The Large Space of Information Structures
Abstract
We revisit the question of modeling incomplete information among 2 Bayesian players, following an ex-ante approach based on values of zero-sum games. being the finite set of possible parameters, an information structure is defined as a probability distribution with finite support over with the interpretation that: is publicly known by the players, is selected according to , then (resp. ) is announced to player 1 (resp. player 2). Given a payoff structure , composed of matrix games indexed by the state, the value of the incomplete information game defined by and is denoted . We evaluate the pseudo-distance between 2 information structures and by the supremum of for all with payoffs in , and study the metric space of equivalent information structures. We first provide a tractable characterization of , as the minimal distance between 2 polytopes, and recover the characterization of Peski (2008) for , generalizing to 2 players Blackwell's comparison of experiments via garblings. We then show that , endowed with a weak distance , is homeomorphic to the set of consistent probabilities with finite support over the universal belief space of Mertens and Zamir. Finally we show the existence of a sequence of information structures, where players acquire more and more information, and of such that any two elements of the sequence have distance at least : having more and more information may lead now here. As a consequence, the completion of is not compact, hence not homeomorphic to the set of consistent probabilities over the states of the world {\it \`a la} Mertens and Zamir. This example answers by the negative the second (and last unsolved) of the three problems posed by J.F. Mertens in his paper ``Repeated Games", ICM 1986.
Keywords
Cite
@article{arxiv.1904.00875,
title = {The Large Space of Information Structures},
author = {Fabien Gensbittel and Marcin Peski and Jérôme Renault},
journal= {arXiv preprint arXiv:1904.00875},
year = {2019}
}