Evaluating wireless carrier consolidation using semiparametric demand estimation

被引:16
|
作者
Bajari, Patrick [2 ,3 ]
Fox, Jeremy T. [1 ]
Ryan, Stephen P. [3 ,4 ]
机构
[1] Univ Chicago, Chicago, IL 60637 USA
[2] Univ Minnesota, Minneapolis, MN USA
[3] Natl Bur Econ Res, Cambridge, MA 02138 USA
[4] MIT, Cambridge, MA 02139 USA
来源
QME-QUANTITATIVE MARKETING AND ECONOMICS | 2008年 / 6卷 / 04期
基金
美国国家科学基金会;
关键词
Market share ranks; Semiparametric; Demand estimation; Amazon; Mergers; Antitrust; Telecommunications; Mobile phones; Online; Discrete choice;
D O I
10.1007/s11129-008-9044-x
中图分类号
F [经济];
学科分类号
02 ;
摘要
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 justification for past consolidation. As market level quantity data are not publicly available, we devise an econometric procedure that allows us to estimate the willingness to pay using market share ranks collected from the 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 online retailers where product ranks, but not quantities, are observed.
引用
收藏
页码:299 / 338
页数:40
相关论文
共 50 条
  • [31] Efficient Carrier Frequency Offset Estimation in Wireless Sensor Networks
    Liu, Siqi
    Wang, Shaowei
    IEEE SENSORS LETTERS, 2023, 7 (05)
  • [32] Carrier frequency offset estimation for MIMO single-carrier FDMA system in wireless communication
    Badran, Ehab F. F.
    Samara, Marwa
    Ismail, Nour Eldin
    ALEXANDRIA ENGINEERING JOURNAL, 2022, 61 (09) : 6907 - 6917
  • [33] Estimation and inference of semiparametric models using data from several sources
    Buchinsky, Moshe
    Li, Fanghua
    Liao, Zhipeng
    JOURNAL OF ECONOMETRICS, 2022, 226 (01) : 80 - 103
  • [34] Prediction of global ionospheric TEC using the semiparametric kernel estimation method
    Wang XiJiang
    Bian ShaoFeng
    Li ZiShen
    Jiang Ke
    Ren QingYang
    Pan Xiong
    CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION, 2020, 63 (04): : 1271 - 1281
  • [35] Algorithm for Evaluating the Difficulty of Land Consolidation Using Cadastral Data
    Maciag, Michal
    Maciag, Klaudia
    Len, Przemyslaw
    SUSTAINABILITY, 2024, 16 (13)
  • [36] SEMIPARAMETRIC ESTIMATION OF COVARIATE EFFECTS USING THE POSITIVE STABLE FRAILTY MODEL
    WANG, ST
    KLEIN, JP
    MOESCHBERGER, ML
    APPLIED STOCHASTIC MODELS AND DATA ANALYSIS, 1995, 11 (02): : 121 - 133
  • [37] Small Area Estimation Using a Semiparametric Spatial Model with Application in Insurance
    Hosseini, Seyede Elahe
    Shahsavani, Davood
    Rabiei, Mohammad Reza
    Arashi, Mohammad
    Baghishani, Hossein
    SYMMETRY-BASEL, 2022, 14 (10):
  • [38] Causal estimation using semiparametric transformation models under prevalent sampling
    Cheng, Yu-Jen
    Wang, Mei-Cheng
    BIOMETRICS, 2015, 71 (02) : 302 - 312
  • [39] Evaluating On-Demand Data Collection with Mobile Elements in Wireless Sensor Networks
    He, Liang
    Zhuang, Yanyan
    Pan, Jianping
    Xu, Jingdong
    2010 IEEE 72ND VEHICULAR TECHNOLOGY CONFERENCE FALL, 2010,
  • [40] Wideband channel estimation and prediction in single-carrier wireless systems
    Liu, W
    Yang, LL
    Hanzo, L
    VTC2005-SPRING: 2005 IEEE 61ST VEHICULAR TECHNOLOGY CONFERENCE, VOLS 1-5, PROCEEDINGS, 2005, : 543 - 547