An empirical evaluation of Prelec's compound invariant functions as models of probability weighting in prospect theory

Prospect theory, which proposes both reference-dependent utilityand probability weighting, has proved to be the most successful ofseveral approaches to generalising nonnative expected utility theory. It has been widely adopted in the social sciences to explain risk behaviour, with applications rangi...

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Bibliographic Details
Main Author: Wickham, Philip Arthur
Published: University of Leeds 2006
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Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.486090
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Summary:Prospect theory, which proposes both reference-dependent utilityand probability weighting, has proved to be the most successful ofseveral approaches to generalising nonnative expected utility theory. It has been widely adopted in the social sciences to explain risk behaviour, with applications ranging from infrahuman, pre-industrial, financial, corporate and political decision-making. This wide, and growing, range of applications demands effective econometric analysis ofthe prospect theoretical framework. A major advance has been Prelec's approach using a weak consistency condition known as compound invariance (Cn as an axiomatic basis for developing exponential functions that describe probability weighting. Combined .with a standardly adopted constant relative risk aversion (CRRA) utility function this leads to a CI+CRRA model. Prelec proposl?s two versions ofthis model, one in which probability weighting is described by two (a probability sensitivity and a probability attractiveness) parameter and a one-parameter version in which the probability attractiveness parameter is axiomatically eliminated. One mathematical convenience ofthis version ofthe model is that it may be linearised via a double log transfonnation to provide risk decision descriptive parameters from the plot's intercept ~d gradient of certainty equivalence ~aluations. The research uses standard laboratory gambles (under - , varied incentive and problem presentation conditions) as the basis oftesting this model and the predictions ofprospect theory relating to risk attitude, pattern ofprobability weighting, gain-loss risk attitude reflection, four-fold inversion ofrisk attitude, loss aversion and framing effects. The research, involving over 12,000 individual prospect valuations generally finds strongly for prospect theory predictions. However, the two-parameter version of the CI+CRRA model performs far better as a predictor ofsubjects' prospect valuation than the one-parameter version. This is largely due to the increasing subadditivity ofvaluation as outcome value increases. Consequently the results draw into question the multiplicative assumption in prospect theory that outcome value and probability weighting are psychometrically independent. The dissertation concludes with considerations on how the model might be developed and applied to ecological risk decision-making studies in the future.