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Turkish Aggregate Electricity Demand: An Outlook to 2020

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Listed:
  • Zafer Dilaver

    () (Surrey Energy Economics Centre (SEEC), Department of Economics, University of Surrey)

  • Lester C Hunt

    () (Surrey Energy Economics Centre (SEEC), Department of Economics, University of Surrey)

Abstract

This paper investigates the relationship between Turkish aggregate electricity consumption, GDP and electricity prices in order to forecast future Turkish aggregate electricity demand. To achieve this, an aggregate electricity demand function for Turkey is estimated by applying the structural time series technique to annual data over the period 1960 to 2008. The results suggest that GDP, electricity prices and an underlying energy demand trend (UEDT) are all important drivers of Turkish electricity demand. The estimated income and price elasticities are found to be 0.17 and -0.11 respectively with the estimated UEDT found to be generally upward sloping (electricity using) but at a generally decreasing rate. Based on the estimated equation, and different forecast assumptions, it is predicted that Turkish aggregate electricity demand will be somewhere between 259 TWh and 368 TWh in 2020.

Suggested Citation

  • Zafer Dilaver & Lester C Hunt, 2011. "Turkish Aggregate Electricity Demand: An Outlook to 2020," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 132, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
  • Handle: RePEc:sur:seedps:132
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    References listed on IDEAS

    as
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    Cited by:

    1. Alkhathlan, Khalid & Javid, Muhammad, 2015. "Carbon emissions and oil consumption in Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 105-111.
    2. Adom, Philip Kofi & Bekoe, William, 2012. "Conditional dynamic forecast of electrical energy consumption requirements in Ghana by 2020: A comparison of ARDL and PAM," Energy, Elsevier, vol. 44(1), pages 367-380.
    3. Javid, Muhammad & Qayyum, Abdul, 2014. "Electricity consumption-GDP nexus in Pakistan: A structural time series analysis," Energy, Elsevier, vol. 64(C), pages 811-817.
    4. Tanrisever, Fehmi & Derinkuyu, Kursad & Heeren, Michael, 2013. "Forecasting electricity infeed for distribution system networks: An analysis of the Dutch case," Energy, Elsevier, vol. 58(C), pages 247-257.
    5. Özer, Betül & Görgün, Erdem & İncecik, Selahattin, 2013. "The scenario analysis on CO2 emission mitigation potential in the Turkish electricity sector: 2006–2030," Energy, Elsevier, vol. 49(C), pages 395-403.
    6. Sakmani, Ahmad Safwan & Lam, Wei-Haur & Hashim, Roslan & Chong, Heap-Yih, 2013. "Site selection for tidal turbine installation in the Strait of Malacca," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 590-602.
    7. Mirlatifi, A.M. & Egelioglu, F. & Atikol, U., 2015. "An econometric model for annual peak demand for small utilities," Energy, Elsevier, vol. 89(C), pages 35-44.
    8. repec:eee:rensus:v:75:y:2017:i:c:p:123-136 is not listed on IDEAS
    9. Hamzacebi, Coskun & Es, Huseyin Avni, 2014. "Forecasting the annual electricity consumption of Turkey using an optimized grey model," Energy, Elsevier, vol. 70(C), pages 165-171.
    10. Du, Gang & Lin, Wei & Sun, Chuanwang & Zhang, Dingzhong, 2015. "Residential electricity consumption after the reform of tiered pricing for household electricity in China," Applied Energy, Elsevier, vol. 157(C), pages 276-283.
    11. Ackah, Ishmael, 2015. "On the relationship between energy consumption, productivity and economic growth: Evidence from Algeria, Ghana, Nigeria and South Africa," MPRA Paper 64887, University Library of Munich, Germany.
    12. Jian Chai & Shubin Wang & Shouyang Wang & Ju’e Guo, 2012. "Demand Forecast of Petroleum Product Consumption in the Chinese Transportation Industry," Energies, MDPI, Open Access Journal, vol. 5(3), pages 1-22, March.
    13. Lin, Boqiang & Wu, Ya & Zhang, Li, 2012. "Electricity saving potential of the power generation industry in China," Energy, Elsevier, vol. 40(1), pages 307-316.
    14. repec:eco:journ2:2017-04-33 is not listed on IDEAS
    15. Gouveia, João Pedro & Fortes, Patrícia & Seixas, Júlia, 2012. "Projections of energy services demand for residential buildings: Insights from a bottom-up methodology," Energy, Elsevier, vol. 47(1), pages 430-442.
    16. Arisoy, Ibrahim & Ozturk, Ilhan, 2014. "Estimating industrial and residential electricity demand in Turkey: A time varying parameter approach," Energy, Elsevier, vol. 66(C), pages 959-964.
    17. Atalla, Tarek N. & Hunt, Lester C., 2016. "Modelling residential electricity demand in the GCC countries," Energy Economics, Elsevier, vol. 59(C), pages 149-158.

    More about this item

    Keywords

    Turkish Turkish Aggregate Electricity Demand; Structural Time Series Model (STSM); Energy Demand Modelling and Future Scenarios.;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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