Modelling Cascading Physical Climate Risk in Supply Chains with Adaptive Firms: A Spatial Agent-Based Framework

Yara Mohajerani

Papers from arXiv.org

Abstract: We present an open-source Python framework for modelling cascading physical climate risk in a spatial supply-chain economy. The framework integrates geospatial flood hazards with an agent-based model of firms and households, enabling simulation of both direct asset losses and indirect disruptions propagated through economic networks. Firms adapt endogenously through two channels: capital hardening, which reduces direct damage, and backup-supplier search, which mitigates input disruptions. In an illustrative global network, capital hardening reduces direct losses by 26%, while backup-supplier search reduces supplier disruption by 48%, with both partially stabilizing production and consumption. Notably, firms that are never directly flooded still bear a substantial share of disruption, highlighting the importance of indirect cascade effects. The framework provides a reproducible platform for analyzing systemic physical climate risk and adaptation in economic networks.

Date: 2025-09, Revised 2026-04
New Economics Papers: this item is included in nep-env, nep-evo and nep-hme
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