Abstract: This paper studies the impact of uncertainty about underlying demand process on investment and welfare in container shipping. In particular, I explore how such uncertainty interacts with demand fluctuations and firms' strategic incentives. I construct and estimate a dynamic oligopoly model in which agents do not know the true parameters in the demand process, but form and revise their beliefs based on information available at each decision-making moment. I find that uncertainty about the demand process amplifies investment cycles through (i) leading firms to revise beliefs more drastically as they experience demand fluctuations, and (ii) intensifying strategic incentives among firms.
A Computational Framework for Analyzing Dynamic Procurement Auctions: The Market Impact of Information Sharing (with John Asker, Chaim Fershtman, and Ariel Pakes)
NBER Working Paper No. 22836.
Abstract: This paper develops a computational framework to analyze dynamic auctions and uses it to investigate the impact of information sharing among bidders. We show that allowing for the dynamics implicit in many auction environments enables the emergence of equilibrium states that can only be reached when firms are responding to dynamic incentives. The impact of information sharing depends on the extent of dynamics and provides support for the claim that information sharing, even of strategically important data, need not be welfare reducing. Our methodological contribution is to show how to adapt the Experience Based Equilibrium concept to a dynamic auction environment and to provide an implementable boundary consistency condition that mitigates the extent of multiple equilibria.
Firms’ Beliefs and Learning: Models, Identification, and Empirical Evidence (with Victor Aguirregabiria)
Abstract: This paper reviews recent literature on structural models of oligopoly competition where firms have biased beliefs about primitives of the model (e.g. demand, costs) or about the strategic behavior of other firms in the market. We describe different structural models that have been proposed to study this phenomenon and examine the approaches used to identify firms' beliefs. We discuss empirical results in recent studies and show that accounting for firms' biased beliefs and learning can have important implications on our measures and interpretation of market efficiency.
Work in Progress
Endogenous Information Acquisition and Insurance Choice (with Zach Y. Brown)
Patient Costs and Physicians’ Information (with Michael J. Dickstein and Eduardo Morales)