Convexity in multidimensional mechanism design

The present article initiates a systematic study of the behavior of a strictly increasing, C2 , utility function u(a), seen as a function of agents' types, a, when the set of types, A, is a compact, convex subset of iRm . When A is a m-dimensional rectangle it shows that there is a diffeomorphism of A such that the function U = u o H is strictly increasing, C2 , and strictly convexo Moreover, when A is a strictly convex leveI set of a nowhere singular function, there exists a change of coordinates H such that B = H-1(A) is a strictly convex set and U = u o H : B ~ iR is a strictly convex function, as long as a characteristic number of u is smaller than a characteristic number of A. Therefore, a utility function can be assumed convex in agents' types without loss of generality in a wide variety of economic environments.

Integral representation with convex capacities that are squeeze of (additive) probability measures

In this paper I will investigate the conditions under which a convex capacity (or a non-additive probability which exhibts uncertainty aversion) can be represented as a squeeze of a(n) (additive) probability measure associate to an uncertainty aversion function. Then I will present two alternatives forrnulations of the Choquet integral (and I will extend these forrnulations to the Choquet expected utility) in a parametric approach that will enable me to do comparative static exercises over the uncertainty aversion function in an easy way.