Determinants of Financial Development Sustainability: Evidence from Saudi Arabia

This study aims to investigate the determinants of financial development and explore the impact of population and GDP on financial development. Annual time series data covering the period from 2000 to 2022 were used, focusing on variables including the number of listed companies (NLC) and bank Z-score (BZS) as financial development indicators, and urban population (UP), rural population (RP), and Gross Domestic Product as determinants. Unit root tests and the Auto Regressive Distributed Lag (ARDL) bound technique are used to find the long-run co-integration relationship of the model. The Vector Error Correction (VEC) technique detects short-run relationships. The stability and reliability of the models are assessed through diagnostic tests, recursive analysis, and dynamic ordinary least squares. Granger causality analysis is employed to examine the causal relationships between the variables. The results indicate that population and GDP significantly affect the NLC and BZS in the long term, and a negative short-term relationship is observed between the financial indicators and explanatory variables. CUSUM and CUSUMSQ plots confirm the effectiveness of the modeling, and DOLS supports the reliability of the ARDL models. Granger causality suggests unidirectional causality from population to NLC and BZS, while NLC and BZS are found to be Granger causes of GDP. Based on the impact of population on financial development, policymakers are recommended to focus on strategies for population growth, including healthcare improvements, education access, and family planning programs. Additionally, diversifying economies, promoting sustainable growth, and implementing favorable economic policies are suggested to enhance financial development. JEL Codes: B26, C01, G21, R23.