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In this paper, we exploit micro data from the ECB survey of professional forecasters to examine the link between the characteristics of macroeconomic density forecasts (such as their location, spread, skewness, and tail risk) and density forecast performance. Controlling for the effects of common macroeconomic shocks, we apply cross-sectional and fixed effect panel regressions linking such density characteristics and density forecast performance. Our empirical results suggest that many macroeconomic experts could systematically improve their density performance by correcting a downward bias in their variances. Aside from this shortcoming in the second moment characteristics of the individual densities, other higher moment features, such as skewness or variation in the degree of probability mass given to the tails of the predictive distributions, tend-as a rule-not to contribute significantly to enhancing individual density forecast performance.
density forecasting; forecast evaluation; survey of professional forecasters; panel data