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Methods Available to Monetary Policy Makers to Deal with Uncertainty

  • Katerina Smidkova

    (Czech National Bank)

Three sources – research on monetary policy under uncertainty, the managerial literature, and the real-life strategies of five inflation targeters – have been used to survey methods that are available to monetary policy makers to deal with uncertainty. The methods have been compared within a framework that is based on a decision matrix. The comparative framework has been designed in order to encompass different representations of uncertainty employed by various central banks. The results of comparative analysis suggest that central banks use models, intuition, judgement as well as traditional managerial methods to deal with uncertainty. This finding helps understanding why economic research cannot fully explain differences between monetary policy actions and outcomes of model simulations. The results of the comparative analysis also suggest that central banks have not so far fully utilised the whole spectrum of methods available to them. Economic research, other banks’ strategies as well as decision analysis may be interesting sources of inspiration when designing the decision-making process. It is emphasised that central banks introducing inflation targeting should pay equal attention to both building their forecasting models as well as selecting methods to deal with uncertainty. In the case of emerging economies where uncertainty can be much higher than in advanced economies, neglecting uncertainty may increase probability of policy errors significantly.

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Paper provided by EconWPA in its series Macroeconomics with number 0310002.

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Length: 38 pages
Date of creation: 06 Oct 2003
Date of revision:
Handle: RePEc:wpa:wuwpma:0310002
Note: Type of Document - ; pages: 38 . The paper has been prepared for the conference “Forecasting in a Central Bank”, Bank of England, August 2003, London.
Contact details of provider: Web page: http://econwpa.repec.org

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  1. Geraats, Petra M., 2000. "Why Adopt Transparency? The Publication of Central Bank Forecasts," Center for International and Development Economics Research, Working Paper Series qt0hw7h7cp, Center for International and Development Economics Research, Institute for Business and Economic Research, UC Berkeley.
  2. Katerina Smidkova, 2003. "Targeting Inflation under Uncertainty: Policy Makers' Perspective," Research and Policy Notes 2003/02, Czech National Bank, Research Department.
  3. Alan S. Blinder & John Morgan, 2001. "Are Two Heads Better Than One?: An Experimental Analysis of Group vs. Individual Decisionmaking," Working Papers 130, Princeton University, Department of Economics, Center for Economic Policy Studies..
  4. Lars E O Svensson, 1996. "Inflation Forecast Targeting: Implementing and Monitoring Inflation Targets," Bank of England working papers 56, Bank of England.
  5. Andrew Levin & Volker Wieland & John C. Williams, 1998. "Robustness of Simple Monetary Policy Rules under Model Uncertainty," NBER Working Papers 6570, National Bureau of Economic Research, Inc.
  6. Tiff Macklem, 2002. "Information and Analysis for Monetary Policy: Coming to a Decision," Bank of Canada Review, Bank of Canada, vol. 2002(Summer), pages 11-18.
  7. Athanasios Orphanides, 1998. "Monetary policy evaluation with noisy information," Finance and Economics Discussion Series 1998-50, Board of Governors of the Federal Reserve System (U.S.).
  8. Cogley, Timothy & Morozov, Sergei & Sargent, Thomas J., 2005. "Bayesian fan charts for U.K. inflation: Forecasting and sources of uncertainty in an evolving monetary system," Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 1893-1925, November.
  9. Douglas Laxton & Alasdair Scott & David Rose, 2009. "Developing a Structured Forecasting and Policy Analysis System to Support Inflation-Forecast Targeting (IFT)," IMF Working Papers 09/65, International Monetary Fund.
  10. Clare Lombardelli & James Proudman & James Talbot, 2002. "Committees versus individuals: an experimental analysis of monetary policy decision-making," Bank of England working papers 165, Bank of England.
  11. Lavan Mahadeva & Katerina Smidkova, 2004. "Modelling transmission mechanism of monetary policy in the Czech Republic," Macroeconomics 0402032, EconWPA.
  12. Peter Isard & Douglas Laxton & Ann-Charlotte Eliasson, 1999. "Simple Monetary Policy Rules Under Model Uncertainty," International Tax and Public Finance, Springer, vol. 6(4), pages 537-577, November.
  13. Andrew G. Haldane & Nicoletta Batini, 1998. "Forward-Looking Rules for Monetary Policy," NBER Working Papers 6543, National Bureau of Economic Research, Inc.
  14. J. Tetlow, Robert & von zur Muehlen, Peter, 2001. "Robust monetary policy with misspecified models: Does model uncertainty always call for attenuated policy?," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 911-949, June.
  15. John C. Robertson, 2000. "Central bank forecasting: an international comparison," Economic Review, Federal Reserve Bank of Atlanta, issue Q2, pages 21-32.
  16. Christopher A. Sims, 2001. "Pitfalls of a Minimax Approach to Model Uncertainty," American Economic Review, American Economic Association, vol. 91(2), pages 51-54, May.
  17. Lars E.O. Svensson, 2003. "Optimal Policy with Low-Probability Extreme Events," NBER Working Papers 10196, National Bureau of Economic Research, Inc.
  18. Alan S. Blinder, 1999. "Central Banking in Theory and Practice," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262522608, June.
  19. Srour, Gabriel, 1999. "Inflation Targeting under Uncertainty," Technical Reports 85, Bank of Canada.
  20. Otmar Issing, 2002. "Monetary Policy In A World of Uncertainty," Economie Internationale, CEPII research center, issue 92, pages 165-179.
  21. Simon Hall & Chris Salmon & Tony Yates & Nicoletta Batini, 1999. "Uncertainty and Simple Monetary Policy Rules - An illustration for the United Kingdom," Bank of England working papers 96, Bank of England.
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