Inflation targeting under imperfect knowledge

Athanasios Orphanides and John Williams

No 2006-14, Working Paper Series from Federal Reserve Bank of San Francisco

Abstract: A central tenet of inflation targeting is that establishing and maintaining well-anchored inflation expectations are essential. In this paper, we reexamine the role of key elements of the inflation targeting framework towards this end, in the context of an economy where economic agents have an imperfect understanding of the macroeconomic landscape within which the public forms expectations and policymakers must formulate and implement monetary policy. Using an estimated model of the U.S. economy, we show that monetary policy rules that would perform well under the assumption of rational expectations can perform very poorly when we introduce imperfect knowledge. We then examine the performance of an easily implemented policy rule that incorporates three key characteristics of inflation targeting: transparency, commitment to maintaining price stability, and close monitoring of inflation expectations, and find that all three play an important role in assuring its success. Our analysis suggests that simple difference rules in the spirit of Knut Wicksell excel at tethering inflation expectations to the central bank's goal and in so doing achieve superior stabilization of inflation and economic activity in an environment of imperfect knowledge.

Keywords: Inflation (Finance); Monetary policy; Econometric models (search for similar items in EconPapers)
Date: 2006
New Economics Papers: this item is included in nep-cba, nep-mac and nep-mon
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Citations: View citations in EconPapers (13)

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Related works:
Chapter: Inflation Targeting under Imperfect Knowledge (2007)
Journal Article: Inflation targeting under imperfect knowledge (2007)
Working Paper: Inflation Targeting Under Imperfect Knowledge (2006)
Working Paper: Inflation Targeting under Imperfect Knowledge (2006)
Working Paper: Inflation targeting under imperfect knowledge (2006)
Working Paper: Inflation Targeting under Imperfect Knowledge (2006)
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