Scenario discovery to address deep uncertainty in monetary policy

Abstract

We analyse shock and parameter uncertainty in a Dynamic Stochastic General Equilibrium (DSGE) model by exploratory modelling and analysis (EMA). This method evaluates in a novel way the performance of monetary policy under deep uncertainty about the shock and model parameters. Scenarios are designed based on the outcomes of interest for the policymaker. We assess the performance of different policies on their objectives in the scenarios. This maps out the policy trade-offs and supports the central bank in making robust policy decisions. We find that in response to a negative supply shock, policies with low interest rate smoothing and a strong response to inflation most obviously contribute to price stability under deep uncertainty.