Updating ambiguity averse preferences
Full Bayesian updating, going back to contributions by Fagin and Halpern (1991) and Jaffray (1992), was axiomatized for general capacities by Eichberger et al.
Maximum-likelihood updating (MLU) is a well-known approach for extending static ambiguity sensitive preferences to dynamic set-ups.This paper demonstrates that MLU, both in the strict and the generalized form, gives rise to the switch in betting preferences surrounding risky and ambiguous urns.The deeper reason is that MLU does not respect set inclusion stability over the course of the updating process. Section 2 presents the simple example in which exante and ex-post betting preferences are surprisingly unaligned. Apart from a white and a black ball, each urn contains a third ball that is either black or white.Alternatively, you can download the file locally and open with any standalone PDF reader: https://link.springer.com/content/pdf/10.1007/s11238-017-9611-2Ambiguity aversion under maximum-likelihood updating Daniel Heyen 0 0 Grantham Research Institute, London School of Economics , London , UK Maximum-likelihood updating (MLU) is a well-known approach for extending static ambiguity sensitive preferences to dynamic set-ups.Rather, it results from MLU's selection of extreme priors, causing a violation of the stability of set inclusion over the course of the updating process.