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

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

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.

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File URL: http://hdl.handle.net/10.1002/mde.1513
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Article provided by John Wiley & Sons, Ltd. in its journal Managerial and Decision Economics.

Volume (Year): 32 (2011)
Issue (Month): 1 (January)
Pages: 1-15

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Handle: RePEc:wly:mgtdec:v:32:y:2011:i:1:p:1-15
Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/7976

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  1. Esteves, Rosa-Branca, 2010. "Pricing with customer recognition," International Journal of Industrial Organization, Elsevier, vol. 28(6), pages 669-681, November.
  2. Lee, Lung-Fei, 1995. "Asymptotic Bias in Simulated Maximum Likelihood Estimation of Discrete Choice Models," Econometric Theory, Cambridge University Press, vol. 11(03), pages 437-483, June.
  3. 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.
  4. Oksana Loginova & Curtis R. Taylor, 2005. "Price Experimentation with Strategic Buyers," Working Papers 0509, Department of Economics, University of Missouri.
  5. Glenn Harrison & John List, 2004. "Field experiments," Artefactual Field Experiments 00058, The Field Experiments Website.
  6. Alessandro Acquisti & Hal R. Varian, 2005. "Conditioning Prices on Purchase History," Marketing Science, INFORMS, vol. 24(3), pages 367-381, May.
  7. 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, June.
  8. Vassilis A. Hajivassiliou & Paul A. Ruud, 1993. "Classical Estimation Methods for LDV Models Using Simulation," Cowles Foundation Discussion Papers 1051, Cowles Foundation for Research in Economics, Yale University.
  9. 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.
  10. Aghion, P. & Bolton, P. & Harris, C. & Jullien, B., 1990. "Optimal Learning By Experimentation," DELTA Working Papers 90-10, DELTA (Ecole normale supérieure).
  11. Rothschild, Michael, 1974. "A two-armed bandit theory of market pricing," Journal of Economic Theory, Elsevier, vol. 9(2), pages 185-202, October.
  12. Aghion, Philippe, et al, 1991. "Optimal Learning by Experimentation," Review of Economic Studies, Wiley Blackwell, vol. 58(4), pages 621-54, July.
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