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Erscheinungsjahr: 
2023
Quellenangabe: 
[Journal:] Cogent Economics & Finance [ISSN:] 2332-2039 [Volume:] 11 [Issue:] 1 [Article No.:] 2209951 [Year:] 2023 [Pages:] 1-24
Verlag: 
Taylor & Francis, Abingdon
Zusammenfassung: 
This paper examines the relationship between Federal Reserve policy and the Taylor rule, a commonly used model for guiding monetary policy. The study analyzes the deviation of the actual Federal Funds Rate from the Taylor Rule model during distinct structural changes, using real-time macroeconomic data available to the Fed at the time of their interest rate decision. The research focuses on whether former Fed chair Alan Greenspan's policies from 2003 to 2006, which have been linked to the housing bubble, were deviant from the Taylor Rule. The findings show that there isn't sufficient statistical evidence to support this claim, and a machine learning text analysis of the Federal Open Market Committee transcripts confirms the presence of only one regime during this period. These results contribute to the existing literature on monetary policy and its impact on the economy, providing valuable insights into the relationship between Federal Reserve policy and the Taylor Rule.
Schlagwörter: 
Alan Greenspan
machine learning
monetary policy regimes
Taylor rule
text clustering
JEL: 
E44
E52
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