Forecasting Interest Rates and Inflation: Blue Chip Clairvoyants or Econometrics?

Abstract

This study examines the performance of the professional analysts in the Blue Chip Financial Forecasts vis-a-vis set of competing econometric benchmarks, including shrinkage versions that adjust for in-sample over-fit in improving out-of-sample performance. The individual participants perform the best overall for short horizon forecasts of short to medium term yields and inflation. Econometric models with shrinkage perform the best over longer horizons and maturities. Aggregating over a larger set of analysts improves inflation surveys while generally degrading interest rates surveys. We document predictability in the survey forecast errors, which exhibit substantial variability across di fferent economic episodes, and propose a new adjustment that can substantially improve the performance of the survey participants.