Logo
Munich Personal RePEc Archive

Collective Learning and Distributive Uncertainty

Ginzburg, Boris (2022): Collective Learning and Distributive Uncertainty.

[thumbnail of MPRA_paper_112780.pdf]
Preview
PDF
MPRA_paper_112780.pdf

Download (418kB) | Preview

Abstract

I study a committee that is considering a costly project whose distributive consequences are unknown. The committee is divided into two factions. Support of both factions is required for the project to be approved. By delaying approval, the committee can gradually learn which faction benefits from the project. I show that a project that gives a lower payoff to everyone is more likely to be approved than a more socially efficient project. Furthermore, the equilibrium amount of learning is excessive, and a deadline on adopting the project is socially optimal in a wide range of settings.

Atom RSS 1.0 RSS 2.0

Contact us: mpra@ub.uni-muenchen.de

This repository has been built using EPrints software.

MPRA is a RePEc service hosted by Logo of the University Library LMU Munich.