A multidimensional analysis of corporate governance mechanisms and their impact on sustainable economic development: A case study of Ghana's financial sector

Heliyon. 2024 Jan 23;10(3):e24673. doi: 10.1016/j.heliyon.2024.e24673. eCollection 2024 Feb 15.

Abstract

Efficiency remains pivotal to the banking sector, serving as a linchpin for resource allocation and competitive prowess. This study delves into the intricate dynamics between corporate governance and banking efficiency in Ghana, with an analytical lens on cost efficiency (CE) and total efficiency (TE). Utilizing Data Envelopment Analysis (DEA), our investigation spans over a decade (2008-2019) and encompasses a data set of 23 Ghanaian banks. The study findings unveils that rigorous corporate governance mechanisms, as quantified by the Corporate Governance Index (CGI), exert a salutary influence on both cost and total efficiencies. Moreover, a well-defined Risk Management Index (RMI) positively correlates with cost efficiency, albeit without a substantial impact on total efficiency. Conversely, the study identifies a counterintuitive effect: the current make-up of supervisory boards, as gauged by the Supervisory Board Index (SBI), inversely impacts both efficiency metrics, signaling sub-optimal governance structures. Significantly, the research also highlights a pressing concern: the average total efficiency of Ghanaian banks lags behind the global benchmarks prescribed by the World Bank. This discrepancy underscores an exigency for efficiency optimization within the sector. The study thereby offers invaluable insights for multiple stakeholders-including regulatory bodies, investment communities, and policymakers-by delineating the governance variables that can enhance or impede banking efficiency. It also identifies actionable avenues for improvement, specifically in the realms of risk management and board composition, with the potential to catalyze a transformation in Ghana's banking landscape.

Keywords: Bank efficiency; Corporate governance; Cost and technical efficiency; Data envelopment analysis.