Lu Cheng, Hanken School of Economics

"Price Dynamics with Learning in Search Equilibrium"

Abstract

In online marketplaces, the information environment is structured by the platform. I develop a model of this matching market where buyers and sellers trade products under quality uncertainty. The study examines how the revelation of historical price offers can dampen market learning about product quality and, in turn, alter market price dynamics and welfare allocation. It shows that a steeper equilibrium price path emerges when such information is revealed, as opposed to when it is concealed. As in the former information environment, sellers can credibly manipulate the learning process through strategic pricing. Market transparency harms buyers and exacerbates the adverse selection problem. I highlight how market efficiency is affected by this observability mechanism and derive implications on policy schemes from the platform’s point of view.

Contact person: Egor Starkov