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Economic variables and electricity consumption in Northern Cyprus

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  • Egelioglu, F.
  • Mohamad, A.A.
  • Guven, H.

Abstract

The influence of economic variables on the annual electricity consumption in N. Cyprus for the period of 1988–1997 has been investigated. Utilising historical energy consumption, historical economic databases and multiple regression analyses, it was found that the number of customers, the price of electricity and the number of tourists correlate with the annual electricity consumption. The annual energy consumption was strongly related to the number of the customers, with adjusted R2 equal to 0.906 and 0.930 if the price of electricity and the number of tourists were included in the model. The results indicate that the model using the number of customers, the number of tourists and the electricity prices as regressors has very strong predictive ability and can be used to forecast future annual electricity consumption.

Suggested Citation

  • Egelioglu, F. & Mohamad, A.A. & Guven, H., 2001. "Economic variables and electricity consumption in Northern Cyprus," Energy, Elsevier, vol. 26(4), pages 355-362.
    • Handle: RePEc:eee:energy:v:26:y:2001:i:4:p:355-362
    DOI: 10.1016/S0360-5442(01)00008-1
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    References listed on IDEAS

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    1. Lam, Joseph C., 1996. "An analysis of residential sector energy use in Hong Kong," Energy, Elsevier, vol. 21(1), pages 1-8.
    2. Michalik, G. & Khan, M.E. & Bonwick, W.J. & Mielczarski, W., 1997. "Structural modelling of energy demand in the residential sector: 2. The use of linguistic variables to include uncertainty of customers' behaviour," Energy, Elsevier, vol. 22(10), pages 949-958.
    3. Abdel-Aal, R.E. & Al-Garni, A.Z. & Al-Nassar, Y.N., 1997. "Modelling and forecasting monthly electric energy consumption in eastern Saudi Arabia using abductive networks," Energy, Elsevier, vol. 22(9), pages 911-921.
    4. Yee Yan, Yuk, 1998. "Climate and residential electricity consumption in Hong Kong," Energy, Elsevier, vol. 23(1), pages 17-20.
    5. Sheinbaum, C. & Martínez, M. & Rodríguez, L., 1996. "Trends and prospects in Mexican residential energy use," Energy, Elsevier, vol. 21(6), pages 493-504.
    6. Abdel-Aal, R.E. & Al-Garni, A.Z., 1997. "Forecasting monthly electric energy consumption in eastern Saudi Arabia using univariate time-series analysis," Energy, Elsevier, vol. 22(11), pages 1059-1069.
    7. Ranjan, Manish & Jain, V.K., 1999. "Modelling of electrical energy consumption in Delhi," Energy, Elsevier, vol. 24(4), pages 351-361.
    8. Michalik, G. & Khan, M.E. & Bonwick, W.J. & Mielczarski, W., 1997. "Structural modelling of energy demand in the residential sector: 1. Development of structural models," Energy, Elsevier, vol. 22(10), pages 937-947.
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