Nikolay Gospodinov and Esfandiar Maasoumi
Working Paper 2025-12
October 2025
Full text 
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
Nikolay Gospodinov (nikolay.gospodinov@atl.frb.org) is in the Research Department, Federal Reserve Bank of Atlanta, 1000 Peachtree Street NE, Atlanta, GA 30309-4470. Esfandiar Maasoumi (esfandiar.maasoumi@emory.edu) 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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