Based on a critique on econometric and DSGE models (in particular in the context of the financial crisis), Doyne Farmer presents his current research programme that aims at building an agent-based model of the financial and economic crisis. It models heterogeneous agents and from there simulates the economy, firstly for the housing market. The interview gives a short insight in the research programme.

Diese Vorlesung gibt einen ersten Einblick in die Komplexitätsökonomie.

Antoine Godin gives a bright, illustrated, introduction to agent-based, stock-flow-consistent modeling, with a clear focus on the agent-based aspect.

One method of economic modelling that has become increasingly popular in academia, government and the private sector is Agent Based Models, or ABM. These simulate the actions and interactions of thousands or even millions of people to try to understand the economy – for this reason ABM was once described to me as being “like Sim City without the graphics”. One advantage of ABM is that it is flexible, since you can choose how many agents there are (an agent just means some kind of 'economic decision maker' like a firm, consumer, worker or government); how they behave (do they use complicated or simple rules to make decisions?); as well as the environment they act in, then just run the simulation and see what happens as they interact over time.

This article considers the strengths of agent-based modelling and the ways that it can be used to help central banks understand the economy. These models provide a complement to more traditional economic modelling which has been criticised in the wake of the Great Recession.

Eine erfolgreiche Wirtschaftstransformation hängt von einer Veränderung der ökonomischen Praktiken der Akteure ab. Die „Spirale transformativen Lernens“ identifiziert, welche Fähigkeiten dafür entscheidend sind.