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Estimating Firm-Level Demand at a Price Comparison Site: Accounting for Shoppers and the Number of Competitors

Author

Listed:
  • Michael R. Baye

    (Kelley School of Business, Indiana University)

  • J. Rupert J. Gatti

    (Trinity College, University of Cambridge)

  • Paul Kattuman

    (The Judge Institute of Management, University of Cambridge)

  • John Morgan

    (Haas School of Business & Department of Economics, University of California, Berkeley)

Abstract

Clearinghouse models of online pricing---such as Varian (1980), Rosenthal (1980), Narasimhan (1988), and Baye-Morgan (2001)---view a price comparison site as an 'information clearinghouse' where shoppers and loyals obtain price and product information to make online purchases. These models predict that the responsiveness of a firm's demand to a change in its price depends on the number of sellers and whether the price change results in the firm charging the lowest price in the market. Using a unique firm-level dataset from Kelkoo.com (Yahoo!'s European price comparison site), we examine these predictions by providing estimates of the demand for PDAs. Our results indicate that the number of competing sellers and both the firm's location on the screen and relative ranking in the list of prices are important determinants of an online retailer's demand. We find that an online monopolist faces an elasticity of demand of about -2, while sellers competing against 10 other sellers face an elasticity of about -6. We also find empirical evidence of a discontinuous jump in a firm's demand as its price declines from the second-lowest to the lowest price. Our estimates suggest that about 13% of the consumers at Kelkoo are 'shoppers' who purchase from the seller offering the lowest price.

Suggested Citation

  • Michael R. Baye & J. Rupert J. Gatti & Paul Kattuman & John Morgan, 2005. "Estimating Firm-Level Demand at a Price Comparison Site: Accounting for Shoppers and the Number of Competitors," Microeconomics 0504005, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpmi:0504005
    Note: Type of Document - pdf; pages: 49
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    References listed on IDEAS

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    Cited by:

    1. Harriet Gamper, 2012. "How Can Internet Comparison Sites Work Optimally for Consumers?," Journal of Consumer Policy, Springer, vol. 35(3), pages 333-353, September.
    2. Anindya Ghose & Bin Gu, 2006. "Search Costs, Demand Structure and Long Tail in Electronic Markets: Theory and Evidence," Working Papers 06-19, NET Institute, revised Oct 2006.
    3. Häring, Julia, 2005. "The Virtual Location of E-Tailers: Evidence from a B2C E-Commerce Market," ZEW Discussion Papers 05-52, ZEW - Leibniz Centre for European Economic Research.
    4. Glenn Ellison & Sara Fisher Ellison, 2006. "Internet Retail Demand: Taxes, Geography, and Online-Offline Competition," NBER Working Papers 12242, National Bureau of Economic Research, Inc.
    5. Haynes, Michelle & Thompson, Steve, 2008. "Price, price dispersion and number of sellers at a low entry cost shopbot," International Journal of Industrial Organization, Elsevier, vol. 26(2), pages 459-472, March.
    6. Martin Natter & Ana-Marija Ozimec & Ju-Young Kim, 2015. "Practice Prize Winner—ECO: Entega’s Profitable New Customer Acquisition on Online Price Comparison Sites," Marketing Science, INFORMS, vol. 34(6), pages 789-803, November.
    7. Michael R. Baye & John Morgan & Patrick Scholten, 2006. "Information, Search, and Price Dispersion," Working Papers 2006-11, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
    8. Steve Thompson, 2009. "Grey Power: An Empirical Investigation of the Impact of Parallel Imports on Market Prices," Journal of Industry, Competition and Trade, Springer, vol. 9(3), pages 219-232, September.
    9. Michael R. Baye & John Morgan, 2009. "Brand and Price Advertising in Online Markets," Management Science, INFORMS, vol. 55(7), pages 1139-1151, July.
    10. Kosmopoulou, Georgia & De Silva, Dakshina G., 2007. "The effect of shill bidding upon prices: Experimental evidence," International Journal of Industrial Organization, Elsevier, vol. 25(2), pages 291-313, April.

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    JEL classification:

    • D1 - Microeconomics - - Household Behavior
    • D2 - Microeconomics - - Production and Organizations
    • D3 - Microeconomics - - Distribution
    • D4 - Microeconomics - - Market Structure, Pricing, and Design

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