A Bayesian Approach to Optimal Monetary Policy with Parameter and Model Uncertainty

This paper undertakes a Bayesian analysis of optimal monetary policy for the United Kingdom. We estimate a suite of monetary policy models that include both forward and backward-looking representations as well as large and small-scale models. We find an optimal simple Taylor-type rule that accounts for both model and parameter uncertainty. For the most part, backward-looking models are highly fault tolerant with respect to policies optimised for forward-looking representations, while forward-looking models have low fault tolerance with respect to policies optimised for backward-looking representations. In addition, backward-looking models often have lower posterior probabilities than forward-looking models. Bayesian policies therefore have characteristics suitable for inflation and output stabilisation in forward-looking models