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Evaluating wireless carrier consolidation using semiparametric demand estimation

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  • Patrick Bajari
  • Jeremy Fox
  • Stephen Ryan

Abstract

The US mobile phone service industry has dramatically consolidated over the last two decades. One justification for consolidation is that merged firms can provide consumers with larger coverage areas at lower costs. We estimate the willingness to pay for national coverage to evaluate this motivation for past consolidation. As market level quantity data is not publicly available, we devise an econometric procedure that allows us to estimate the willingness to pay using market share ranks collected from a popular online retailer, Amazon. Our semiparametric maximum score estimator controls for consumers' heterogeneous preferences for carriers, handsets and minutes of calling time. We find that national coverage is strongly valued by consumers, providing an efficiency justification for across-market mergers. The methods we propose can estimate demand for other products using data from Amazon or other online retailers where quantities are not observed, but product ranks are observed. Since Amazon data can easily be gathered by researchers, these methods may be useful for the analysis of other product markets where high quality data are not publicly available.
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Suggested Citation

  • Patrick Bajari & Jeremy Fox & Stephen Ryan, 2008. "Evaluating wireless carrier consolidation using semiparametric demand estimation," Quantitative Marketing and Economics (QME), Springer, vol. 6(4), pages 299-338, December.
    • Handle: RePEc:kap:qmktec:v:6:y:2008:i:4:p:299-338
    DOI: 10.1007/s11129-008-9044-x
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    2. Crawford, Gregory S. & Griffith, Rachel & Iaria, Alessandro, 2021. "A survey of preference estimation with unobserved choice set heterogeneity," Journal of Econometrics, Elsevier, vol. 222(1), pages 4-43.
    3. Jason R. Blevins, 2013. "Non-Standard Rates of Convergence of Criterion-Function-Based Set Estimators," Working Papers 13-02, Ohio State University, Department of Economics.
    4. Marcoux, Mathieu, 2022. "Strategic interactions in mobile network investment with a new entrant and unobserved heterogeneity," International Journal of Industrial Organization, Elsevier, vol. 82(C).
    5. Ting Zhu & Hongju Liu & Pradeep Chintagunta, 2015. "Wireless Carriers’ Exclusive Handset Arrangements: an Empirical Look at the iPhone," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(2), pages 177-190, June.
    6. Ching-I Huang, 2013. "Intra-household effects on demand for telephone service: Empirical evidence," Quantitative Marketing and Economics (QME), Springer, vol. 11(2), pages 231-261, June.
    7. Kretschmer, Tobias & Peukert, Christian, 2014. "Video killed the radio star? Online music videos and digital music sales," LSE Research Online Documents on Economics 60276, London School of Economics and Political Science, LSE Library.
    8. Christopher T. Conlon & Julie Holland Mortimer, 2013. "Demand Estimation under Incomplete Product Availability," American Economic Journal: Microeconomics, American Economic Association, vol. 5(4), pages 1-30, November.
    9. Chris Forman & Anindya Ghose & Avi Goldfarb, 2006. "Geography and Electronic Commerce: Measuring Convenience, Selection, and Price," Working Papers 06-15, NET Institute, revised Sep 2006.
    10. Jeremy T. Fox, 2018. "Estimating matching games with transfers," Quantitative Economics, Econometric Society, vol. 9(1), pages 1-38, March.
    11. Taiju KITANO, 2016. "Measures to Promote Green Cars: Evaluation at the car variant level," Discussion papers 16075, Research Institute of Economy, Trade and Industry (RIETI).
    12. Yan, Jin & Yoo, Hong Il, 2019. "Semiparametric estimation of the random utility model with rank-ordered choice data," Journal of Econometrics, Elsevier, vol. 211(2), pages 414-438.
    13. Paul B. Ellickson & Stephanie Houghton & Christopher Timmins, 2010. "Estimating Network Economies in Retail Chains: A Revealed Preference Approach," NBER Working Papers 15832, National Bureau of Economic Research, Inc.
    14. Jun B. Kim & Paulo Albuquerque & Bart J. Bronnenberg, 2010. "Online Demand Under Limited Consumer Search," Marketing Science, INFORMS, vol. 29(6), pages 1001-1023, 11-12.
    15. Yupin Yang & Mengze Shi & Avi Goldfarb, 2009. "Estimating the Value of Brand Alliances in Professional Team Sports," Marketing Science, INFORMS, vol. 28(6), pages 1095-1111, 11-12.
    16. Suguru Otani, 2021. "Estimating Endogenous Coalitional Mergers: Merger Costs and Assortativeness of Size and Specialization," Papers 2108.12744, arXiv.org, revised Mar 2023.
    17. Michael Thacker & Wesley Wilson, 2015. "Telephony choices and the evolution of cell phones," Journal of Regulatory Economics, Springer, vol. 48(1), pages 1-25, August.
    18. Woroch, Glenn A, 2020. "Spectrum Concentration and Performance of the U.S. Wireless Industry," Department of Economics, Working Paper Series qt8vv381jt, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    19. Glenn A. Woroch, 2020. "Spectrum Concentration and Performance of the U.S. Wireless Industry," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 56(1), pages 73-105, February.

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    More about this item

    Keywords

    Market share ranks; Semiparametric; Demand estimation; Amazon; Mergers; Antitrust; Telecommunications; Mobile phones; Online; Discrete choice; L4; L63; C35; C13; C14;
    All these keywords.

    JEL classification:

    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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