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The Central Banker as a Risk Manager: Estimating the Federal Reserve's Preferences under Greenspan

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  • Kilian, Lutz
  • Manganelli, Simone

Abstract

Motivated by policy statements of central bankers, we propose to regard the central banker as a risk manager who aims at containing inflation and the deviation of output from potential within pre-specified bounds. We develop formal tools of risk management that may be used to quantify the risks of failing to attain that objective. Risk measures inherently depend on the loss function of the user. We propose a simple, yet flexible class of loss functions that nests the standard assumption of quadratic symmetric preferences, while being congruent with a risk management model. We show how the parameters of this loss function under weak assumptions may be estimated from realizations for inflation and output gap data even in the absence of a fully specified structural model of the economy. We present estimates of the Federal Reserve’s risk aversion parameters with respect to the inflation and output objectives during the Greenspan period. We formally test for and reject the standard assumptions of quadratic and symmetric preference that underlies the derivation of the Taylor rule. Our results suggest that Fed policy decisions under Greenspan are better understood in terms of the Fed weighing upside and downside risks to their objectives rather than simply responding to the conditional mean of inflation and of the output gap. We derive a natural generalization of the Taylor rule that links changes in the interest rate to the balance of the risks implied by the dual objective of sustainable economic growth and price stability. Unlike standard Taylor rules, this generalized policy rule is consistent with the wording of policy decisions by the Federal Reserve.

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Bibliographic Info

Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 6031.

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Date of creation: Jan 2007
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Handle: RePEc:cpr:ceprdp:6031

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Keywords: Greenspan; inflation; monetary policy; output; policy rule; preferences; risk;

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References

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  1. Suleyman Basak & Alexander Shapiro, 1999. "Value-at-Risk Based Risk Management: Optimal Policies and Asset Prices," New York University, Leonard N. Stern School Finance Department Working Paper Seires 99-032, New York University, Leonard N. Stern School of Business-.
  2. Mark Gertler & Jordi Gali & Richard Clarida, 1999. "The Science of Monetary Policy: A New Keynesian Perspective," Journal of Economic Literature, American Economic Association, vol. 37(4), pages 1661-1707, December.
  3. Francisco Javier Ruge-Murcia, 2001. "Inflation Targeting Under Asymmetric Preferences," IMF Working Papers 01/161, International Monetary Fund.
  4. Richard Clarida & Jordi Galí & Mark Gertler, 1997. "Monetary policy rules and macroeconomic stability: Evidence and some theory," Economics Working Papers 350, Department of Economics and Business, Universitat Pompeu Fabra, revised May 1999.
  5. Taimur Baig & Jörg Decressin & Tarhan Feyzioglu & Manmohan S. Kumar & Chris Faulkner-MacDonagh, 2003. "Deflation," IMF Occasional Papers 221, International Monetary Fund.
  6. Daniel F. Waggoner & Tao Zha, 1998. "Conditional forecasts in dynamic multivariate models," Working Paper 98-22, Federal Reserve Bank of Atlanta.
  7. Ben S. Bernanke & Jean Boivin, 2001. "Monetary Policy in a Data-Rich Environment," NBER Working Papers 8379, National Bureau of Economic Research, Inc.
  8. 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.
  9. Lutz Kilian & Simone Manganelli, 2007. "Quantifying the Risk of Deflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(2-3), pages 561-590, 03.
  10. Holthausen, Duncan M, 1981. "A Risk-Return Model with Risk and Return Measured as Deviations from a Target Return," American Economic Review, American Economic Association, vol. 71(1), pages 182-88, March.
  11. Hall, Alastair R. & Inoue, Atsushi & Jana, Kalidas & Shin, Changmock, 2007. "Information in generalized method of moments estimation and entropy-based moment selection," Journal of Econometrics, Elsevier, vol. 138(2), pages 488-512, June.
  12. Fishburn, Peter C, 1977. "Mean-Risk Analysis with Risk Associated with Below-Target Returns," American Economic Review, American Economic Association, vol. 67(2), pages 116-26, March.
  13. Alex Cukierman & Anton Muscatelli, 2001. "Do Central Banks have Precautionary Demands for Expansions and for Price Stability?," Working Papers 2002_4, Business School - Economics, University of Glasgow, revised Mar 2002.
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Cited by:
  1. Baghestani, Hamid & Khallaf, Ashraf, 2012. "Predictions of growth in U.S. corporate profits: Asymmetric vs. symmetric loss," International Review of Economics & Finance, Elsevier, vol. 22(1), pages 222-229.
  2. Manzan, Sebastiano & Zerom, Dawit, 2013. "Are macroeconomic variables useful for forecasting the distribution of U.S. inflation?," International Journal of Forecasting, Elsevier, vol. 29(3), pages 469-478.
  3. Ron Alquist & Lutz Kilian & Robert J. Vigfusson, 2011. "Forecasting the Price of Oil," Working Papers 11-15, Bank of Canada.
  4. Matteo Barigozzi & Marco Capasso, 2007. "A Multivariate Perspective for Modeling and Forecasting Inflation's Conditional Mean and Variance," LEM Papers Series 2007/21, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  5. Manzan, Sebastiano & Zerom, Dawit, 2009. "Are Macroeconomic Variables Useful for Forecasting the Distribution of U.S. Inflation?," MPRA Paper 14387, University Library of Munich, Germany.
  6. Christian Pierdzioch & Jan-Christoph Rülke & Peter Tillmann, 2013. "Using forecasts to uncover the loss function of FOMC members," MAGKS Papers on Economics 201302, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).

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