Enterprise AI Analysis

Underlying Structure of the Economic Simulation

The framework is built in Python using the Mesa ABM framework, ensuring modularity and reproducibility. It models a simplified global economic network featuring 100 firms (commodity, manufacturing, retail) and 1000 households, all geolocated on a 0.25-degree resolution grid. Firms employ a Leontief production function and engage in a demand-driven planning cycle, with dynamic wage and price adjustments.

At its core, the hazard-conditional adaptation system allows firms to endogenously respond to perceived climate risks. This adaptation capacity is managed as a 'continuity-capacity' stock, which can be deployed through two distinct strategies, enabling the model to compare their effectiveness.

Illustrative Application Results and Cascade Effects

The simulation under RCP8.5 riverine flooding demonstrates that without adaptation, the economy experiences significant weakening: production falls by 4.9%, consumption by 5.6%, capital by 6.0%, and real wages by 6.4% relative to a no-hazard baseline.

Both adaptation strategies, capital hardening and backup-supplier search, successfully recover approximately 2% of lost production and consumption. However, neither fully restores the baseline, and they achieve their benefits through distinct channels: capital hardening primarily mitigates direct losses, while backup-supplier search focuses on reducing input disruptions.

A crucial finding highlights the importance of indirect cascade effects: roughly 29% of firms are never directly flooded throughout the simulation, yet this subset still accounts for 25–29% of aggregate output and bears 26–36% of the total supplier-disruption burden. This underscores that traditional direct-damage-only assessments significantly underestimate systemic climate risks.

Current Limitations and Roadmap for Expansion

This study serves as a proof of concept using an illustrative economic network of 100 global firms. Consequently, the observed outcomes are illustrative and do not represent predictions of actual economy-wide impacts. The model is not externally calibrated against specific historical data, limiting its immediate applicability for quantitative policy conclusions.

Current scope is limited to acute riverine flooding under RCP8.5 and employs a deliberately simplified abstraction for 'continuity-capacity' which suppresses strategy-specific details like lead times and accounting distinctions.

Future work will focus on external calibration with firm-level or sector-level input-output data, broadening the scope to include additional acute and chronic hazards, and incorporating more granular, empirically-driven models of adaptation lead times and financial mechanisms.