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Coupling of regional infrastructure damage prediction and macro-economic modeling to estimate local socioeconomic impacts of disasters

Graduate Researcher(s): 
Maryia Markhvida (
Faculty Advisor/PI: 
Jack Baker
Stephane Hallegatte (World Bank), Brian Walsh (World Bank)
Project Sponsor: 
UPS Endowment at Stanford University

This research aims to quantify the effect of earthquakes on the Bay Area industries, unemployment and the households' well being at both regional and local levels, in order to identify areas of socioeconomic vulnerability. This requires understanding physical damage from an earthquake and how the damage in turn affects industries’ production, interindustry supply, employment, households and their consumption during the recovery. To quantify socioeconomic metrics during the recovery, the proposed research will combine engineering risk analysis, macro-economic and micro-economic modeling integrating spatial infrastructure and socioeconomic data. The goal is to investigate the hypothesis that some geographical regions and socioeconomic groups are disproportionately affected during disaster recovery.

Disasters cause two types of economic losses. Direct losses are associated with the cost of infrastructure repair and reconstruction. Indirect losses result from business interruption and decreased output caused by lost production capacity, supply constraints, and demand changes. In large earthquakes, indirect losses can greatly exceed direct losses, dramatically amplifying the consequences. Reduction in output also causes temporary and permanent unemployment. Since unemployment following a disaster varies across geographic regions and socioeconomic groups, it creates a differential vulnerability to disasters. Areas with lower income also see their well-being more affected by asset losses and unemployment.

Modeling indirect losses and the impacts of earthquakes on economic wellbeing is challenging as it requires integration of complex processes such as earthquake hazard analysis, simulation of regional infrastructure damage, incorporation of post-disaster dynamics of the local economy, and modeling of the downstream effect on the population. Current research on urban disasters thus does not integrate the whole process from start to end. This project integrates  the seismic risk analysis that quantifies direct losses with a macro-economic model and socioeconomic impact assessment. The findings from this study will help inform risk mitigation strategies across different socioeconomic groups at both regional and local levels.