Efficiency through feedback-contingent fees and rewards in auction marketplaces with adverse selection and moral hazard

This paper proposes a novel mechanism for inducing cooperation in online auction settings with noisy monitoring of quality and adverse selection. The mechanism combines the ability of electronic markets to solicit feedback from buyers with the more traditional ability to levy listing fees from sellers. Each period the mechanism charges a listing fee contingent on a seller's announced expected quality. It subsequently pays the seller a reward contingent on both his announced quality and the rating posted for that seller by that period's winning bidder. I show that, in the presence of a continuum of seller types with different cost functions, imperfect private monitoring of a seller's effort level and a simple "binary" feedback mechanism that asks buyers to rate a transaction as "good" or "bad", it is possible to derive a schedule of fees and rewards that induces all seller types to produce at their respective first-best quality levels and to truthfully announce their intended quality levels to buyers. The mechanism maximizes average social welfare for the entire community and is robust to a number of contingencies of particular concern in online environments, such as easy name changes and the existence of inept sellers. On the other hand, the mechanism distorts the resulting payoffs of individual sellers relative to the complete information case, transferring part of the payoffs of more efficient sellers to less efficient sellers. The magnitude of this distortion is proportional to the amount of noise associated with observing and reporting the quality of a good.