The Centre’s activities are focused on research in behavioural and experimental economics and on the dynamics of models of learning and adaptation.

Experimental economics has found increasing use in exploring issues such as how people react to different market or auction rules, their choices under differing degrees of uncertainty, and the relative efficiency of alternative market and non-market allocative institutions. Results have been used, for example, to determine allocation of airport ‘slots’, to improve rules of securities exchanges, and to design auctions for awards of communication channels.

Behavioural economics grew out of the interests of market researchers, cognitive scientists and social psychologists. While much of the work is carried out with the use of experiments; behavioural economics studies use a much wider range of research methods. Some of the most prominent findings have been the ones that raised serious questions about traditional behavioural assumptions of economics. Behavioural economics findings are also being used in various applied areas, such as finance and law. They have also been shown to be of importance to environmental issues. These have included demonstrations that people value losses, such as environmental losses, much more than objectively commensurate gains, and weaknesses in current methods of assessing the economic value of environmental changes.

Despite its near universal acceptance, the Rational Expectations Hypothesis continues to be controversial. Many researchers believe that it rests on implausible informational assumptions. As an alternative, models of learning and adaptation have gained in importance over the last decade. These are the models that depart from traditional economic theory and assume bounded rationality of economic agents (in various degrees). Economies are inhabited by heterogeneous, interacting agents who have to learn about their environment and, based on their learning, update their beliefs and strategies, and make economic decisions. The updating of beliefs and the resulting decisions, in turn, affect the economic outcomes. The interactions between agents and economic environment result in, usually, nonlinear self-referential systems with complex and interesting dynamics.

These models have been able to capture some important features of the behavior observed in the experimental laboratories with human subjects that the traditional theory has not been able to account for. In addition, they can explain some of the important empirical facts about the behaviour of economic time series that again the traditional theory could not account for. On the other hand, experimental data can be used to test competing hypotheses and models of agents' learning, and to narrow the class of plausible algorithms. 

Finally, models of learning and adaptation can be used as computer testbeds for a thorough search over the space of parameters that are relevant for the economic model’s performance. Using experiments with human subjects to study these effects is often prohibitively expensive in both monetary and time resources. Thus computer testbeds can provide a valuable tool to study these effects. The results will not only be significant in themselves but they will provide a way to sort out what the most important experiments might be.

Due to the complementarity between experimental economics and behavioural models of learning and adaptation, the field has grown rapidly over the past decade and has attracted considerable interest.