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Optimal Constrained Interest-Rate Rules

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  • GEORGE W. EVANS
  • BRUCE McGOUGH

Abstract

We show that if policymakers compute the optimal unconstrained interest-rate rule within a Taylor-type class, they may be led to rules that generate indeterminacy and/or instability under learning. This problem is compounded by uncertainty about structural parameters since an optimal rule that is determinate and stable under learning for one calibration may be indeterminate or unstable under learning under a different calibration. We advocate a procedure in which policymakers restrict attention to rules constrained to lie in the determinate learnable region for all plausible calibrations, and that minimize the expected loss, computed using structural parameter priors, subject to this constraint. Copyright 2007 The Ohio State University.

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Bibliographic Info

Article provided by Blackwell Publishing in its journal Journal of Money, Credit and Banking.

Volume (Year): 39 (2007)
Issue (Month): 6 (09)
Pages: 1335-1356

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Handle: RePEc:mcb:jmoncb:v:39:y:2007:i:6:p:1335-1356

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Web page: http://www.blackwellpublishing.com/journal.asp?ref=0022-2879

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Cited by:
  1. Robert J. Tetlow & Peter von zur Muehlen, 2006. "Robustifying Learnability," 2006 Meeting Papers 439, Society for Economic Dynamics.
  2. George W. Evans & Seppo Honkapohja, 2008. "Expectations, Learning and Monetary Policy: An Overview of Recent Research," CDMA Working Paper Series 200802, Centre for Dynamic Macroeconomic Analysis.
  3. Basak, Suleyman & Chabakauri, Georgy, 2011. "Dynamic Hedging in Incomplete Markets: A Simple Solution," CEPR Discussion Papers 8402, C.E.P.R. Discussion Papers.
  4. Takushi Kurozumi & Willem Van Zandweghe, 2010. "Learning about monetary policy rules when labor market search and matching frictions matter," Research Working Paper RWP 10-14, Federal Reserve Bank of Kansas City.
  5. George Waters, 2011. "Dangers of commitment under rational expectations," Journal of Economics and Finance, Springer, vol. 35(4), pages 371-381, October.

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