Structural Estimation

We explore marketplace design in the context of a B2B platform specializing in liquidation auctions and establish that the platform’s ability to use its design levers to manage the availability of supply over time yields significant value. Exploiting a natural experiment, we illustrate that consolidating auctions’ ending times to certain weekdays increases the platform’s revenues by 7.3% by inducing a higher level of bidder participation. Also, we estimate a structural model that endogenizes bidders’ dynamic behavior and find that appropriately designing a recommendation system yields an additional revenue increase by reducing supply-side cannibalization and altering the composition of participating bidders.

We present empirical evidence that monitoring products online is associated with successfully obtaining discounts. Further, we develop a structural model of consumers’ dynamic monitoring to find substantial heterogeneity in consumers’ opportunity costs for an online visit ranging from 2 to 25$. A randomized markdown policy benefits retailers by combining price commitment with the exploitation of heterogeneity in consumers’ monitoring costs. We estimate that the retailer’s profit under randomized markdowns is 81% higher than from subgame-perfect, state-contingent pricing, because the retailer need not limit its inventory to credibly limit markdowns.