Brian W. Rogers

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We present a dynamic model of network formation where nodes find other nodes with whom to form links in two ways: some are found uniformly at random, while others are found by searching locally through the current structure of the network (e.g., meeting friends of friends). This combination of meeting processes results in a spectrum of features exhibited by(More)
We explore an equilibrium model of games where behavior is given by logit response functions, but payoff responsiveness and beliefs about others’ responsiveness are heterogeneous. We study two substantively different ways of extending quantal response equilibrium (QRE) to this setting: (1) Heterogeneus QRE, where players share identical correct beliefs(More)
We report experimental results from long sequences of decisions in environments that are theoretically prone to severe information cascades. Observed behavior is much different—information cascades are ephemeral. We study the implications of a model based on quantal response equilibrium, in which the observed cascade formation/collapse/formation cycles(More)
We examine the spread of a disease or behavior through a social network. In particular, we analyze how infection rates depend on the distribution of degrees (numbers of links) among the nodes in the network. We introduce new techniques using firstand second order stochastic dominance relationships of the degree distribution in order to compare infection(More)
We introduce a search-based economic model of network formation. Individuals enter over time and find others at random and through a local search process, and then decide which links to form based on myopic self-interested utility maximization. This model simultaneously accounts for three stylized features of a number of observed large networks: (i)(More)
We model network formation when heterogeneous nodes enter sequentially and form connections through both random meetings and network-based search, but with type-dependent biases. We show that there is “long-run integration,” whereby the composition of types in sufficiently old nodes’ neighborhoods approaches the global type distribution, provided that the(More)
We present a model of network formation where entering nodes find other nodes to link to both completely at random and through search of the neighborhoods of these randomly met nodes. We show that this model exhibits the full spectrum of features that have been found to characterize large socially generated networks. Moreover, we derive the distribution of(More)