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Optimal Monetary Policy under Learning in a New Keynesian Model with Cost Channel and Inflation Inertia

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Listed author(s):
  • Bask, Mikael

    ()

    (Department of Economics)

  • Proaño, Christian R

    (Department of Economics)

Abstract

We show that a so-called expectations-based optimal monetary policy rule has desirable properties in a standard New Keynesian model augmented with a cost channel and inflation rate expectations that are partly backward-looking. In particular, optimal monetary policy under commitment is associated with a determinate rational expectations equilibrium that is stable under least squares learning for all parameter constellations considered, whereas, under discretion in policy-making, the central bank has to be sufficiently inflation rate averse for the rational expectations equilibrium to have the same properties.

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File URL: http://uu.diva-portal.org/smash/get/diva2:509121/FULLTEXT01.pdf
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Paper provided by Uppsala University, Department of Economics in its series Working Paper Series with number 2012:7.

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Length: 25 pages
Date of creation: 29 Feb 2012
Handle: RePEc:hhs:uunewp:2012_007
Contact details of provider: Postal:
Department of Economics, Uppsala University, P. O. Box 513, SE-751 20 Uppsala, Sweden

Phone: + 46 18 471 25 00
Fax: + 46 18 471 14 78
Web page: http://www.nek.uu.se/
Email:


More information through EDIRC

Keywords: Commitment; Cost Channel; Determinacy; Discretion; Inflation Inertia; Least Squares Learning; Optimal Monetary Policy;

Find related papers by JEL classification:

  • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
  • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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  22. Surico, Paolo, 2008. "The Cost Channel Of Monetary Policy And Indeterminacy," Macroeconomic Dynamics, Cambridge University Press, vol. 12(05), pages 724-735, November.
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