摘要：In situations of relative calm and certainty, policy makers have confidence in the mechanisms at work and feel capable of attaining precise and ambitious results. As the environment becomes less and less certain, policy makers are confronted with the fact that there is a trade-off between the quality of a certain outcome and the confidence (robustness) with which it can be attained. Added to that, in the presence of Knightian uncertainty, confidence itself can no longer be represented in probabilistic terms (because probabilities are unknown). We adopt the technique of Info-Gap Robust Satisficing to first define confidence under Knightian uncertainty, and second quantify the trade-off between quality and robustness explicitly. We apply this to a standard monetary policy example and provide Central Banks with a framework to rank policies in a way that will allow them to pick the one that either maximizes confidence given an acceptable level of performance, or alternatively, optimizes performance for a given level of confidence.
