## 4 Results
Moreover, the Ramsey RESET test results (Table 12) confirm the robustness of the estimated models, indicating that the inclusion of non-linearities does not significantly alter the findings. The quantile slope equality tests and symmetric quantiles tests suggest the presence of heterogeneous effects across different levels of banking performance, reinforcing the necessity of adopting a quantile-based approach to understanding financial determinants in the EU banking sector. In the broader EU context, these findings highlight the importance of digitalization, innovation, and human capital investment in enhancing banking performance. While digital inclusion is consistently beneficial across all quantiles, the challenges associated with implementing digital transformation strategies underscore the need for careful planning and execution. Additionally, the persistent negative effect of banking employment suggests \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Test** & \multicolumn{1}{c}{**Chi-Sq. Stat.**} & **Chi-Sq. d.f.** & \(p\)**-Value** \\ \hline \multirow{4}{*}{Ramsey RESET Test (QLR L-statistic)} & (Tau = 0.25) & 7.933586 & 1 & 0.0049 \\  & (Tau = 0.50) & 20.25475 & 1 & 0.0000 \\  & (Tau = 0.75) & 8.617398 & 1 & 0.0033 \\  & (Tau = 0.90) & 1.240242 & 1 & 0.2654 \\ \hline \multirow{4}{*}{\
\begin{tabular}{c} Quantile Slope Equality Test \\ (Wald Test) \\ \end{tabular} } & (Tau = 0.25) & 77.26342 & 20 & 0.0000 \\  & (Tau = 0.50) & 77.26342 & 20 & 0.0000 \\  & (Tau = 0.75) & 77.26342 & 20 & 0.0000 \\  & (Tau = 0.90) & 84.31933 & 30 & 0.0000 \\ \hline \multirow{4}{*}{
\begin{tabular}{c} Symmetric Quantiles Test (Wald Test) \\ \end{tabular} } & (Tau = 0.25) & 29.69842 & 11 & 0.0018 \\  & (Tau = 0.50) & 29.69842 & 11 & 0.0018 \\ \cline{1-1}  & (Tau = 0.75) & 29.69842 & 11 & 0.0018 \\ \cline{1-1}  & (Tau = 0.90) & 105.6690 & 22 & 0.0000 \\ \hline \end{tabular} Source: Author’s own calculation.  
\end{table} 
Table 12: Ramsey RESET tests, quantile slope equality test and symmetric quantiles test. that efficiency improvements in employment structures remain an important consideration for policymakers and financial regulators within the EU. Ultimately, the MMQR results underscore the heterogeneous nature of banking performance in the European banking sector and the significant role of digital and financial innovation in shaping long-term profitability. The application of the MMQR (Method of Moments Quantile Regression) methodology allows for a nuanced examination of financial and technological indicators across European Union countries. By considering the varying effects of independent variables at different quantiles of the dependent variable's distribution, MMQR captures heterogeneity that traditional regression methods may overlook. In the context of EU countries, this approach is particularly insightful given the diverse economic structures, digital inclusion levels, and banking performance metrics that characterize the region. When analyzing return on equity (ROE) through the MMQR framework, significant differences emerge across EU member states. Countries such as Romania and Hungary demonstrate higher ROE values, particularly in upper quantiles, suggesting that banks in these economies experience stronger profitability dynamics under favorable conditions. Conversely, Germany and France, despite their economic size and stability, exhibit lower ROE values, particularly in lower quantiles, indicating potential structural constraints on profitability. This disparity may stem from differences in banking sector efficiency, capital allocation, and digital adaptation, which influence banking performance across the quantile spectrum. Digital inclusion and technological integration emerge as key determinants of financial outcomes, with varying impacts depending on the level of digitalization. Countries such as Denmark, Finland, and Estonia, characterized by high digital inclusion and strong E-banking penetration, show more consistent and stable banking performance across quantiles.