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Discussion Paper
Combining Models for Forecasting and Policy Analysis
Model uncertainty is pervasive. Economists, bloggers, policymakers all have different views of how the world works and what economic policies would make it better. These views are, like it or not, models. Some people spell them out in their entirety, equations and all. Others refuse to use the word altogether, possibly out of fear of being falsified. No model is “right,” of course, but some models are worse than others, and we can have an idea of which is which by comparing their predictions with what actually happened. If you are open-minded, you may actually want to combine models in ...
Working Paper
Probability Forecast Combination via Entropy Regularized Wasserstein Distance
We propose probability and density forecast combination methods that are defined using the entropy regularized Wasserstein distance. First, we provide a theoretical characterization of the combined density forecast based on the regularized Wasserstein distance under the Gaus-sian assumption. Second, we show how this type of regularization can improve the predictive power of the resulting combined density. Third, we provide a method for choosing the tuning parameter that governs the strength of regularization. Lastly, we apply our proposed method to the U.S. inflation rate density forecasting, ...