Insurance Policies for Monetary Policy in the Euro Area

In this paper, we design a monetary policy for the euro area at the start of monetary union. We compare and ultimately combine Bayesian and worst-case analysis using four reference models developed at the ECB and estimated with pre-EMU synthetic data. We start by computing the cost of insurance against model uncertainty. We find that maximum insurance across this range of models can be obtained at moderate costs relative to a Bayesian policy with flat priors. However, there are three shortcomings of this worst-case insurance policy: (i) prior beliefs indicate that such insurance is strongly oriented towards the model with highest baseline losses; (ii) the Minimax policy is not as tolerant towards small perturbations of policy parameters as the Bayesian policy; and (iii) the Minimax policy offers no avenue for incorporating posterior model probabilities derived from data available since monetary union. Thus, we propose preferences for robust policy design that reflect a mixture of the Bayesian and Minimax approaches. These preferences incorporate model probabilities while still giving extra weight to the worst uncertain outcomes