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The Simple Empirics of Optimal Online Auctions

Author

Listed:
  • Dominic Coey
  • Bradley Larsen
  • Kane Sweeney
  • Caio Waisman

Abstract

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.

Suggested Citation

  • Dominic Coey & Bradley Larsen & Kane Sweeney & Caio Waisman, 2018. "The Simple Empirics of Optimal Online Auctions," NBER Working Papers 24698, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:24698
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    More about this item

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General

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