Optimal Pooling in Taylor Rule Estimation with Multiple-Horizon Forecast Panels

Edward Herbst and Karen Page

No 2026-064, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

Abstract: Multiple-horizon forecast panels are increasingly used to infer perceived monetary policy rules, but inference depends on how coefficients are pooled across forecasters, dates, and horizons. We treat this pooling structure as the object of inference. In a participant-date-horizon Taylor-rule regression model, we compare pooling patterns using Bayesian marginal likelihoods, applying the framework to the Blue Chip Financial Forecasts, Survey of Professional Forecasters, and the Summary of Economic Projections. The preferred specifications place much of the systematic variation in policy-rate forecasts in intercepts that vary across forecast horizons and survey dates. Evidence of "changing perceptions" of monetary policy via economically meaningful time-varying response coefficients is weak overall.

Keywords: Taylor rules; monetary policy expectations; survey forecasts; Bayesian model selection; coefficient heterogeneity (search for similar items in EconPapers)
JEL-codes: C11 C23 E47 E52 (search for similar items in EconPapers)
Pages: 39 p.
Date: 2026-09-18
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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedgfe:103790

DOI: 10.17016/FEDS.2026.064

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