Working Paper: CEPR ID: DP4587
Authors: Lucio Sarno; Daniel L. Thornton; Giorgio Valente
Abstract: We examine the forecasting performance of a range of time-series models of the daily US effective federal funds (FF) rate recently proposed in the literature. We find that: (i) most of the models and predictor variables considered produce satisfactory one-day-ahead forecasts of the FF rate; (ii) the best forecasting model is a simple univariate model where the future FF rate is forecast using the current difference between the FF rate and its target; (iii) combining the forecasts from various models generally yields modest improvements on the best performing model. These results have a natural interpretation and clear policy implications.
Keywords: federal fund rate; forecasting; nonlinearity; term structure
JEL Codes: E43; E47
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| current difference between the federal funds rate and its target (E52) | forecasting future rates (E47) |
| predictor variables (C29) | forecasting performance of models for the federal funds rate (E47) |
| combining forecasts from various models (C53) | improvements over the best-performing model (C52) |
| best forecasting model (C53) | federal funds rate (E52) |