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

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  • Eric Swanson

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in this framework, allowing for tractability and application to forward-looking models, but policymakers’ beliefs are no longer updated in a linear fashion, allowing for plausible nonlinearities in optimal policy.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

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2005 with number 147.

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Date of creation: 11 Nov 2005
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Handle: RePEc:sce:scecf5:147

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Keywords: nonlinear policy; optimal filtering; signal extraction; learning; non-normal priors;

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  1. Svensson, Lars & Woodford, Michael, 2000. "Indicator Variables for Optimal Policy," Seminar Papers 688, Stockholm University, Institute for International Economic Studies.
  2. Pearlman, Joseph G., 1992. "Reputational and nonreputational policies under partial information," Journal of Economic Dynamics and Control, Elsevier, vol. 16(2), pages 339-357, April.
  3. Volker Wieland, . "Monetary Policy and Uncertainty about the Natural Unemployment Rate," Computing in Economics and Finance 1997 11, Society for Computational Economics.
  4. Eric T. Swanson, 2005. "Optimal nonlinear policy: signal extraction with a non-normal prior," Working Paper Series 2005-24, Federal Reserve Bank of San Francisco.
  5. Laurence H. Meyer & Eric T. Swanson & Volker W. Wieland, 2001. "NAIRU Uncertainty and Nonlinear Policy Rules," American Economic Review, American Economic Association, vol. 91(2), pages 226-231, May.
  6. Andrew J. Filardo, 1998. "New evidence on the output cost of fighting inflation," Economic Review, Federal Reserve Bank of Kansas City, issue Q III.
  7. Douglas Staiger & James H. Stock & Mark W. Watson, 1996. "How Precise are Estimates of the Natural Rate of Unemployment?," NBER Working Papers 5477, National Bureau of Economic Research, Inc.
  8. Sack, Brian & Wieland, Volker, 2000. "Interest-rate smoothing and optimal monetary policy: a review of recent empirical evidence," Journal of Economics and Business, Elsevier, vol. 52(1-2), pages 205-228.
  9. Pearlman, Joseph & Currie, David & Levine, Paul, 1986. "Rational expectations models with partial information," Economic Modelling, Elsevier, vol. 3(2), pages 90-105, April.
  10. Taylor, John B., 1993. "Discretion versus policy rules in practice," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 195-214, December.
  11. repec:cup:macdyn:v:8:y:2004:i:1:p:27-50 is not listed on IDEAS
  12. Swanson, Eric T., 2004. "Signal Extraction And Non-Certainty-Equivalence In Optimal Monetary Policy Rules," Macroeconomic Dynamics, Cambridge University Press, vol. 8(01), pages 27-50, February.
  13. Orphanides, Athanasios & Wieland, Volker, 1999. "Inflation zone targeting," Working Paper Series 0008, European Central Bank.
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Cited by:
  1. Neuenkirch, Matthias & Tillmann, Peter, 2014. "Inflation targeting, credibility, and non-linear Taylor rules," Journal of International Money and Finance, Elsevier, vol. 41(C), pages 30-45.
  2. Laurence H. Meyer & Eric T. Swanson & Volker W. Wieland, 2001. "NAIRU uncertainty and nonlinear policy rules," Finance and Economics Discussion Series 2001-01, Board of Governors of the Federal Reserve System (U.S.).
  3. Martin Mandler, 2010. "Macroeconomic dynamics and inflation regimes in the U.S. Results from threshold vector autoregressions," MAGKS Papers on Economics 201012, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  4. Paul D. McNelis & Guay Lim, 2006. "Inflation Targeting, Learning and Q Volatility in Small Open Economies," Computing in Economics and Finance 2006 104, Society for Computational Economics.
  5. Eric Swanson, 2005. "Optimal Nonlinear Policy: Signal Extraction with a Non-Normal Prior," Computing in Economics and Finance 2005 147, Society for Computational Economics.

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