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Confessions of an internet monopolist: demand estimation for a versioned information good

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  • Henry W. Chappell
  • Paulo Guimarães
  • Orgül Demet Öztürk

Abstract

We develop and apply a method for estimating demand system parameters for versioned information goods. Our analysis uses data collected from a web-based field experiment in which prices and versions of an information good were exogenously varied. Using a maximum simulated likelihood (MSL) procedure, we estimate parameters characterizing distributions of utility functions over a population of potential buyers. We then construct profit‐maximizing versioning and pricing plans for the seller and assess the welfare implications of those plans. Because firms increasingly have opportunities to collect information by tracking behavior of customers, methods similar to ours could be useful in future commercial applications. Copyright (C) 2010 John Wiley & Sons, Ltd.

Suggested Citation

  • Henry W. Chappell & Paulo Guimarães & Orgül Demet Öztürk, 2011. "Confessions of an internet monopolist: demand estimation for a versioned information good," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 32(1), pages 1-15, January.
    • Handle: RePEc:wly:mgtdec:v:32:y:2011:i:1:p:1-15
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    File URL: http://hdl.handle.net/10.1002/mde.1513
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    1. Philippe Aghion & Patrick Bolton & Christopher Harris & Bruno Jullien, 1991. "Optimal Learning by Experimentation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(4), pages 621-654.
    2. Loginova, Oksana & Taylor, Curtis, 2003. "Price Experimentation with Strategic Buyers," Working Papers 03-02, Duke University, Department of Economics.
    3. Oksana Loginova & Curtis Taylor, 2008. "Price experimentation with strategic buyers," Review of Economic Design, Springer;Society for Economic Design, vol. 12(3), pages 165-187, September.
    4. Glenn W. Harrison & John A. List, 2004. "Field Experiments," Journal of Economic Literature, American Economic Association, vol. 42(4), pages 1009-1055, December.
    5. Rothschild, Michael, 1974. "A two-armed bandit theory of market pricing," Journal of Economic Theory, Elsevier, vol. 9(2), pages 185-202, October.
    6. Hajivassiliou, Vassilis A. & Ruud, Paul A., 1986. "Classical estimation methods for LDV models using simulation," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 40, pages 2383-2441, Elsevier.
    7. Esteves, Rosa-Branca, 2010. "Pricing with customer recognition," International Journal of Industrial Organization, Elsevier, vol. 28(6), pages 669-681, November.
    8. Lee, Lung-Fei, 1995. "Asymptotic Bias in Simulated Maximum Likelihood Estimation of Discrete Choice Models," Econometric Theory, Cambridge University Press, vol. 11(3), pages 437-483, June.
    9. Alessandro Acquisti & Hal R. Varian, 2005. "Conditioning Prices on Purchase History," Marketing Science, INFORMS, vol. 24(3), pages 367-381, May.
    10. Gourieroux, Christian & Monfort, Alain, 1993. "Simulation-based inference : A survey with special reference to panel data models," Journal of Econometrics, Elsevier, vol. 59(1-2), pages 5-33, September.
    11. Brian Kahin & Hal R. Varian (ed.), 2000. "Internet Publishing and Beyond: The Economics of Digital Information and Intellectual Property," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262611597, December.
    12. Arias, Carlos & Cox, Thomas L., 1999. "Maximum Simulated Likelihood: A Brief Introduction For Practitioners," Staff Papers 12662, University of Wisconsin-Madison, Department of Agricultural and Applied Economics.
    13. Carlos Arias & THOMAS L. COX, 1999. "Maximum Simulated Likelihood: A Brief Introduction for Practitioners," Wisconsin-Madison Agricultural and Applied Economics Staff Papers 421, Wisconsin-Madison Agricultural and Applied Economics Department.
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    1. John S. Jatta & Krishna Kumar Krishnan, 2016. "An empirical assessment of a univariate time series for demand planning in a demand-driven supply chain," International Journal of Business Forecasting and Marketing Intelligence, Inderscience Enterprises Ltd, vol. 2(3), pages 269-290.

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    More about this item

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D42 - Microeconomics - - Market Structure, Pricing, and Design - - - Monopoly
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments

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