Ellsberg paradox: Ambiguity and complexity aversions compared
- 672 Downloads
We present a simple model where preferences with complexity aversion, rather than ambiguity aversion, resolve the Ellsberg paradox. We test our theory using laboratory experiments where subjects choose among lotteries that “range” from a simple risky lottery, through risky but more complex lotteries, to one similar to Ellsberg’s ambiguity urn. Our model ranks lotteries according to their complexity and makes different—at times contrasting—predictions than most models of ambiguity in response to manipulations of prizes. The results support that complexity aversion preferences play an important and separate role from beliefs with ambiguity aversion in explaining behavior under uncertainty.
KeywordsAmbiguity Complexity Compound risk Ellsberg paradox Risk Uncertainty
JEL ClassificationC91 D01 D81
- Abdellaoui, M., Klibanoff, P., & Placido, L. (2011). Ambiguity and compound risk attitudes: an experiment. Mimeo, HEC Paris.Google Scholar
- Chew, S.H., Miao, B., & Zhong, S. (2013). Partial ambiguity. Mimeo, National University of Singapore.Google Scholar
- Dean, M., & Ortoleva, P. (2015). Is it All Connected? A Testing Ground for Unified Theories of Behavioral Economics Phenomena, mimeo: Columbia University.Google Scholar
- Gilboa, I., & Marinacci, M. (2013). Ambiguity and the Bayesian paradigm. In D. Acemoglu, M. Arellano, & E. Dekel (Eds.), Advances in economics and econometrics: theory and applications, 10th World Congress of the Econometric Society. New York: Cambridge University Press.Google Scholar
- Grant, S., Polak, B., & Strzalecki, T. (2009). Second-order expected utility. Mimeo, Harvard University.Google Scholar
- Hill, B. (2011). Confidence and decision. Mimeo, HEC Paris (http://www.hec.fr/hill).
- Savage, L. J. (1954). The foundations of statistics. New York: Wiley.Google Scholar