Sources of economic policy uncertainty in the euro area: a ready-to-use database
Andres Azqueta-Gavaldon,
Marina Diakonova,
Corinna Ghirelli and
Javier Pérez
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Marina Diakonova: Banco de España
Corinna Ghirelli: Banco de España
No 2315, Occasional Papers from Banco de España
Abstract:
In this paper, we build a publicly-available database of economic policy uncertainty (EPU) indicators based on the methodology proposed by Azqueta-Gavaldón, Hirschbühl, Onorante and Saiz (2023), which uses topic modelling techniques to identify distinct components of EPU. This database is regularly updated and can be accessed on the Banco de España’s website. Currently, the dataset covers the four largest countries in the euro area, namely Spain, Italy, France, and Germany. Our data coverage is continually expanding to include more euro area countries. Additionally, we compute the aggregated EPU indexes for the euro area. This comprehensive dataset and the resulting euro area indexes provide valuable tools for researchers, policymakers and analysts to assess and monitor the dynamics of economic policy uncertainty in real time.
Keywords: economic policy uncertainty; euro area; machine learning; Latent Dirichlet Allocation; word embeddings (search for similar items in EconPapers)
JEL-codes: D80 E20 E66 G18 (search for similar items in EconPapers)
Pages: 23 pages
Date: 2023-07
New Economics Papers: this item is included in nep-big, nep-cmp and nep-eec
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)
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https://www.bde.es/f/webbe/SES/Secciones/Publicaci ... 23/Files/do2315e.pdf First version, July 2023 (application/pdf)
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Persistent link: https://EconPapers.repec.org/RePEc:bde:opaper:2315
DOI: 10.53479/33155
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