Assessing Shock Propagation and Cascading Uncertainties Using the Input–Output Framework: Analysis of an Oil Refinery Accident in Singapore

Abstract

The impacts of shock events frequently cascade beyond the primarily affected sector(s), through the interdependent economic system, and result in higher-order indirect losses in other sectors. This study employed the inoperability input–output model (IIM) and the dynamic IIM (DIIM) to model recovery of sectors after a shock event and quantify associated total losses. Considering data limitations and uncertainties regarding sectoral recovery time, a key variable in DIIM, a probabilistic approach is used for modelling uncertainty in recovery times. The event analyzed is the 2011 oil refinery fire accident in Pulau Bukom (PB) island, Singapore, which caused the refinery to shut down for 11 days and be partially operational for several days thereafter. The impacts are assessed using the regrouped 15-sector Singapore IO data of year 2010, with manufacturing sector as the directly affected sector. The initial economic impact of the PB refinery fire is assessed in the top-down framework using the refinery’s contribution to the manufacturing sector and nation’s GDP. The higher-order losses are quantified considering different recovery paths for the directly affected sector and accounting for its inventory. Simulation experiments using synthetic IO tables are also carried out to understand relationship between recovery characteristics of directly and indirectly affected sectors. The results from IIM analysis show that the indirect losses are about 35–38% of direct losses. The DIIM analysis reveal that the utilities sectors (e.g., electricity, water supply and treatment) suffer the largest inoperability among indirectly affected sectors for a given direct damage to the manufacturing sector. The results also illustrate the dependence of overall losses on the recovery path of the directly affected sector, and associated uncertainties in sectoral recovery times.