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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, ...
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Ordinal Complementarity
This paper introduces ordinal complementarity: a feature of stochastic production functions that is robust to monotonic transformations of inputs X and output Y. It has two equivalent definitions: supermodularity of the conditional survival function under a first-order stochastic dominance ordering, and supermodularity of E[Q(Y )|X] for all non-decreasing valuations Q. Relative to existing conventions, this definition offers a strengthening with more robust policy implications. Ordinal complementarity is necessary and sufficient for a number of social planner problems to have monotone ...