On Model Aggregation and Forecast Combination
October 09, 2025
Summary
The authors of this working paper look at robust aggregation of information under pervasive model uncertainty. Their proposed method offers a scientific basis for the informal way policy makers refer to diversity of opinions and models available to them. The paper presents compelling evidence for the advantages of entropy-based aggregation for forecasting inflation.
View PaperWorking 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
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.
Federal Reserve Bank of Atlanta working papers, including revised versions, are available on the Atlanta Fed’s website at www.atlantafed.org. Click "Publications" and then "Working Papers." To receive e-mail notifications about new papers, go to subscribe.