Classification of monetary and fiscal dominance regimes using machine learning techniques
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Cited by:
- Heinemann, Friedrich & Kemper, Jan, 2022. "Inflation of objectives instead of focus on inflation? Evidence on the ECB objective function from a textual analysis," ZEW Expert Briefs 22-07, ZEW - Leibniz Centre for European Economic Research.
- Daniel Stempel & Johannes Zahner, 2022. "DSGE Models and Machine Learning: An Application to Monetary Policy in the Euro Area," MAGKS Papers on Economics 202232, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
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More about this item
Keywords
Monetary-fiscal interaction; Machine Learning; Classification; Markov-switching DSGE;All these keywords.
JEL classification:
- C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
- E63 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Comparative or Joint Analysis of Fiscal and Monetary Policy; Stabilization; Treasury Policy
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2020-10-19 (Big Data)
- NEP-CBA-2020-10-19 (Central Banking)
- NEP-CMP-2020-10-19 (Computational Economics)
- NEP-MAC-2020-10-19 (Macroeconomics)
- NEP-MON-2020-10-19 (Monetary Economics)
- NEP-ORE-2020-10-19 (Operations Research)
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