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Energy intensity and its components in Iran: Determinants and trends

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  • Farajzadeh, Zakariya
  • Nematollahi, Mohammad Amin

Abstract

Iran energy intensity is among the highest in the world, which has been increasing during the recent decades, originating from the channels related to the efficiency and structural (scale) changes. The present study aimed to investigate the changes in the aggregate energy intensity (EI) and its components including the Efficiency (EE) and Structural Change (SC) indices as well as their driving forces based on a regression analysis. Furthermore, the multilayer perceptron and wavelet-based neural networks (WNN) were proposed to evaluate the ability of regression models in forecasting energy intensity and its components. The results suggested a non-linear relationship between the energy intensity indices and income as well as the capital-output ratio. However, no significant role was observed for trade and energy price index. Further, the turning points measured for income and the capital-labor ratio indicated that the effect of income on energy intensity is increasing while the capital-energy is turning out to be as the substitutes. Furthermore, urbanization could significantly reduce energy intensity. The forecast results indicated that energy intensity and its components may be predicted with a prediction error of less than 0.35%. Finally, EE and SC can be predicted more accurately based on the ANN-based models while the regression models can predict the EI index more precisely.

Suggested Citation

  • Farajzadeh, Zakariya & Nematollahi, Mohammad Amin, 2018. "Energy intensity and its components in Iran: Determinants and trends," Energy Economics, Elsevier, vol. 73(C), pages 161-177.
    • Handle: RePEc:eee:eneeco:v:73:y:2018:i:c:p:161-177
    DOI: 10.1016/j.eneco.2018.05.021
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    Cited by:

    1. Guanglei Yang & Dongqin Cao & Guoxing Zhang, 2023. "How does industry-university-research collaborative innovation affect energy intensity in China: a novel explanation based on political turnover," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
    2. Liyang Tang, 2020. "Application of Nonlinear Autoregressive with Exogenous Input (NARX) neural network in macroeconomic forecasting, national goal setting and global competitiveness assessment," Papers 2005.08735, arXiv.org.
    3. Muhlis Can & Zahoor Ahmed, 2023. "Towards sustainable development in the European Union countries: Does economic complexity affect renewable and non‐renewable energy consumption?," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(1), pages 439-451, February.
    4. Adekoya, Oluwasegun B. & Kenku, Oluwademilade T. & Oliyide, Johnson A. & Al-Faryan, Mamdouh Abdulaziz Saleh & Ogunjemilua, Oluwafemi D., 2023. "Does economic complexity drive energy efficiency and renewable energy transition?," Energy, Elsevier, vol. 278(C).
    5. Soltani, Mohammad & Rahmani, Omeid & Ghasimi, Dara S.M. & Ghaderpour, Yousef & Pour, Amin Beiranvand & Misnan, Siti Hajar & Ngah, Ibrahim, 2020. "Impact of household demographic characteristics on energy conservation and carbon dioxide emission: Case from Mahabad city, Iran," Energy, Elsevier, vol. 194(C).
    6. Mohammad Soltani & Omeid Rahmani & Amin Beiranvand Pour & Yousef Ghaderpour & Ibrahim Ngah & Siti Hajar Misnan, 2019. "Determinants of Variation in Household Energy Choice and Consumption: Case from Mahabad City, Iran," Sustainability, MDPI, vol. 11(17), pages 1-20, September.
    7. Peng Hou & Yilin Li & Yong Tan & Yuanjie Hou, 2020. "Energy Price and Energy Efficiency in China: A Linear and Nonlinear Empirical Investigation," Energies, MDPI, vol. 13(16), pages 1-24, August.
    8. Trinh, Hai Hong & Sharma, Gagan Deep & Tiwari, Aviral Kumar & Vo, Diem Thi Hong, 2022. "Examining the heterogeneity of financial development in the energy-environment nexus in the era of climate change: Novel evidence around the world," Energy Economics, Elsevier, vol. 116(C).
    9. Hongyun Han & Shu Wu, 2018. "Structural Change and Its Impact on the Energy Intensity of Agricultural Sector in China," Sustainability, MDPI, vol. 10(12), pages 1-23, December.
    10. Dargahi, Hassan & Khameneh, Kazem Biabany, 2019. "Energy intensity determinants in an energy-exporting developing economy: Case of Iran," Energy, Elsevier, vol. 168(C), pages 1031-1044.
    11. Setyawan, Dhani, 2020. "Decomposing the Influencing Factors of Energy Intensity in the Passenger Transportation Sector in Indonesia," MPRA Paper 106114, University Library of Munich, Germany.
    12. Yulan Lv & Wei Chen & Jianquan Cheng, 2019. "Direct and Indirect Effects of Urbanization on Energy Intensity in Chinese Cities: A Regional Heterogeneity Analysis," Sustainability, MDPI, vol. 11(11), pages 1-20, June.
    13. Wu, Shu & Ding, Song, 2021. "Efficiency improvement, structural change, and energy intensity reduction: Evidence from Chinese agricultural sector," Energy Economics, Elsevier, vol. 99(C).
    14. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2020. "Effects of urbanization on energy efficiency in China: New evidence from short run and long run efficiency models," Energy Policy, Elsevier, vol. 147(C).
    15. Maaouane, Mohamed & Zouggar, Smail & Krajačić, Goran & Zahboune, Hassan, 2021. "Modelling industry energy demand using multiple linear regression analysis based on consumed quantity of goods," Energy, Elsevier, vol. 225(C).
    16. Pan, Xiongfeng & Uddin, Md. Kamal & Saima, Umme & Jiao, Zhiming & Han, Cuicui, 2019. "How do industrialization and trade openness influence energy intensity? Evidence from a path model in case of Bangladesh," Energy Policy, Elsevier, vol. 133(C).
    17. Jin, Taeyoung, 2022. "Impact of heat and electricity consumption on energy intensity: A panel data analysis," Energy, Elsevier, vol. 239(PA).
    18. Mouhamadou Lamine DIAL, 2022. "Les effets de l’urbanisation et de l’industrialisation sur l’intensité énergétique dans la CEDEAO," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 56, pages 41-59.
    19. Alizadeh, Reza & Gharizadeh Beiragh, Ramin & Soltanisehat, Leili & Soltanzadeh, Elham & Lund, Peter D., 2020. "Performance evaluation of complex electricity generation systems: A dynamic network-based data envelopment analysis approach," Energy Economics, Elsevier, vol. 91(C).
    20. Azhgaliyeva, Dina & Liu, Yang & Liddle, Brantley, 2020. "An empirical analysis of energy intensity and the role of policy instruments," Energy Policy, Elsevier, vol. 145(C).
    21. Wang, Bin & Wang, Jun, 2020. "Energy futures and spots prices forecasting by hybrid SW-GRU with EMD and error evaluation," Energy Economics, Elsevier, vol. 90(C).
    22. Wang, En-Ze & Lee, Chien-Chiang & Li, Yaya, 2022. "Assessing the impact of industrial robots on manufacturing energy intensity in 38 countries," Energy Economics, Elsevier, vol. 105(C).
    23. Shakya, S.R. & Adhikari, R. & Poudel, S. & Rupakheti, M., 2022. "Energy equity as a major driver of energy intensity in South Asia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).

    More about this item

    Keywords

    Energy intensity; Efficiency; Structural change; ANN; Iran;
    All these keywords.

    JEL classification:

    • N75 - Economic History - - Economic History: Transport, International and Domestic Trade, Energy, and Other Services - - - Asia including Middle East
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

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