Federal Funds Rate Prediction

نویسندگان

  • Lucio Sarno
  • Daniel L. Thornton
  • Giorgio Valente
چکیده

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 oneday-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. JEL classification: E43; E47.

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تاریخ انتشار 2003