Forecasting telecommunications data with linear models
Gary Madden and
Joachim Tan
MPRA Paper from University Library of Munich, Germany
Abstract:
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. 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.
Keywords: linear models; ITU Recommendations; telecommunications forecasting (search for similar items in EconPapers)
JEL-codes: L96 (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (5)
Published in Telecommunications Policy 1.31(2007): pp. 31-44
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Journal Article: Forecasting telecommunications data with linear models (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:14739
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