The Performance of Forecast-Based Monetary Policy Rules Under Model Uncertainty

Abstract

We investigate the performance of forecast-based monetary policy rules using five macroeconomic models that reflect a wide range of views on aggregate dynamics. We identify the key characteristics of rules that are robust to model uncertainty: such rules respond to the one-year ahead inflation forecast and to the current output gap, and incorporate a substantial degree of policy inertia. In contrast, rules with longer forecast horizons are less robust and are prone to generating indeterminacy. In light of these results, we identify a robust benchmark rule that performs very well in all five models over a wide range of policy preferences.