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Optimal Nonlinear Policy: Signal Extraction With a Non-Normal Prior


Eric T. Swanson


Federal Reserve Bank of San Francisco

December 2005

Federal Reserve Bank of San Francisco Working Paper Series 2005-24

Abstract:     
The literature on optimal monetary policy typically makes three major assumptions: (1) policymakers' preferences are quadratic, (2) the economy is linear, and (3) stochastic shocks and policymakers' prior beliefs about unobserved variables are normally distributed. This paper relaxes the third assumption and explores its implications for optimal policy. The separation principle continues to hold in this framework, allowing for tractability and application to forward-looking models, but policymakers' beliefs are no longer updated in a linear fashion, allowing for plausible nonlinearities in optimal policy. We consider in particular a class of models in which policymakers' priors about the natural rate of unemployment are diffuse in a region around the mean. When this is the case, it is optimal for policy to respond cautiously to small surprises in the observed unemployment rate, but become increasingly aggressive at the margin. These features of optimal policy match statements by Federal Reserve officials and the behavior of the Fed in the 1990s.

Number of Pages in PDF File: 24

Keywords: Monetary policy, Econometric models

JEL Classification: E52

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Date posted: July 24, 2007  

Suggested Citation

Swanson, Eric T., Optimal Nonlinear Policy: Signal Extraction With a Non-Normal Prior (December 2005). Available at SSRN: http://ssrn.com/abstract=892358 or http://dx.doi.org/10.2139/ssrn.892358

Contact Information

Eric T. Swanson (Contact Author)
Federal Reserve Bank of San Francisco ( email )
101 Market Street
San Francisco, CA 94105
United States
415-974-3172 (Phone)
HOME PAGE: http://www.ericswanson.pro
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