survey-based point predictions have been found to outperform successful forecasting models, corresponding variance forecasts are frequently diagnosed as heavily distorted. Forecasters who report inconspicuously low ex-ante variances often produce squared forecast errors that are much larger on average. In this paper, we document the novel stylized fact that this variance misalignment is related to the rounding behavior of survey participants. Rounding may reflect the fact that some survey participants employ a rather judgmental approach to forecasting as opposed to using a formal model. We use the distinct numerical accuracies of panelists' reported probabilities as a means to propose several alternative and easily implementable corrections that i) can be carried out in real time, i.e., before outcomes are observed, and ii) deliver a significantly improved match between ex-ante and ex-post forecast uncertainty. According to our estimates, uncertainty about inflation, output growth and unemployment in the U.S. and the Euro area is higher after correcting for the rounding effect. The increase in the share of non-rounded responses in recent years also helps to understand the trajectory of survey-based average uncertainty during the years since the financial and sovereign debt crisis.
Keywords: Survey data; probabilistic forecasting; rounding; macroeconomic uncertainty. (search for similar items in EconPapers)
JEL-codes: C32 C52 C53 C83 (search for similar items in EconPapers)
Date: 2020-01, Revised 2020-01
New Economics Papers: this item is included in nep-for and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:mib:wpaper:427
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