Monetary Policy under Uncertainty in Micro-Founded Macroeconometric Models


Andrew T. Levin

Alexei Onatski

Noah Williams

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2005-15 | July 1, 2005

We use a micro-founded macroeconometric modeling framework to investigate the design of monetary policy when the central bank faces uncertainty about the true structure of the economy. We apply Bayesian methods to estimate the parameters of the baseline specification using postwar U.S. data and then determine the policy under commitment that maximizes household welfare. We find that the performance of the optimal policy is closely matched by a simple operational rule that focuses solely on stabilizing nominal wage inflation. Furthermore, this simple wage stabilization rule is remarkably robust to uncertainty about the model parameters and to various assumptions regarding the nature and incidence of the innovations. However, the characteristics of optimal policy are very sensitive to the specification of the wage contracting mechanism, thereby highlighting the importance of additional research regarding the structure of labor markets and wage determination.

Article Citation

Onatski, Alexei, Andrew T. Levin, John C. Williams, and Noah Williams. 2005. “Monetary Policy under Uncertainty in Micro-Founded Macroeconometric Models,” Federal Reserve Bank of San Francisco Working Paper 2005-15. Available at

About the Author
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. Dr. Williams was previously the executive vice president and director of research for the San Francisco bank, which he joined in 2002. He began his career in 1994 as an […] Learn more about John C. Williams