Abstract
Abstract The Federal Reserve target rate has a lower bound. Changes to the target rate occur with discrete increments. Using out-of-sample forecasts of the target rate, we evaluate models incorporating these two realistic non-linear features. Incorporating these features mitigates in-sample over-fitting and improves out-of-sample forecast accuracy of the target rate level and volatility. A model with these features performs better relative to the linear models because (i) it produces stronger responses of forecasts to inflation and unemployment and a weaker response to lagged target rate, and because (ii) it yields very different forecast distributions when the target rate is close to the lower bound.
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