The relationship between bank capitalization and socio-economic development: Evidence from European countries

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Bank capitalization is a key factor in the banking system’s resilience to economic shocks, as outlined in the Basel Accords on banking regulation. The paper aims to empirically evaluate the connection between bank capitalization and the socio-economic development level. The study uses World Bank data across 34 European countries of varying income levels (high, upper-middle, and lower-middle) for the years 2010, 2015, and 2020 as periods of financial and socio-economic turbulence. The study applies principal component analysis and correlation methods to identify relevant indicators. Countries were grouped using hierarchical clustering and K-means clustering methods. The results of the variance analysis revealed that only two indicators of bank capitalization – the share of non-performing loans and return on assets, and three socio-economic indicators – the Gini index, inflation, and unemployment, were statistically significant. As a result of both qualitative and quantitative changes between clusters, countries were reallocated from four clusters in 2010 and 2015 to three clusters by 2020: high-income countries, including Austria, Belgium, Denmark, Ireland, Iceland, Latvia, and others, consolidated into a single stable cluster (Cluster 3) in terms of both bank capitalization and socio-economic development. The primary drivers of inter-cluster movements were the positive dynamics of non-performing loans and bank assets, superior bank capitalization ratios, and improvements in inflation and unemployment levels. Based on the study’s findings, a matrix of transformational sustainability among European countries has been developed. The analysis confirms a relationship between the components of the chain: “level of bank capitalization – level of socio-economic development”.

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    • Figure 1. Dendrograms of clustering of the studied countries by bank capitalization levels and levels of socio-economic development in 2010, 2015, and 2020 using the Ward method
    • Figure 2. Chart of average values of factor indicators for clusters by bank capitalization and level of socio-economic development in 2010 (a), 2015 (b), and 2020 (c)
    • Table 1. Input data
    • Table 2. Correlation matrix
    • Table 3. Principal component analysis results
    • Table 4. Correlation matrix of socio-economic development indicators
    • Table 5. Principal component method outcomes
    • Table 6. Results of analysis of variance for 2010, 2015, and 2020
    • Table 7. Composition of the obtained clusters by the banks’ capitalization level and level of socio-economic development in 2010, 2015, and 2020
    • Table 8. Matrix of transformational resilience of European countries in 2010, 2015, and 2020
    • Funding acquisition
      Anzhela Kuznyetsova, Joanna Koczar
    • Resources
      Anzhela Kuznyetsova, Anton Chub
    • Supervision
      Anzhela Kuznyetsova, Iryna Pozovna
    • Writing – original draft
      Anzhela Kuznyetsova, Alina Yefimenko, Iryna Pozovna, Joanna Koczar, Anton Chub, Olena Dobrovolska, Iryna Panaseyko
    • Writing – review & editing
      Anzhela Kuznyetsova, Alina Yefimenko, Iryna Pozovna, Joanna Koczar, Anton Chub, Olena Dobrovolska, Iryna Panaseyko
    • Conceptualization
      Alina Yefimenko, Iryna Pozovna
    • Data curation
      Alina Yefimenko, Olena Dobrovolska
    • Investigation
      Alina Yefimenko, Olena Dobrovolska, Iryna Panaseyko
    • Methodology
      Alina Yefimenko, Iryna Pozovna
    • Validation
      Alina Yefimenko, Anton Chub
    • Visualization
      Alina Yefimenko, Joanna Koczar, Olena Dobrovolska
    • Formal Analysis
      Iryna Pozovna, Anton Chub, Iryna Panaseyko
    • Project administration
      Joanna Koczar
    • Software
      Olena Dobrovolska, Iryna Panaseyko