Modeling Supply-Chain and Transport Resilience to Climate Risks: Lessons from Four Regions

Celian Colon and Stephane Hallegatte

No 12950, CESifo Working Paper Series from CESifo

Abstract: Building resilience to natural hazards requires more than identifying critical assets. It requires understanding how supply chains respond to disruptions: where suppliers are located, what inventories firms hold, how diversified their sourcing is, and how products are transported. This paper summarizes key insights from DisruptSC, a spatial agent-based model that jointly represents the transport network and firm-level supply chains, applied to four countries or regions: Tanzania, Cambodia, Ecuador, and the Middle Corridor (Central Asia and South Caucasus). Five policy-relevant findings emerge. First, the duration of a disruption is a primary driver of total economic losses, making fast recovery a crucial lever for risk reduction. Second, the distribution of direct damages across firms and facilities matters as much as the total damages in determining total economic losses. Third, compounding events striking in close succession amplify losses in non-trivial ways, so that individual events cannot be assessed in isolation. Fourth, shorter supply chains do not always increase resilience: they buffer small, frequent disruptions but amplify large ones, reflecting a trade-off between efficiency and resilience that depends on the characteristics of the firm network and the nature of the risks. And fifth, resilience is a network externality—its benefits spill across firms and across borders — so markets under-provide it, and coordinated policy, within and between countries, has a role to play. The paper also illustrates how the model can be used for operational risk assessments or investment prioritization through transport investment stress testing, hotspot identification, and cost-benefit analyses that capture supply chain impacts.

Keywords: supply chains; transport resilience; natural disaster; climate adaptation; criticality; agent-based modeling (search for similar items in EconPapers)
JEL-codes: C63 D57 D85 H54 O18 Q54 R42 (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:ces:ceswps:_12950

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