# The descriptive and predictive adequacy of theories of decision making under uncertainty/ambiguity

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## Abstract

In this paper we examine the performance of theories of decision making under uncertainty/ambiguity from the perspective of their descriptive and predictive power. To this end, we employ an innovative experimental design which enables us to reproduce ambiguity in the laboratory in a transparent and non-probabilistic way. We find that judging theories on the basis of their theoretical appeal, or on their ability to do well in terms of estimation, is not the same as judging them on the basis of their predictive power. We find that the models that perform better in an aggregate sense are Gilboa and Schmeidler’s MaxMin and MaxMax Expected Utility Models, and Ghiradarto et al.’s Alpha Model, implying that more elegant theoretical models do not perform as well as relatively simple models. This suggests that decision-makers, when confronted with a difficult problem, try to simplify it, rather than apply a sophisticated decision rule.

## Keywords

Ambiguity Bingo blower Choquet expected utility Decision field theory Decision making (Subjective) expected utility (Gilboa and Schmeidler) MaxMin EU (Gilboa and Schmeidler) MaxMax EU (Ghirardato) alpha model MaxMin MaxMax Minimum regret Prospect theory Uncertainty## JEL Classifications

D81 C91## References

- Ahn, D., Choi, S., Gale, D. & Kariv, S. (2007). Estimating ambiguity aversion in a portfolio choice problem, research paper, http://www.nyu.edu/econ/user/galed/papers.html
- Busemeyer, J., & Townsend, J. (1993). Decision field theory: A dynamic-cognitive approach to decision making in an uncertain environment.
*Psychological Review, 100*, 432–459.CrossRefGoogle Scholar - Choquet, G. (1955). Theory of capacities.
*Annales de L’institut Fourier (Grenoble), 5*, 131–295.Google Scholar - Ellsberg, D. (1961). Risk, ambiguity and the Savage axioms.
*Quarterly Journal of Economics, 75*, 643–669.CrossRefGoogle Scholar - Fox, C. R., & Tversky, A. (1995). Ambiguity aversion and comparative ignorance.
*Quarterly Journal of Economics, 110*, 585–603.CrossRefGoogle Scholar - Ghirardato, P., Maccheroni, F., & Marinacci, M. (2004). Differentiating ambiguity and ambiguity attitude.
*Journal of Economic Theory, 118*, 133–173.CrossRefGoogle Scholar - Gilboa, I., & Schmeidler, D. (1989). Maxmin expected utility with a non-unique prior.
*Journal of Mathematical Economics, 18*, 141–153.CrossRefGoogle Scholar - Greiner, B. (2004) The online recruitment system ORSEE 2.0 — A guide for the organization of experiments in economics, University of Cologne Discussion Paper (www.orsee.org).
- Halevy, Y. (2007). Ellsberg revisited: An experimental study.
*Econometrica, 75*, 503–536.CrossRefGoogle Scholar - Hey, J. D., & Lee, J. (2005). Do subjects separate (or are they sophisticated)?
*Experimental Economics, 8*, 233–265.CrossRefGoogle Scholar - Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk.
*Econometrica, 47*, 263–291.CrossRefGoogle Scholar - Klibanoff, P., Marinacci, M., & Mukerji, S. (2005). A smooth model of decision making under ambiguity.
*Econometrica, 73*, 1849–1892.CrossRefGoogle Scholar - Luce, R. D., & Raiffa, H. (1957).
*Games and decisions*. New York: Wiley.Google Scholar - Moffatt, P. G., & Peters, S. A. (2001). Testing for the presence of a tremble in economic experiments.
*Experimental Economics, 4*, 221–228.Google Scholar - Savage, L. J. (1951). The theory of statistical decision.
*Journal of the American Statistical Association, 46*, 55–67.CrossRefGoogle Scholar - Savage, L. J. (1954).
*Foundations of statistics*. New York: Wiley.Google Scholar - Segal, U. (1987). The Ellsberg Paradox and risk aversion: An anticipated utility approach.
*International Economic Review, 28*, 175–202.CrossRefGoogle Scholar - Stoye, J. (2008).
*Axioms for minimax regret choice correspondences*. Working Paper: New York University.Google Scholar - Vuong, Q. (1989). Likelihood ratio tests for model selection and non-nested hypotheses.
*Econometrica, 57*, 307–333.CrossRefGoogle Scholar - Wilcox, N. (2008). Stochastic models for binary discrete choice under risk: A critical primer and econometric comparison. In J. C. Cox & G. W. Harrison (Eds.),
*Research in experimental economics vol. 12: Risk aversion in experiments*(pp. 197–292). Bingley: Emerald.CrossRefGoogle Scholar - Wilcox, N. (2009). Stochastically more risk averse: A contextual theory of stochastic discrete choice under risk.
*Journal of Econometrics*, corrected proof, available online.Google Scholar