Working Paper: CEPR ID: DP16858
Authors: Dirk Bergemann; Tibor Heumann; Stephen Morris; Constantine Sorokin; Eyal Winter
Abstract: We characterize the revenue-maximizing information structure in the second price auction. The seller faces a classic economic trade-off: providing more information improves the efficiency of the allocation but also creates higher information rents for bidders. The information disclosure policy that maximizes the revenue of the seller is to fully reveal low values (where competition will be high) but to pool high values (where competition will be low). The size of the pool is determined by a critical quantile that is independent of the distribution of values and only dependent on the number of bidders. We discuss how this policy provides a rationale for conflation in digital advertising.
Keywords: auctions; second-price auctions; information design; information disclosure; digital advertising; conflation
JEL Codes: D44; D47; D83; D84
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| level of information disclosure (G38) | expected revenue for the seller (D44) |
| number of bidders (D44) | threshold for pooling high values (C55) |
| threshold for pooling high values (C55) | competition among high-value bidders (D44) |
| competition among high-value bidders (D44) | seller revenue (L85) |
| optimal information structure (D83) | seller revenue (L85) |
| allocation efficiency (D61) | information rents for bidders (D44) |