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The Economics of Internet Search

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  • Hal R. Varian

    (University of California at Berkeley)

Abstract

This lecture provides an introduction to the economics of Internet search engines. After a brief review of the historical development of the technology and the industry, I describe some of the economic features of the auction system used for displaying ads. It turns out that some relatively simple economic models provide significant insight into the operation of these auctions. In particular, the classical theory of two-sided matching markets turns out to be very useful in this context.

Suggested Citation

  • Hal R. Varian, 2006. "The Economics of Internet Search," Rivista di Politica Economica, SIPI Spa, vol. 96(6), pages 9-23, November-.
    • Handle: RePEc:rpo:ripoec:v:96:y:2006:i:6:p:9-23
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    References listed on IDEAS

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    1. Vijay Krishna & Motty Perry, 1997. "Efficient Mechanism Design," Game Theory and Information 9703010, University Library of Munich, Germany, revised 28 Apr 1998.
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    Cited by:

    1. Emanuele Tarantino, 2012. "A Note on Vertical Search Engines’ Foreclosure," Chapters, in: Joseph E. Harrington Jr & Yannis Katsoulacos (ed.), Recent Advances in the Analysis of Competition Policy and Regulation, chapter 8, Edward Elgar Publishing.
    2. Tarantino, Emanuele, 2013. "A simple model of vertical search engines foreclosure," Telecommunications Policy, Elsevier, vol. 37(1), pages 1-12.
    3. Vlastakis, Nikolaos & Markellos, Raphael N., 2012. "Information demand and stock market volatility," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1808-1821.
    4. Massimo PERI & Daniela VANDONE & Lucia BALDI, 2012. "Internet, noise trading and commodity prices," Departmental Working Papers 2012-07, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    5. Moussa, Faten & Delhoumi, Ezzeddine & Ouda, Olfa Ben, 2017. "Stock return and volatility reactions to information demand and supply," Research in International Business and Finance, Elsevier, vol. 39(PA), pages 54-67.
    6. Sasson, Elan & Ravid, Gilad & Pliskin, Nava, 2015. "Improving similarity measures of relatedness proximity: Toward augmented concept maps," Journal of Informetrics, Elsevier, vol. 9(3), pages 618-628.
    7. Yanwu Yang & Daniel Zeng & Yinghui Yang & Jie Zhang, 2015. "Optimal Budget Allocation Across Search Advertising Markets," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 285-300, May.
    8. Peri, Massimo & Vandone, Daniela & Baldi, Lucia, 2014. "Internet, noise trading and commodity futures prices," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 82-89.
    9. Peri, Massimo & Vandone, Daniela & Baldi, Lucia, 2012. "Information Demand and Agriculture Commodity Prices," 2012 International European Forum, February 13-17, 2012, Innsbruck-Igls, Austria 144973, International European Forum on System Dynamics and Innovation in Food Networks.

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    More about this item

    JEL classification:

    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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