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  4. Beware of black swans: Taking stock of the description–experience gap in decision under uncertainty

Beware of black swans: Taking stock of the description–experience gap in decision under uncertainty

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Author(s)
de Palma, André
•
Abdellaoui, Mohammed
•
Attanasi, Giuseppe
•
Erev, Ido
•
Fehr-Duda, Helga
•
Fok, Dennis
•
Fox, Craig R.
•
Hertwig, Ralph
•
Picard, Nathalie
•
Wakker, Peter P
more
Date Issued
July 2014
Journal
Marketing Letters
Publisher
Springer US
Citation
de Palma, André et al. “Beware of Black Swans: Taking Stock of the Description–experience Gap in Decision under Uncertainty.” Marketing Letters 25.3 (2014): 269–280.
Version
Author's final manuscript
Abstract
Uncertainty pervades most aspects of life. From selecting a new technology to choosing a career, decision makers rarely know in advance the exact outcomes of their decisions. Whereas the consequences of decisions in standard decision theory are explicitly described (the decision from description (DFD) paradigm), the consequences of decisions in the recent decision from experience (DFE) paradigm are learned from experience. In DFD, decision makers typically overrespond to rare events. That is, rare events have more impact on decisions than their objective probabilities warrant (overweighting). In DFE, decision makers typically exhibit the opposite pattern, underresponding to rare events. That is, rare events may have less impact on decisions than their objective probabilities warrant (underweighting). In extreme cases, rare events are completely neglected, a pattern known as the “Black Swan effect.” This contrast between DFD and DFE is known as a description–experience gap. In this paper, we discuss several tentative interpretations arising from our interdisciplinary examination of this gap. First, while a source of underweighting of rare events in DFE may be sampling error, we observe that a robust description–experience gap remains when these factors are not at play. Second, the residual description–experience gap is not only about experience per se but also about the way in which information concerning the probability distribution over the outcomes is learned in DFE. Econometric error theories may reveal that different assumed error structures in DFD and DFE also contribute to the gap.
MIT Department
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
http://creativecommons.org/licenses/by-nc-sa/4.0/
Persistent DSpace Link
http://hdl.handle.net/1721.1/105459
DOI of Published Version
https://doi.org/10.1007/s11002-014-9316-z
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