From the paper: "Online
freelance marketplaces are websites that match buyers of electronically
deliverable services with freelancers. While freelancing has grown in recent
years, it faces the classic ‘information asymmetry’ problem – buyers face
uncertainty over seller quality. Typically, these markets use reputation
systems to alleviate this issue, but the effectiveness of these systems is open
to debate. We present a dynamic structural framework to estimate the returns to
seller reputations in freelance sites. In our model, each period, a buyer
decides whether to choose a bid from her current set of bids, cancel the
auction, or wait for more bids. In the process, she trades-off sellers’ price,
reputation, other attributes, and the costs of waiting and canceling. Our framework
addresses ‘dynamic selection’, which can lead to underestimation of reputation,
through two types of persistent unobserved heterogeneities – in bid
arrival-rates and buyers’ unobserved preference for bids. We apply our
framework to data from a leading freelance firm. We find that buyers are
forward-looking, that they place significant weight on seller reputation, and
that not controlling for dynamics and selection can bias reputation estimates.
Using counterfactual simulations, we infer the dollar value of seller
reputations and provide guidelines to managers of freelance firms." Read more
