Abstract
We employ the robust-satisficing approach to derive robust monetary policy when parameters of a macro model are uncertain. There is a trade-off between robustness of policies and their performance. Hence, under uncertainty, the policy maker is assumed to be content with policy performance at some satisfactory level rather than a level thought to be optimal based on available information. Our empirical analysis illustrates key properties of robustsatisficing policies and compares them with min-max policies implied by the robust-control approach. Intuitively, our empirical results suggest that higher robustness can be achieved by overstating challenges to the economy and understating the abilities to meet them. How much to overstate the challenges or understate the abilities depends on the robustness sought. Robustness is achieved by lowering one’s aspirations regarding the performance of policies and is therefore costly. Moreover, costs of robustness increase with the level of robustness, making robustness to apparently extreme parameter values particularly costly. We also find that robust-satisficing policies are generally less aggressive than min-max policies.