Publication | Closed Access
The Rich Domain of Uncertainty: Source Functions and Their Experimental Implementation
545
Citations
71
References
2011
Year
EngineeringBehavioral Decision MakingUncertain DataUncertain ReasoningUncertainty FormalismUncertainty ModelingUncertain EventsUncertainty QuantificationDeep UncertaintyBiasRisk ManagementExperimental EconomicsDecision TheoryApproximation TheoryStatisticsSubjective ProbabilitiesSource MethodEconomicsBehavioral SciencesHigh UncertaintyProbability TheoryBehavioral EconomicsTheir Experimental ImplementationSource FunctionsBusinessStatistical InferenceUncertainty ManagementDecision ScienceRich Domain
We often deal with uncertain events for which no probabilities are known. Several normative models have been proposed. Descriptive studies have usually been qualitative, or they estimated ambiguity aversion through one single number. This paper introduces the source method, a tractable method for quantitatively analyzing uncertainty empirically. The theoretical key is the distinction between different sources of uncertainty, within which subjective (choice-based) probabilities can still be defined. Source functions convert those subjective probabilities into willingness to bet. We apply our method in an experiment, where we do not commit to particular ambiguity attitudes but let the data speak. (JEL D81)
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