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Collective action in networks : communication, cooperation and redistribution

A person's friends, neighbours and other social relationships can have a large impact on their economic outcomes. We examine three important ways that networks can affect people's lives: when networks describe who they communicate with, who they can trust, and who benefits from their public good provision. We analyse information transmission in networks in a new, intuitive way which removes the problematic redundancy of double counting the signals that travel through more than one walk between nodes. Two-connectedness and cycles of length four play an important role in whether players are `visible', which means that other players can communicate about them. Next, using this approach to network communication, we investigate cooperation and punishment in a society where information flows about cheating are determined by an arbitrary fixed network. We identify which players can trust and cooperate with each other in a repeated game where members of a community are randomly matched in pairs. Our model shows how two aspects of trust depend on players' network position: they are `trusting' if they are more likely to receive information about other players' types; and they are `trusted' if others can communicate about them, giving them strong incentives not to deviate. Lastly, in networks with private provision of public goods, we show that a `neutral' policy corresponds to a switch in the direction of the impact of income redistribution. Where redistribution is non- neutral, we can identify the welfare effects of transfers, including whether or not Pareto-improving transfers are possible. If not, we find the implicit welfare weights of the original equilibrium. In this setting, we also identify a transfer paradox, where, counter-intuitively, a transfer of wealth between economic agents can result in the giver being better off at the new Nash equilibrium, while the recipient is worse off.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:766027
Date January 2017
CreatorsKing, Maia
PublisherQueen Mary, University of London
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://qmro.qmul.ac.uk/xmlui/handle/123456789/30711

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