Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We analyze how sellers of used construction equipment sort products between online and offline auctions based on the quality and transparency of different machine attributes. Sellers are more likely to offer machines online if quality is high for attributes whose integrity can be measured via photo (e.g., appearance) and more likely to offer machines offline if quality is high for attributes whose integrity is more reliably evaluated in person (e.g., engine). Quality averaged across all attributes is unrelated to auction choice, meaning standard tests of adverse selection can mask the subtle but significant effects of asymmetric information in this market.