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Usage-Based Pricing and Demand for Residential Broadband

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  • Aviv Nevo
  • John L. Turner
  • Jonathan W. Williams

Abstract

We estimate demand for residential broadband using high-frequency data from subscribers facing a three-part tariff. The three-part tariff makes data usage during the billing cycle a dynamic problem; thus, generating variation in the (shadow) price of usage. We provide evidence that subscribers respond to this variation, and use their dynamic decisions to estimate a flexible distribution of willingness to pay for different plan characteristics. Using the estimates, we simulate demand under alternative pricing and find that usage-based pricing eliminates low-value traffic. Furthermore, we show that the costs associated with investment in fiber-optic networks are likely recoverable in some markets, but that there is a large gap between social and private incentives to invest.

Suggested Citation

  • Aviv Nevo & John L. Turner & Jonathan W. Williams, 2015. "Usage-Based Pricing and Demand for Residential Broadband," NBER Working Papers 21321, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:21321
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    1. Nicholas Economides & Katja Seim & V. Brian Viard, 2008. "Quantifying the benefits of entry into local phone service," RAND Journal of Economics, RAND Corporation, vol. 39(3), pages 699-730, September.
    2. Greenstein, Shane & McDevitt, Ryan C., 2011. "The broadband bonus: Estimating broadband Internet's economic value," Telecommunications Policy, Elsevier, vol. 35(7), pages 617-632, August.
    3. Adam Copeland & Cyril Monnet, 2009. "The Welfare Effects of Incentive Schemes," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(1), pages 93-113.
    4. Judith Chevalier & Austan Goolsbee, 2009. "Are Durable Goods Consumers Forward-Looking? Evidence from College Textbooks," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(4), pages 1853-1884.
    5. Aviva Aron-Dine & Liran Einav & Amy Finkelstein & Mark R. Cullen, 2012. "Moral Hazard in Health Insurance: How Important Is Forward Looking Behavior?," NBER Working Papers 17802, National Bureau of Economic Research, Inc.
    6. Gregory S. Crawford & Matthew Shum, 2005. "Uncertainty and Learning in Pharmaceutical Demand," Econometrica, Econometric Society, vol. 73(4), pages 1137-1173, July.
    7. Michael D. Grubb & Matthew Osborne, 2015. "Cellular Service Demand: Biased Beliefs, Learning, and Bill Shock," American Economic Review, American Economic Association, vol. 105(1), pages 234-271, January.
    8. Daniel Ackerberg, 2009. "A new use of importance sampling to reduce computational burden in simulation estimation," Quantitative Marketing and Economics (QME), Springer, vol. 7(4), pages 343-376, December.
    9. Sanjog Misra & Harikesh Nair, 2011. "A structural model of sales-force compensation dynamics: Estimation and field implementation," Quantitative Marketing and Economics (QME), Springer, vol. 9(3), pages 211-257, September.
    10. Doug J. Chung & Thomas Steenburgh & K. Sudhir, 2014. "Do Bonuses Enhance Sales Productivity? A Dynamic Structural Analysis of Bonus-Based Compensation Plans," Marketing Science, INFORMS, vol. 33(2), pages 165-187, March.
    11. Anja Lambrecht & Katja Seim & Bernd Skiera, 2007. "Does Uncertainty Matter? Consumer Behavior Under Three-Part Tariffs," Marketing Science, INFORMS, vol. 26(5), pages 698-710, 09-10.
    12. Austan Goolsbee & Peter J. Klenow, 2006. "Valuing Consumer Products by the Time Spent Using Them: An Application to the Internet," American Economic Review, American Economic Association, vol. 96(2), pages 108-113, May.
    13. Rosston Gregory L. & Savage Scott J & Waldman Donald M, 2010. "Household Demand for Broadband Internet in 2010," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 10(1), pages 1-45, September.
    14. Jonathan D. Ketcham & Claudio Lucarelli & Eugenio J. Miravete & M. Christopher Roebuck, 2012. "Sinking, Swimming, or Learning to Swim in Medicare Part D," American Economic Review, American Economic Association, vol. 102(6), pages 2639-2673, October.
    15. Jeremy T. Fox & Kyoo il Kim & Stephen P. Ryan & Patrick Bajari, 2011. "A simple estimator for the distribution of random coefficients," Quantitative Economics, Econometric Society, vol. 2(3), pages 381-418, November.
    16. Patrick Bajari & Jeremy T. Fox & Stephen P. Ryan, 2007. "Linear Regression Estimation of Discrete Choice Models with Nonparametric Distributions of Random Coefficients," American Economic Review, American Economic Association, vol. 97(2), pages 459-463, May.
    17. Benjamin R. Handel, 2013. "Adverse Selection and Inertia in Health Insurance Markets: When Nudging Hurts," American Economic Review, American Economic Association, vol. 103(7), pages 2643-2682, December.
    18. Wesley Hartmann, 2006. "Intertemporal effects of consumption and their implications for demand elasticity estimates," Quantitative Marketing and Economics (QME), Springer, vol. 4(4), pages 325-349, December.
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    More about this item

    JEL classification:

    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications

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