Measuring Loss Aversion under Ambiguity: A Method to Make Prospect Theory Completely Observable
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We propose a simple, parameter-free method that, for the first time, makes it possible to completely observe Tversky and Kahneman’s (1992) prospect theory. While methods exist to measure event weighting and the utility for gains and losses separately, there was no method to measure loss aversion under ambiguity. Our method allows this and thereby it can measure prospect theory’s entire utility function. Consequently, we can properly identify properties of utility and perform new tests of prospect theory. We implemented our method in an experiment and obtained support for prospect theory. Utility was concave for gains and convex for losses and there was substantial loss aversion. Both utility and loss aversion were the same for risk and ambiguity, as assumed by prospect theory, and sign-comonotonic trade-off consistency, the central condition of prospect theory, held.
KeywordsProspect theory Loss aversion Utility for gains and losses Risk Ambiguity Elicitation methods
JEL ClassificationsC91 D03 D81
We gratefully acknowledge helpful comments from Aurélien Baillon, Ferdinand Vieider, Peter P. Wakker, Horst Zank, and an anonymous reviewer and financial support from the Erasmus Research Institute of Management, the Netherlands Organisation for Scientific Research (NWO), the Tinbergen Institute, Rennes Metropole district (AIS_2013), and the Economic and Social Research Council via the Network for Integrated Behavioral Sciences (award n. ES/K002201/1).
- Baltussen, G., Van den Assem, M., & Van Dolder, D. (forthcoming). Risky choice in the limelight. Review of Economics and Statistics.Google Scholar
- Bardsley, N., Cubitt, R., Loomes, G., Moffatt, P., Starmer, C., & Sugden, R. (2010). Experimental economics: Rethinking the rules. Princeton and Oxford: Princeton University Press.Google Scholar
- Bruhin, A., Fehr-Duda, H., & Epper, T. (2010). Risk and rationality: Uncovering heterogeneity in probability distortion. Econometrica, 78, 1372–1412.Google Scholar
- Gaechter, S., Johnson, E. J., & Herrmann, A. (2007). Individual-level loss aversion in risky and riskless choice. IZA Discussion Paper No. 2961.Google Scholar
- Ghirardato, P. & M. Marinacci (2001). Ambiguity Made Precise: A Comparative Foundation, Journal of Economic Theory, 102, 251–289Google Scholar
- Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 159–174.Google Scholar
- Luce, R. D (1991). Rank- and sign-dependent linear utility models for binary gambles. Journal of Economic Theory, 53, 75–100.Google Scholar
- Luce, R. D. (2000). Utility of gains and losses: Measurement-theoretical and experimental approaches. Mahwah, NJ: Lawrence Erlbaum Associates, Inc.Google Scholar
- Vieider, F. M., Cingl, L., Martinsson, P., & Stojic, H. (2013). Separating attitudes towards money from attitudes towards probabilities: Stake effects and ambiguity as a test for prospect theory. WZB Berlin: Working Paper.Google Scholar