Government Effectiveness in the Petroleum Sector: Two-step Analysis Combining Linear Regression and Artificial Neural Networks

Abstract Background and Purpose To encourage petroleum industry development, a country needs to set up a regulatory framework that standardizes investment conditions. The objective of the research was to investigate the determinants of government effectiveness in the petroleum sector. Design/Methodology/Approach Multiple regression analysis was conducted to investigate if government effectiveness in the petroleum sector is influenced by the country’s political stability, regulatory quality, the intensity of petroleum exploration and production activities, government take, and type of contract used. Artificial neural network analysis was additionally conducted to identify the importance of independent variables. Results Political stability, regulatory quality, government take attractiveness, and the intensity of petroleum activities positively influence government effectiveness. A more attractive government take enhances effectiveness, while the type of contract for awarding petroleum rights did not significantly impact effectiveness. Artificial neural network analysis revealed that the most important variables were regulatory quality and political stability. Conclusion The research concluded that political stability, regulatory quality, and the intensity of petroleum activities are key factors in enhancing government effectiveness in the petroleum sector. These findings have practical implications, as they emphasize the importance of stable and well-regulated environments for achieving higher government effectiveness in the petroleum industry. This equips policymakers and industry professionals with actionable insights for improving the sector’s performance.