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Risk aversion and framing effects

Published online by Cambridge University Press:  14 March 2025

Louis Lévy-Garboua*
Affiliation:
Paris School of Economics, Centre d'Economie de la Sorbonne, Université Paris 1 Panthéon-Sorbonne, Paris, France CIRANO, Montreal, Canada
Hela Maafi*
Affiliation:
Paris School of Economics, Centre d'Economie de la Sorbonne, Université Paris 1 Panthéon-Sorbonne, Paris, France GREGHEC-HEC School of Management, Paris, France
David Masclet*
Affiliation:
CIRANO, Montreal, Canada CNRS-CREM-University of Rennes 1, Rennes, France
Antoine Terracol*
Affiliation:
Paris School of Economics, Centre d'Economie de la Sorbonne, Université Paris 1 Panthéon-Sorbonne, Paris, France

Abstract

We present a new experimental evidence of how framing affects decisions in the context of a lottery choice experiment for measuring risk aversion. We investigate framing effects by replicating the Holt and Laury's (Am. Econ. Rev. 92:1644-1655, 2002) procedure for measuring risk aversion under various frames. We first examine treatments where participants are confronted with the 10 decisions to be made either simultaneously or sequentially. The second treatment variable is the order of appearance of the ten lottery pairs. Probabilities of winning are ranked either in increasing, decreasing, or in random order. Lastly, payoffs were increased by a factor of ten in additional treatments. The rate of inconsistencies was significantly higher in sequential than in simultaneous treatment, in increasing and random than in decreasing treatment. Both experience and salient incentives induce a dramatic decrease in inconsistent behaviors. On the other hand, risk aversion was significantly higher in sequential than in simultaneous treatment, in decreasing and random than in increasing treatment, in high than in low payoff condition. These findings suggest that subjects use available information which has no value for normative theories, like throwing a glance at the whole connected set of pairwise choices before making each decision in a connected set of lottery pairs.

Type
Original Paper
Copyright
Copyright © 2011 Economic Science Association

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References

Allais, M. (1953). Le comportement de l'homme rationnel devant le risque: critique des postulats et axiomes de l'ecole américaine. Econometrica, 21, 503546.CrossRefGoogle Scholar
Blavatskyy, P. R. (2007). Stochastic expected utility theory. Journal of Risk and Uncertainty, 34, 259286.CrossRefGoogle Scholar
Blavatskyy, P. R. (2010). A model of probabilistic choice satisfying first-order stochastic dominance. Management Science, 57, 542548.CrossRefGoogle Scholar
Camerer, C. (1989). An experimental test of several generalized utility theories. Journal of Risk and Uncertainty, 2, 61104.CrossRefGoogle Scholar
Chew, S., Epstein, L., & Segal, U. (1991). Mixture symmetry and quadratic utility. Econometrica, 59, 139163.CrossRefGoogle Scholar
Fechner, G. (1860). Elements of psychophysics. New York: Holt, Rinehart and Winston.Google Scholar
Fischbacher, U. (2007). z-Tree: Zurich toolbox for ready-made economic experiments. Experimental Economics, 10(2), 171178.CrossRefGoogle Scholar
Harrison, G. W., Johnson, E., McInnes, M. M., & Rutström, E. E. (2005). Risk aversion and incentive effects: comment. American Economic Review, 95, 897901.CrossRefGoogle Scholar
Hey, J. D., & Orme, C. (1994). Investigating generalizations of expected utility theory using experimental data. Econometrica, 62, 12911326.CrossRefGoogle Scholar
Holt, C. A., & Laury, S. K. (2002). Risk aversion and incentive effects. American Economic Review, 92, 16441655.CrossRefGoogle Scholar
Kahneman, D., & Tversky, A. (1984). Choices, values, and frames. American Psychologist, 39(4), 341350.CrossRefGoogle Scholar
Laury, S. K. (2005). Pay one or pay all: random selection of one choice for payment. Andrew Young School of Policy Studies Research Paper Series, No. 06-13.CrossRefGoogle Scholar
Loomes, G. (2005). Modelling the stochastic component of ehaviour in experiments: some issues for the interpretation of data. Experimental Economics, 8, 301323.CrossRefGoogle Scholar
Loomes, G., & Sugden, R. (1998). Testing different stochastic specifications of risky choice. Economica, 65, 581598.CrossRefGoogle Scholar
Loomes, G., Moffatt, P.G., & Sugden, R. (2002). Microeconometric test of alternative stochastic theories of risky choice. Journal of Risk and Uncertainty, 24, 103130.CrossRefGoogle Scholar
Masclet, D., Colombier, N., Denant-Boemont, L., & Loheac, Y (2009). Group and individual risk preferences: a lottery-choice experiment with self-employed and salaried workers. Journal of Economic Behavior and Organization, 70, 470484.CrossRefGoogle Scholar
Starmer, C. (2000). Developments in non-expected utility theory: the hunt for a descriptive theory of choice under risk. Journal of Economic Literature, 38, 332382.CrossRefGoogle Scholar
Starmer, Ch., & Sugden, R. (1989). Probability and juxtaposition effects: an experimental investigation of the common ratio effect. Journal of Risk and Uncertainty, 2, 159178.CrossRefGoogle Scholar
Tversky, A., & Kahneman, D. (1981). The framing of decision and the psychology of choice. Science, 211, 453458.CrossRefGoogle ScholarPubMed
Tversky, A., & Kahneman, D. (1986). Rational choice and the framing of decisions. Journal of Business, 59, 251278.CrossRefGoogle Scholar
Wu, G. (1994). An empirical test of ordinal independence. Journal of Risk and Uncertainty, 9, 3960.CrossRefGoogle Scholar