4th Choice Prediction Competition

ellsberg paradox

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The Department of Environmental Economics and Management

The Robert H. Smith Faculty
of Agriculture, Food and Environment
The Hebrew University of Jerusalem

PO Box 12, Rehovot 76100
Fax: 08-9466267

Department Head:
Prof. Ayal Kimhi, Tel: 08-9489376

Head of the teaching program:
Prof.Iddo Kan, Tel: 08-9489233

Miri Arazi, Tel: 08-9489230

Choice Prediction Competition for Decisions under Risk and Ambiguity

CPC 2015 - Supported by the Max Wertheimer Minerva Center
for Cognitive Processing and Human Performance

Organized by: Ido Erev, Eyal Ert, and Ori Plonsky

4th Choice Prediction Competition:

Decisions under Risk and Ambiguity


Experimental studies of human choice behavior have documented clear violations of rational economic theory and triggered the development of behavioral economics. Yet, the impact of these careful studies on applied economic analyses, and policy decisions, is not large. One justification for the tendency to ignore the experimental evidence involves the assertion that the behavioral literature highlights contradicting deviations from maximization, and it is not easy to predict which deviation is likely to be more important in specific situations. To address this problem Kahneman and Tversky (1979) proposed a model (Prospect theory) that captures the joint effect of four of the most important deviations from maximization: the certainty effect (Allais paradox, Allais, 1953), the reflection effect, overweighting of low probability extreme events, and loss aversion (see top four rows in Table 1). The current paper extends this and similar efforts (see e.g., Thaler & Johnson, 1990; Brandstätter, Gigerenzer, & Hertwig, 2006; Birnbaum, 2008; Wakker, 2010; Erev et al., 2010) by facilitating the derivation and comparison of models that capture the joint impact of the four "prospect theory effects" and ten additional phenomena (see Table 1). These choice phenomena were replicated under one "standard" setting (Hertwig & Ortmann, 2001): choice with real stakes in a space of experimental tasks wide enough to replicate all the phenomena illustrated in Table 1. The results suggest that all 14 phenomena emerge in our setting. Yet, their magnitude tends to be smaller than their magnitude in the original demonstrations. The current choice prediction competition focuses on developing models that can capture all of these phenomena but also predict behavior in other choice problems. To calibrate the models we ran an “estimation set” study that included 60, randomly selected, choice problems.