Implementing new strategies to mitigate the impacts of climate change may influence an economy’s vulnerability to natural disasters. It is thus important to develop mechanisms for evaluating the impact of these changes prior to their implementation. Recent works have demonstrated the effectiveness of inoperability input–output models in assessing the impact of natural disasters on interconnected economic systems. This study develops a multi-criteria framework that measures the vulnerability of economic sectors by considering plausible disaster scenarios and the resulting “ripple effects” of such disruptions. The approach proposed here uses three metrics: average propagation length, economic loss, and inoperability. The model then uses the analytic hierarchy process to measure the importance of each component in a hierarchical framework to derive a composite vulnerability index. The method is used to assess the implications of implementing the mandatory bioethanol blending program in Vietnam, using cassava and sugarcane as bioethanol feedstocks. The disaster scenarios assessed include the incidence of typhoons, floods, and pest infestation. Results show that the cassava, sugarcane, and other manufacturing sectors are the key economic sectors which are most affected by these disasters. Furthermore, sensitivity analysis on different bioethanol blend rates indicates that a 5 % bioethanol blend policy does not significantly affect Vietnam’s economy, while raising the blend to 10 % bioethanol or more may considerably change the country’s economic structure and disaster vulnerability.