Arbeitspapier
Classification of monetary and fiscal dominance regimes using machine learning techniques
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.
- Sprache
-
Englisch
- ISBN
-
978-3-95729-772-3
- Erschienen in
-
Series: Deutsche Bundesbank Discussion Paper ; No. 51/2020
Klassifikation
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
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
Thema
Monetary-fiscal interaction
Machine Learning
Classification
Markov-switching DSGE
Machine Learning
Classification
Markov-switching DSGE
Ereignis
Geistige Schöpfung
(wer)
Hinterlang, Natascha
Hollmayr, Josef
Hollmayr, Josef
Ereignis
Veröffentlichung
(wer)
Deutsche Bundesbank
(wo)
Frankfurt a. M.
(wann)
2020
- Handle
- Letzte Aktualisierung
-
20.09.2024, 08:21 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Hinterlang, Natascha
- Hollmayr, Josef
- Deutsche Bundesbank
Entstanden
- 2020
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