Ramsey games with giants

The classical result in the theory of random graphs, proved by Erdos and Renyi in 1960, concerns the threshold for the appearance of the giant component in the random graph process. We consider a variant of this problem, with a Ramsey flavor. Now, each random edge that arrives in the sequence of rounds must be colored with one of R colors. The goal can be either to create a giant component in every color class, or alternatively, to avoid it in every color. One can analyze the offline or online setting for this problem. In this paper, we consider all these variants and provide nontrivial upper and lower bounds; in certain cases (like online avoidance) the obtained bounds are asymptotically tight.Comment: 29 pages; minor revision

Behavioral Communities and the Atomic Structure of Networks

We develop a theory of `behavioral communities' and the `atomic structure' of networks. We define atoms to be groups of agents whose behaviors always match each other in a set of coordination games played on the network. This provides a microfoundation for a method of detecting communities in social and economic networks. We provide theoretical results characterizing such behavior-based communities and atomic structures and discussing their properties in large random networks. We also provide an algorithm for identifying behavioral communities. We discuss applications including: a method of estimating underlying preferences by observing behavioral conventions in data, and optimally seeding diffusion processes when there are peer interactions and homophily. We illustrate the techniques with applications to high school friendship networks and rural village networks

Truth, trust, and sanctions: On institutional selection in sender-receiver games

We conduct a laboratory experiment to investigate the impact of institutions and institutional choice on truth-telling and trust in sender-receiver games. We find that in an institution with sanctioning opportunities, receivers sanction predominantly after having trusted lies. Individuals who sanction are responsible for truth-telling beyond standard equilibrium predictions and are more likely to choose the sanctioning institution. Sanctioning and non-sanctioning institutions coexist if their choice is endogenous and the former shows a higher level of truth-telling but lower material payoffs. It is shown that our experimental findings are consistent with the equilibrium analysis of a logit agent quantal response equilibrium with two distinct groups of individuals: one consisting of subjects who perceive non-monetary lying costs as senders and non-monetary costs when being lied to as receivers and one consisting of payoff maximizers.Experiment, Sender-receiver games, Strategic information transmission, Institutional selection

The Emergence of Local Norms in Networks

We develop an explanation of the emergence of local norms, and the associated phenom- enon of geographical variation in behavior. Individuals are assumed to interact locally with neighbors in an environment with a network externality. Although many patterns of behavior are possible, the dispersed interactive choices of agents are shown to select behavior that is locally uniform but globally diverse. The range of applications of the theory includes regional variation in the practice of medicine, technology choice, and corruption. The framework is also useful for further developing our understanding of important phenomena like lock-in, critical thresholds, and contagionSocial norms, networks, geographical variation

Constrained Interactions and Social Coordination

We consider a co-evolutionary model of social coordination and network formation whereagents may decide on an action in a 2 x 2- coordination game and on whom to establish costly links to. We find that a payoff dominant convention is selected for a wider parameter range when agents may only support a limited number of links as compared to a scenario where agents are not constrained in their linking choice. The main reason behind this result is that constrained interactions create a tradeoff between the interactions an agent has and those he would rather have. Further, we discuss convex linking costs and provide suffcient conditions for the payoff dominant convention to be selected in mxm coordination games.

Sharp identification regions in models with convex moment predictions

We provide a tractable characterization of the sharp identification region of the parameters θ in a broad class of incomplete econometric models. Models in this class have set valued predictions that yield a convex set of conditional or unconditional moments for the observable model variables. In short, we call these models with convex moment predictions. Examples include static, simultaneous move finite games of complete and incomplete information in the presence of multiple equilibria; best linear predictors with interval outcome and covariate data; and random utility models of multinomial choice in the presence of interval regressors data. Given a candidate value for θ, we establish that the convex set of moments yielded by the model predictions can be represented as the Aumann expectation of a properly defined random set. The sharp identification region of θ, denoted Θ 1, can then be obtained as the set of minimizers of the distance from a properly specified vector of moments of random variables to this Aumann expectation. Algorithms in convex programming can be exploited to efficiently verify whether a candidate θ is in Θ 1. We use examples analyzed in the literature to illustrate the gains in identification and computational tractability afforded by our method. This paper is a revised version of CWP27/09.