Imperfect Knowledge and the Pitfalls of Optimal Control Monetary Policy

Authors

Athanasios Orphanides

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2008-09 | July 1, 2008

This paper examines the robustness characteristics of optimal control policies derived under the assumption of rational expectations to alternative models of expectations formation and uncertainty about the natural rates of interest and unemployment. We assume that agents have imperfect knowledge about the precise structure of the economy and form expectations using a forecasting model that they continuously update based on incoming data. We also allow for central bank uncertainty regarding the natural rates of interest and unemployment. We find that the optimal control policy derived under the assumption of perfect knowledge about the structure of the economy can perform poorly when knowledge is imperfect. These problems are exacerbated by natural rate uncertainty, even when the central bank’s estimates of natural rates are efficient. We show that the optimal control approach can be made more robust to the presence of imperfect knowledge by deemphasizing the stabilization of real economic activity and interest rates relative to inflation in the central bank loss function. That is, robustness to the presence of imperfect knowledge about the economy provides an incentive to employ a "conservative" central banker. We then examine two types of simple monetary policy rules from the literature that have been found to be robust to model misspecification in other contexts. We find that these policies are robust to the alternative models of learning that we study and natural rate uncertainty and outperform the optimal control policy and generally perform as well as the robust optimal control policy that places less weight on stabilizing economic activity and interest rates.

About the Authors
John C. Williams served as President and Chief Executive Officer of the Federal Reserve Bank of San Francisco from March 1, 2011 to June 17, 2018. Learn more about John C. Williams