[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/p/sur/seedps/132.html
   My bibliography  Save this paper

Turkish Aggregate Electricity Demand: An Outlook to 2020

Author

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
    as

    Download full text from publisher

    File URL: https://repec.som.surrey.ac.uk/seeds/SEEDS132.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Hamzacebi, Coskun, 2007. "Forecasting of Turkey's net electricity energy consumption on sectoral bases," Energy Policy, Elsevier, vol. 35(3), pages 2009-2016, March.
    2. Hunt, Lester C. & Judge, Guy & Ninomiya, Yasushi, 2003. "Underlying trends and seasonality in UK energy demand: a sectoral analysis," Energy Economics, Elsevier, vol. 25(1), pages 93-118, January.
    3. Amarawickrama, Himanshu A. & Hunt, Lester C., 2008. "Electricity demand for Sri Lanka: A time series analysis," Energy, Elsevier, vol. 33(5), pages 724-739.
    4. Dilaver, Zafer & Hunt, Lester C, 2011. "Modelling and forecasting Turkish residential electricity demand," Energy Policy, Elsevier, vol. 39(6), pages 3117-3127, June.
    5. Erol Taymaz & Kamil Yılmaz, 2008. "Integration with the Global Economy: The Case of Turkish Automobile and Consumer Electronics Industries," Koç University-TUSIAD Economic Research Forum Working Papers 0801, Koc University-TUSIAD Economic Research Forum.
    6. Akay, Diyar & Atak, Mehmet, 2007. "Grey prediction with rolling mechanism for electricity demand forecasting of Turkey," Energy, Elsevier, vol. 32(9), pages 1670-1675.
    7. Lester C. Hunt & Guy Judge & Yasushi Ninomiya, 2003. "Modelling underlying energy demand trends," Chapters, in: Lester C. Hunt (ed.), Energy in a Competitive Market, chapter 9, Edward Elgar Publishing.
    8. Dilaver, Zafer & Hunt, Lester C., 2011. "Industrial electricity demand for Turkey: A structural time series analysis," Energy Economics, Elsevier, vol. 33(3), pages 426-436, May.
    9. Dordonnat, V. & Koopman, S.J. & Ooms, M. & Dessertaine, A. & Collet, J., 2008. "An hourly periodic state space model for modelling French national electricity load," International Journal of Forecasting, Elsevier, vol. 24(4), pages 566-587.
    10. Lester C. Hunt & Yasushi Ninomiya, 2003. "Unravelling Trends and Seasonality: A Structural Time Series Analysis of Transport Oil Demand in the UK and Japan," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 63-96.
    11. John Dimitropoulos & Lester Hunt & Guy Judge, 2005. "Estimating underlying energy demand trends using UK annual data," Applied Economics Letters, Taylor & Francis Journals, vol. 12(4), pages 239-244.
    12. Ediger, Volkan S. & Akar, Sertac, 2007. "ARIMA forecasting of primary energy demand by fuel in Turkey," Energy Policy, Elsevier, vol. 35(3), pages 1701-1708, March.
    13. Lester C. Hunt (ed.), 2003. "Energy in a Competitive Market," Books, Edward Elgar Publishing, number 2519.
    14. Kaya, Durmus, 2006. "Renewable energy policies in Turkey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(2), pages 152-163, April.
    15. Harvey, Andrew C & Koopman, Siem Jan, 1992. "Diagnostic Checking of Unobserved-Components Time Series Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 377-389, October.
    16. Erdogdu, Erkan, 2007. "Electricity demand analysis using cointegration and ARIMA modelling: A case study of Turkey," Energy Policy, Elsevier, vol. 35(2), pages 1129-1146, February.
    17. Lester C. Hunt & Guy Judge & Yashushi Ninomiya, 2000. "Modelling Technical Progress: An Application of the Stochastic Trend Model to UK Energy Demand," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 99, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    18. World Bank, 2010. "World Development Indicators 2010," World Bank Publications - Books, The World Bank Group, number 4373.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dilaver, Zafer & Hunt, Lester C., 2011. "Industrial electricity demand for Turkey: A structural time series analysis," Energy Economics, Elsevier, vol. 33(3), pages 426-436, May.
    2. Dilaver, Zafer & Hunt, Lester C, 2011. "Modelling and forecasting Turkish residential electricity demand," Energy Policy, Elsevier, vol. 39(6), pages 3117-3127, June.
    3. Tehreem Fatima & Enjun Xia & Muhammad Ahad, 2019. "Oil demand forecasting for China: a fresh evidence from structural time series analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(3), pages 1205-1224, June.
    4. 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.
    5. Atalla, Tarek N. & Hunt, Lester C., 2016. "Modelling residential electricity demand in the GCC countries," Energy Economics, Elsevier, vol. 59(C), pages 149-158.
    6. Javid, Muhammad & Qayyum, Abdul, 2014. "Electricity consumption-GDP nexus in Pakistan: A structural time series analysis," Energy, Elsevier, vol. 64(C), pages 811-817.
    7. Adeyemi, Olutomi I. & Hunt, Lester C., 2014. "Accounting for asymmetric price responses and underlying energy demand trends in OECD industrial energy demand," Energy Economics, Elsevier, vol. 45(C), pages 435-444.
    8. Broadstock, David C. & Hunt, Lester C., 2010. "Quantifying the impact of exogenous non-economic factors on UK transport oil demand," Energy Policy, Elsevier, vol. 38(3), pages 1559-1565, March.
    9. Atalla, Tarek N. & Gasim, Anwar A. & Hunt, Lester C., 2018. "Gasoline demand, pricing policy, and social welfare in Saudi Arabia: A quantitative analysis," Energy Policy, Elsevier, vol. 114(C), pages 123-133.
    10. Rodrigues, Niágara & Losekann, Luciano & Silveira Filho, Getulio, 2018. "Demand of automotive fuels in Brazil: Underlying energy demand trend and asymmetric price response," Energy Economics, Elsevier, vol. 74(C), pages 644-655.
    11. Tajudeen, Ibrahim A., 2015. "Examining the role of energy efficiency and non-economic factors in energy demand and CO2 emissions in Nigeria: Policy implications," Energy Policy, Elsevier, vol. 86(C), pages 338-350.
    12. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
    13. 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.
    14. Ringlund, Guro Bornes & Rosendahl, Knut Einar & Skjerpen, Terje, 2008. "Does oilrig activity react to oil price changes An empirical investigation," Energy Economics, Elsevier, vol. 30(2), pages 371-396, March.
    15. Aldubyan, Mohammad & Gasim, Anwar, 2021. "Energy price reform in Saudi Arabia: Modeling the economic and environmental impacts and understanding the demand response," Energy Policy, Elsevier, vol. 148(PB).
    16. Adeyemi, Olutomi I. & Broadstock, David C. & Chitnis, Mona & Hunt, Lester C. & Judge, Guy, 2010. "Asymmetric price responses and the underlying energy demand trend: Are they substitutes or complements? Evidence from modelling OECD aggregate energy demand," Energy Economics, Elsevier, vol. 32(5), pages 1157-1164, September.
    17. Olaniyan, Monisola J. & Evans, Joanne, 2014. "The importance of engaging residential energy customers' hearts and minds," Energy Policy, Elsevier, vol. 69(C), pages 273-284.
    18. Ouedraogo, Nadia S., 2017. "Africa energy future: Alternative scenarios and their implications for sustainable development strategies," Energy Policy, Elsevier, vol. 106(C), pages 457-471.
    19. 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.
    20. Melikoglu, Mehmet, 2013. "Vision 2023: Forecasting Turkey's natural gas demand between 2013 and 2030," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 393-400.

    More about this item

    Keywords

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

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sur:seedps:132. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mona Chitnis (email available below). General contact details of provider: https://edirc.repec.org/data/eesuruk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.