Social interactions and complex networks
Daniel Opolot
#2012-014
This 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.
Keywords: Complex networks, Partial information, Local externality,
Global externality, Adoption.
JEL codes: C72, D82, D84, 033