IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v184y2022icp990-1001.html
   My bibliography  Save this article

Energy intensity and energy-specific technological progress: A case study in Guangdong province of China

Author

Listed:
  • Huang, Junbing
  • Wang, Yajun
  • Guo, Lili

Abstract

Examining the dynamics of technological progress in determining energy intensity not only helps in assessing the relative strength of contributing factors, but also beneficial in designing effective energy policies. The effect of technology on energy intensity was widely discussed, as a whole, without narrowing down to the energy field and considering the technological absorption capacity as well as the heterogeneity. In view of the importance of sustainability in Guangdong province to the Greater Bay Area, this study focused on energy-specific technological progress and investigated the effect of energy-specific technology on energy intensity using a panel dataset covering cities in Guangdong Province for 2005–2017. The empirical evidence shows that energy-specific technology is beneficial in reducing the energy intensity. However, the energy intensity reduction effect is primarily from energy-saving technology rather than the alternative energy technology. From the sources of energy technology, enterprises, rather than from higher education institutions and independent research institutions, are more effective in cutting the energy intensity. In addition, utility-type energy-specific technology shows a stronger reduction effect on energy intensity compared to creation-type. Finally, the study concludes that technological absorption capacity is an important determinant for the effectiveness of energy-specific technology in reducing energy intensity.

Suggested Citation

  • Huang, Junbing & Wang, Yajun & Guo, Lili, 2022. "Energy intensity and energy-specific technological progress: A case study in Guangdong province of China," Renewable Energy, Elsevier, vol. 184(C), pages 990-1001.
  • Handle: RePEc:eee:renene:v:184:y:2022:i:c:p:990-1001
    DOI: 10.1016/j.renene.2021.11.087
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148121016724
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2021.11.087?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rachel Griffith & Stephen Redding & John Van Reenen, 2004. "Mapping the Two Faces of R&D: Productivity Growth in a Panel of OECD Industries," The Review of Economics and Statistics, MIT Press, vol. 86(4), pages 883-895, November.
    2. Joseph E. Stiglitz, 1974. "Growth with Exhaustible Natural Resources: The Competitive Economy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 41(5), pages 139-152.
    3. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    4. Bu, Maoliang & Li, Shuang & Jiang, Lei, 2019. "Foreign direct investment and energy intensity in China: Firm-level evidence," Energy Economics, Elsevier, vol. 80(C), pages 366-376.
    5. Ang, James B., 2009. "CO2 emissions, research and technology transfer in China," Ecological Economics, Elsevier, vol. 68(10), pages 2658-2665, August.
    6. Huang, Junbing & Xiang, Shiqi & Wang, Yajun & Chen, Xiang, 2021. "Energy-saving R&D and carbon intensity in China," Energy Economics, Elsevier, vol. 98(C).
    7. Aydin, Celil & Esen, Ömer, 2018. "Does the level of energy intensity matter in the effect of energy consumption on the growth of transition economies? Evidence from dynamic panel threshold analysis," Energy Economics, Elsevier, vol. 69(C), pages 185-195.
    8. Voigt, Sebastian & De Cian, Enrica & Schymura, Michael & Verdolini, Elena, 2014. "Energy intensity developments in 40 major economies: Structural change or technology improvement?," Energy Economics, Elsevier, vol. 41(C), pages 47-62.
    9. Pfeiffer, Birte & Mulder, Peter, 2013. "Explaining the diffusion of renewable energy technology in developing countries," Energy Economics, Elsevier, vol. 40(C), pages 285-296.
    10. Zheng, Yingmei & Qi, Jianhong & Chen, Xiaoliang, 2011. "The effect of increasing exports on industrial energy intensity in China," Energy Policy, Elsevier, vol. 39(5), pages 2688-2698, May.
    11. Wu, Haitao & Hao, Yu & Weng, Jia-Hsi, 2019. "How does energy consumption affect China's urbanization? New evidence from dynamic threshold panel models," Energy Policy, Elsevier, vol. 127(C), pages 24-38.
    12. Joseph Stiglitz, 1974. "Growth with Exhaustible Natural Resources: Efficient and Optimal Growth Paths," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 41(5), pages 123-137.
    13. Dong, Kangyin & Sun, Renjin & Hochman, Gal & Li, Hui, 2018. "Energy intensity and energy conservation potential in China: A regional comparison perspective," Energy, Elsevier, vol. 155(C), pages 782-795.
    14. Tan, Ruipeng & Lin, Boqiang, 2018. "What factors lead to the decline of energy intensity in China's energy intensive industries?," Energy Economics, Elsevier, vol. 71(C), pages 213-221.
    15. Fisher-Vanden, Karen & Jefferson, Gary H. & Liu, Hongmei & Tao, Quan, 2004. "What is driving China's decline in energy intensity?," Resource and Energy Economics, Elsevier, vol. 26(1), pages 77-97, March.
    16. Li, Ke & Lin, Boqiang, 2016. "Impact of energy technology patents in China: Evidence from a panel cointegration and error correction model," Energy Policy, Elsevier, vol. 89(C), pages 214-223.
    17. Huang, Junbing & Xiang, Shiqi & Wu, Panling & Chen, Xiang, 2022. "How to control China's energy consumption through technological progress: A spatial heterogeneous investigation," Energy, Elsevier, vol. 238(PC).
    18. Stephanie Kremer & Alexander Bick & Dieter Nautz, 2013. "Inflation and growth: new evidence from a dynamic panel threshold analysis," Empirical Economics, Springer, vol. 44(2), pages 861-878, April.
    19. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
    20. Wu, Jie & Zhu, Qingyuan & Liang, Liang, 2016. "CO2 emissions and energy intensity reduction allocation over provincial industrial sectors in China," Applied Energy, Elsevier, vol. 166(C), pages 282-291.
    21. Gilbert E. Metcalf, 2008. "An Empirical Analysis of Energy Intensity and Its Determinants at the State Level," The Energy Journal, , vol. 29(3), pages 1-26, July.
    22. Huang, Junbing & Du, Dan & Tao, Qizhi, 2017. "An analysis of technological factors and energy intensity in China," Energy Policy, Elsevier, vol. 109(C), pages 1-9.
    23. repec:igg:jssoe0:v:7:y:2017:i:1:p:45-57 is not listed on IDEAS
    24. M. S. Dresselhaus & I. L. Thomas, 2001. "Alternative energy technologies," Nature, Nature, vol. 414(6861), pages 332-337, November.
    25. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    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. Feng, Yanchao & Zhang, Juan & Geng, Yong & Jin, Shurui & Zhu, Ziyi & Liang, Zhou, 2023. "Explaining and modeling the reduction effect of low-carbon energy transition on energy intensity: Empirical evidence from global data," Energy, Elsevier, vol. 281(C).
    2. Zeng, Shihong & Li, Tengfei & Wu, Shaomin & Gao, Weijun & Li, Gen, 2024. "Does green technology progress have a significant impact on carbon dioxide emissions?," Energy Economics, Elsevier, vol. 133(C).
    3. Fan, Min & Lu, Zhixi & Zhou, Yun & Wang, Jian, 2024. "Threshold and spillovers effects of fintech on China's energy dependence on fossil fuel," Resources Policy, Elsevier, vol. 91(C).
    4. Pang, Qinghua & Dong, Xianwei & Zhang, Lina & Chiu, Yung-ho, 2023. "Drivers and key pathways of the household energy consumption in the Yangtze river economic belt," Energy, Elsevier, vol. 262(PA).
    5. Feng, Cuiyang & Dong, Liyan & Adbiat, Muhsen & Xu, Lixiao & Yu, Ao, 2023. "Critical transmission sectors in China's energy supply chains," Energy, Elsevier, vol. 266(C).
    6. Chen, Changhua & Luo, Yuqing & Zou, Hong & Huang, Junbing, 2023. "Understanding the driving factors and finding the pathway to mitigating carbon emissions in China's Yangtze River Delta region," Energy, Elsevier, vol. 278(PB).
    7. Yin, Zi Hui & Zeng, Wei Ping, 2023. "The effects of industrial intelligence on China's energy intensity: The role of technology absorptive capacity," Technological Forecasting and Social Change, Elsevier, vol. 191(C).

    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. Huang, Junbing & Luan, Bingjiang & He, Wanrui & Chen, Xiang & Li, Mengfan, 2022. "Energy technology of conservation versus substitution and energy intensity in China," Energy, Elsevier, vol. 244(PA).
    2. Huang, Junbing & Lai, Yali & Wang, Yajun & Hao, Yu, 2020. "Energy-saving research and development activities and energy intensity in China: A regional comparison perspective," Energy, Elsevier, vol. 213(C).
    3. Huang, Junbing & Lai, Yali & Hu, Hanlei, 2020. "The effect of technological factors and structural change on China's energy intensity: Evidence from dynamic panel models," China Economic Review, Elsevier, vol. 64(C).
    4. Wu, Shu & Ding, Song, 2021. "Efficiency improvement, structural change, and energy intensity reduction: Evidence from Chinese agricultural sector," Energy Economics, Elsevier, vol. 99(C).
    5. Liu, Liang & Yang, Kun & Fujii, Hidemichi & Liu, Jun, 2021. "Artificial intelligence and energy intensity in China’s industrial sector: Effect and transmission channel," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 276-293.
    6. Hu, Changshuai & Du, Dan & Huang, Junbing, 2023. "The driving effect of energy demand evolution: From the perspective of heterogeneity in technology," Energy, Elsevier, vol. 275(C).
    7. Shuxing Chen & Xiangyang Du & Junbing Huang & Cheng Huang, 2019. "The Impact of Foreign and Indigenous Innovations on the Energy Intensity of China’s Industries," Sustainability, MDPI, vol. 11(4), pages 1-18, February.
    8. Luan, Bingjiang & Zou, Hong & Chen, Shuxing & Huang, Junbing, 2021. "The effect of industrial structure adjustment on China’s energy intensity: Evidence from linear and nonlinear analysis," Energy, Elsevier, vol. 218(C).
    9. Xiekui Zhang & Peiyao Liu & Hongfei Zhu, 2022. "The Impact of Industrial Intelligence on Energy Intensity: Evidence from China," Sustainability, MDPI, vol. 14(12), pages 1-16, June.
    10. Huang, Junbing & Lian, Shijia & Qu, Ran & Luan, Bingjiang & Wang, Yajun, 2023. "Investigating the role of enterprises' property rights in China's provincial industrial energy intensity," Energy, Elsevier, vol. 282(C).
    11. Huang, Junbing & Xiang, Shiqi & Wang, Yajun & Chen, Xiang, 2021. "Energy-saving R&D and carbon intensity in China," Energy Economics, Elsevier, vol. 98(C).
    12. Capolupo, Rosa, 2009. "The New Growth Theories and Their Empirics after Twenty Years," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 3, pages 1-72.
    13. Chen, Chaoyi & Pinar, Mehmet & Stengos, Thanasis, 2021. "Determinants of renewable energy consumption: Importance of democratic institutions," Renewable Energy, Elsevier, vol. 179(C), pages 75-83.
    14. Zhang, Wenyue & Li, Jianan & Sun, Chuanwang, 2022. "The impact of OFDI reverse technology spillovers on China's energy intensity: Analysis of provincial panel data," Energy Economics, Elsevier, vol. 116(C).
    15. Huang, Junbing & Hao, Yu & Lei, Hongyan, 2018. "Indigenous versus foreign innovation and energy intensity in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1721-1729.
    16. Huang, Junbing & Li, Xinghao & Wang, Yajun & Lei, Hongyan, 2021. "The effect of energy patents on China's carbon emissions: Evidence from the STIRPAT model," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    17. Chen, Chaoyi & Pinar, Mehmet & Stengos, Thanasis, 2022. "Renewable energy and CO2 emissions: New evidence with the panel threshold model," Renewable Energy, Elsevier, vol. 194(C), pages 117-128.
    18. Wang, Yajun & Huang, Junbing, 2022. "Pathway to develop a low-carbon economy through energy-substitution technology in China," Energy, Elsevier, vol. 261(PA).
    19. Huang, Junbing & Chen, Xiang, 2020. "Domestic R&D activities, technology absorption ability, and energy intensity in China," Energy Policy, Elsevier, vol. 138(C).
    20. Cavalcanti, Tiago V. de V. & Mohaddes, Kamiar & Raissi, Mehdi, 2011. "Growth, development and natural resources: New evidence using a heterogeneous panel analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(4), pages 305-318.

    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:eee:renene:v:184:y:2022:i:c:p:990-1001. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.