Interacting with complex systems: models and games for a sustainable economy

Abstract

This Report is one of the deliverables of the Global System Dynamics and Policies (GSD) Project (www. globalsystemdynamics.eu) which is coordinated and funded by the Future & Emerging Technologies Division of the European Commission (Work Package 3: Appendix A). Chapter 1 provides an introduction to economic growth models in the context of macro problems such as resource depletion and ecosystem degradation. The first Chapter examines the standard ‘textbook’ models within the larger framework of different worldviews and the various ways in which these models can be improved. In Chapter 2 we provide the reader with an overview of the literature on Complex Systems Science (CSS) in the search for better ‘elementary models for a sustainable economy’ – which was the title used for a workshop held in Utrecht in January 2010 (Appendix B). This overview is in fact biased as it is largely based on the contributions of workshop participants. It contains brief descriptions of economic growth engine models, supply-demand mechanisms at microlevel, evolutionary economics models, generalised utility function formulations, income distribution mechanisms, agent-based models of economic behaviour, energy and knowledge as production factors and the incorporation of catastrophic regime shifts and provision of services in ecosystems. The description of this rapidly growing field is, of course, incomplete. In subsequent chapters we describe some research done in the context of the GSD project. We first report on the SusClime model, which has been used to explore the role of decision making rules in the transition to renewable (noncarbon) energy sources to offset natural resource depletion and climate change. This has led to the use of a model in which utility-maximising strategies are simulated in a world of finite oil reserves and climate change. The utility loss for a competitive strategy (where each region optimises for itself) is compared against a cooperative strategy (where a central planner optimises) and is shown for a set of modelling experiments. Strengthening the science-policy interface is partly a matter of legitimacy – hence the importance of simple, interactive models and simulation games about (the perception of) macro-problems. In the last chapter a brief description is given of an MSc research project done on the perception and behaviour of climate change risks under uncertainty.