Peer Effects in Consideration and Preferences

We develop a general model of discrete choice that incorporates peer effects in preferences and consideration sets. We characterize the equilibrium behavior and establish conditions under which all parts of the model can be recovered from a sequence of choices. We allow peers to affect only preferences, only consideration, or both. We exploit different types of variations to separate the peer effects in preferences and consideration sets. This allows us to recover the set (and type) of connections between the agents in the network. We then use this information to recover the random preferences and the attention mechanisms of each agent. These nonparametric identification results allow unrestricted heterogeneity across agents and do not rely on the variation of either covariates or the set of available options (or menus). We apply our results to model expansion decisions by coffee chains and find evidence of limited consideration. We simulate counterfactual predictions and show how limited consideration slows down competition