English, Article, Journal or magazine article edition: Robust Learning Stability with Operational Monetary Policy Rules George W. Evans; Seppo Honkapohja

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Bookmark: http://trove.nla.gov.au/version/210425
Physical Description
  • preprint
Language
  • English

Edition details

Title
  • Robust Learning Stability with Operational Monetary Policy Rules
Author
  • George W. Evans
  • Seppo Honkapohja
Physical Description
  • preprint
Notes
  • RePEc:san:cdmacp:0808
  • We consider “robust stability” of a rational expectations equilibrium, which we define as stability under discounted (constant gain) least-squares learning, for a range of gain parameters. We find that for operational forms of policy rules, i.e. rules that do not depend on contemporaneous values of endogenous aggregate variables, many interest-rate rules do not exhibit robust stability. We consider a variety of interest-rate rules, including instrument rules, optimal reaction functions under discretion or commitment, and rules that approximate optimal policy under commitment. For some reaction functions we allow for an interest-rate stabilization motive in the policy objective. The expectations-based rules proposed in Evans and Honkapohja (2003, 2006) deliver robust learning stability. In contrast, many proposed alternatives become unstable under learning even at small values of the gain parameter.
  • Commitment, interest-rate setting, adaptive learning, stability, determinacy.
  • RePEc:san:cdmawp:0719
  • We consider robust stability under learning of alternative interest-rate rules. By “robust stability” we mean stability of the rational expectations equilibrium, under discounted (constant gain) least-squares learning, for a range of gain parameters. We find that many interest-rate rules are not robust, in this sense, when operational forms of policy rules are employed. Rules are considered operational if they do not depend on contemporaneous values of endogenous aggregate variables. We consider a variety of interest-rate rules, including instrument rules, optimal reaction functions under discretion or commitment, and rules that approximate optimal policy under commitment. For some of the rules that aim to achieve optimal policy, we allow for an interest-rate stabilization motive in the policy objective. The expectations-based rules proposed in Evans and Honkapohja (2003, 2006) deliver robust learning stability. In contrast, many proposed alternatives become unstable under learning even at small values of the gain parameter.
  • RePEc:chb:bcchwp:504
Language
  • English
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