Ambiguity and uncertainty in Ellsberg and Shackle
Marcello Basili () and
Carlo Zappia ()
Department of Economics University of Siena from Department of Economics, University of Siena
This paper argues that Ellsberg’s and Shackle’s frameworks for discussing the limits of the (subjective) probabilistic approach to decision theory are not as different as they may appear. To stress the common elements in their theories Keynes’s Treatise on Probability provides an essential starting point. Keynes’s rejection of well-defined probability functions, and of maximisation as a guide to human conduct, is shown to imply a reconsideration of what probability theory can encompass, that is in the same vein of Ellsberg’s and Shackle’s concern in the years of the consolidation of Savage’s new probabilistic mainstream. The parallel between Keynes and the two decision theorists is drawn by means of a particular assessment of Shackle’s theory of decision, namely, it is interpreted in the light of Ellsberg’s doctoral dissertation. In this thesis, published only as late as 2001, Ellsberg developed the details and devised the philosophical background of his criticism of Savage as first put forward in the famed 1961 QJE article. The paper discusses the grounds on which the ambiguity surrounding the decision maker in Ellsberg’s urn experiment can be deemed analogous to the uncertainty faced by Shackle’s entrepreneur taking “unique decisions.” The paper argues also that the insights at the basis of the work of both Shackle and Ellsberg, as well as the criteria for decision under uncertainty they put forward, are relevant to understand the development of modern decision theory.
Keywords: uncertainty; weight of argument; non-additive probability (search for similar items in EconPapers)
JEL-codes: B21 D21 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cbe and nep-hpe
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Journal Article: Ambiguity and uncertainty in Ellsberg and Shackle (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:usi:wpaper:460
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