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Indicator Variables for Optimal Policy under Asymmetric Information
Stockholm University, Faculty of Social Sciences, Institute for International Economic Studies.
Princeton University.
2001 (English)Report (Other academic)
Abstract [en]

The optimal weights on indicators in models with partial informatoin about the state of the economy and forward-looking variables are derived and interpreted, both for equilibria under discretion and under commitment. The private sector is assumed to have information about the state of the economy that the policymaker does not possess. Certainty-equivalence is shown to apply, in the sense that optimal policy reactions to optimally estimated states of the economy are independent of the degree of uncertainty. The usual separation principle does not hold, since the estimation of the state of the economy is not independent of optimization and is in general quite complex. We present a general characterization of optimal filtering and control in settings of this kind, and discuss an application of our methods to the problem of the optimal use of "real-time" macroeconomic data in the conduct of monetary policy.

Place, publisher, year, edition, pages
Stockholm: IIES , 2001. , 36 p.
Series
Seminar Paper / Institute for International Economic Studies, Stockholm University. (Online), ISSN 1653-610X
Keyword [en]
Partial information, Kalman filter, monetary policy, discretion and commitment, certainty equivalence, separation policy
National Category
Economics
Identifiers
URN: urn:nbn:se:su:diva-41166OAI: oai:DiVA.org:su-41166DiVA: diva2:328725
Available from: 2010-07-07 Created: 2010-07-06 Last updated: 2016-04-08Bibliographically approved

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Svensson, Lars E.O.
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf