IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v65y2017icp41-50.html
   My bibliography  Save this article

The driving forces of the change in China's energy intensity: An empirical research using DEA-Malmquist and spatial panel estimations

Author

Listed:
  • Huang, Junbing
  • Du, Dan
  • Hao, Yu

Abstract

Energy shortage and environmental degradation have become significant hurdles for China's sustainable development nowadays. One of the most efficient and effective ways to ease energy shortage is to sufficiently reduce energy intensity. In the extant literature on the influential factors of China's energy intensity, the regional imbalance and spatial spillover effects were basically ignored, which may yield to biased and unreasonable results. As a result, in this paper, the driving forces of China's provincial energy intensity were for the first time investigated by combining the Data Envelopment Analysis (DEA)-Malmquist and spatial panel approaches for the period between 2000 and 2014. The results indicate that technological progress plays a dominant role in decreasing China's overall energy intensity. In both the Eastern and Central regions, the technological progress and its components can decrease energy intensity, while this effect doesnot significantly exist in the Western region. Rapid industrialization should be responsible for China's currently high energy intensity, while energy price hiking is conducive to the decrease in energy intensity. Moreover, there is also clear evidence that these factors influence on energy intensity partly through the spatial spillover effects.

Suggested Citation

  • Huang, Junbing & Du, Dan & Hao, Yu, 2017. "The driving forces of the change in China's energy intensity: An empirical research using DEA-Malmquist and spatial panel estimations," Economic Modelling, Elsevier, vol. 65(C), pages 41-50.
  • Handle: RePEc:eee:ecmode:v:65:y:2017:i:c:p:41-50
    DOI: 10.1016/j.econmod.2017.04.027
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999316308458
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econmod.2017.04.027?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. Bhattacharya, Mita & Rafiq, Shuddhasattwa & Bhattacharya, Sankar, 2015. "The role of technology on the dynamics of coal consumption–economic growth: New evidence from China," Applied Energy, Elsevier, vol. 154(C), pages 686-695.
    2. 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.
    3. Meng, Fanyi & Su, Bin & Thomson, Elspeth & Zhou, Dequn & Zhou, P., 2016. "Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey," Applied Energy, Elsevier, vol. 183(C), pages 1-21.
    4. 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.
    5. Rafiq, Shuddhasattwa & Salim, Ruhul & Nielsen, Ingrid, 2016. "Urbanization, openness, emissions, and energy intensity: A study of increasingly urbanized emerging economies," Energy Economics, Elsevier, vol. 56(C), pages 20-28.
    6. Wang, Ke & Wei, Yi-Ming, 2016. "Sources of energy productivity change in China during 1997–2012: A decomposition analysis based on the Luenberger productivity indicator," Energy Economics, Elsevier, vol. 54(C), pages 50-59.
    7. Yingnan Liu & Ke Wang, 2015. "Energy efficiency of China's industry sector: An adjusted network DEA-based decomposition analysis," CEEP-BIT Working Papers 83, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    8. Zeng, Lin & Xu, Ming & Liang, Sai & Zeng, Siyu & Zhang, Tianzhu, 2014. "Revisiting drivers of energy intensity in China during 1997–2007: A structural decomposition analysis," Energy Policy, Elsevier, vol. 67(C), pages 640-647.
    9. Rafiq, Shudhasattwa & Sgro, Pasquale & Apergis, Nicholas, 2016. "Asymmetric oil shocks and external balances of major oil exporting and importing countries," Energy Economics, Elsevier, vol. 56(C), pages 42-50.
    10. Shuddhasattwa Rafiq & Ruhul A. Salim, 2009. "Temporal Causality between Energy Consumption and Income in Six Asian Emerging Countries," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 55(4), pages 335-350.
    11. Islam, Faridul & Shahbaz, Muhammad & Ahmed, Ashraf U. & Alam, Md. Mahmudul, 2013. "Financial development and energy consumption nexus in Malaysia: A multivariate time series analysis," Economic Modelling, Elsevier, vol. 30(C), pages 435-441.
    12. Ang, B.W. & Mu, A.R. & Zhou, P., 2010. "Accounting frameworks for tracking energy efficiency trends," Energy Economics, Elsevier, vol. 32(5), pages 1209-1219, September.
    13. Song, Feng & Zheng, Xinye, 2012. "What drives the change in China's energy intensity: Combining decomposition analysis and econometric analysis at the provincial level," Energy Policy, Elsevier, vol. 51(C), pages 445-453.
    14. 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.
    15. Choi, Ki-Hong & Ang, B.W., 2012. "Attribution of changes in Divisia real energy intensity index — An extension to index decomposition analysis," Energy Economics, Elsevier, vol. 34(1), pages 171-176.
    16. Wang, Qunwei & Zhao, Zengyao & Zhou, Peng & Zhou, Dequn, 2013. "Energy efficiency and production technology heterogeneity in China: A meta-frontier DEA approach," Economic Modelling, Elsevier, vol. 35(C), pages 283-289.
    17. Liu, Yingnan & Wang, Ke, 2015. "Energy efficiency of China's industry sector: An adjusted network DEA (data envelopment analysis)-based decomposition analysis," Energy, Elsevier, vol. 93(P2), pages 1328-1337.
    18. Lin, Boqiang & Du, Kerui, 2014. "Decomposing energy intensity change: A combination of index decomposition analysis and production-theoretical decomposition analysis," Applied Energy, Elsevier, vol. 129(C), pages 158-165.
    19. 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.
    20. 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.
    21. Zeus Guevara & João F. D. Rodrigues, 2016. "Structural transitions and energy use: a decomposition analysis of Portugal 1995--2010," Economic Systems Research, Taylor & Francis Journals, vol. 28(2), pages 202-223, June.
    22. Daniel Hoechle, 2007. "Robust standard errors for panel regressions with cross-sectional dependence," Stata Journal, StataCorp LP, vol. 7(3), pages 281-312, September.
    23. Sadorsky, Perry, 2013. "Do urbanization and industrialization affect energy intensity in developing countries?," Energy Economics, Elsevier, vol. 37(C), pages 52-59.
    24. Ma, Ben, 2015. "Does urbanization affect energy intensities across provinces in China?Long-run elasticities estimation using dynamic panels with heterogeneous slopes," Energy Economics, Elsevier, vol. 49(C), pages 390-401.
    25. Adams, F. Gerard & Shachmurove, Yochanan, 2008. "Modeling and forecasting energy consumption in China: Implications for Chinese energy demand and imports in 2020," Energy Economics, Elsevier, vol. 30(3), pages 1263-1278, May.
    26. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    27. Kounetas, Kostas & Tsekouras, Kostas, 2010. "Are the Energy Efficiency Technologies efficient?," Economic Modelling, Elsevier, vol. 27(1), pages 274-283, January.
    28. 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.
    29. Jiang, Lei & Folmer, Henk & Ji, Minhe, 2014. "The drivers of energy intensity in China: A spatial panel data approach," China Economic Review, Elsevier, vol. 31(C), pages 351-360.
    30. Salim, Ruhul A. & Rafiq, Shuddhasattwa, 2012. "Why do some emerging economies proactively accelerate the adoption of renewable energy?," Energy Economics, Elsevier, vol. 34(4), pages 1051-1057.
    31. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    32. Ang, B.W. & Zhang, F.Q., 2000. "A survey of index decomposition analysis in energy and environmental studies," Energy, Elsevier, vol. 25(12), pages 1149-1176.
    33. Li, Yi & Sun, Linyan & Feng, Taiwen & Zhu, Chunyan, 2013. "How to reduce energy intensity in China: A regional comparison perspective," Energy Policy, Elsevier, vol. 61(C), pages 513-522.
    34. Feng, Taiwen & Sun, Linyan & Zhang, Ying, 2009. "The relationship between energy consumption structure, economic structure and energy intensity in China," Energy Policy, Elsevier, vol. 37(12), pages 5475-5483, December.
    35. Yu, Huayi, 2012. "The influential factors of China's regional energy intensity and its spatial linkages: 1988–2007," Energy Policy, Elsevier, vol. 45(C), pages 583-593.
    36. Liu, Yaobin & Xie, Yichun, 2013. "Asymmetric adjustment of the dynamic relationship between energy intensity and urbanization in China," Energy Economics, Elsevier, vol. 36(C), pages 43-54.
    37. 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.
    38. Li, Ke & Lin, Boqiang, 2014. "The nonlinear impacts of industrial structure on China's energy intensity," Energy, Elsevier, vol. 69(C), pages 258-265.
    39. Zha, Donglan & Ding, Ning, 2015. "Threshold characteristic of energy efficiency on substitution between energy and non-energy factors," Economic Modelling, Elsevier, vol. 46(C), pages 180-187.
    40. Lei Jiang & Minhe Ji, 2016. "China’s Energy Intensity, Determinants and Spatial Effects," Sustainability, MDPI, vol. 8(6), pages 1-15, June.
    Full references (including those not matched with items on IDEAS)

    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. Yan, Huijie, 2015. "Provincial energy intensity in China: The role of urbanization," Energy Policy, Elsevier, vol. 86(C), pages 635-650.
    2. 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.
    3. 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.
    4. 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).
    5. 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.
    6. Guang, Fengtao & He, Yongxiu & Wen, Le & Sharp, Basil, 2019. "Energy intensity and its differences across China’s regions: Combining econometric and decomposition analysis," Energy, Elsevier, vol. 180(C), pages 989-1000.
    7. 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).
    8. Jiang, Xuemei & Duan, Yuwan & Green, Christopher, 2017. "Regional disparity in energy intensity of China and the role of industrial and export structure," Resources, Conservation & Recycling, Elsevier, vol. 120(C), pages 209-218.
    9. 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.
    10. Wu, Shu & Ding, Song, 2021. "Efficiency improvement, structural change, and energy intensity reduction: Evidence from Chinese agricultural sector," Energy Economics, Elsevier, vol. 99(C).
    11. Zhang, Dayong & Cao, Hong & Wei, Yi-Ming, 2016. "Identifying the determinants of energy intensity in China: A Bayesian averaging approach," Applied Energy, Elsevier, vol. 168(C), pages 672-682.
    12. Huang, Junbing & Chen, Xiang, 2020. "Domestic R&D activities, technology absorption ability, and energy intensity in China," Energy Policy, Elsevier, vol. 138(C).
    13. Löschel, Andreas & Pothen, Frank & Schymura, Michael, 2015. "Peeling the onion: Analyzing aggregate, national and sectoral energy intensity in the European Union," Energy Economics, Elsevier, vol. 52(S1), pages 63-75.
    14. Chen, Zhongfei & Huang, Wanjing & Zheng, Xian, 2019. "The decline in energy intensity: Does financial development matter?," Energy Policy, Elsevier, vol. 134(C).
    15. 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.
    16. 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.
    17. Yang, Guangfei & Li, Wenli & Wang, Jianliang & Zhang, Dongqing, 2016. "A comparative study on the influential factors of China's provincial energy intensity," Energy Policy, Elsevier, vol. 88(C), pages 74-85.
    18. Elliott, Robert J.R. & Sun, Puyang & Zhu, Tong, 2017. "The direct and indirect effect of urbanization on energy intensity: A province-level study for China," Energy, Elsevier, vol. 123(C), pages 677-692.
    19. Adom, Philip Kofi, 2015. "Business cycle and economic-wide energy intensity: The implications for energy conservation policy in Algeria," Energy, Elsevier, vol. 88(C), pages 334-350.
    20. Li, Ke & Lin, Boqiang, 2015. "The improvement gap in energy intensity: Analysis of China's thirty provincial regions using the improved DEA (data envelopment analysis) model," Energy, Elsevier, vol. 84(C), pages 589-599.

    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:ecmode:v:65:y:2017:i:c:p:41-50. 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.elsevier.com/locate/inca/30411 .

    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.