Does FinTech Amplify Green Finance? Moderating and Heterogeneous Effects on Financial Development

Le résumé fourni par la source

Purpose— This study aims to explore the impact of financial technologies (FT) and green finance (GFN) on financial development (FD). The study also examines the moderating effect of FT in enhancing the contribution of GFN to FD in OECD countries. Study Design/methodology/approach— The study uses principal component analysis (PCA) to create composite indices for GFN and FT. A balanced panel of 26 OECD countries from 2013 to 2022 is analysed. The empirical estimation is conducted by using two steps: System Generalized Method of Moments (GMM), which is suitable for dynamic panel settings having large cross sections and small time periods to address potential endogeneity, unobserved heterogeneity, and persistence in FD. Findings—The empirical results demonstrate that both GFN and FT positively and significantly enhance FD in OECD countries. Specifically, GFN exerts a significantly positive effect on FD (β = 0.052, p < .05), while FT also shows a significant positive contribution (β = 0.033, p < .01). The comparative magnitude of the coefficients suggests that GFN has a relatively stronger direct impact on FD than FT. Furthermore, the interaction term between FT and GFN is positive and statistically significant (β = 0.010, p < .01), indicating that FT strengthens the effectiveness of GFN in promoting FD. A disaggregated analysis of GFN variables confirms the consistency of the empirical results. The heterogeneity investigation reveals that FT and GFN have a greater impact in low-income economies. Moreover, GFN has a more significant impact on low-GFN-adoption countries, while the impact of FT is more significant on low-FT-adoption countries. Practical Implications— The study's findings provide policymakers with insight into how GFN, FT, and their interactions drive FD in OECD economies. Originality/Value— This study contributes to the literature on GFN, FT, and FD by examining their direct and interactive effects in OECD economies. Although previous research has examined the relationships between these constructs, evidence on their combined and moderating effects in a unified panel-data framework is limited. The study builds on previous research by combining GFN and FT in a dynamic panel setting and examining the moderating role of FT across FD. In addition, the introduction of heterogeneity analysis strengthens the policy relevance and contextual understanding of results for the countries in the OECD. The results provide new empirical and policy-relevant evidence on OECD countries and do not provide a new theoretical framework.

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