Abstract

The rising cost of governance in Nigeria poses significant challenges to the nation’s economic growth and fiscal sustainability. This study investigates the drivers, implications, and optimization strategies for governance costs using a robust data-driven methodology. Quantitative data on public expenditure and economic indicators were collected from reputable institutions, while qualitative insights from policymakers and experts were analyzed. Statistical tools, including regression and time series analysis, were employed to evaluate the relationships between governance costs and economic indicators such as GDP, inflation, and unemployment. Optimization techniques like linear programming and stochastic modeling were utilized to propose cost-efficient governance structures. Findings reveal that GDP significantly influences governance costs, while the effects of inflation and unemployment are less pronounced. The study recommends policy reforms targeting fiscal discipline, streamlined government structures, and enhanced tax efficiency. Additionally, leveraging on artificial intelligence, cloud computing, and advanced technologies can further enhance governance efficiency. These measures aim to reduce governance costs and bolster Nigeria’s economic resilience.