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Activity Number:
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161
- Advances in Forecasting of Macroeconomic Variables: New Methods and Applications
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 4, 2020 : 10:00 AM to 11:50 AM
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Sponsor:
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Business and Economic Statistics Section
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Abstract #312583
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Title:
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Measuring disagreement in probabilistic and density forecasts
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Author(s):
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Minchul Shin* and Ryan Cumings and Keith Sill
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Companies:
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Federal Reserve Bank of Philadelphia and US Census Bureau and Federal Reserve Bank of Philadelphia
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Keywords:
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Disagreement ;
Dispersion;
Density forecasting;
Wasserstein distance;
Optimal transport;
Survey of Professional Forecasters
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Abstract:
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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 Euro zone. The second application employs our measure to gauge disagreement among multivariate predictive distributions generated by different forecasting methods.
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Authors who are presenting talks have a * after their name.
