Retailers may face uncertainty about the profitability of local markets, which provide opportunities for learning when making entry decisions. To quantify these informational benefits, I develop an empirical framework for studying dynamic retail entry with uncertainty and learning (from others)....

Besides their role in reducing frictions and facilitating trade, two-sided platforms increasingly collect and process data, e.g., supply and demand forecasts, that can further affect market outcomes. This paper studies how a platform may choose to disclose its information about future demand to...

Crowd-sourced recommender platforms organize social learning about products by recommending items based on information collected from previous users. A crucial design question is the level of experimentation over the life cycle of a product. I study how market structure affects experimentation,...

We address the issue of risk aversion in a competitive equilibrium when some buyers engage in learning and information is conveyed through the price system. Specifically, since the learning process yields uncertainty, we study the effect of risk aversion on the equilibrium outcomes of the model,...

We study a general static noisy rational expectations model, where investors have private information about asset payoffs, with common and private components, and about their own exposure to an aggregate risk factor, and derive conditions for existence and uniqueness (or multiplicity) of...