Economic policy uncertainty in the euro area: an unsupervised machine learning approach
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Note: 2460732
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Cited by:
- Saiz, Lorena & Ashwin, Julian & Kalamara, Eleni, 2021. "Nowcasting euro area GDP with news sentiment: a tale of two crises," Working Paper Series 2616, European Central Bank.
- Diana Petrova & Pavel Trunin, 2023. "Estimation of Economic Policy Uncertainty," Russian Journal of Money and Finance, Bank of Russia, vol. 82(3), pages 48-61, September.
- Pablo Garcia, 2021. "Learning, expectations and monetary policy," BCL working papers 153, Central Bank of Luxembourg.
- Liosi, Konstantina, 2023. "The sources of economic uncertainty: Evidence from eurozone markets," Journal of Multinational Financial Management, Elsevier, vol. 69(C).
- de Lucio, Juan & Mora-Sanguinetti, Juan S., 2022. "Drafting “better regulation”: The economic cost of regulatory complexity," Journal of Policy Modeling, Elsevier, vol. 44(1), pages 163-183.
- Hauzenberger, Niko & Pfarrhofer, Michael & Stelzer, Anna, 2021.
"On the effectiveness of the European Central Bank’s conventional and unconventional policies under uncertainty,"
Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 822-845.
- Niko Hauzenberger & Michael Pfarrhofer & Anna Stelzer, 2020. "On the effectiveness of the European Central Bank's conventional and unconventional policies under uncertainty," Papers 2011.14424, arXiv.org.
- Quelhas, João, 2022. "Monetary Policy Uncertainty and its impact on the real economy: Empirical Evidence from the Euro area," MPRA Paper 113621, University Library of Munich, Germany, revised May 2022.
- Juan de Lucio & Juan S. Mora-Sanguinetti, 2021. "New dimensions of regulatory complexity and their economic cost. An analysis using text mining," Working Papers 2107, Banco de España.
- Roman Valovic & Daniel Pastorek, 2023. "A Robustness Analysis of Newspaper-based Indices," MENDELU Working Papers in Business and Economics 2023-89, Mendel University in Brno, Faculty of Business and Economics.
- Ademmer, Martin & Beckmann, Joscha & Bode, Eckhardt & Boysen-Hogrefe, Jens & Funke, Manuel & Hauber, Philipp & Heidland, Tobias & Hinz, Julian & Jannsen, Nils & Kooths, Stefan & Söder, Mareike & Stame, 2021. "Big Data in der makroökonomischen Analyse," Kieler Beiträge zur Wirtschaftspolitik 32, Kiel Institute for the World Economy (IfW Kiel).
- Charemza, Wojciech & Makarova, Svetlana & Rybiński, Krzysztof, 2022. "Economic uncertainty and natural language processing; The case of Russia," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 546-562.
More about this item
Keywords
economic policy uncertainty; Europe; machine learning; textual-data;All these keywords.
JEL classification:
- C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
- D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
- E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
- E66 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General Outlook and Conditions
- G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
- G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2020-02-03 (Big Data)
- NEP-CMP-2020-02-03 (Computational Economics)
- NEP-EEC-2020-02-03 (European Economics)
- NEP-MAC-2020-02-03 (Macroeconomics)
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