How Does the FOMC Form Forecasts? An Adaptive Learning Approach Utilizing SEP Data

Stephen Cole ()
Additional contact information
Stephen Cole: Department of Economics Marquette University

No 2025-02, Working Papers and Research from Marquette University, Center for Global and Economic Studies and Department of Economics

Abstract: This paper examines how FOMC participants construct their Summary of Economic Projections (SEP) forecasts. FOMC expectations are assumed to contain two components: (1) an endogenous part that follows an adaptive learning model and (2) an exogenous part defined as sentiment (waves of optimism and/or pessimism). The results include key policy takeaways. The forecasts of FOMC members are responsive to new economic information. Their sentiment about future GDP growth and inflation also displays persistence and is correlated with each other. Moreover, FOMC participants rely more on their endogenous/learning model to form expectations. However, sentiment plays a larger role during and around recessions.

Keywords: summary of economic projections; FOMC; constant-gain learning; sentiment shocks; waves of optimism and pessimism; evolving beliefs; monetary policy (search for similar items in EconPapers)
JEL-codes: C52 D84 E50 E52 E58 E60 E70 E71 (search for similar items in EconPapers)
Date: 2025-06
New Economics Papers: this item is included in nep-for and nep-mon
References: Add references at CitEc
Citations:

Downloads: (external link)
https://epublications.marquette.edu/econ_workingpapers/101 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:mrq:wpaper:2025-02

Access Statistics for this paper

More papers in Working Papers and Research from Marquette University, Center for Global and Economic Studies and Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Andrew G. Meyer ().