Modelling the costs of natural disasters (earthquakes, floods and wildfires)

Abstract

This study investigated the cost-effectiveness of various mitigation and adaptation strategies for reducing the economic impact of natural disasters on a nation. Utilizing Indonesia as a case study, I employed probabilistic models and Monte Carlo simulations to predict future losses from earthquakes, floods and wildfires. This approach mirrored the risk assessment practices of insurance companies, leveraging historical disaster data to reproduce past loss patterns in specific regions. JMP statistical software facilitated the analysis generating estimates that empower policymakers to implement the most cost-effective measures for minimizing economic disruption. The discussions analyse these strategies to identify the most effective ones for reducing the financial burden.