B04: Decentralized markets

Digitalization and its welfare consequences on decentralized markets are a current societal challenge. Decentralized markets differ significantly from the frictionless Walrasian ideal. Informational asymmetries result in market power and dispersed prices. We analyze the functioning of decentralized markets theoretically and empirically. We are interested in the effectiveness of various market design aspects, with online markets as our central application. We pursue two themes.

First, we revisit the theory of trade in decentralized settings with frictions, focusing on search theory. We explore the connections of search and auctions. We study scenarios in which agents are uncertain about their environment, giving rise to learning dynamics for individual agents, information provision incentives, and the question of whether decentralized markets can efficiently aggregate dispersed information.

Second, we further the theory of social learning by modeling the buyers’ communication of experiences gained in past transactions via ratings. Ratings are essential for the functioning of many anonymous markets, especially those conducted online. We study strategic and non-strategic information disclosure, their equilibrium consequences for market entry and exit, and the impact of interventions by intermediaries and a regulator.

On the empirical end, we develop methods to estimate demand in search models, allowing for consumer heterogeneity in tastes and sampling probabilities. We study the empirical relevance of search frictions in explaining substitution patterns across products following price changes, and how ignoring those frictions biases policy evaluation. We also explore rating formation—who rates and why—and the effects of ratings on the sellers’ market entry and exit.

A running example is eBay. It is a structured decentralized marketplace where buyers often search for idiosyncratic products and may bid or bargain over prices, rather than taking a market price as given. Moreover, ratings and other information disclosures are essential for overcoming adverse selection and moral hazard. Finally, eBay itself acts as an intermediary and a “regulator” who designs aspects of the market place. In fact, eBay is not just an example—its administrative raw data constitute one of the primary databases we use to test our theories.