IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v184y2023ics1364032123004434.html
   My bibliography  Save this article

Impact of labor and energy allocation imbalance on carbon emission efficiency in China's industrial sectors

Author

Listed:
  • Zhang, Sheng
  • Yu, Ran
  • Wen, Zuhui
  • Xu, Jiayu
  • Liu, Peihan
  • Zhou, Yunqiao
  • Zheng, Xiaoqi
  • Wang, Lei
  • Hao, Jiming

Abstract

Greenhouse gas emission is the focus of global climate change concerns. The change in industrial structure can impact carbon emission efficiency (CEE) by affecting labor and energy input. However, there is an obvious imbalance of labor and energy allocation within China's industrial sectors. Here, we use the super-slacks-based model data envelopment analysis (Super-SBM-DEA) to calculate the CEE of 32 industrial sectors and adopt the Tobit model to analyze the impact of industrial allocation imbalance on CEE. The results show that the overall industry and manufacturing CEE is still at a low level, with an average CEE of 0.53. The industrial sectors with higher CEE are these sectors with advanced innovative technology and low energy consumption. The results of the Tobit model show that the imbalance of labor and energy allocation is the key factor limiting carbon emission efficiency improvement. Furthermore, the imbalance of labor allocation hurts the CEE of labor-intensive sectors. The coefficient of labor allocation imbalance (distL) is −2.483, and the inflow of labor can improve the CEE of non-labor-intensive sectors. The CEE of energy-intensive sectors is sensitive to the imbalance of energy allocation, the marginal impact of energy allocation imbalance (distE) is −2.296. Improving energy efficiency is a key task to reduce carbon emissions in sectors relying on energy input. But for non-energy-intensive sectors, optimizing energy allocation has a limited effect on reducing carbon emissions. This research can provide insights for emerging economies to coordinate carbon reduction and industrial transformation.

Suggested Citation

  • Zhang, Sheng & Yu, Ran & Wen, Zuhui & Xu, Jiayu & Liu, Peihan & Zhou, Yunqiao & Zheng, Xiaoqi & Wang, Lei & Hao, Jiming, 2023. "Impact of labor and energy allocation imbalance on carbon emission efficiency in China's industrial sectors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    • Handle: RePEc:eee:rensus:v:184:y:2023:i:c:s1364032123004434
    DOI: 10.1016/j.rser.2023.113586
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032123004434
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2023.113586?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. Liu, Yaqin & Zhao, Guohao & Zhao, Yushan, 2016. "An analysis of Chinese provincial carbon dioxide emission efficiencies based on energy consumption structure," Energy Policy, Elsevier, vol. 96(C), pages 524-533.
    2. Wang, Yihan & Wen, Zongguo & Cao, Xin & Dinga, Christian Doh, 2022. "Is information and communications technology effective for industrial energy conservation and emission reduction? Evidence from three energy-intensive industries in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    3. Zhang, Fan & Deng, Xiangzheng & Phillips, Fred & Fang, Chuanglin & Wang, Chao, 2020. "Impacts of industrial structure and technical progress on carbon emission intensity: Evidence from 281 cities in China," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    4. Jaehyuk Park & Ian B. Wood & Elise Jing & Azadeh Nematzadeh & Souvik Ghosh & Michael D. Conover & Yong-Yeol Ahn, 2019. "Global labor flow network reveals the hierarchical organization and dynamics of geo-industrial clusters," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    5. Zhang, Shangfeng & Li, Xiujie & Zhang, Chaojie & Luo, Jiayu & Cheng, Can & Ge, Wanjun, 2023. "Measurement of factor mismatch in industrial enterprises with labor skills heterogeneity," Journal of Business Research, Elsevier, vol. 158(C).
    6. Griffin, James M & Gregory, Paul R, 1976. "An Intercountry Translog Model of Energy Substitution Responses," American Economic Review, American Economic Association, vol. 66(5), pages 845-857, December.
    7. Zhu Liu & Dabo Guan & Wei Wei & Steven J. Davis & Philippe Ciais & Jin Bai & Shushi Peng & Qiang Zhang & Klaus Hubacek & Gregg Marland & Robert J. Andres & Douglas Crawford-Brown & Jintai Lin & Hongya, 2015. "Reduced carbon emission estimates from fossil fuel combustion and cement production in China," Nature, Nature, vol. 524(7565), pages 335-338, August.
    8. Mr. Sakai Ando & Koffie Ben Nassar, 2017. "Indexing Structural Distortion: Sectoral Productivity, Structural Change and Growth," IMF Working Papers 2017/205, International Monetary Fund.
    9. Auci, Sabrina & Becchetti, Leonardo, 2006. "The instability of the adjusted and unadjusted environmental Kuznets curves," Ecological Economics, Elsevier, vol. 60(1), pages 282-298, November.
    10. Zhang, Ning & Wang, Bing & Liu, Zhu, 2016. "Carbon emissions dynamics, efficiency gains, and technological innovation in China's industrial sectors," Energy, Elsevier, vol. 99(C), pages 10-19.
    11. Chowdhury, Jahedul Islam & Hu, Yukun & Haltas, Ismail & Balta-Ozkan, Nazmiye & Matthew, George Jr. & Varga, Liz, 2018. "Reducing industrial energy demand in the UK: A review of energy efficiency technologies and energy saving potential in selected sectors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 1153-1178.
    12. Tran, Trung Hieu & Mao, Yong & Nathanail, Paul & Siebers, Peer-Olaf & Robinson, Darren, 2019. "Integrating slacks-based measure of efficiency and super-efficiency in data envelopment analysis," Omega, Elsevier, vol. 85(C), pages 156-165.
    13. Friedl, Birgit & Getzner, Michael, 2003. "Determinants of CO2 emissions in a small open economy," Ecological Economics, Elsevier, vol. 45(1), pages 133-148, April.
    14. David H. Autor & David Dorn & Gordon H. Hanson, 2013. "The Geography of Trade and Technology Shocks in the United States," American Economic Review, American Economic Association, vol. 103(3), pages 220-225, May.
    15. 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).
    16. Zhao, Xin & Shang, Yuping & Song, Malin, 2020. "Industrial structure distortion and urban ecological efficiency from the perspective of green entrepreneurial ecosystems," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
    17. 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.
    18. Ellabban, Omar & Abu-Rub, Haitham & Blaabjerg, Frede, 2014. "Renewable energy resources: Current status, future prospects and their enabling technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 748-764.
    19. Kuishuang Feng & Steven J. Davis & Laixiang Sun & Klaus Hubacek, 2015. "Drivers of the US CO2 emissions 1997–2013," Nature Communications, Nature, vol. 6(1), pages 1-8, November.
    20. Qiao, Sen & Zhao, Dong Hao & Guo, Zi Xin & Tao, Zhang, 2022. "Factor price distortions, environmental regulation and innovation efficiency: An empirical study on China's power enterprises," Energy Policy, Elsevier, vol. 164(C).
    21. Jaehyuk Park & Ian Wood & Elise Jing & Azadeh Nematzadeh & Souvik Ghosh & Michael Conover & Yong-Yeol Ahn, 2019. "Global labor flow network reveals the hierarchical organization and dynamics of geo-industrial clusters in the world economy," Papers 1902.04613, arXiv.org, revised Mar 2019.
    22. 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.
    23. Song, Malin & An, Qingxian & Zhang, Wei & Wang, Zeya & Wu, Jie, 2012. "Environmental efficiency evaluation based on data envelopment analysis: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4465-4469.
    24. Lin, Boqiang & Chen, Xing, 2020. "How technological progress affects input substitution and energy efficiency in China: A case of the non-ferrous metals industry," Energy, Elsevier, vol. 206(C).
    25. Zhifu Mi & Jing Meng & Dabo Guan & Yuli Shan & Malin Song & Yi-Ming Wei & Zhu Liu & Klaus Hubacek, 2017. "Chinese CO2 emission flows have reversed since the global financial crisis," Nature Communications, Nature, vol. 8(1), pages 1-10, December.
    26. Yu, Bolin & Fang, Debin & Xiao, Kun & Pan, Yuling, 2023. "Drivers of renewable energy penetration and its role in power sector's deep decarbonization towards carbon peak," Renewable and Sustainable Energy Reviews, Elsevier, vol. 178(C).
    27. Sun, Chuanwang & Li, Zhi & Ma, Tiemeng & He, Runyong, 2019. "Carbon efficiency and international specialization position: Evidence from global value chain position index of manufacture," Energy Policy, Elsevier, vol. 128(C), pages 235-242.
    28. Ding, Feng & Yang, Jianping & Zhou, Zan, 2023. "Economic profits and carbon reduction potential of photovoltaic power generation for China's high-speed railway infrastructure," Renewable and Sustainable Energy Reviews, Elsevier, vol. 178(C).
    29. Paramati, Sudharshan Reddy & Shahzad, Umer & Doğan, Buhari, 2022. "The role of environmental technology for energy demand and energy efficiency: Evidence from OECD countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    30. 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.
    31. Koetse, Mark J. & de Groot, Henri L.F. & Florax, Raymond J.G.M., 2008. "Capital-energy substitution and shifts in factor demand: A meta-analysis," Energy Economics, Elsevier, vol. 30(5), pages 2236-2251, September.
    32. Zha, Donglan & Zhou, Dequn, 2014. "The elasticity of substitution and the way of nesting CES production function with emphasis on energy input," Applied Energy, Elsevier, vol. 130(C), pages 793-798.
    33. Pochont, Nitin Ralph & Sekhar Y, Raja, 2023. "Recent trends in photovoltaic technologies for sustainable transportation in passenger vehicles – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 181(C).
    34. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    35. Li, Ke & Lin, Boqiang, 2014. "The nonlinear impacts of industrial structure on China's energy intensity," Energy, Elsevier, vol. 69(C), pages 258-265.
    36. Fang Cai, 2023. "Regaining China's Resource Reallocative Efficiency to Boost Growth," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 31(1), pages 5-21, January.
    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. Yan Li & Gaizhi Ma, 2024. "A Study on the High-Quality Development Path and Implementation Countermeasures of China’s Construction Industry toward the Carbon Peaking and Carbon Neutralization Goals," Sustainability, MDPI, vol. 16(2), pages 1-14, January.
    2. Qiang Wang & Tingting Sun & Rongrong Li, 2024. "Does larger scale enhance carbon efficiency? Assessing the impact of corporate size on manufacturing carbon emission efficiency," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    3. Xu, Meng & Zhang, Silu & Li, Panwei & Weng, Zhixiong & Xie, Yang & Lan, Yan, 2024. "Energy-related carbon emission reduction pathways in Northwest China towards carbon neutrality goal," Applied Energy, Elsevier, vol. 358(C).
    4. Fang Yang & Chutong Li, 2024. "The Status Quo, Dilemma, and Transformation Path of the Carbon Neutrality-Related Policy of the ASEAN," Sustainability, MDPI, vol. 16(3), pages 1-25, February.

    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. Song, Malin & Zhu, Shuai & Wang, Jianlin & Zhao, Jiajia, 2020. "Share green growth: Regional evaluation of green output performance in China," International Journal of Production Economics, Elsevier, vol. 219(C), pages 152-163.
    2. Juanjuan Tian & Xiaoqian Song & Jinsuo Zhang, 2022. "Spatial-Temporal Pattern and Driving Factors of Carbon Efficiency in China: Evidence from Panel Data of Urban Governance," Energies, MDPI, vol. 15(7), pages 1-24, March.
    3. Li-Ming Xue & Zhi-Xue Zheng & Shuo Meng & Mingjun Li & Huaqing Li & Ji-Ming Chen, 2022. "Carbon emission efficiency and spatio-temporal dynamic evolution of the cities in Beijing-Tianjin-Hebei Region, China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(6), pages 7640-7664, June.
    4. Valeria Costantini & Francesco Crespi & Elena Paglialunga, 2019. "Capital–energy substitutability in manufacturing sectors: methodological and policy implications," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 9(2), pages 157-182, June.
    5. Jie Zhang & Zhencheng Xing & Jigan Wang, 2016. "Analysis of CO 2 Emission Performance and Abatement Potential for Municipal Industrial Sectors in Jiangsu, China," Sustainability, MDPI, vol. 8(7), pages 1-15, July.
    6. Zhang, Pengfeng & Gu, Haiying, 2023. "Potential policy coordination: Can energy intensity targets affect energy poverty?," Energy Economics, Elsevier, vol. 126(C).
    7. Yu, Bolin & Fang, Debin & Pan, Yuling & Jia, Yunxia, 2023. "Countries’ green total-factor productivity towards a low-carbon world: The role of energy trilemma," Energy, Elsevier, vol. 278(PB).
    8. Xian’En Wang & Shimeng Wang & Xipan Wang & Wenbo Li & Junnian Song & Haiyan Duan & Shuo Wang, 2019. "The Assessment of Carbon Performance under the Region-Sector Perspective based on the Nonparametric Estimation: A Case Study of the Northern Province in China," Sustainability, MDPI, vol. 11(21), pages 1-23, October.
    9. Wang, Jie & Xiong, Yiling & Tian, Xin & Liu, Shangwei & Li, Jiashuo & Tanikawa, Hiroki, 2018. "Stagnating CO2 emissions with in-depth socioeconomic transition in Beijing," Applied Energy, Elsevier, vol. 228(C), pages 1714-1725.
    10. Chen, Weiming & Zhang, Zhenjun & Chen, Kaiyuan, 2023. "Inter-regional economic-environmental correlation effects of power sector in China," Energy, Elsevier, vol. 278(C).
    11. Liu, Xiaohong & Yang, Jiangjiang & Xu, Chengzhen & Li, Xingchen & Zhu, Qingyuan, 2023. "Environmental regulation efficiency analysis by considering regional heterogeneity," Resources Policy, Elsevier, vol. 83(C).
    12. Jinkai Li & Jingjing Ma & Wei Wei, 2020. "Analysis and Evaluation of the Regional Characteristics of Carbon Emission Efficiency for China," Sustainability, MDPI, vol. 12(8), pages 1-22, April.
    13. Shi, Huiting & Chai, Jian & Lu, Quanying & Zheng, Jiali & Wang, Shouyang, 2022. "The impact of China's low-carbon transition on economy, society and energy in 2030 based on CO2 emissions drivers," Energy, Elsevier, vol. 239(PD).
    14. Bingjie Xu & Ruoyu Zhong & Yifeng Liu, 2019. "Comparison of CO 2 emissions reduction efficiency of household fuel consumption in China," Sustainability, MDPI, vol. 11(4), pages 1-13, February.
    15. Zhao, Nan & Liu, Xiaojie & Pan, Changfeng & Wang, Chenyang, 2021. "The performance of green innovation: From an efficiency perspective," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    16. Ya Chen & Wei Xu & Qian Zhou & Zhixiang Zhou, 2020. "Total Factor Energy Efficiency, Carbon Emission Efficiency, and Technology Gap: Evidence from Sub-Industries of Anhui Province in China," Sustainability, MDPI, vol. 12(4), pages 1-21, February.
    17. Cao, Jing & Ho, Mun S. & Ma, Rong, 2020. "Analyzing carbon pricing policies using a general equilibrium model with production parameters estimated using firm data," Energy Economics, Elsevier, vol. 92(C).
    18. Lyu, Yanwei & Wu, You & Zhang, Jinning, 2023. "How industrial structure distortion affects energy poverty? Evidence from China," Energy, Elsevier, vol. 278(C).
    19. Liu, Kui & Bai, Hongkun & Yin, Shuo & Lin, Boqiang, 2018. "Factor substitution and decomposition of carbon intensity in China's heavy industry," Energy, Elsevier, vol. 145(C), pages 582-591.
    20. Lagomarsino, Elena, 2020. "Estimating elasticities of substitution with nested CES production functions: Where do we stand?," Energy Economics, Elsevier, vol. 88(C).

    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:rensus:v:184:y:2023:i:c:s1364032123004434. 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/wps/find/journaldescription.cws_home/600126/description#description .

    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.