Pricing and Fees in Auction Platforms with Two-Sided Entry

This paper presents, solves, and estimates the first structural auction model with seller selection. This allows me to quantify network effects arising from endogenous bidder and seller entry into auction platforms, facilitating the estimation of theoretically ambiguous fee impacts by tracing them through the game. Relevant model primitives are identified from variation in second-highest bids and reserve prices. My estimator builds off the discrete choice literature to address the double nested fixed point characterization of the entry equilibrium. Using new wine auction data, I estimate that this platform's revenues increase up to 60% when introducing a bidder discount and simultaneously increasing seller fees. More bidders enter when the platform is populated with lower-reserve setting sellers, driving up prices. Moreover, I show that meaningful antitrust damages can be estimated in a platform setting despite this two-sidedness.