IDEAS home Printed from https://ideas.repec.org/a/sae/engenv/v31y2020i3p389-404.html
   My bibliography  Save this article

Exploring the efficiency of new energy generation: Evidence from OECD and non-OECD countries

Author

Listed:
  • Xin Long Xu
  • Sen Qiao
  • Hsing Hung Chen

Abstract

In this study, we defined new energy generation inputs as the installed capacity of solar energy, wind power, geothermal energy and biofuel production, and we defined electricity from new energy as an output indicator. Based on panel data in OECD and non-OECD countries from 2007 to 2016, we used stochastic frontier analysis to calculate the efficiency of new energy generation and analyzed the influencing factors. We found the following results: the efficiency of global new energy generation is improving; the energy price, technological progress and education level have positive impacts on the efficiency of new energy generation; and industrial structure and opening up have a negative impact on the efficiency of new energy generation. Based on our study results, we offer some recommendations to promote the development of new energy generation.

Suggested Citation

  • Xin Long Xu & Sen Qiao & Hsing Hung Chen, 2020. "Exploring the efficiency of new energy generation: Evidence from OECD and non-OECD countries," Energy & Environment, , vol. 31(3), pages 389-404, May.
    • Handle: RePEc:sae:engenv:v:31:y:2020:i:3:p:389-404
    DOI: 10.1177/0958305X19871675
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0958305X19871675
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0958305X19871675?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Yuan, Jia-Hai & Kang, Jian-Gang & Zhao, Chang-Hong & Hu, Zhao-Guang, 2008. "Energy consumption and economic growth: Evidence from China at both aggregated and disaggregated levels," Energy Economics, Elsevier, vol. 30(6), pages 3077-3094, November.
    2. Zhang, Yue-Jun & Da, Ya-Bin, 2015. "The decomposition of energy-related carbon emission and its decoupling with economic growth in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1255-1266.
    3. Bloch, Harry & Rafiq, Shuddhasattwa & Salim, Ruhul, 2015. "Economic growth with coal, oil and renewable energy consumption in China: Prospects for fuel substitution," Economic Modelling, Elsevier, vol. 44(C), pages 104-115.
    4. Chen, Zhongfei & Barros, Carlos Pestana & Borges, Maria Rosa, 2015. "A Bayesian stochastic frontier analysis of Chinese fossil-fuel electricity generation companies," Energy Economics, Elsevier, vol. 48(C), pages 136-144.
    5. Filippini, Massimo & Hunt, Lester C., 2012. "US residential energy demand and energy efficiency: A stochastic demand frontier approach," Energy Economics, Elsevier, vol. 34(5), pages 1484-1491.
    6. Gale A. Boyd, 2008. "Estimating Plant Level Energy Efficiency with a Stochastic Frontier," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 23-44.
    7. Sami Alpanda & Adrian Peralta-Alva, 2010. "Oil Crisis, Energy-Saving Technological Change and the Stock Market Crash of 1973-74," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 13(4), pages 824-842, October.
    8. Rashid, Abdul & Kandemir, Ӧzge, 2016. "Variations in energy use and output growth dynamics: An assessment for intertemporal and contemporaneous relationship," Energy, Elsevier, vol. 102(C), pages 388-396.
    9. Khoshnevisan, Benyamin & Rafiee, Shahin & Omid, Mahmoud & Mousazadeh, Hossein, 2013. "Reduction of CO2 emission by improving energy use efficiency of greenhouse cucumber production using DEA approach," Energy, Elsevier, vol. 55(C), pages 676-682.
    10. Elliott, Robert J.R. & Sun, Puyang & Chen, Siyang, 2013. "Energy intensity and foreign direct investment: A Chinese city-level study," Energy Economics, Elsevier, vol. 40(C), pages 484-494.
    11. Olanrewaju, O.A. & Jimoh, A.A. & Kholopane, P.A., 2012. "Integrated IDA–ANN–DEA for assessment and optimization of energy consumption in industrial sectors," Energy, Elsevier, vol. 46(1), pages 629-635.
    12. Unknown, 2016. "Energy for Sustainable Development," Conference Proceedings 253270, Guru Arjan Dev Institute of Development Studies (IDSAsr).
    13. Patrick J. Kehoe & Andrew Atkeson, 1999. "Models of Energy Use: Putty-Putty versus Putty-Clay," American Economic Review, American Economic Association, vol. 89(4), pages 1028-1043, September.
    14. Jacobson, Mark Z. & Delucchi, Mark A., 2011. "Providing all global energy with wind, water, and solar power, Part I: Technologies, energy resources, quantities and areas of infrastructure, and materials," Energy Policy, Elsevier, vol. 39(3), pages 1154-1169, March.
    15. Ouyang, Jinlong & Long, Enshen & Hokao, Kazunori, 2010. "Rebound effect in Chinese household energy efficiency and solution for mitigating it," Energy, Elsevier, vol. 35(12), pages 5269-5276.
    16. Bin Su & B. W. Ang, 2012. "Structural Decomposition Analysis Applied To Energy And Emissions: Aggregation Issues," Economic Systems Research, Taylor & Francis Journals, vol. 24(3), pages 299-317, March.
    17. Xu, Xin-long & Chen, Hsing Hung, 2018. "Examining the efficiency of biomass energy: Evidence from the Chinese recycling industry," Energy Policy, Elsevier, vol. 119(C), pages 77-86.
    18. Buck, J. & Young, D., 2007. "The potential for energy efficiency gains in the Canadian commercial building sector: A stochastic frontier study," Energy, Elsevier, vol. 32(9), pages 1769-1780.
    19. Ouyang, Xiaoling & Lin, Boqiang, 2015. "An analysis of the driving forces of energy-related carbon dioxide emissions in China’s industrial sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 838-849.
    20. Shi, Guang-Ming & Bi, Jun & Wang, Jin-Nan, 2010. "Chinese regional industrial energy efficiency evaluation based on a DEA model of fixing non-energy inputs," Energy Policy, Elsevier, vol. 38(10), pages 6172-6179, October.
    21. Sorrell, Steve, 2009. "Jevons' Paradox revisited: The evidence for backfire from improved energy efficiency," Energy Policy, Elsevier, vol. 37(4), pages 1456-1469, April.
    22. Aranda-Usón, Alfonso & Ferreira, Germán & Mainar-Toledo, M.D. & Scarpellini, Sabina & Llera Sastresa, Eva, 2012. "Energy consumption analysis of Spanish food and drink, textile, chemical and non-metallic mineral products sectors," Energy, Elsevier, vol. 42(1), pages 477-485.
    23. Azadeh, A. & Amalnick, M.S. & Ghaderi, S.F. & Asadzadeh, S.M., 2007. "An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors," Energy Policy, Elsevier, vol. 35(7), pages 3792-3806, July.
    24. Fang, Zheng & Chen, Yang, 2017. "Human capital and energy in economic growth – Evidence from Chinese provincial data," Energy Economics, Elsevier, vol. 68(C), pages 340-358.
    25. Su, Bin & Ang, B.W., 2012. "Structural decomposition analysis applied to energy and emissions: Some methodological developments," Energy Economics, Elsevier, vol. 34(1), pages 177-188.
    26. Lin, Boqiang & Du, Kerui, 2013. "Technology gap and China's regional energy efficiency: A parametric metafrontier approach," Energy Economics, Elsevier, vol. 40(C), pages 529-536.
    27. Lin, Boqiang & Yang, Lisha, 2013. "The potential estimation and factor analysis of China′s energy conservation on thermal power industry," Energy Policy, Elsevier, vol. 62(C), pages 354-362.
    28. Huang, Yun-Hsun & Wu, Jung-Hua, 2013. "Analyzing the driving forces behind CO2 emissions and reduction strategies for energy-intensive sectors in Taiwan, 1996–2006," Energy, Elsevier, vol. 57(C), pages 402-411.
    29. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Victor Moutinho & Mara Madaleno, 2021. "Assessing Eco-Efficiency in Asian and African Countries Using Stochastic Frontier Analysis," Energies, MDPI, vol. 14(4), pages 1-17, February.
    2. Li, Wanying & Ji, Zhengsen & Dong, Fugui & Yang, Yugui, 2024. "Evaluation of provincial renewable energy generation efficiency and spatio-temporal heterogeneity of influencing factors in China," Renewable Energy, Elsevier, vol. 226(C).
    3. Paul, Satya & Shankar, Sriram, 2022. "Regulatory reforms and the efficiency and productivity growth in electricity generation in OECD countries," Energy Economics, Elsevier, vol. 108(C).
    4. D’Errico, Maria Chiara, 2024. "Sustainable economic growth and energy security nexus: A stochastic frontier analysis across OECD countries," Energy Economics, Elsevier, vol. 132(C).
    5. Dan Zhou & Qi Zhang & Yangqing Dan & Fanghong Guo & Jun Qi & Chenyuan Teng & Wenwei Zhou & Haonan Zhu, 2022. "Research on Renewable-Energy Accommodation-Capability Evaluation Based on Time-Series Production Simulations," Energies, MDPI, vol. 15(19), pages 1-15, September.

    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. Lin, Boqiang & Wang, Xiaolei, 2014. "Exploring energy efficiency in China׳s iron and steel industry: A stochastic frontier approach," Energy Policy, Elsevier, vol. 72(C), pages 87-96.
    2. Akihiro Otsuka, 2020. "How do population agglomeration and interregional networks improve energy efficiency?," Asia-Pacific Journal of Regional Science, Springer, vol. 4(1), pages 1-25, February.
    3. Amjadi, Golnaz & Lundgren, Tommy, 2022. "Is industrial energy inefficiency transient or persistent? Evidence from Swedish manufacturing," Applied Energy, Elsevier, vol. 309(C).
    4. Akihiro Otsuka, 2018. "Regional Determinants of Energy Efficiency: Residential Energy Demand in Japan," Energies, MDPI, vol. 11(6), pages 1-14, June.
    5. Zhang, Shanshan & Lundgren, Tommy & Zhou, Wenchao, 2016. "Energy efficiency in Swedish industry," Energy Economics, Elsevier, vol. 55(C), pages 42-51.
    6. Du, Minzhe & Wang, Bing & Zhang, Ning, 2018. "National research funding and energy efficiency: Evidence from the National Science Foundation of China," Energy Policy, Elsevier, vol. 120(C), pages 335-346.
    7. Giovanni Marin & Alessandro Palma, 2015. "Technology invention and diffusion in residential energy consumption. A stochastic frontier approach," IEFE Working Papers 81, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    8. Wei, Zixiang & Han, Botang & Pan, Xiuzhen & Shahbaz, Muhammad & Zafar, Muhammad Wasif, 2020. "Effects of diversified openness channels on the total-factor energy efficiency in China's manufacturing sub-sectors: Evidence from trade and FDI spillovers," Energy Economics, Elsevier, vol. 90(C).
    9. Boogen, Nina, 2017. "Estimating the potential for electricity savings in households," Energy Economics, Elsevier, vol. 63(C), pages 288-300.
    10. Lei Jiang & Henk Folmer & Minhe Ji & Jianjun Tang, 2017. "Energy efficiency in the Chinese provinces: a fixed effects stochastic frontier spatial Durbin error panel analysis," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 58(2), pages 301-319, March.
    11. Akihiro Otsuka & Mika Goto, 2015. "Estimation and determinants of energy efficiency in Japanese regional economies," Regional Science Policy & Practice, Wiley Blackwell, vol. 7(2), pages 89-101, June.
    12. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    13. Victor Moutinho & Mara Madaleno, 2021. "Assessing Eco-Efficiency in Asian and African Countries Using Stochastic Frontier Analysis," Energies, MDPI, vol. 14(4), pages 1-17, February.
    14. Otsuka, Akihiro, 2023. "Industrial electricity consumption efficiency and energy policy in Japan," Utilities Policy, Elsevier, vol. 81(C).
    15. Chang, Ming-Chung, 2016. "Applying the energy productivity index that considers maximized energy reduction on SADC (Southern Africa Development Community) members," Energy, Elsevier, vol. 95(C), pages 313-323.
    16. Fernández González, P. & Presno, M.J. & Landajo, M., 2015. "Regional and sectoral attribution to percentage changes in the European Divisia carbonization index," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1437-1452.
    17. Ouyang, Xiaoling & Chen, Jiaqi & Du, Kerui, 2021. "Energy efficiency performance of the industrial sector: From the perspective of technological gap in different regions in China," Energy, Elsevier, vol. 214(C).
    18. Qiao, Sen & Chen, Hsing Hung & Zhang, Rong Rong, 2021. "Examining the impact of factor price distortions and social welfare on innovation efficiency from the microdata of Chinese renewable energy industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    19. Wang, Qunwei & Su, Bin & Sun, Jiasen & Zhou, Peng & Zhou, Dequn, 2015. "Measurement and decomposition of energy-saving and emissions reduction performance in Chinese cities," Applied Energy, Elsevier, vol. 151(C), pages 85-92.
    20. Marin, Giovanni & Palma, Alessandro, 2017. "Technology invention and adoption in residential energy consumption," Energy Economics, Elsevier, vol. 66(C), pages 85-98.

    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:sae:engenv:v:31:y:2020:i:3:p:389-404. 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: SAGE Publications (email available below). General contact details of provider: .

    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.