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

Author

Listed:
  • 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)

Abstract

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.

Suggested Citation

  • Yonghong An & Michael R Baye & Yingyao Hu & John Morgan & Matt Shum, 2010. "Identification and Estimation of Online Price Competition with an Unknown Number of Firms," Working Papers 2010-17, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy, revised Nov 2012.
    • Handle: RePEc:iuk:wpaper:2010-17
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    References listed on IDEAS

    as
    1. 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.
    2. Varian, Hal R, 1980. "A Model of Sales," American Economic Review, American Economic Association, vol. 70(4), pages 651-659, September.
    3. Ganesh Iyer & David Soberman & J. Miguel Villas-Boas, 2005. "The Targeting of Advertising," Marketing Science, INFORMS, vol. 24(3), pages 461-476, May.
    4. An, Yonghong & Hu, Yingyao & Shum, Matthew, 2010. "Estimating first-price auctions with an unknown number of bidders: A misclassification approach," Journal of Econometrics, Elsevier, vol. 157(2), pages 328-341, August.
    5. Michael R. Baye & John Morgan, 2009. "Brand and Price Advertising in Online Markets," Management Science, INFORMS, vol. 55(7), pages 1139-1151, July.
    6. 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.
    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," Journal of Industrial Economics, Wiley Blackwell, vol. 52(4), pages 463-496, December.
    8. 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.
    9. 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.
    10. 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 1575-1579, September.
    11. Han Hong & Matthew Shum, 2006. "Using price distributions to estimate search costs," RAND Journal of Economics, RAND Corporation, vol. 37(2), pages 257-275, June.
    12. 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.
    13. Armstrong, Mark, 2008. "Interactions between competition and consumer policy," MPRA Paper 7258, University Library of Munich, Germany.
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    Citations

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    Cited by:

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    2. Moraga-Gonzalez, Jose L. & Wildenbeest, Matthijs R., 2011. "Comparison sites," IESE Research Papers D/933, IESE Business School.
      • Jose Luis Moraga-Gonzalez & Matthijs R. Wildenbeest, 2011. "Comparison Sites," Working Papers 2011-04, Indiana University, Kelley School of Business, Department of Business Economics and Public Policy.
    3. Raúl Bajo-Buenestado, 2021. "Market prices, spatial distribution of consumers and firms’ optimal locations in a linear city," Empirical Economics, Springer, vol. 61(1), pages 443-467, July.
    4. Shelegia, Sandro & Wilson, Chris, 2016. "A Generalized Model of Sales," EconStor Preprints 147411, ZBW - Leibniz Information Centre for Economics.
    5. Hu, Yingyao, 2017. "The econometrics of unobservables: Applications of measurement error models in empirical industrial organization and labor economics," Journal of Econometrics, Elsevier, vol. 200(2), pages 154-168.
    6. Zhang, Yinjunjie & Xu, Zhicheng Phil & Palma, Marco A., 2017. "Misclassification Errors of Subjective Well-being: A New Approach to Mapping Happiness," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258553, Agricultural and Applied Economics Association.
    7. Yingyao Hu, 2015. "Microeconomic models with latent variables: applications of measurement error models in empirical industrial organization and labor economics," CeMMAP working papers 03/15, Institute for Fiscal Studies.
    8. Yingyao Hu, 2015. "Microeconomic models with latent variables: applications of measurement error models in empirical industrial organization and labor economics," CeMMAP working papers CWP03/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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    More about this item

    Keywords

    E-Retail Markets; Nonparametric Identification; Structural Estimation;
    All these keywords.

    JEL classification:

    • L0 - Industrial Organization - - General

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