Erev, Ido, Ert, Eyal, Plonsky, Ori, Cohen, Doron and Cohen, Oded (2017) From anomalies to forecasts : toward a descriptive model of decisions under risk, under ambiguity, and from experience. Psychological Review, 124 (4). pp. 369-409. doi:10.1037/rev0000062 ISSN 0033-295X.

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Abstract

Experimental studies of choice behavior document distinct, and sometimes contradictory, deviations from maximization. For example, people tend to overweight rare events in 1-shot decisions under risk, and to exhibit the opposite bias when they rely on past experience. The common explanations of these results assume that the contradicting anomalies reflect situation-specific processes that involve the weighting of subjective values and the use of simple heuristics. The current article analyzes 14 choice anomalies that have been described by different models, including the Allais, St. Petersburg, and Ellsberg paradoxes, and the reflection effect. Next, it uses a choice prediction competition methodology to clarify the interaction between the different anomalies. It focuses on decisions under risk (known payoff distributions) and under ambiguity (unknown probabilities), with and without feedback concerning the outcomes of past choices. The results demonstrate that it is not necessary to assume situation-specific processes. The distinct anomalies can be captured by assuming high sensitivity to the expected return and 4 additional tendencies: pessimism, bias toward equal weighting, sensitivity to payoff sign, and an effort to minimize the probability of immediate regret. Importantly, feedback increases sensitivity to probability of regret. Simple abstractions of these assumptions, variants of the model Best Estimate and Sampling Tools (BEAST), allow surprisingly accurate ex ante predictions of behavior. Unlike the popular models, BEAST does not assume subjective weighting functions or cognitive shortcuts. Rather, it assumes the use of sampling tools and reliance on small samples, in addition to the estimation of the expected values.

Item Type:	Journal Article
Subjects:	H Social Sciences > HB Economic Theory
Divisions:	Faculty of Social Sciences > Warwick Business School > Behavioural Science Faculty of Social Sciences > Warwick Business School
Library of Congress Subject Headings (LCSH):	Risk -- Mathematical models, Uncertainty -- Mathematical models, Decision making -- Mathematical models
Journal or Publication Title:	Psychological Review
Publisher:	American Psychological Association
ISSN:	0033-295X
Official Date:	July 2017
Dates:	Date Event July 2017 Published 1 July 2017 Available 9 March 2017 Updated 1 April 2017 Accepted
Volume:	124
Number:	4
Page Range:	pp. 369-409
DOI:	10.1037/rev0000062
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Date of first compliant deposit:	5 September 2017
Date of first compliant Open Access:	5 September 2017
Funder:	Israel Science Foundation (ISF)
Grant number:	Grant no. 1821/12, Grant no. 1739/14 (ISF)

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