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Forecasting aggregate and disaggregate energy consumption using arima models: A literature survey

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  • Samuel Asuamah Yeboah
  • Manu Ohene
  • T.B. Wereko

Abstract

The paper is aimed at contributing to the body of knowledge that exist in the area of energy forecasting by reviewing relevant empirical works on energy forecasting using ARIMA models. This paper is relevant in the face of frequent power outage and the dependence on external economies for energy supply. The study is based on secondary data obtained from electronic journals through archival studies. In all 10 articles were selected through purposive sampling method and were analysis using content analysis method. The results indicate that future energy consumption is expected to increase in economies in which these forecasts have been done. Hence, energy use must be efficient to avoid energy crisis in future. Future research should look at review of works on forecasting in a comparative manner comparing other models that have been used in forecasting energy demand. The paper is limited by the use of only secondary data. Errors in variables and omissions may not be known by the researchers. The findings may also lack external validity since the sample size is small and was selected by non probability sample.

Suggested Citation

  • Samuel Asuamah Yeboah & Manu Ohene & T.B. Wereko, 2012. "Forecasting aggregate and disaggregate energy consumption using arima models: A literature survey," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 1(2), pages 1-7.
  • Handle: RePEc:spt:stecon:v:1:y:2012:i:2:f:1_2_7
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    Cited by:

    1. Samuel Yeboah Asuamah & Joseph Ohene-Manu, 2015. "An Econometric Investigation of Forecasting Premium Fuel," International Journal of Energy Economics and Policy, Econjournals, vol. 5(3), pages 716-724.
    2. Sen, Parag & Roy, Mousumi & Pal, Parimal, 2016. "Application of ARIMA for forecasting energy consumption and GHG emission: A case study of an Indian pig iron manufacturing organization," Energy, Elsevier, vol. 116(P1), pages 1031-1038.

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