This paper argues that a representation of the epistemic state of the individual through a non-additive measure provides a novel account of Keynes’s view of probability theory proposed in the Treatise on Probability. The paper shows, first, that Keynes’s “non-numerical” probabilities can be interpreted in terms of decision weights and distortions of the probability priors. Second, it is argued that the degree of non-additivity of the probability measure can account for the confidence in a probability assessment without any reference to a second order probability, as suggested by Keynes’s notion of “weight of argument”. And, third, it is identified a criterion for decision making under uncertainty developed in the non-additive literature that incorporates a measure of the degree of confidence in the probability assessment. The paper aims to substantiate the view, put forward in a recent paper in this journal, that Keynes’s analysis of uncertainty has continuing relevance to decision theory and can provide the foundations for a theory of decision making under uncertainty that is arguably more general than subjective expected utility theory.
Basili, M., Zappia, C. (2009). Keynes's "non-numerical" probabilities and non-additive measures. JOURNAL OF ECONOMIC PSYCHOLOGY, 30, 419-430 [10.1016/j.joep.2008.11.003].
Keynes's "non-numerical" probabilities and non-additive measures.
BASILI, MARCELLO;ZAPPIA, CARLO
2009-01-01
Abstract
This paper argues that a representation of the epistemic state of the individual through a non-additive measure provides a novel account of Keynes’s view of probability theory proposed in the Treatise on Probability. The paper shows, first, that Keynes’s “non-numerical” probabilities can be interpreted in terms of decision weights and distortions of the probability priors. Second, it is argued that the degree of non-additivity of the probability measure can account for the confidence in a probability assessment without any reference to a second order probability, as suggested by Keynes’s notion of “weight of argument”. And, third, it is identified a criterion for decision making under uncertainty developed in the non-additive literature that incorporates a measure of the degree of confidence in the probability assessment. The paper aims to substantiate the view, put forward in a recent paper in this journal, that Keynes’s analysis of uncertainty has continuing relevance to decision theory and can provide the foundations for a theory of decision making under uncertainty that is arguably more general than subjective expected utility theory.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/20381
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