October 09, 2025

• Working Papers
• Publication
• Macroeconomy
• Monetary Policy

Working Paper 2025-12

Abstract: Policy makers express their views and decisions via the lens of a particular model or theory. But since any model is a highly stylized representation of the unknowable object of interest, all these models are inherently misspecified, and the resulting ambiguity injects uncertainty in the decision-making process. We argue that entropy-based aggregation is a convenient device to confront this uncertainty and summarize relevant information from a set of candidate models and forecasts. The proposed aggregation tends to robustify the decision-making process to various sources of risks and uncertainty. We find compelling evidence for the advantages of entropy-based aggregation for forecasting inflation.

JEL classification: C52, C53, E37, G11

Key words: model uncertainty, model aggregation, forecast combination, robust policy

https://doi.org/10.29338/wp2025-12

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Nikolay Gospodinov is in the Research Department, Federal Reserve Bank of Atlanta, 1000 Peachtree Street NE, Atlanta, GA 30309-4470. Esfandiar Maasoumi is in the Emory University Department of Economics, Rich Memorial Building 324, 1602 Fishburne Drive, Atlanta, GA 30322-2240. The views expressed here are those of the authors and do not necessarily reflect those of the Federal Reserve Bank of Atlanta or the Federal Reserve System.

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