“Two-Sided Learning and Optimal Open Economy Monetary Policy” by Timothy KAM
University of Western Australia
In this paper, we consider a dynamic New Keynesian model of the small open economy in the light of bounded rationality. This entails private agents and the central bank updating their beliefs about the laws of motion of inflation, the output gap and real exchange rate when forming their optimal decisions. It is shown that a fundamental-shock representation of optimal discretionary policy in the small open economy will yield multiple REE, and in particular, the fundamentals REE cannot be achieved under expectational learning. The alternative representation of optimal policy — an open-economy forecast-based rule — yields a stable fundamentals REE only under certain parameterization when agents learn. Furthermore, the Taylor principle need not be satisfied because part of the stabilization is carried out by the real-exchange-rate channel.