Classification of monetary and fiscal dominance regimes using machine learning techniques

Arbeitspapier

This paper identifies U.S. monetary and fiscal dominance regimes using machine learning techniques. The algorithms are trained and verified by employing simulated data from Markov-switching DSGE models, before they classify regimes from 1968-2017 using actual U.S. data. All machine learning methods outperform a standard logistic regression concerning the simulated data. Among those the Boosted Ensemble Trees classifier yields the best results. We find clear evidence of fiscal dominance before Volcker. Monetary dominance is detected between 1984-1988, before a fiscally led regime turns up around the stock market crash lasting until 1994. Until the beginning of the new century, monetary dominance is established, while the more recent evidence following the financial crisis is mixed with a tendency towards fiscal dominance.

Object Details

• ISBN: 978-3-95729-772-3
• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Deutsche Bundesbank Discussion Paper ; No. 51/2020

Classification and Topics

• Classification: Wirtschaft ; Multiple or Simultaneous Equation Models: Classification Methods; Cluster Analysis; Principal Components; Factor Models ; Price Level; Inflation; Deflation ; Comparative or Joint Analysis of Fiscal and Monetary Policy; Stabilization; Treasury Policy
• Subject: Monetary-fiscal interaction ; Machine Learning ; Classification ; Markov-switching DSGE

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Hinterlang, Natascha ; Hollmayr, Josef
• Event: Veröffentlichung
• (who): Deutsche Bundesbank
• (where): Frankfurt a. M.
• (when): 2020

Further information

• Handle: http://hdl.handle.net/10419/224929
• Last update: 10.03.2025, 11:44 AM CET