Author
Abstract
This study examines financial risk profiles across EU Member States, exploring their relationships with financial literacy, financial behavior, education, income, and digital competencies. We utilize data from the Flash Eurobarometer 525, surveying over 26,139 individuals across the EU, and employ cluster analysis based on self-reported financial fragility as a proxy for risk aversion. Statistical methods, including correlation analysis, unifactorial regressions, and t-tests for means, assess the relationships between variables above. The t-tests results highlight significant differences in risk attitudes across quartiles, with higher quartiles (less risk-averse) showing systematically distinct risk profiles. In contrast, the corresponding financial literacy, digital competencies, and financial behavior show limited variation, except for a marginal difference between intermediate quartiles. Education and household income reveal significant disparities primarily in the extreme quartiles, suggesting that economic conditions and educational attainment shape risk preferences. Findings challenge classical economic theories by showing that higher financial literacy correlates with greater risk aversion, while higher education levels align with lower risk aversion. Household income exhibits a moderate negative relationship with risk tolerance. The results underscore the heterogeneity in financial behaviors across the EU, emphasizing the need for tailored financial policies—ranging from risk-mitigating regulations in risk-tolerant clusters to strategies fostering financial market participation in risk-averse ones.
Suggested Citation
Uifalean Razvan, 2025.
"Cluster Analysis of Financial Risk Profiles Across the EU,"
Proceedings of the International Conference on Business Excellence, Sciendo, vol. 19(1), pages 3041-3056.
Handle:
RePEc:vrs:poicbe:v:19:y:2025:i:1:p:3041-3056:n:1016
DOI: 10.2478/picbe-2025-0233
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:poicbe:v:19:y:2025:i:1:p:3041-3056:n:1016. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.