Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/98571 
Year of Publication: 
2013
Citation: 
[Journal:] Games [ISSN:] 2073-4336 [Volume:] 4 [Issue:] 2 [Publisher:] MDPI [Place:] Basel [Year:] 2013 [Pages:] 208-242
Publisher: 
MDPI, Basel
Abstract: 
The relationship between risk in the environment, risk aversion and inequality aversion is not well understood. Theories of fairness have typically assumed that pie sizes are known ex-ante. Pie sizes are, however, rarely known ex ante. Using two simple allocation problems-the Dictator and Ultimatum game-we explore whether, and how exactly, unknown pie sizes with varying degrees of risk ('endowment risk') influence individual behavior. We derive theoretical predictions for these games using utility functions that capture additively separable constant relative risk aversion and inequity aversion. We experimentally test the theoretical predictions using two subject pools: students of Czech Technical University and employees of Prague City Hall. We find that: (1) Those who are more risk-averse are also more inequality-averse in the Dictator game (and also in the Ultimatum game but there not statistically significantly so) in that they give more; (2) Using the within-subject feature of our design, and in line with our theoretical prediction, varying risk does not influence behavior in the Dictator game, but does so in the Ultimatum game (contradicting our theoretical prediction for that game); (3) Using the within-subject feature of our design, subjects tend to make inconsistent decisions across games; this is true on the level of individuals as well as in the aggregate. This latter finding contradicts the evidence in Blanco et al. (2011); (4) There are no subject-pool differences once we control for the elicited risk attitude and demographic variables that we collect.
Subjects: 
fairness
risk aversion
risk
subject-pool effects
economics experiments
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
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