Signaling Competition in Two-Sided Markets

Abstract

We consider decentralized platforms facilitating many-to-many matches between two sides of a marketplace. In the absence of direct matching, inefficiency in market outcomes can easily arise. For instance, popular supply agents may garner many units from the demand side, while other supply units may not receive any match. A central question for the platform is how to manage congestion and improve market outcomes. We study the impact of a detail-free lever: the disclosure of information to agents on current competition levels. Disclosing competition reduces the perceived value of popular units, but, at the same time, it can help agents on the other side better elect across options. How large are such effects, and how do they affect overall market outcomes? We answer this question empirically. We partner with the largest service marketplace in Latin America, which sells non-exclusive labor market leads to workers. We propose a structural model which allows workers to internalize competition at the lead level and captures the equilibrium effect of such reaction to competition at the platform level. We estimate the model by leveraging agents’ exogenous arrival times and a change in the platform’s pricing policy. Using the estimated model, we conduct counterfactual analyses to study the impact of signaling competition on workers’ lead purchasing decisions, the platform’s revenue, and the expected number of matches. We find that signaling competition is a powerful lever for the platform to reduce congestion, redirecting demand, and ultimately improving the expected number of matches for the markets we analyze.