Monte Carlo simulation-based financial risk identification for industrial estate as post-mining land usage in Indonesia

Abstract

The issue of post-mining land usage is emerging in Indonesia due to the significant contribution of the mining industry to the country's economic development. Among the popular options for utilizing these lands is the establishment of industrial estates. The objective of this study is to investigate the complexities associated with identifying financial risks using an integrated framework to be implemented in industrial estates located on post-mining lands in Indonesia. The framework was constructed by combining traditional feasibility study methods with Monte Carlo simulation. The financial model was built using 31 input variables (assumptions) and 3 output variables (forecasts). The Monte Carlo simulation results revealed that there is an approximately 82.32% probability of the project's payback period being within 25 years, and a 94.23% probability of a positive net present value. Three input variables were found to contribute to 80% of the variation in average earnings. Additionally, five variables were identified as financial risk factors impacting net present value and discounted payback period. Out of the thirteen financial risk factors, ten were internal factors that require a management plan to mitigate them effectively. The framework contributed an emphasize on the importance of risk analysis as complementary analysis in a feasibility study.