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Identification and Estimation of Online Price Competition with an Unknown Number of Firms

  • Yonghong An

    (Johns Hopkins University)

  • Michael R Baye

    (Department of Business Economics and Public Policy, Indiana University Kelley School of Business)

  • Yingyao Hu

    (Johns Hopkins University)

  • John Morgan

    (University of California - Berkeley)

  • Matt Shum

    (Caltech)

This paper considers identification and estimation of a general model for online price competition. We show that when the number of competing firms is unknown, the underlying parameters of the model can still be identified and estimated employing recently developed results on measurement error. With the estimates of model parameters, we are able to analyze the competitive effects of online competition when the number of firms changes. We illustrate our methodology using UK data for personal digital assistants and employ the estimates to simulate competitive effects. Our results reveal that heightened competition has differential effects on the prices paid by different consumer segments.

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File URL: http://kelley.iu.edu/riharbau/RePEc/iuk/wpaper/bepp2010-17-abhms.pdf
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Paper provided by Indiana University, Kelley School of Business, Department of Business Economics and Public Policy in its series Working Papers with number 2010-17.

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Date of creation: Jul 2010
Date of revision: Nov 2012
Handle: RePEc:iuk:wpaper:2010-17
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Web page: http://kelley.iu.edu/bepp/
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  1. 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.
  2. Michael R. Baye & J. Rupert J. Gatti & Paul Kattuman & John Morgan, 2009. "Clicks, Discontinuities, and Firm Demand Online," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 18(4), pages 935-975, December.
  3. Michael R. Baye & John Morgan, 2005. "Brand and Price Advertising in Online Markets," Working Papers 2005-08, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
  4. Armstrong, Mark, 2008. "Interactions between competition and consumer policy," MPRA Paper 7258, University Library of Munich, Germany.
  5. 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.
  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. 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.
  8. Hu, Yingyao, 2008. "Identification and estimation of nonlinear models with misclassification error using instrumental variables: A general solution," Journal of Econometrics, Elsevier, vol. 144(1), pages 27-61, May.
  9. Yingyao Hu & Matthew Shum, 2007. "Estimating First-Price Auctions with an Unknown Number of Bidders: A Misclassification Approach," Economics Working Paper Archive 541, The Johns Hopkins University,Department of Economics.
  10. Moraga-González, José Luis & Wildenbeest, Matthijs R., 2008. "Maximum likelihood estimation of search costs," European Economic Review, Elsevier, vol. 52(5), pages 820-848, July.
  11. Ganesh Iyer & David Soberman & J. Miguel Villas-Boas, 2005. "The Targeting of Advertising," Marketing Science, INFORMS, vol. 24(3), pages 461-476, May.
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