Do post-corona European economic policies lift growth prospects? Exploring an ML-methodology
- This article explores the determinants of people’s growth prospects in survey data as well as the impact of the European recovery fund to future growth. The focus is on the aftermath of the Corona pandemic, which is a natural limit to the sample size. We use Eurobarometer survey data and macroeconomic variables, such as GDP, unemployment, public deficit, inflation, bond yields, and fiscal spending data. We estimate a variety of panel regression models and develop a new simulation-regression methodology due to limitation of the sample size. We find the major determinant of people’s growth prospect is domestic GDP per capita, while European fiscal aid does not significantly matter. In addition, we exhibit with the simulation-regression method novel scientific insights, significant outcomes, and a policy conclusion alike.
Author of HS Reutlingen | Herzog, Bodo |
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URN: | urn:nbn:de:bsz:rt2-opus4-36348 |
DOI: | https://doi.org/10.3390/jrfm15030120 |
ISSN: | 1911-8066 |
eISSN: | 1911-8074 |
Erschienen in: | Journal of risk and financial management : JRFM |
Publisher: | MDPI |
Place of publication: | Basel |
Document Type: | Journal article |
Language: | English |
Publication year: | 2022 |
Tag: | AI; European Union; Julia programming; data science; growth theory; simulation-regression |
Volume: | 15 |
Issue: | 3 |
Page Number: | 13 |
Article Number: | 120 |
DDC classes: | 650 Management |
Open access?: | Ja |
Licence (German): | Creative Commons - CC BY - Namensnennung 4.0 International |