Multilevel IRT models to explore heterogeneity in subjective financial knowledge at individual and regional levels: the Italian case - Fabbricatore, Rosa; Palazzo, Lucio (Frontiers in Applied Mathematics and Statistics, 2023)
Modern FinTech tools (e.g., instant payments, blockchain, roboadvisor) represent the new frontier of digital finance. Consequently, the evaluation of the knowledge level of the population about these topics is a crucial concern. In this context, several exogenous factors may influence individual differences in financial literacy. In particular, the territorial characteristics can have an impact on FinTech. In this work, we investigate individual heterogeneity in subjective financial knowledge in Italy, specifically focusing on modern FinTech tools, and exploring the differences at the individual and regional levels. To this aim, a sample of 598 Italian individuals from 10 different Italian regions was involved. To assess the level of FinTech knowledge, a multilevel IRT model is performed to evaluate the level of FinTech individual knowledge and the differences according to Italian regions to account for the hierarchical structure of the data. Results reported a weak regional effect, revealing that heterogeneity in financial knowledge can be mainly attributed to individual characteristics. At the individual level, age, economic condition, knowledge of traditional financial objects and numeracy showed a significant effect. In addition, a scientific field of study and work have an impact on respondents' knowledge level. What is shown and discussed in this contribution can inspire policymakers' actions to increase financial literacy in the population.