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Learning, expectations formation and the pitfalls of optimal control monetary policy

  • Athanasios Orphanides
  • John C. Williams

This paper examines the robustness characteristics of optimal control policies derived under the assumption of rational expectations to alternative models of expectations. 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 find that the optimal control policy derived under the assumption of rational expectations can perform poorly when expectations deviate modestly from rational expectations. We then show that the optimal control policy can be made more robust by deemphasizing the stabilization of real economic activity and interest rates relative to inflation in the central bank loss function. That is, robustness to learning 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 empirically plausible parameterizations of the learning models and perform about as well or better than optimal control policies.

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Paper provided by Federal Reserve Bank of San Francisco in its series Working Paper Series with number 2008-05.

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Date of creation: 2008
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Handle: RePEc:fip:fedfwp:2008-05
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  1. Orphanides, Athanasios & Williams, John C, 2006. "Inflation Targeting under Imperfect Knowledge," CEPR Discussion Papers 5664, C.E.P.R. Discussion Papers.
  2. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
  3. Lars E.O. Svensson, 2002. "Inflation Targeting: Should It Be Modeled as an Instrument Rule or a Targeting Rule?," NBER Working Papers 8925, National Bureau of Economic Research, Inc.
  4. John C. Williams, 2003. "Simple rules for monetary policy," Economic Review, Federal Reserve Bank of San Francisco, pages 1-12.
  5. Robert E. Hall, 1984. "Monetary strategy with an elastic price standard," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 137-167.
  6. Rogoff, Kenneth, 1985. "The Optimal Degree of Commitment to an Intermediate Monetary Target," The Quarterly Journal of Economics, MIT Press, vol. 100(4), pages 1169-89, November.
  7. Athanasios Orphanides & John C. Williams, 2002. "Robust monetary policy rules with unknown natural rates," Working Paper Series 2003-01, Federal Reserve Bank of San Francisco.
  8. Robert J. Tetlow, 2010. "Real-time model uncertainty in the United States: 'Robust' policies put to the test," Finance and Economics Discussion Series 2010-15, Board of Governors of the Federal Reserve System (U.S.).
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  10. Dean Croushore, 1993. "Introducing: the survey of professional forecasters," Business Review, Federal Reserve Bank of Philadelphia, issue Nov, pages 3-15.
  11. Branch, William A. & Evans, George W., 2006. "A simple recursive forecasting model," Economics Letters, Elsevier, vol. 91(2), pages 158-166, May.
  12. Andrew Levin & Volker Wieland & John C. Williams, 2003. "The Performance of Forecast-Based Monetary Policy Rules Under Model Uncertainty," American Economic Review, American Economic Association, vol. 93(3), pages 622-645, June.
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  22. 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.
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  24. Svensson, Lars E. O. & Williams, Noah, 2005. "Monetary policy with model uncertainty: distribution forecast targeting," Discussion Paper Series 1: Economic Studies 2005,35, Deutsche Bundesbank, Research Centre.
  25. Thomas J. Sargent, 2008. "Evolution and Intelligent Design," American Economic Review, American Economic Association, vol. 98(1), pages 5-37, March.
  26. Marc Giannoni & Michael Woodford, 2004. "Optimal Inflation-Targeting Rules," NBER Chapters, in: The Inflation-Targeting Debate, pages 93-172 National Bureau of Economic Research, Inc.
  27. N. Gregory Mankiw & Ricardo Reis & Justin Wolfers, 2003. "Disagreement about Inflation Expectations," NBER Working Papers 9796, National Bureau of Economic Research, Inc.
  28. Taylor, John B, 1975. "Monetary Policy during a Transition to Rational Expectations," Journal of Political Economy, University of Chicago Press, vol. 83(5), pages 1009-21, October.
  29. Kosuke Aoki & Kalin Nikolov, 2006. "Rule-Based Monetary Policy under Central Bank Learning," NBER Chapters, in: NBER International Seminar on Macroeconomics 2004, pages 145-195 National Bureau of Economic Research, Inc.
  30. Taylor, John B., 1998. "The Robustness and Efficiency of Monetary Policy Rules as Guidelines for Interest Rate Setting by the European Central Bank," Seminar Papers 649, Stockholm University, Institute for International Economic Studies.
  31. Andrew T.. Levin & Volker Wieland & John Williams, 1999. "Robustness of Simple Monetary Policy Rules under Model Uncertainty," NBER Chapters, in: Monetary Policy Rules, pages 263-318 National Bureau of Economic Research, Inc.
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  33. Mccallum, Bennet T., 1988. "Robustness properties of a rule for monetary policy," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 29(1), pages 173-203, January.
  34. Schmidt-Hebbel, Klaus & Tapia, Matias, 2002. "Inflation targeting in Chile," The North American Journal of Economics and Finance, Elsevier, vol. 13(2), pages 125-146, August.
  35. Ferrero, Giuseppe, 2007. "Monetary policy, learning and the speed of convergence," Journal of Economic Dynamics and Control, Elsevier, vol. 31(9), pages 3006-3041, September.
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