| Date | 22 March 2022, Tuesday |
| Time | 4:00 pm - 5:30 pm (Hong Kong time, GMT +8) |
| Speaker |
Prof. Ilia M. Tsetlin Professor of Decision Sciences, INSEAD |
| Online Registration |
https://lingnan.au1.qualtrics.com/jfe/form/SV_3C1BttmeK0x6cXY |
Abstract
Co-authors: Jingyuan Li, Fan Wang
Knightian uncertainty (aka ambiguity), where it is not easy to assign precise probabilities to different outcomes, has a long tradition in decision theory with abound theoretical and empirical work. However, this literature is rather vague on the distinction between known and unknown probabilities, especially in a realistic scenario (as opposed to an artificial/laboratory setting). We suggest the notion of a verifiable lottery, which is equivalent to a classical one (based on a symmetry of the outcomes). Then we develop an axiomatic framework that yields preference representations similar to a smooth ambiguity model, but with a clear distinction between verifiable (objective) and non-verifiable (subjective) probabilities. One powerful illustration is preferences over income profiles under the veil of ignorance. We also discuss broader implications for normative and descriptive decision making.
Biography of speaker
|
Prof. Ilia M. Tsetlin Professor of Decision Sciences, INSEAD |
Professor Ilia M. Tsetlin is Professor of Decision Sciences at INSEAD. His teaching and research interests are in modeling decisions under uncertainty, with particular focus on decision making with multiple attributes, target-based and contest-based settings, and situations with background risk. Other research streams are related to negotiation, auction theory, and collective choice. His work has been published in a number of academic journals including Management Science, Operations Research, Journal of Risk and Uncertainty, Journal of Economic Theory, Games and Economic Behavior, and Social Choice and Welfare. Professor Ilia is currently serving as a Department Editor in Management Science.
|
