This paper develops a dynamic model of discrete choice that incorporates peer effects into  consideration sets. We characterize  equilibrium behavior and study the empirical content of the dynamic modelwe offer . In our set-up, the choices of friends act as exclusion restrictions in the stochastic variation of the subset of alternatives that each person considers at the moment of picking an option. They allow us to recover (from a sequence of observed choices) the ranking of preferences of each person , the attention mechanism , and the set of connections or nodes between the people in the network . The identification strategy we offer does not rely on the variation of the set of available options (or menus) which remain the same across all the observations .
This paper develops a dynamic model of discrete choice that incorporates peer effects into random consideration sets. We characterize the equilibrium behavior and study the empirical content of the model . In our setup, changes in the choices of friends induce changes in the distribution of the consideration sets. We exploit this variation to recover the ranking of preferences , the attention mechanisms , and the network connections. These identification results allow unrestricted heterogeneity across people and do not rely on variation of either covariates or the set of available options . Our methodology leads to a maximum-likelihood estimator that performs well in simulations .
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act as exclusion restrictions in the stochastic variation of the subset of alternatives that each person considers at the moment of picking an option. They allow us to recover (from a sequence of observed choices)
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