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  Incomplete-Information Games in Large Populations with Anonymity

Hellwig, M. F. (2019). Incomplete-Information Games in Large Populations with Anonymity.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0005-1DB7-D Version Permalink: http://hdl.handle.net/21.11116/0000-0005-1DB8-C
Genre: Paper

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 Creators:
Hellwig, Martin F.1, Author              
Affiliations:
1Max Planck Institute for Research on Collective Goods, Max Planck Society, ou_2173688              

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Free keywords: Incomplete-information games, large populations, belief functions, common priors, exchangeability, conditional independence, conditional exact law of large numbers
 JEL: C70 - General
 JEL: D82 - Asymmetric and Private Information; Mechanism Design
 JEL: D83 - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
 Abstract: The paper provides mathematical foundations for modelling strategic interdependence with a continuum of agents where uncertainty has an aggregate component and an agent-specific component and the latter satis.es a conditional law of large numbers. This decomposition of uncertainty is implied by a condition of anonymity in beliefs, under which the agent in question considers the other agents. types to be essentially pairwise exchangeable. If there is also anonymity in payoff functions, all strategically relevant aspects of beliefs are contained in an agent’s macro beliefs about the cross-section distribution of the other agents’ types. The paper also gives conditions under which a function assigning macro beliefs to types is compatible with the existence of a common prior.

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 Dates: 2019-11-15
 Publication Status: Published online
 Pages: -
 Publishing info: Bonn : Max Planck Institute for Research on Collective Goods, Discussion Paper 2019/14
 Table of Contents: -
 Rev. Method: -
 Identifiers: Other: 2019/14
 Degree: -

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