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

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Author Info

  • 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.

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File URL: http://128.118.178.162/eps/mic/papers/0504/0504005.pdf
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Bibliographic Info

Paper provided by EconWPA in its series Microeconomics with number 0504005.

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Length: 49 pages
Date of creation: 14 Apr 2005
Date of revision:
Handle: RePEc:wpa:wuwpmi:0504005

Note: Type of Document - pdf; pages: 49
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Web page: http://128.118.178.162

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Keywords: Internet; Price Dispersion; Advertising;

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References

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  1. Glenn Ellison & Sara Fisher Ellison, 2004. "Search, Obfuscation, and Price Elasticities on the Internet," NBER Working Papers 10570, National Bureau of Economic Research, Inc.
  2. Terza, J.V., 1995. "Estmiating Count Data Models with Endogenous Switching and Sample Selection," Papers 4-95-14, Pennsylvania State - Department of Economics.
  3. Narasimhan, Chakravarthi, 1988. "Competitive Promotional Strategies," The Journal of Business, University of Chicago Press, vol. 61(4), pages 427-49, October.
  4. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
  5. Rosenthal, Robert W, 1980. "A Model in Which an Increase in the Number of Sellers Leads to a Higher Price," Econometrica, Econometric Society, vol. 48(6), pages 1575-79, September.
  6. Jerry A. Hausman & Bronwyn H. Hall & Zvi Griliches, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," NBER Technical Working Papers 0017, National Bureau of Economic Research, Inc.
  7. Austan Goolsbee & Judith Chevalier, 2002. "Measuring Prices and Price Competition Online: Amazon and Barnes and Noble," Yale School of Management Working Papers ysm290, Yale School of Management, revised 12 Sep 2008.
  8. Varian, Hal R, 1980. "A Model of Sales," American Economic Review, American Economic Association, vol. 70(4), pages 651-59, September.
  9. Gourieroux Christian & Monfort Alain & Trognon A, 1982. "Pseudo maximum lilelihood methods : applications to poisson models," CEPREMAP Working Papers (Couverture Orange) 8203, CEPREMAP.
  10. Judith Chevalier & Austan Goolsbee, 2003. "Measuring Prices and Price Competition Online: Amazon.com and BarnesandNoble.com," Quantitative Marketing and Economics, Springer, vol. 1(2), pages 203-222, June.
  11. Cameron, A. Colin & Trivedi, Pravin K., 1990. "Regression-based tests for overdispersion in the Poisson model," Journal of Econometrics, Elsevier, vol. 46(3), pages 347-364, December.
  12. Gourieroux Christian & Monfort Alain & Trognon A, 1981. "Pseudo maximum likelihood methods : theory," CEPREMAP Working Papers (Couverture Orange) 8129, CEPREMAP.
  13. Michael R. Baye & John Morgan & Patrick Scholten, 2004. "Price Dispersion in the Small and in the Large: Evidence from an Internet Price Comparison Site," Working Papers 2004-03, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
  14. Michael R. Baye & John Morgan & Patrick Scholten, 2004. "Temporal Price Dispersion: Evidence from an Online Consumer Electronics Market," Working Papers 2004-04, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
  15. Shilony, Yuval, 1977. "Mixed pricing in oligopoly," Journal of Economic Theory, Elsevier, vol. 14(2), pages 373-388, April.
  16. Terza, Joseph V., 1998. "Estimating count data models with endogenous switching: Sample selection and endogenous treatment effects," Journal of Econometrics, Elsevier, vol. 84(1), pages 129-154, May.
  17. Cameron, A Colin & Trivedi, Pravin K, 1986. "Econometric Models Based on Count Data: Comparisons and Applications of Some Estimators and Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 1(1), pages 29-53, January.
  18. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
  19. Michael R. Baye & John Morgan, 2001. "Information Gatekeepers on the Internet and the Competitiveness of Homogeneous Product Markets," American Economic Review, American Economic Association, vol. 91(3), pages 454-474, June.
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Citations

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Cited by:
  1. Michael Baye & John Morgan, 2005. "Brand and Price Advertising in Online Markets," Microeconomics 0504009, EconWPA.
  2. Harriet Gamper, 2012. "How Can Internet Comparison Sites Work Optimally for Consumers?," Journal of Consumer Policy, Springer, vol. 35(3), pages 333-353, September.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. Häring, Julia, 2005. "The Virtual Location of E-Tailers: Evidence from a B2C E-Commerce Market," ZEW Discussion Papers 05-52, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.

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