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Analysis and Prediction of Telephone Demand in Local Geographical Areas

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Author Info
Douglas M. Dunn
William H. Williams
W. Allen Spivey
Abstract

An approach to forecasting the demand for local area telephone service is presented in this paper. The specific problem discussed is the forecasting of main stations in three Michigan metropolitan areas. Several different statistical models are used. The first class of models introduced used adaptive exponential smoothing and is based solely on the past history of the time series involved. Although appropriate data at the local area level are very difficult to obtain, two exogenous time series related to household formation are used to construct more elaborate models for one of the areas. The various models are evaluated by both the average absolute and the root-mean-square forecast error. In terms of these criteria, the first class of models referred to above performs reasonably well while the second set does considerably better. This argues strongly that future improvements in forecasting accuracy will be made by the more extensive involvement of exogenous variables.

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Publisher Info
Article provided by The RAND Corporation in its journal Bell Journal of Economics.

Volume (Year): 2 (1971)
Issue (Month): 2 (Autumn)
Pages: 561-576
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Handle: RePEc:rje:bellje:v:2:y:1971:i:autumn:p:561-576

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  1. Xavier Mancero & Eduardo Saavedra, 2006. "Un modelo de entrada y competencia en telecomunicaciones," Revista de Analisis Economico – Economic Analysis Review, Ilades-Georgetown University, Economics Department, vol. 21(1), pages 29-57, July. [Downloadable!]
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  2. Eduardo Saavedra & Xavier Mancero, . "Entry, Cream Skimming, and Competition: Theory and Simulation for Chile's Local Telephony Market," ILADES-Georgetown University Working Papers inv132, Ilades-Georgetown University, School of Economics and Bussines. [Downloadable!]
  3. John J. Beggs, 1981. "The Demand for Telephone Services in Australia and the Welfare Implications of Alternative Pricing Policies," Cowles Foundation Discussion Papers 584, Cowles Foundation, Yale University. [Downloadable!]
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