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Estimating demand for cellular phone service under nonlinear pricing

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  • Ching-I Huang

Abstract

Cellular phone carriers typically offer complicated nonlinear tariffs. Consumers make a discrete choice among several rate plans. Each plan has a nonlinear price schedule, and price is usually lower for in-network calls. I present an empirical framework to estimate demand under such nonlinear pricing schemes by using parsimonious data and apply the estimation method to analyze the cellular phone service market in Taiwan. Based on the estimated model, I evaluate the impacts of termination-based pricing schemes on the market structure. While the existence of in-network discounts causes considerable tipping effects on market shares, the effects come primarily from reducing the average prices, not from the difference between in-network and off-network prices. There is no evidence showing that termination-based pricing by itself has significant effects on market structure.
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Suggested Citation

  • Ching-I Huang, 2008. "Estimating demand for cellular phone service under nonlinear pricing," Quantitative Marketing and Economics (QME), Springer, vol. 6(4), pages 371-413, December.
  • Handle: RePEc:kap:qmktec:v:6:y:2008:i:4:p:371-413
    DOI: 10.1007/s11129-008-9040-1
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    3. Shi, Mengze & Yang, Botao & Chiang, Jeongwen, 2018. "Dyad Calling Behavior: Asymmetric Power and Tie Strength Dynamics," Journal of Interactive Marketing, Elsevier, vol. 42(C), pages 63-79.
    4. Koichiro Ito, 2014. "Do Consumers Respond to Marginal or Average Price? Evidence from Nonlinear Electricity Pricing," American Economic Review, American Economic Association, vol. 104(2), pages 537-563, February.
    5. Kim, Hyun-gyu, 2019. "Estimating demand response in an extreme block pricing environment: Evidence from Korea's electricity pricing system, 2005–2014," Energy Policy, Elsevier, vol. 132(C), pages 1076-1086.
    6. Fruchter, Gila E. & Sigué, Simon P., 2013. "Dynamic pricing for subscription services," Journal of Economic Dynamics and Control, Elsevier, vol. 37(11), pages 2180-2194.
    7. Gadi Fibich & Roy Klein & Oded Koenigsberg & Eitan Muller, 2017. "Optimal Three-Part Tariff Plans," Operations Research, INFORMS, vol. 65(5), pages 1177-1189, October.
    8. Dalton, Christina M., 2014. "Estimating demand elasticities using nonlinear pricing," International Journal of Industrial Organization, Elsevier, vol. 37(C), pages 178-191.
    9. Sridhar Narayanan & Pradeep Chintagunta & Eugenio Miravete, 2007. "The role of self selection, usage uncertainty and learning in the demand for local telephone service," Quantitative Marketing and Economics (QME), Springer, vol. 5(1), pages 1-34, March.
    10. 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.
    11. Jiekai ZHANG, 2016. "The impact of advertising length caps on TV: Evidence from the French broadcast TV industry," Working Papers 16-06, NET Institute.
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    More about this item

    Keywords

    Termination-based price discrimination; Optional rate plans; Cellular phone service; Structural estimation; Three-part tariffs; C35; L11; L15; L96;
    All these keywords.

    JEL classification:

    • L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality

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