Asymmetric information, adverse selection and seller revelation on eBay motors

Since the pioneering work of Akerlof (1970), economists have been aware of the adverse selection problem that asymmetric information can create in durable goods markets. The success of eBay Motors, an online auction market for used cars, thus poses something of a puzzle. I argue that the key to resolving this puzzle is the auction webpage, which allows sellers to reduce information asymmetries by revealing credible signals about car quality in the form of text, photos and graphics. To validate my claim, I develop a new model of a common value eBay auction with costly seller revelation and test its implications using a unique panel dataset of car auctions from eBay Motors. Precise testing requires a struc-tural estimation approach, so I develop a new pseudo-maximum likelihood estimator for this model, accounting for the endogeneity of information with a semiparametric control function. I find that bidders adjust their valuations in response to seller revelations, as the theory predicts. To quantify how important these revelations are in reducing information asymmetries, I simulate a counterfactual in which sellers cannot post information to the auction webpage and show that in this case a significant gap between vehicle value and expected price can arise. Since this gap is dramatically narrowed by seller revelations, I con-clude that information asymmetry and adverse selection on eBay Motors are endogenously reduced by information transmitted through the auction webpage