Calendrier du 17 mars 2016
RISK Working Group
Du 17/03/2016 de 17:00 à 18:15
Campus jourdan,Bâtiment A, Rez de chaussée, Salle 4
CRAINICH David (IESEG)
Saving and the demand for protection against risk
écrit avec Co-author : Richard Peter
TOM (Théorie, Organisation et Marchés) Lunch Seminar
Du 17/03/2016 de 12:30 à 14:30
Campus jourdan,Bâtiment E, Rez de chaussée, Salle 101
BONNET Celine(Toulouse School of Economics, INRAE)
GEEROLF François(UCLA)
Information Design: The Random Posterior Approach (1)
(1)Information affects behavior by affecting beliefs. Information design studies how to disclose information to a group of players to incentivize them to behave in a desired way. This paper is a theoretical investigation of information design, culminating with a representation theorem and a fundamental application of it. We adopt a random posterior perspective, viewing information design as belief manipulation rather than information disclosure. The representation theorem shows that it is as if the designer manipulated beliefs in a specific way, shaping the approach in games, as did Kamenica and Gentzkow (2011) in one-agent problems. The representation theorem can also be implemented in specific problems, for example in the beauty contest and multiple-agent problems. We focus on an application that we dub the Mother's Problem.
(joint with J. Perego and I. Taneva)
(2)This paper shows that Pareto distributions can arise from production functions rather than from the distribution of primitives. A version of Garicano (2000)’s knowledge-based production hierarchies microfounds such a production function. It generates under very limited assumptions on the distribution of primitives (here, agents’ skills), Pareto distributions for span of control of CEOs as well as intermediary managers, and in particular Zipf’s law for firm sizes when the number of layers of management becomes large. This breakdown of the aggregate firm size distribution receives important empirical support in the French matched employer-employee administrative data. This novel justification of Pareto distributions can shed a new light on why outcomes are often so out of proportion compared to underlying primitives. For example, it provides a framework to study the recent rise in top income inequality. The analysis also has striking implications on the literature on firm heterogeneity: Pareto distributions are in fact the benchmark distributions arising in the case of perfect homogeneity, while heterogeneity in primitives should instead be backed out in the deviations from Pareto distributions.