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Fairness in Risky Environments: Theory and Evidence

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  • Silvester Van Koten

    () (Academy of Sciences of the Czech Republic, Economics Institute (EI), P.O. Box 882, Politických vězňů. 7, 111 21 Prague, Czech Republic
    Department of Institutional Economics, University of Economics, Prague, Czech Republic)

  • Andreas Ortmann

    () (Australian School of Business, University of New South Wales, Sydney NSW 2052, Australia)

  • Vitezslav Babicky

    () (Academy of Sciences of the Czech Republic, Economics Institute (EI), P.O. Box 882, Politických vězňů. 7, 111 21 Prague, Czech Republic)

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.

Suggested Citation

  • Silvester Van Koten & Andreas Ortmann & Vitezslav Babicky, 2013. "Fairness in Risky Environments: Theory and Evidence," Games, MDPI, Open Access Journal, vol. 4(2), pages 1-35, May.
  • Handle: RePEc:gam:jgames:v:4:y:2013:i:2:p:208-242:d:26148
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    References listed on IDEAS

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    Cited by:

    1. Alexander W. Cappelen & James Konow & Erik ?. S?rensen & Bertil Tungodden, 2013. "Just Luck: An Experimental Study of Risk-Taking and Fairness," American Economic Review, American Economic Association, vol. 103(4), pages 1398-1413, June.
    2. Richards, Timothy J. & Liaukonyte, Jura & Streletskaya, Nadia A., 2016. "Personalized pricing and price fairness," International Journal of Industrial Organization, Elsevier, vol. 44(C), pages 138-153.
    3. Christoph Engel & Sebastian Goerg, 2015. "If the Worst Comes to the Worst. Dictator Giving When Recipient’s Endowments are Risky," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2015_15, Max Planck Institute for Research on Collective Goods.
    4. Richards, Timothy & Liaukonyte, Jura & Nadia, Streletskya, 2016. "Personalized Pricing and Price Fairness," 2016 Annual Meeting, July 31-August 2, 2016, Boston, Massachusetts 235809, Agricultural and Applied Economics Association.

    More about this item

    Keywords

    fairness; risk aversion; risk; subject-pool effects; economics experiments;

    JEL classification:

    • C - Mathematical and Quantitative Methods
    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • C71 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Cooperative Games
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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