Forecasting telecommunications data with linear models
For 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.
If 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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
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|
|Order Information:|| Postal: http://www.elsevier.com/wps/find/journaldescription.cws_home/30471/bibliographic|
References listed on IDEAS
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.:
- Fildes, Robert, 1992. "The evaluation of extrapolative forecasting methods," International Journal of Forecasting, Elsevier, vol. 8(1), pages 81-98, June.
- 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.
- 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.
- Grambsch, Patricia & Stahel, Werner A., 1990. "Forecasting demand for special telephone services: A case study," International Journal of Forecasting, Elsevier, vol. 6(1), pages 53-64.
- Everette S. Gardner, Jr. & Ed. Mckenzie, 1985. "Forecasting Trends in Time Series," Management Science, INFORMS, vol. 31(10), pages 1237-1246, October.
- 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.
- Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
When requesting a correction, please mention this item's handle: RePEc:eee:telpol:v:31:y:2007:i:1:p:31-44. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Shamier, Wendy)
If references are entirely missing, you can add them using this form.