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Modelling and Forecasting Mobile Telecommunication Services: The case of Greece



In this paper we try to model the adoption pattern of mobile telecommunication services into the Greek market for the period from 1993 to 2005. Two separate sigmoid curves, the Gompertz and the Logistic, are fitted to the observed number of subscribers by means of non-linear least squares. The in-sample fit to data favoured the use of the Logistic curve in describing the diffusion process, fact which is further supported by Frances’ parametric test (1994b). The dominance of the Logistic curve over the Gompertz is also verified via a pseudo out-of-sample forecasting exercise. Furthermore, an attempt is made to predict the expected number of subscribers up to 2015, solely based on the Logistic curve. Taking into account the prediction’s uncertainty, the variance of the forecast errors is calculated utilising the non-parametric bootstrap method. Our empirical results reached to three conclusions. First, the introduction of the pre-paid mobile telephony in 1997 along with the entry of the third mobile operator in 1998 has boosted the diffusion process in Greece; second, the levelling-off process in the diffusion of mobile phones has already begun; finally, the average expected growth rate in new subscribers is less than half percent for the period between 2006 and 2015.

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  • Theologos Dergiades & Apostolos Dasilas, 2009. "Modelling and Forecasting Mobile Telecommunication Services: The case of Greece," Discussion Paper Series 2009_13, Department of Economics, University of Macedonia, revised Sep 2009.
  • Handle: RePEc:mcd:mcddps:2009_13

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    References listed on IDEAS

    1. Romeo, Anthony A, 1977. "The Rate of Imitation of a Capital-Embodied Process Innovation," Economica, London School of Economics and Political Science, vol. 44(173), pages 63-69, February.
    2. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    3. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    4. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-259, April.
    5. Gruber, Harald & Verboven, Frank, 2001. "The diffusion of mobile telecommunications services in the European Union," European Economic Review, Elsevier, vol. 45(3), pages 577-588, March.
    6. Minkyu Lee & Youngsang Cho, 2007. "The diffusion of mobile telecommunications services in Korea," Applied Economics Letters, Taylor & Francis Journals, vol. 14(7), pages 477-481.
    7. Silvia Massini, 2004. "The diffusion of mobile telephony in Italy and the UK: an empirical investigation," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 13(3), pages 251-277.
    8. Pedro Pereira & José C. Pernías-Cerrillo, 2005. "The Diffusion of Cellular Telephony in Portugal before UMTS: A Time Series Approach," Working Papers 08, Portuguese Competition Authority.
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    Cited by:

    1. Yamakawa, Peter & Rees, Gareth H. & Manuel Salas, José & Alva, Nikolai, 2013. "The diffusion of mobile telephones: An empirical analysis for Peru," Telecommunications Policy, Elsevier, vol. 37(6), pages 594-606.
    2. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.

    More about this item


    Electricity Demand; ARDL; Cointegration.;

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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