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Do Informational Cascades Happen with Non-myopic Agents?

We consider an environment where players need to decide whether to buy a certain product (or adopt a technology) or not. The product is either good or bad, but its true value is unknown to the players. Instead, each player has her own private information on its quality. Each player can observe the previous actions of other players and estimate the quality of the product. A classic result in the literature shows that in similar settings informational cascades occur where learning stops for the whole network and players repeat the actions of their predecessors. In contrast to this literature, in this work, players get more than one opportunity to act. In each turn, a player is chosen uniformly at random from all players and can decide to buy the product and leave the market or wait. Her utility is the total expected discounted reward, and thus myopic strategies may not constitute equilibria. We provide a characterization of perfect Bayesian equilibria (PBE) with forward-looking strategies through a fixed-point equation of dimensionality that grows only quadratically with the number of players. Using this tractable fixed-point equation, we show the existence of a PBE and characterize PBE with threshold strategies. Based on this characterization we study informational cascades in two regimes. First, we show that for a discount factor {\delta} strictly smaller than one, informational cascades happen with high probability as the number of players N increases. Furthermore, only a small portion of the total information in the system is revealed before a cascade occurs ...

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