Social interactions and complex networks
AbstractThis paper studies the impact of interaction topologies on individual and aggregate behavior in environments with social interactions. We study social interaction games of an infnitely large population with local and global externalities. Local externalities are limited within agents' ego-networks while the global externality is derived from aggregate distribution in a feedback manner. We consider two forms of heterogeneity, that due to individual intrinsic tastes and that due to ego-networks. The agents know the potential number of other agents they will interact with but do not posses complete information about their neighbors' types and strategies so they base their decisions on expectations and beliefs. We characterize the existence, uniqueness and multiplicity of equilibrium distribution of strategies. By considering arbitrary interaction topologies, we show that the interaction structure greatly determines the uniqueness and multiplicity of equilibrium outcomes, as well as the equilibrium aggregate distribution of strategies as measured by the mean strategy.
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Bibliographic InfoPaper provided by United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT) in its series MERIT Working Papers with number 014.
Date of creation: 2012
Date of revision:
Complex networks; Partial information; Local externality; Global externality; Adoption;
Find related papers by JEL classification:
- C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
- D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
- D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
- O33 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
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