We provide an axiomatization of generalized utilitarian social welfare functions in the context of Harsanyi's impartial observer theorem. To do this, we reformulate Harsanyi's problem such that lotteries over identity (accidents of birth) and lotteries over outcomes (life chances) are...

We provide an axiomatization of an additively separable social welfare function in the context of Harsanyi’s impartial observer theorem. To do this, we reformulate Harsanyi’s setting to make the lotteries over the identities the observer may assume independent of the social alternative....

We confront two common objections to Harsanyi's impartial observer theorem; one to do with 'fairness', and the other to do with different individuals' having different attitudes toward risk. Both these objections can be accommodated if we drop the reduction axiom; in particular, if we...

Savage motivated his Sure Thing Principle by arguing that, whenever an act would be preferred if an event obtains and preferred if that event did not obtain, then it should be preferred overall. The idea that it should be possible to decompose and recompose decision problems in this way has...

What is the relationship between an agent's attitude towards information, and her attitude towards risk? If an agent always prefers more information, does this imply that she obeys the independence axiom? We provide a substitution property on preferences that is equivalent to the agent...

We compare the Skiadas approach with the standard Savage framework of choice under uncertainty. At first glance, properties of Skiadas "conditional preferences" such as coherence and disappointment seem analogous to similarly motivated notions of decomposability and disappointment aversion...

We provide necessary and sufficient conditions for a dynamically consistent agent always to prefer more informative signals (in single-agent problems). These conditions do not imply recursivity, reduction or independence. We provide a simple definition of dynamically consistent behavior, and we...