Radical Uncertainty and Its Implications for Economics
Editor: Paul Ormerod, University College London and Volterra Partners, London, UK, and David Tuckett, University College London, UK
Should we build a high-speed rail link? When should we expect a motorway system to reach saturation? What will be the local effects of a global trade agreement? When should we restrict credit to prevent a bubble? How can we spot emerging risk and take action to prevent it? When should we abandon particular flood defences? When should the EU permit marketing of particular GM crops, if at all? How should countries respond to epidemics in other countries?
Decisions of this sort involve complex judgments. They are a few typical examples from the inbox of challenges requiring decisions from government, business and society in a globalised world that is more rapidly interconnected and inter-dependent than ever before. The expected outcomes of such decisions are both highly consequential for the development of any economy and deeply uncertain.
For about 60 years decision science (particularly in economics and judgement and decision making research in psychology) has fostered the development of top-down dual process models (including risk models) in which decision-makers can be modelled as calculating machines, optimising subjective expected utility under constraints. Can we think of other ways of proceeding and still produce rigorous models capable of empirically validated prediction?
Contributions addressing how decision-making under radical uncertainty can be studied with a view to incorporating it better into economic thinking are invited from workers in any discipline. Ideally, contributions should not exceed 8,000 words (or word equivalent) in length, though longer ones will not be rejected on these grounds.