This study aims to examine the causal relationship between financial development (FD) and economic growth (EG) in 20 developing countries, evaluating the dynamics across multiple time and frequency scales to determine the validity of four key hypotheses: supply-leading, demand-following, feedback and neutrality.
Using monthly data from January 2000 to July 2023, this study uses wavelet transformation (WT) to decompose FD and EG series into multiple scales. A total of 18,000 causality and correlation tests are conducted to explore the interactions between FD and EG under various temporal and frequency contexts.
Results show that 40% of the tests at the level, short-run and business cycle scales reveal no causality, aligning with the neutrality hypothesis. However, in the long run, 60% of cases display strong bidirectional causality, supporting the feedback hypothesis. This indicates a reinforcing relationship between FD and EG, with frequency scales exerting a stronger influence on causality than time scales.
This study focuses on quarterly lag structures because of computational constraints, excluding monthly lags that could offer more granular insights. Future research may expand the frequency decomposition or consider alternative econometric methods to validate the findings.
Policymakers in developing countries should design frequency-sensitive and long-term financial strategies. Strengthening financial institutions, improving regulatory mechanisms and promoting system-wide financial stability are crucial for reinforcing the mutually beneficial relationship between FD and EG.
This study contributes to the finance–growth literature by incorporating both time and frequency domain analyses using a large-scale data set. It challenges the conventional reliance on time-based causality frameworks and offers new insights into the scale-dependent nature of FD–EG linkages in developing economies.
