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The Effect of Information on Auction Outcomes: A Large Scale Field Experiment

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  • Tadelis, Steve
  • Zettelmeyer, Florian

Abstract

When choosing auction mechanisms sellers can decide how much information to reveal to buyers regarding the quality of the goods sold. Using a field experiment in a market for wholesale automobile auctions we are able to measure the effects of information on auction outcomes. We create random assignments of information about quality, and manipulate the availability of information over time. Our results suggest that, as the theoretical literature generally predicts, more information increases expected revenues. Furthermore, by measuring the effects on different quality grades of automobiles it seems like the increase in revenues are due to more competition for any given vehicle. Finally, we quantify the value of gathering information and releasing it to potential buyers in this setup. JEL classifications C93, D44, D82, L15.

Suggested Citation

  • Tadelis, Steve & Zettelmeyer, Florian, 2009. "The Effect of Information on Auction Outcomes: A Large Scale Field Experiment," Department of Economics, Working Paper Series qt7t4834h2, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    • Handle: RePEc:cdl:econwp:qt7t4834h2
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    References listed on IDEAS

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    1. Milgrom,Paul, 2004. "Putting Auction Theory to Work," Cambridge Books, Cambridge University Press, number 9780521536721, September.
    2. Jacob K. Goeree & Theo Offerman, 2003. "Competitive Bidding in Auctions with Private and Common Values," Economic Journal, Royal Economic Society, vol. 113(489), pages 598-613, July.
    3. Milgrom, Paul R & Weber, Robert J, 1982. "A Theory of Auctions and Competitive Bidding," Econometrica, Econometric Society, vol. 50(5), pages 1089-1122, September.
    4. Eric Overby & Sandy Jap, 2009. "Electronic and Physical Market Channels: A Multiyear Investigation in a Market for Products of Uncertain Quality," Management Science, INFORMS, vol. 55(6), pages 940-957, June.
    5. Kagel, John H & Harstad, Ronald M & Levin, Dan, 1987. "Information Impact and Allocation Rules in Auctions with Affiliated Private Values: A Laboratory Study," Econometrica, Econometric Society, vol. 55(6), pages 1275-1304, November.
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    Cited by:

    1. David Grether & David Porter & Matthew Shum, 2011. "Intimidation or Impatience? Jump Bidding in On-line Ascending Automobile Auctions," Working Papers 11-07, Chapman University, Economic Science Institute.
    2. David Grether & David Porter & Matthew Shum, 2015. "Cyber-Shilling in Automobile Auctions: Evidence from a Field Experiment," American Economic Journal: Microeconomics, American Economic Association, vol. 7(3), pages 85-103, August.

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    More about this item

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality

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