In my thesis I investigate the higher-order economic losses and damages due to extreme weather events along the global supply network. I (co-)developed the Acclimate model, which I use to study the resilience of the global supply system. My particular focus in that is the identification of possibilities and limits of global adaptation strategies under different warming scenarios.
Acclimate simulates the spreading of production losses induced by local demand, supply, or price shocks in the global supply network. It assumes an agent-based approach with representative firms (or regional sectors) and consumers as economic agents. These are the nodes in a complex network of trade and supply relations which is built-up from empirical input-output data providing the unperturbed baseline state. Its global economy is assumed to be demand-driven. By forming explicit expectations on the future demand of their purchasers and the supply capabilities of their suppliers, in each daily timestep, each economic agent individually decides upon its optimal production level and its distribution of demand among its suppliers by maximizing its future expected profit. In order to capture the spreading of supply failures resulting from local production disruptions (e.g. due to climate extremes) in the global supply network, the model accounts for the most important short-term economic flexibilities: transport and storage inventories buffering supply shocks and idle production capacities that can be activated in times of high demand. The model temporally resolves short-term disequilibrium situations arising in the shock aftermath due to supply and demand mismatches and describes the relaxation of these perturbations back to the baseline equilibrium over a time scale determined by the market.
Being based on local optimization principles, the model accounts for local price effects such as demand surge which are important for an comprehensive assessment of the total costs of disasters. Overall, Acclimate tries to strike a balance between the high flexibility of equilibrium models and the high rigidity of input- output models. Currently the model incorporates around 5,000 agents and is used to determine the direct and indirect losses due to unanticipated extreme weather events.
The current version was developed by Sven Willner and Christian Otto, early versions by Robert Bierkandt, Leonie Wenz and Sven Willner.A detailed description is given in:
You can find some software I wrote on my GitHub account. Here is an excerpt.
Agent-based model for loss-propagation in the global supply-chain network using optimization based on local, limited information as basis for agent decisions.
A short description is given above.
The implementation of only the two earlier, simpler model versions can be found in another GitHub repository.
C++-Implementation of the DICE Dynamic Integrated Climate-Economy Model of the Economics of Global Warming by W. Nordhaus.
Python interface for the simple global climate carbon-cycle model Hector. It makes Hector easily installable and usable from Python and can for example be used in the analysis of mitigation scenarios, in integrated assessment models, complex climate model emulation, and uncertainty analyses.