CMStatistics 2021: Start Registration
View Submission - CFE
Title: Uncertainty measures from partially rounded probabilistic forecast surveys Authors:  Matthias Hartmann - Deutsche Bundesbank (Germany) [presenting]
Alexander Glas - FAU Erlangen-Nuernberg (Germany)
Abstract: 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. We document the novel stylized fact that this variance misalignment is related to the rounding behavior of survey participants. Rounding may reflect 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 way to propose several alternatives and easily implementable corrections that 1. can be carried out in real-time, i.e., before outcomes are observed, and 2. 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.