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Welfare-Maximizing Monetary Policy under Parameter Uncertainty

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Listed author(s):
  • Thomas Laubach

    (Federal Reserve Board)

  • John C. Williams

    (Federal Reserve Bank of San Francisco)

  • Rochelle M. Edge

    (Federal Reserve Board))

Abstract

This paper examines welfare-maximizing monetary policy in an estimated dynamic stochastic general equilibrium model of the U.S. economy where the policymaker faces uncertainty about the true values of model parameters. Uncertainty about parameters describing preferences and technology implies not only uncertainty about model dynamics but also uncertainty about the “natural” level of output that the central bank should aim to achieve. We analyze the characteristics and performance of alternative monetary policy rules given the estimated covariance of parameter estimates. We find that the natural rates of output is very imprecisely estimated. We then show that policy rules that rely on the output gap and therefore estimates estimates of the natural rate of output perform poorly under parameter uncertainty. Instead, optimal policies respond primarily to indirect signals regarding natural rates extracted from observed prices and wages.

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File URL: https://economicdynamics.org/meetpapers/2007/paper_311.pdf
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Paper provided by Society for Economic Dynamics in its series 2007 Meeting Papers with number 311.

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Date of creation: 2007
Handle: RePEc:red:sed007:311
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Society for Economic Dynamics Marina Azzimonti Department of Economics Stonybrook University 10 Nicolls Road Stonybrook NY 11790 USA

Web page: http://www.EconomicDynamics.org/
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Find related papers by JEL classification:
  • E5 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit

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Cited by:

  1. Rochelle M. Edge & Thomas Laubach & John C. Williams, 2010. "Welfare-maximizing monetary policy under parameter uncertainty," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 129-143.
  2. Pei-Tha Gan, 2014. "The Optimal Economic Uncertainty Index: A Grid Search Application," Computational Economics, Springer;Society for Computational Economics, vol. 43(2), pages 159-182, February.
  3. Sala, Luca & Söderström, Ulf & Trigari, Antonella, 2008. "Monetary policy under uncertainty in an estimated model with labor market frictions," Journal of Monetary Economics, Elsevier, vol. 55(5), pages 983-1006, July.
  4. Özer Karagedikli & Troy Matheson & Christie Smith & Shaun P. Vahey, 2010. "RBCs AND DSGEs: THE COMPUTATIONAL APPROACH TO BUSINESS CYCLE THEORY AND EVIDENCE," Journal of Economic Surveys, Wiley Blackwell, vol. 24(1), pages 113-136, 02.
  5. Williams, John C., 2013. "A defense of moderation in monetary policy," Journal of Macroeconomics, Elsevier, vol. 38(PB), pages 137-150.
  6. Carl Walsh, 2007. "Inflation Targeting and the Role of Real Objectives," Research and Policy Notes 2007/02, Czech National Bank, Research Department.
  7. Anthony Diercks, 2016. "The Equity Premium, Long-Run Risk, and Optimal Monetary Policy," 2016 Meeting Papers 207, Society for Economic Dynamics.
  8. Taylor, John B. & Williams, John C., 2010. "Simple and Robust Rules for Monetary Policy," Handbook of Monetary Economics,in: Benjamin M. Friedman & Michael Woodford (ed.), Handbook of Monetary Economics, edition 1, volume 3, chapter 15, pages 829-859 Elsevier.
  9. Avouyi-Dovi, Sanvi & Sahuc, Jean-Guillaume, 2011. "On the welfare costs of misspecified monetary policy objectives," Journal of Macroeconomics, Elsevier, vol. 33(2), pages 151-161, June.
  10. Paez-Farrell, Juan, 2014. "Resuscitating the ad hoc loss function for monetary policy analysis," Economics Letters, Elsevier, vol. 123(3), pages 313-317.
  11. André P. Calmon & Thomas Vallée & João B. R. Do Val, 2009. "Monetary policy as a source of uncertainty," Working Papers hal-00422454, HAL.

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