Person:

Farronato, Chiara

Auctions were very popular in the early days of internet commerce, but today online sellers mostly use posted prices. We model the choice between auctions and posted prices as a trade-off between competitive price discovery and convenience. Evidence from eBay fits the theory: auctions are favored by less experienced sellers and for idiosyncratic products, and auction listings sell at a discount but with higher probability relative to comparable posted price listings. We then show that the decline in auctions was not driven by changes in the type of sellers and items. Instead, seller incentives changed. We estimate the demand facing individual sellers at different points in time, and document falling sale probabilities and a fall in the relative demand for auctions. Both favor posted prices; our estimates suggest the latter is more important for explaining the shift away from auctions. We provide supporting evidence from a survey of eBay sellers, and discuss why sellers might use a mix of auctions and posted prices in order to price discriminate.

Digital platforms are increasingly the subject of regulatory scrutiny. In comparison to multiple competitors, a single platform may increase consumer welfare if network effects are large or may decrease welfare due to higher prices or reduction in platform variety. We study the net effect of this trade-off in the context of the merger between the two largest platforms for pet-sitting services. We exploit variation in pre-merger market shares and a difference-in-differences approach to causally estimate network effects at the platform and market level. We find that consumers are, on average, not substantially better off with a single combined platform than with two separate and competing platforms. On one hand, users of the acquiring platform benefited from the merger because of network effects. On the other hand, users of the acquired platform experienced worse outcomes. Our results highlight the importance of platform differentiation even when platforms enjoy network effects.

We study the demand and supply implications of occupational licensing using transaction-level data from a large online platform for home improvement services. We find that demand is more responsive to a professional's reviews than to the professional's platform-verified licensing status. We show some evidence that consumers view licenses and reviews as substitutes. We confirm the generality of our findings off the platform in an independent consumer survey. Combining state-level licensing regulation data with platform microdata, we find that more stringent requirements are associated with less competition, higher prices, and no increase in demand or consumer satisfaction.

Peer-to-peer markets such as eBay, Uber, and Airbnb allow small suppliers to compete with traditional providers of goods or services. We view the primary function of these markets as making it easy for buyers to find sellers and engage in convenient, trustworthy transactions. We discuss elements of market design that make this possible, including search and matching algorithms, pricing, and reputation systems. We then develop a simple model of how these markets enable entry by small or flexible suppliers, and the resulting impact on existing firms. Finally, we consider the regulation of peer-to-peer markets, and the economic arguments for different approaches to licensing and certification, data and employment regulation.