Subjective Determinants of Attitudes Towards Euro Adoption in Non-Euro Countries. A Machine Learning Approach
DOI:
https://doi.org/10.47743/saeb-2026-0026Keywords:
Euro, machine learning, Eurobarometer, Euro adoption.Abstract
The adoption of the euro is a sensitive topic in the European Union (EU) member states that are not yet part of the Euro Area. Public perceptions and attitudes are influenced not only by objective economic factors, but also by subjective factors, such as the level of trust in institutions, perceptions of prices changes or the mixed feelings about EU. This paper investigates the subjective determinants of attitudes towards euro adoption among EU member states before euro adoption, using an approach based on machine learning algorithms. The analysis is based on Flash Eurobarometer data for 2011–2024 and includes only observations from countries in years before they adopted the euro. The results show that price-related perceptions consistently emerge as the most important predictor of attitudes towards euro adoption, while concerns related to national identity and economic control are also strongly associated with lower levels of support. In addition, self-perceived knowledge about the euro appears to be linked to more favourable attitudes. The study contributes methodologically through the comparative application of machine learning techniques and empirically by identifying the main subjective factors associated with public support for euro adoption in the EU.
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