Forecasting telecommunications data with linear models
AbstractFor telecommunication companies to successfully manage their business, companies rely on mapping future trends and usage patterns. However, the evolution of telecommunications technology and systems in the provision of services renders imperfections in telecommunications data and impinges on a company's' ability to properly evaluate and plan their business. International Telecommunication Union (ITU) Recommendation E.507 provides a selection of econometric models for forecasting these trends. However, no specific guidance is given. This paper evaluates whether simple extrapolation techniques in Recommendation E.507 can generate accurate forecasts. Standard forecast error statistics--mean absolute percentage error (MAPE), median absolute percentage error and percentage better--show the ARIMA, Holt and Holt-D models provide better forecasts than a random walk and other linear extrapolation methods.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Elsevier in its journal Telecommunications Policy.
Volume (Year): 31 (2007)
Issue (Month): 1 (February)
Contact details of provider:
Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/30471/description#description
Other versions of this item:
- Madden, Gary G & Tan, Joachim, 2007. "Forecasting telecommunications data with linear models," MPRA Paper 14739, University Library of Munich, Germany.
- L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Makridakis, Spyros & Chatfield, Chris & Hibon, Michele & Lawrence, Michael & Mills, Terence & Ord, Keith & Simmons, LeRoy F., 1993. "The M2-competition: A real-time judgmentally based forecasting study," International Journal of Forecasting, Elsevier, vol. 9(1), pages 5-22, April.
- Grubesic, Tony H. & Murray, Alan T., 2005. "Geographies of imperfection in telecommunication analysis," Telecommunications Policy, Elsevier, vol. 29(1), pages 69-94, February.
- Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
- Fildes, Robert, 1992. "The evaluation of extrapolative forecasting methods," International Journal of Forecasting, Elsevier, vol. 8(1), pages 81-98, June.
- Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June.
- Fildes, Robert & Hibon, Michele & Makridakis, Spyros & Meade, Nigel, 1998. "Generalising about univariate forecasting methods: further empirical evidence," International Journal of Forecasting, Elsevier, vol. 14(3), pages 339-358, September.
- Mack, Elizabeth A. & Grubesic, Tony H., 2009. "Forecasting broadband provision," Information Economics and Policy, Elsevier, vol. 21(4), pages 297-311, November.
If references are entirely missing, you can add them using this form.