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