Bank-Specific as Basis of Banking Sector Development: An ARDL Approach

Abstract

This study aims to examine the bank-specific factors and banking sector development in Nepal by using the ARDL approach technique with economic time series data ranging from 1995 to 2020. The study employed the Autoregressive Distributed Lag (ARDL) model to avoid the spurious regression problem in the construction of contemporary time series econometrics. The study depends on the co-integration analysis to find out the long-run equilibrium relationship among the variables of the model. Banking sector development is measured by the arithmetic average of the normalized values of banking depth, banking efficiency, and banking stability. This study reveals that banking trade has positive and significant influenced the banking sector development in line with theoretical predictions. Electronic banking and liquidity have a positive and statistically significant role to explain banking sector development in Nepal. In addition, it demonstrates that non-performing loans has a negatively and significantly influenced banking sector development whilst branch network has a marginally negative but insignificant impact on banking sector development. This study reveals implications for policymakers as it sheds light on the importance of raising deposits and lending policies and focused on electronic banking. The authorities of a financial institution should be implied to build systems and skills in liquidity management, assets and liability management, and branch networking management to enhance the banking sector's development.

Financial health and economic growth responsiveness as solution to environmental degradation in Pakistan

“…where ECM shows the error correction of the short-run coefficients, which reflects the adjustment speed of the coefficients into long-run cointegration, and is the error term. Furthermore, the stability and reliability of the models are checked by CUSUM and CUSUMSQ as well as through residual diagnostics and Ramsey RESET (Gwachha 2023 ; Ojaghlou et al 2023 ; Razmi and Razmi 2023 ).…”