The Simple Empirics of Optimal Online Auctions
Bradley Larsen (),
Kane Sweeney and
No 24698, NBER Working Papers from National Bureau of Economic Research, Inc
We study reserve prices computed to maximize the expected profit of the seller based on historical observations of incomplete bid data typically available to the auction designer in online auctions for advertising or e-commerce. This direct approach to computing reserve prices circumvents the need to fully recover distributions of bidder valuations. We derive asymptotic results and also provide a new bound, based on the empirical Rademacher complexity, for the number of historical auction observations needed in order for revenue under the estimated reserve price to approximate revenue under the optimal reserve arbitrarily closely. This simple approach to estimating reserves may be particularly useful for auction design in Big Data settings, where traditional empirical auctions methods may be costly to implement. We illustrate the approach with e-commerce auction data from eBay. We also demonstrate how this idea can be extended to estimate all objects necessary to implement the Myerson (1981) optimal auction.
JEL-codes: C10 C55 D44 L10 (search for similar items in EconPapers)
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