Simple Monetary Policy Rules Under Model Uncertainty

Using stochastic simulations and stability analysis, we compare the performances of different monetary rules in a moderately nonlinear model with those in a time-varying nonaccelerating-inflation rate-of-unemployment (NAIRU) model. Rules that perform well in linear models -- but implicitly embody backward-looking measures of real interest rates (such as conventional Taylor rules) or substantial interest rate smoothing -- perform very poorly in models with moderate nonlinearities, particularly when policymakers tend toward serially correlated errors in estimating the NAIRU. This challenges the practice of evaluating rules within linear models, which demonstrate rather unrealistic consequences to myopic responses to significant overheating.