Measuring disagreement in probabilistic and density forecasts
Abstract: In this paper, we introduce and study a class of disagreement measures for probability distribution forecasts based on the Wasserstein metric. We describe a few advantageous properties of this measure of disagreement between forecasters. After describing alternatives to our proposal, we use examples to compare these measures to one another in closed form. We provide two empirical illustrations. The ﬁrst application uses our measure to gauge disagreement among professional forecasters about output growth and inﬂation rate in the Eurozone. The second application employs our measure to gauge disagreement among multivariate predictive distributions generated by diﬀerent forecasting methods.
Provider: Federal Reserve Bank of Philadelphia
Part of Series: Working Papers
Publication Date: 2020-01-26