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Determinants of Mobile Penetration to Forecast New Broadband Adoption: OECD Case

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  • Lütfü Şağbanşua
  • Osman Şahin
  • Muhterem Çöl

Abstract

This paper aims to analyze relationship between Mobile penetration and various indicators of communication infrastructure throughout OECD countries. Panel data is utilized for the purpose of this study. In order to control network effects as well as the endogeneity of variables, the Arellano–Bond dynamic panel estimation is adopted. In particular, this paper attempts to identify what are the factors to promote the 3G mobile phone by using dynamic panel data analysis. In constructing an estimation model, Cellular mobile penetration is taken as a dependent variable, while various technical and economic variables are selected as independent variables. The obtained results can be used to forecast adoption of New Broadband Penetration technology.

Suggested Citation

  • Lütfü Şağbanşua & Osman Şahin & Muhterem Çöl, 2015. "Determinants of Mobile Penetration to Forecast New Broadband Adoption: OECD Case," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 3(2), pages 35-40, December.
  • Handle: RePEc:anm:alpnmr:v:3:y:2015:i:2:p:35-40
    DOI: http://dx.doi.org/10.17093/aj.2015.3.2.5000140094
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    References listed on IDEAS

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    1. Gruber, Harald & Verboven, Frank, 2001. "The evolution of markets under entry and standards regulation -- the case of global mobile telecommunications," International Journal of Industrial Organization, Elsevier, vol. 19(7), pages 1189-1212, July.
    2. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    3. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LP, vol. 9(1), pages 86-136, March.
    4. Xia, Jun, 2011. "The third-generation-mobile (3G) policy and deployment in China: Current status, challenges, and prospects," Telecommunications Policy, Elsevier, vol. 35(1), pages 51-63, February.
    5. Kang, Fei & Hauge, Janice A. & Lu, Ting-Jie, 2012. "Competition and mobile network investment in China’s telecommunications industry," Telecommunications Policy, Elsevier, vol. 36(10), pages 901-913.
    6. David Roodman, 2006. "How to Do xtabond2," North American Stata Users' Group Meetings 2006 8, Stata Users Group.
    7. Distaso, Walter & Lupi, Paolo & Manenti, Fabio M., 2006. "Platform competition and broadband uptake: Theory and empirical evidence from the European union," Information Economics and Policy, Elsevier, vol. 18(1), pages 87-106, March.
    8. Norazah Mohd Suki, 2011. "Subscribers’ intention towards using 3G mobile services," Journal of Economics and Behavioral Studies, AMH International, vol. 2(2), pages 67-75.
    9. Antonio Estache & T. Valletti & M. Manacorda, 2002. "Telecoms, Reform, Access Regulation and Internet Adoption in Latin America," ULB Institutional Repository 2013/43982, ULB -- Universite Libre de Bruxelles.
    10. Akematsu, Yuji & Shinohara, Sobee & Tsuji, Masatsugu, 2012. "Empirical analysis of factors promoting the Japanese 3G mobile phone," Telecommunications Policy, Elsevier, vol. 36(3), pages 175-186.
    11. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    12. Antonio Estache & Marco Manacorda & Tommaso M. Valletti, 2002. "Telecommunications Reform, Access Regulation, and Internet Adoption in Latin America," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Spring 20), pages 153-218, January.
    13. Andrés, Luis & Cuberes, David & Diouf, Mame & Serebrisky, Tomás, 0. "The diffusion of the Internet: A cross-country analysis," Telecommunications Policy, Elsevier, vol. 34(5-6), pages 323-340, June.
    14. Lin, Mao-Shong & Wu, Feng-Shang, 2013. "Identifying the determinants of broadband adoption by diffusion stage in OECD countries," Telecommunications Policy, Elsevier, vol. 37(4), pages 241-251.
    15. Garcia-Murillo, Martha, 2005. "International Broadband Deployment: The Impact of Unbundling," MPRA Paper 2442, University Library of Munich, Germany.
    16. Margherita Pagani, 2006. "Determinants of adoption of High Speed Data Services in the business market : Evidence for a combined technology acceptance model with task technology fit model," Post-Print hal-02313097, HAL.
    17. Singh, Sanjay Kumar, 0. "The diffusion of mobile phones in India," Telecommunications Policy, Elsevier, vol. 32(9-10), pages 642-651, October.
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    More about this item

    Keywords

    Communication; Forecast; Mobile Penetration; New Broadband Adoption; OECD; Panel Data Analysis;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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