What Can Cognitive Science Say or Learn about Economic Crises

Abstract

What Can Cognitive Science Say or Learn about Economic Crises? *Magda Osman (m.osman@qmul.ac.uk) Experimental Biology and Psychology Centre, Queen Mary University London, London, E14NS, UK *Bjorn Meder (meder@mpib-berlin.mpg.de) Gerd Gigerenzer (gigerenzer@mpib-berlin.mpg.de) Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development, 14195 Berlin, Germany Nick Chater (nick.chater@wbs.ac.uk) Daniel Read (daniel.read@wbs.ac.uk) Warwick Business School, University of Warwick, Coventry, CV4 7AL, UK Hansjorg Neth (hneth@uni-goettingen.de) Department of Psychology, University of Gottingen, Gosslerstr. 14, 37073 Gottingen, Germany Keywords: Cognitive Science, Economics, Decision making, Uncertainty, Behavioral Economics, Rationality, Heuristics Uncertainty can permeate all aspects of a decision problem, from constructing the action space, to inferring probabilities of outcomes and the behavior of other agents in the situation. For instance, politicians need to decide whether to bail out fragile banks and countries under time pressure, with incomplete information about the problem space, and the necessity to manage conflicting goals (e.g., also considering the needs of their won electorate). Turning situations of this kind into lottery type tasks may in fact be a way of translating the unmanageable (uncertainty) into something manageable (risk), but at the same time the evidence may be giving answers to the wrong kind of questions. Additionally, there is an issue of scalability. Neoclassical economics assumes that macro-level behavior can be deduced from modeling agents as rational, utility-maximizing individuals. While this oversimplification is often recognized by economists, scaling up to the aggregate level is a necessity when having to inform policy decision. The crucial challenge in revising the microfoundations of economic behavior is how we can build more realistic models, which nevertheless can be scaled up to the aggregate level. The issue Economic crises bring to the fore deep issues for the economic profession: why are such crises often not foreseen, and what does this entail for economic theory? In this symposium we also adopt a self-critical analysis, by asking the following: what can the cognitive science community say or learn about cognition and behavior in the context of economic crises? After all, cognitive science shares one of its principle objectives with economics: to investigate and model the principles that underlie and govern human behavior. Challenges The current financial crisis presents us with a real- world example of decision making under uncertainty. Cognitive science offers a variety of theories and models, from probabilistic models of cognition (Chater & Oaksford, 2008) to heuristic approaches (Gigerenzer & Gaissmaier, 2011), each designed to describe decision making under uncertainty. Empirically, the extant methods used to examine this question in both economics and psychology involve simple choice tasks (e.g., lotteries and games with well-defined probabilities and outcomes). But, are the models sufficient to accurately represent uncertainty, and are the tools adequate for the job of capturing decision making under uncertainty? Goals of the Symposium The symposium is themed around the target questions: What can our community say or learn about cognition and behavior in economic crises?

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