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. 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, 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.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 14739.
Date of creation: 2007
Date of revision:
Publication status: Published in Telecommunications Policy 1.31(2007): pp. 31-44
linear models; ITU Recommendations; telecommunications forecasting;
Other versions of this item:
- Madden, Gary & Tan, Joachim, 2007. "Forecasting telecommunications data with linear models," Telecommunications Policy, Elsevier, vol. 31(1), pages 31-44, February.
- L96 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Telecommunications
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