The environmental economics community is aware that “there are thousands of people involved, including prime ministers and bureaucrats [...]; entrepreneurs and inventors [...]; carbon market analysts, brokers, and bankers [...]; CEOs developing their carbon strategies; engineers in the control room changing the order in which electricity generation plants come on stream” (Convery 2009). The diversity of these interacting agents and their relevant properties (type of preferences and strategies; amount of information and market power; attitude towards risk; degree of rationality, farsightedness, and cooperation; etc.) motivates to interpret carbon markets as interacting complex networks of agents that can be studied not only with game-theoretic and statistical methods but also using agent-based modelling and concepts from statistical physics.
The MOCAP workshop brought together leading experts from the different scientific communities mentioned above to discuss the various ways of modelling the most central policy-relevant question in emissions trading: the formation of carbon prices. To fully understand this, one might need a “close feedback between simulation, testing, data collection and the development of theory. This demands [...] multi-disciplinary collaboration among economists, computer scientists [...] and physical scientists with experience in large-scale modelling.” (Farmer and Foley 2009).
What features, processes, and phenomena distinguish carbon markets from other markets? Which dynamic and strategic trajectories or equilibria of what type can be expected to result on different time-scales? What are the policy implications of this?