Working Paper: NBER ID: w18590
Authors: L. Elisa Celis; Gregory Lewis; Markus M. Mobius; Hamid Nazerzadeh
Abstract: Increasingly detailed consumer information makes sophisticated price discrimination possible. At fine levels of aggregation, demand may not obey standard regularity conditions. We propose a new randomized sales mechanism for such environments. Bidders can "buy-it-now" at a posted price, or "take-a-chance" in an auction where the top d > 1 bidders are equally likely to win. The randomized allocation incentivizes high valuation bidders to buy-it-now. We analyze equilibrium behavior, and apply our analysis to advertiser bidding data from Microsoft Advertising Exchange. In counterfactual simulations, our mechanism increases revenue by 4.4% and consumer surplus by 14.5% compared to an optimal second-price auction.
Keywords: price discrimination; randomized auctions; online advertising; mechanism design
JEL Codes: D4; D44; D47; D82
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| BINTAC mechanism (Y50) | revenue (H27) |
| BINTAC mechanism (Y50) | consumer surplus (D46) |
| BINTAC mechanism (Y50) | bidder participation (D44) |
| BINTAC mechanism (Y50) | auction outcomes (D44) |
| BINTAC mechanism (Y50) | efficiency (D61) |
| BINTAC mechanism (Y50) | unallocated impressions (Y60) |
| BINTAC mechanism (Y50) | competition (L13) |