Unveiling the Impact of Digital Financial Inclusion and Financial Development on Global Unemployment: A Bayesian Quantile Regression Approach
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This study evaluates the impact of Digital Financial Inclusion (DFI) and Financial Development (FD) on Unemployment (UNE) across 112 countries from 2004 to 2022. Using the Bayesian Quantile Regression (BQR) method, we find that DFI reduces unemployment rates at all quantiles, including 0.1, 0.25, 0.5, 0.75, and 0.9. This result suggests that DFI plays a significant role in lowering unemployment, indicating that digital financial inclusion has a consistent effect across various unemployment levels. In contrast, FD reduces unemployment rates at lower quantiles (0.1 and 0.25) but exacerbates unemployment at higher quantiles (0.5, 0.75, and 0.9). This suggests that while financial development may have a positive impact on reducing unemployment in countries with lower unemployment rates, its effect becomes less favorable or even detrimental in countries with higher unemployment rates. Based on these findings, we recommend that countries focus on expanding DFI to promote broader financial inclusion and address unemployment, rather than emphasizing FD.
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