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Forecasting production of fossil fuel sources in Turkey using a comparative regression and ARIMA model

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  • Ediger, Volkan S.
  • Akar, Sertac
  • Ugurlu, Berkin

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  • Ediger, Volkan S. & Akar, Sertac & Ugurlu, Berkin, 2006. "Forecasting production of fossil fuel sources in Turkey using a comparative regression and ARIMA model," Energy Policy, Elsevier, vol. 34(18), pages 3836-3846, December.
    • Handle: RePEc:eee:enepol:v:34:y:2006:i:18:p:3836-3846
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    References listed on IDEAS

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    6. Qi, Min & Zhang, Guoqiang Peter, 2001. "An investigation of model selection criteria for neural network time series forecasting," European Journal of Operational Research, Elsevier, vol. 132(3), pages 666-680, August.
    7. Guy Melard & Jean-Michel Pasteels, 2000. "Automatic ARIMA modeling including interventions, using time series expert software," ULB Institutional Repository 2013/13744, ULB -- Universite Libre de Bruxelles.
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    Cited by:

    1. Daniya Tlegenova, 2015. "Forecasting Exchange Rates Using Time Series Analysis: The sample of the currency of Kazakhstan," Papers 1508.07534, arXiv.org.
    2. 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.
    3. Pin Li & Jin-Suo Zhang, 2018. "A New Hybrid Method for China’s Energy Supply Security Forecasting Based on ARIMA and XGBoost," Energies, MDPI, vol. 11(7), pages 1-28, June.
    4. Shafiee, Shahriar & Topal, Erkan, 2009. "When will fossil fuel reserves be diminished?," Energy Policy, Elsevier, vol. 37(1), pages 181-189, January.
    5. Muhammad Saeed & Zulqarnain Haider, 2021. "Does Financial Development Advanced Environmental Quality in Thailand: Evidenced from ARDL," iRASD Journal of Energy and Environment, International Research Association for Sustainable Development (iRASD), vol. 2(2), pages 90-101, December.
    6. Berk, Istemi & Ediger, Volkan Ş., 2016. "Forecasting the coal production: Hubbert curve application on Turkey's lignite fields," Resources Policy, Elsevier, vol. 50(C), pages 193-203.
    7. Hong Yao & Qingxiang Zhang & Guangyuan Niu & Huan Liu & Yuxi Yang, 2021. "Applying the GM(1,1) model to simulate and predict the ecological footprint values of Suzhou city, China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 11297-11309, August.
    8. Murat Yalçıntaş & Melih Bulu & Murat Küçükvar & Hamidreza Samadi, 2015. "A Framework for Sustainable Urban Water Management through Demand and Supply Forecasting: The Case of Istanbul," Sustainability, MDPI, vol. 7(8), pages 1-18, August.
    9. 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.
    10. Sumer, Kutluk Kagan & Goktas, Ozlem & Hepsag, Aycan, 2009. "The application of seasonal latent variable in forecasting electricity demand as an alternative method," Energy Policy, Elsevier, vol. 37(4), pages 1317-1322, April.
    11. Chuqiao Han & Binbin Lu & Jianghua Zheng, 2021. "Analysis and Prediction of Land Resources’ Carrying Capacity in 31 Provinces of China from 2008 to 2016," Sustainability, MDPI, vol. 13(23), pages 1-20, December.
    12. Mustafa Akpinar & Nejat Yumusak, 2016. "Year Ahead Demand Forecast of City Natural Gas Using Seasonal Time Series Methods," Energies, MDPI, vol. 9(9), pages 1-17, September.
    13. 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.
    14. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
    15. Kankal, Murat & AkpInar, Adem & Kömürcü, Murat Ihsan & Özsahin, Talat Sükrü, 2011. "Modeling and forecasting of Turkey's energy consumption using socio-economic and demographic variables," Applied Energy, Elsevier, vol. 88(5), pages 1927-1939, May.
    16. Mostafa, Mohamed M. & El-Masry, Ahmed A., 2016. "Oil price forecasting using gene expression programming and artificial neural networks," Economic Modelling, Elsevier, vol. 54(C), pages 40-53.
    17. Syed Aziz Ur Rehman & Yanpeng Cai & Rizwan Fazal & Gordhan Das Walasai & Nayyar Hussain Mirjat, 2017. "An Integrated Modeling Approach for Forecasting Long-Term Energy Demand in Pakistan," Energies, MDPI, vol. 10(11), pages 1-23, November.
    18. Cheng, Fangzheng & Li, Tian & Wei, Yi-ming & Fan, Tijun, 2019. "The VEC-NAR model for short-term forecasting of oil prices," Energy Economics, Elsevier, vol. 78(C), pages 656-667.
    19. Abdulkerim Karaaslan & Mesliha Gezen, 2017. "Forecasting of Turkey s Sectoral Energy Demand by Using Fuzzy Grey Regression Model," International Journal of Energy Economics and Policy, Econjournals, vol. 7(1), pages 67-77.
    20. Shafiee, Shahriar & Topal, Erkan, 2008. "An econometrics view of worldwide fossil fuel consumption and the role of US," Energy Policy, Elsevier, vol. 36(2), pages 775-786, February.

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