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

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  • 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
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    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. Sorrell, Steve, 2009. "Jevons' Paradox revisited: The evidence for backfire from improved energy efficiency," Energy Policy, Elsevier, vol. 37(4), pages 1456-1469, April.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. Unknown, 2016. "Energy for Sustainable Development," Conference Proceedings 253270, Guru Arjan Dev Institute of Development Studies (IDSAsr).
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
    28. 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.
    29. 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.
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