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Online Advertising and Privacy

  • Alexandre de Cornière
  • Romain De Nijs

An online platform makes a profit by auctioning an advertising slot that appears whenever a consumer visits its website.� Several firms compete in the auction, and consumers differ in their preferences.� Prior to the auction, the platform gathers data which is statistically correlated with consumers' tastes for products.� We study the implications of the platform's decision to allow potential advertisers to access the data about consumers' characteristics before they bid.� On top of the familiar trade-off between rent extraction and efficiency, we identify a new trade-off: the disclosure of information leads to a better matching between firms and consumers, but results in a higher equilibrum price on the product market.� We find that the equilbrium price is an increasing function of the number of firms.� As the number of firms becomes large, it is always profitable for the platform to disclose the information, but this need not be efficient, because of the distortion caused by the higher prices.� When the quality of the match represents vertical shifts in the demand function, we provide conditions under which disclosure is optimal.

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Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 650.

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Date of creation: 22 Mar 2013
Date of revision:
Handle: RePEc:oxf:wpaper:650
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  1. Bagnoli, M. & Bergstrom, T., 1989. "Log-Concave Probability And Its Applications," Papers 89-23, Michigan - Center for Research on Economic & Social Theory.
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