IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/21321.html
   My bibliography  Save this paper

Usage-Based Pricing and Demand for Residential Broadband

Author

Listed:
  • 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
    Note: IO PR
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w21321.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    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. 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.
    5. 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.
    6. Aviva Aron-Dine & Liran Einav & Amy Finkelstein & Mark Cullen, 2012. "Moral hazard in health insurance: How important is forward looking behavior?," Discussion Papers 11-007, Stanford Institute for Economic Policy Research.
    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. 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.
    9. Gregory S. Crawford & Matthew Shum, 2005. "Uncertainty and Learning in Pharmaceutical Demand," Econometrica, Econometric Society, vol. 73(4), pages 1137-1173, July.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Johannes Abeler & David Huffman & Colin Raymond, 2023. "Incentive Complexity, Bounded Rationality and Effort Provision," Economics Series Working Papers 1012, University of Oxford, Department of Economics.
    2. Abeler, Johannes & Huffman, David B. & Raymond, Collin, 2023. "Incentive Complexity, Bounded Rationality and Effort Provision," IZA Discussion Papers 16284, Institute of Labor Economics (IZA).
    3. 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.
    4. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Invited Paper ---Learning Models: An Assessment of Progress, Challenges, and New Developments," Marketing Science, INFORMS, vol. 32(6), pages 913-938, November.
    5. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Learning Models: An Assessment of Progress, Challenges and New Developments," Economics Papers 2013-W07, Economics Group, Nuffield College, University of Oxford.
    6. Christos Genakos & Costas Roumanias & Tommaso Valletti, 2015. "Loss Aversion on the Phone," CEP Discussion Papers dp1373, Centre for Economic Performance, LSE.
    7. Martin Gaynor & Kate Ho & Robert J. Town, 2015. "The Industrial Organization of Health-Care Markets," Journal of Economic Literature, American Economic Association, vol. 53(2), pages 235-284, June.
    8. Cai, Xiqian & Jiang, Wei & Song, Hong & Xie, Huihua, 2022. "Pay for performance schemes and manufacturing worker productivity: Evidence from a kinked design in China," Journal of Development Economics, Elsevier, vol. 156(C).
    9. Hema Yoganarasimhan, 2013. "The Value of Reputation in an Online Freelance Marketplace," Marketing Science, INFORMS, vol. 32(6), pages 860-891, November.
    10. Hoffman, Mitchell & Burks, Stephen V., 2017. "Worker Overconfidence: Field Evidence and Implications for Employee Turnover and Returns from Training," IZA Discussion Papers 10794, Institute of Labor Economics (IZA).
    11. Gabriel Ahlfeldt & Pantelis Koutroumpis & Tommaso Valletti, 2017. "Speed 2.0: Evaluating Access to Universal Digital Highways," Journal of the European Economic Association, European Economic Association, vol. 15(3), pages 586-625.
    12. Andrew Ching & Susumu Imai & Masakazu Ishihara & Neelam Jain, 2012. "A practitioner’s guide to Bayesian estimation of discrete choice dynamic programming models," Quantitative Marketing and Economics (QME), Springer, vol. 10(2), pages 151-196, June.
    13. Genakos, Christos & Roumanias, Costas & Valletti, Tommaso, 2023. "Is having an expert “friend” enough? An analysis of consumer switching behavior in mobile telephony," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 359-372.
    14. Zarek C. Brot-Goldberg & Amitabh Chandra & Benjamin R. Handel & Jonathan T. Kolstad, 2017. "What does a Deductible Do? The Impact of Cost-Sharing on Health Care Prices, Quantities, and Spending Dynamics," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(3), pages 1261-1318.
    15. Jacob Malone & Aviv Nevo & Jonathan Williams, 2016. "The Tragedy of the Last Mile: Congestion Externalities in Broadband Networks," Working Papers 16-20, NET Institute.
    16. Arun Gopalakrishnan & Raghuram Iyengar & Robert J. Meyer, 2015. "Consumer Dynamic Usage Allocation and Learning Under Multipart Tariffs," Marketing Science, INFORMS, vol. 34(1), pages 116-133, January.
    17. Hai Che & Tülin Erdem & T. Sabri Öncü, 2015. "Consumer learning and evolution of consumer brand preferences," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 173-202, September.
    18. Prieger, James E., 2013. "The broadband digital divide and the economic benefits of mobile broadband for rural areas," Telecommunications Policy, Elsevier, vol. 37(6), pages 483-502.
    19. 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.
    20. Christina M. Dalton & Gautam Gowrisankaran & Robert Town, 2015. "Salience, Myopia, and Complex Dynamic Incentives: Evidence from Medicare Part D," NBER Working Papers 21104, National Bureau of Economic Research, Inc.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nbr:nberwo:21321. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.