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

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  • 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.

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  • 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
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    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Pfeiffer, Birte & Mulder, Peter, 2013. "Explaining the diffusion of renewable energy technology in developing countries," Energy Economics, Elsevier, vol. 40(C), pages 285-296.
    8. Gilbert E. Metcalf, 2008. "An Empirical Analysis of Energy Intensity and Its Determinants at the State Level," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-26.
    9. 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.
    10. 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.
    11. 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.
    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. repec:igg:jssoe0:v:7:y:2017:i:1:p:45-57 is not listed on IDEAS
    14. 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).
    15. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    16. Ang, James B., 2009. "CO2 emissions, research and technology transfer in China," Ecological Economics, Elsevier, vol. 68(10), pages 2658-2665, August.
    17. 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.
    18. 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.
    19. M. S. Dresselhaus & I. L. Thomas, 2001. "Alternative energy technologies," Nature, Nature, vol. 414(6861), pages 332-337, November.
    20. 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.
    21. Huang, Junbing & Xiang, Shiqi & Wang, Yajun & Chen, Xiang, 2021. "Energy-saving R&D and carbon intensity in China," Energy Economics, Elsevier, vol. 98(C).
    22. 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.
    23. 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.
    24. 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)

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