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A Nexus Between Financial Development and its Determinants; A Panel Data Analysis From A Global Perspective

Bilal Ashraf, Qianxiao Zhang, Naveed Aslam, Touqeer Ahmad

Abstract



In this era of globalization, the importance of financial sector growth in economic development procedures is not to be disregarded for economies with high and low incomes, globally. The adoption of ICT-based technology improvements raised and optimized capital accumulation decreased information asymmetry, encouraged and mobilized savings, and supported the economy's current account balance, contributing to the financial sector development's ability to accelerate economic development. This study empirically investigated the linkage amid financial development and its important determinants such as information and communication technology (ICT), natural resource rents (NRR), economic growth (EG), current account balance (CAB), and gross savings (S) in 107 economies worldwide. This paper preferred to employ the second-generation unit root tests to handle the issues of slope heterogeneity and “cross-sectional dependence” in panel data. The results of “Kao, Pedroni, and Westerlund tests” confirm the long-lasting connections among the variables under study, while the significant endings of “cross-sectionally augmented autoregressive distributed lag (CS-ARDL)” exposed that NRR, CAB, and S negatively affected the financial development while ICT and EG stimulates the procedure of FD. Further, the robustness analysis's application of "Feasible Generalized Least Squares (FGLS)" further supports the appropriateness and applicability of CS-ARDL. Finally, the findings of “Dumitrescu-Hurlin causality analysis” endorse the bidirectional causality linkages amongst research factors. Based on the study's empirical outcomes, we suggest some effective policy suggestions that empower the process of financial development to boost the overall economic well-being, globally.

Keywords


Determinants of financial developments, CS-ARDL, financial development, global sample, Causality analysis

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