IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v243y2022ics0360544221033156.html
   My bibliography  Save this article

Exploring the effective way of reducing carbon intensity in the heavy industry using a semiparametric econometric approach

Author

Listed:
  • Xu, Renjing
  • Xu, Bin

Abstract

China has promised that by 2030, its carbon intensity will be cut down by about 60%. The purpose of this article is to investigate the main influencing factors of the heavy industry's carbon intensity. Different from the existing related literature, this article uses a semiparametric model to empirically analyze the carbon intensity of China's heavy industry. The main results are as follows: (1) the relationship between spatial agglomeration and carbon intensity shows a non-linear pattern, mainly caused by the cross-regional flow of production factors. (2) The impact of technological progress on carbon intensity also displays significant non-linear characteristics, mainly due to the staged differences in research and development investment. The following three factors are linearly related to carbon intensity. (1) Energy consumption structure has a more significant linear impact on the carbon intensity in the central and eastern regions, due to the heavy coal consumption of the heavy industry in these two regions. (2) The linear impact of environmental regulations on the carbon intensity in the eastern region is more significant, owing to the region's considerable investments in environmental governance. (3) The industrial structure has the most significant linear impact on the carbon intensity in the eastern region, since the scale of the tertiary industry in this region is larger. The conclusions can provide empirical support for local government managers to formulate differentiated energy policies.

Suggested Citation

  • Xu, Renjing & Xu, Bin, 2022. "Exploring the effective way of reducing carbon intensity in the heavy industry using a semiparametric econometric approach," Energy, Elsevier, vol. 243(C).
    • Handle: RePEc:eee:energy:v:243:y:2022:i:c:s0360544221033156
    DOI: 10.1016/j.energy.2021.123066
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221033156
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2021.123066?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. Román Mínguez & Roberto Basile & María Durbán, 2020. "An alternative semiparametric model for spatial panel data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(4), pages 669-708, December.
    2. Xu, Bin & Lin, Boqiang, 2021. "Investigating spatial variability of CO2 emissions in heavy industry: Evidence from a geographically weighted regression model," Energy Policy, Elsevier, vol. 149(C).
    3. Pedroni, Peter, 2004. "Panel Cointegration: Asymptotic And Finite Sample Properties Of Pooled Time Series Tests With An Application To The Ppp Hypothesis," Econometric Theory, Cambridge University Press, vol. 20(3), pages 597-625, June.
    4. Lu, Shibao & Wang, Jianhua & Shang, Yizi & Bao, Haijun & Chen, Huixiong, 2017. "Potential assessment of optimizing energy structure in the city of carbon intensity target," Applied Energy, Elsevier, vol. 194(C), pages 765-773.
    5. Ouyang, Xiaoling & Fang, Xingming & Cao, Yan & Sun, Chuanwang, 2020. "Factors behind CO2 emission reduction in Chinese heavy industries: Do environmental regulations matter?," Energy Policy, Elsevier, vol. 145(C).
    6. Xu, Bin & Lin, Boqiang, 2016. "Reducing CO2 emissions in China's manufacturing industry: Evidence from nonparametric additive regression models," Energy, Elsevier, vol. 101(C), pages 161-173.
    7. Pulselli, Riccardo Maria & Broersma, Siebe & Martin, Craig Lee & Keeffe, Greg & Bastianoni, Simone & van den Dobbelsteen, Andy, 2021. "Future city visions. The energy transition towards carbon-neutrality: lessons learned from the case of Roeselare, Belgium," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    8. Yue-Jun Zhang & Zhao Liu & Huan Zhang & Tai-De Tan, 2014. "The impact of economic growth, industrial structure and urbanization on carbon emission intensity in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 73(2), pages 579-595, September.
    9. Zhang, Chi & Su, Bin & Zhou, Kaile & Sun, Yuan, 2020. "A multi-dimensional analysis on microeconomic factors of China's industrial energy intensity (2000–2017)," Energy Policy, Elsevier, vol. 147(C).
    10. Cheng, Zhonghua & Li, Lianshui & Liu, Jun, 2018. "Industrial structure, technical progress and carbon intensity in China's provinces," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2935-2946.
    11. Song, Yi & Huang, Jian-Bai & Feng, Chao, 2018. "Decomposition of energy-related CO2 emissions in China's iron and steel industry: A comprehensive decomposition framework," Resources Policy, Elsevier, vol. 59(C), pages 103-116.
    12. Yao, Huizong & Zang, Chuanfu, 2021. "The spatiotemporal characteristics of electrical energy supply-demand and the green economy outlook of Guangdong Province, China," Energy, Elsevier, vol. 214(C).
    13. Xu, Bin & Chen, Jianbao, 2021. "How to achieve a low-carbon transition in the heavy industry? A nonlinear perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    14. Liu, Ying & Lin, Boqiang & Xu, Bin, 2021. "Modeling the impact of energy abundance on economic growth and CO2 emissions by quantile regression: Evidence from China," Energy, Elsevier, vol. 227(C).
    15. Wu, Rong & Wang, Jieyu & Wang, Shaojian & Feng, Kuishuang, 2021. "The drivers of declining CO2 emissions trends in developed nations using an extended STIRPAT model: A historical and prospective analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    16. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    17. Zhu, Bangzhu & Huang, Liqing & Yuan, Lili & Ye, Shunxin & Wang, Ping, 2020. "Exploring the risk spillover effects between carbon market and electricity market: A bidimensional empirical mode decomposition based conditional value at risk approach," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 163-175.
    18. Xu, Bin & Luo, Yuemei & Xu, Renjing & Chen, Jianbao, 2021. "Exploring the driving forces of distributed energy resources in China: Using a semiparametric regression model," Energy, Elsevier, vol. 236(C).
    19. Alshammari, Yousef M., 2021. "Scenario analysis for energy transition in the chemical industry: An industrial case study in Saudi Arabia," Energy Policy, Elsevier, vol. 150(C).
    20. Zhang, Yue-Jun & Liang, Ting & Jin, Yan-Lin & Shen, Bo, 2020. "The impact of carbon trading on economic output and carbon emissions reduction in China’s industrial sectors," Applied Energy, Elsevier, vol. 260(C).
    21. Zhong, Mei-Rui & Xiao, Shun-Li & Zou, Han & Zhang, Yi-Jun & Song, Yi, 2021. "The effects of technical change on carbon intensity in China’s non-ferrous metal industry," Resources Policy, Elsevier, vol. 73(C).
    22. Wang, Miao & Feng, Chao, 2020. "The impacts of technological gap and scale economy on the low-carbon development of China's industries: An extended decomposition analysis," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    23. Jin, Gui & Shi, Xin & Zhang, Lei & Hu, Shougeng, 2020. "Measuring the SCCs of different Chinese regions under future scenarios," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    24. Alla Toktarova & Ida Karlsson & Johan Rootzén & Lisa Göransson & Mikael Odenberger & Filip Johnsson, 2020. "Pathways for Low-Carbon Transition of the Steel Industry—A Swedish Case Study," Energies, MDPI, vol. 13(15), pages 1-18, July.
    25. Ofosu-Adarkwa, Jeffrey & Xie, Naiming & Javed, Saad Ahmed, 2020. "Forecasting CO2 emissions of China's cement industry using a hybrid Verhulst-GM(1,N) model and emissions' technical conversion," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    26. Xu, Bin & Lin, Boqiang, 2020. "Investigating drivers of CO2 emission in China’s heavy industry: A quantile regression analysis," Energy, Elsevier, vol. 206(C).
    27. Hu, Yucai & Ren, Shenggang & Wang, Yangjie & Chen, Xiaohong, 2020. "Can carbon emission trading scheme achieve energy conservation and emission reduction? Evidence from the industrial sector in China," Energy Economics, Elsevier, vol. 85(C).
    28. Xu, Bin & Lin, Boqiang, 2018. "Assessing the development of China's new energy industry," Energy Economics, Elsevier, vol. 70(C), pages 116-131.
    29. Wang, Feng & Sun, Xiaoyu & Reiner, David M. & Wu, Min, 2020. "Changing trends of the elasticity of China's carbon emission intensity to industry structure and energy efficiency," Energy Economics, Elsevier, vol. 86(C).
    30. Chen, Jiandong & Gao, Ming & Mangla, Sachin Kumar & Song, Malin & Wen, Jie, 2020. "Effects of technological changes on China's carbon emissions," Technological Forecasting and Social Change, Elsevier, vol. 153(C).
    31. Wang, Xiaolei & Lin, Boqiang, 2016. "How to reduce CO2 emissions in China׳s iron and steel industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1496-1505.
    32. Fu, Rao & Jin, Gui & Chen, Jinyue & Ye, Yuyao, 2021. "The effects of poverty alleviation investment on carbon emissions in China based on the multiregional input–output model," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    33. Su, Bin & Ang, B.W., 2020. "Demand contributors and driving factors of Singapore’s aggregate carbon intensities," Energy Policy, Elsevier, vol. 146(C).
    34. Haseeb, Muhammad & Haouas, Ilham & Nasih, Mohammad & Mihardjo, Leonardus WW. & Jermsittiparsert, Kittisak, 2020. "Asymmetric impact of textile and clothing manufacturing on carbon-dioxide emissions: Evidence from top Asian economies," Energy, Elsevier, vol. 196(C).
    35. Springer, Cecilia & Evans, Sam & Lin, Jiang & Roland-Holst, David, 2019. "Low carbon growth in China: The role of emissions trading in a transitioning economy," Applied Energy, Elsevier, vol. 235(C), pages 1118-1125.
    36. 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).
    37. Xu, Bin & Lin, Boqiang, 2019. "Can expanding natural gas consumption reduce China's CO2 emissions?," Energy Economics, Elsevier, vol. 81(C), pages 393-407.
    38. Lin, Boqiang & Xu, Bin, 2020. "Effective ways to reduce CO2 emissions from China's heavy industry? Evidence from semiparametric regression models," Energy Economics, Elsevier, vol. 92(C).
    39. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
    40. Liang Jing & Hassan M. El-Houjeiri & Jean-Christophe Monfort & Adam R. Brandt & Mohammad S. Masnadi & Deborah Gordon & Joule A. Bergerson, 2020. "Carbon intensity of global crude oil refining and mitigation potential," Nature Climate Change, Nature, vol. 10(6), pages 526-532, June.
    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. Zhang, Ruchuan & Wei, Qian & Li, Aijun & Ren, LiYing, 2022. "Measuring efficiency and technology inequality of China's electricity generation and transmission system: A new approach of network Data Envelopment Analysis prospect cross-efficiency models," Energy, Elsevier, vol. 246(C).
    2. Mingming Zhu & Jigan Wang & Jie Zhang & Zhencheng Xing, 2022. "Urban Low-Carbon Consumption Performance Assessment: A Case Study of Yangtze River Delta Cities, China," Sustainability, MDPI, vol. 14(16), pages 1-14, August.
    3. Bin Xu, 2022. "How to Efficiently Reduce the Carbon Intensity of the Heavy Industry in China? Using Quantile Regression Approach," IJERPH, MDPI, vol. 19(19), pages 1-24, October.
    4. Chen, Shanshan & Zhang, Ruchuan & Li, Peiwen & Li, Aijun, 2023. "How to improve the performance of China's energy-transport-economy-environment system: An analysis based on new strategy parallel-series input-output data envelopment analysis models," Energy, Elsevier, vol. 281(C).
    5. Tinta, Abdoulganiour Almame, 2023. "Energy substitution in Africa: Cross-regional differentiation effects," Energy, Elsevier, vol. 263(PA).
    6. Kuei-Tien Chou & Hwa-Meei Liou, 2023. "Carbon Tax in Taiwan: Path Dependence and the High-Carbon Regime," Energies, MDPI, vol. 16(1), pages 1-22, January.
    7. Youying Mu & Chengzhuo Duan & Xin Li & Yongbo Wu, 2023. "A Monitoring Method for Corporate Environmental Performance Based on Data Fusion in China under the Double Carbon Target," Sustainability, MDPI, vol. 15(12), pages 1-16, June.
    8. Yanwei Lyu & Jinning Zhang & Fei Yang & Di Wu, 2022. "The “Local Neighborhood” Effect of Environmental Regulation on Green Innovation Efficiency: Evidence from China," IJERPH, MDPI, vol. 19(16), pages 1-20, August.
    9. Honma, Satoshi & Ushifusa, Yoshiaki & Okamura, Soyoka & Vandercamme, Lilu, 2023. "Measuring carbon emissions performance of Japan's metal industry: Energy inputs, agglomeration, and the potential for green recovery reduction," Resources Policy, Elsevier, vol. 82(C).
    10. Ziwei Yan & Chunying Cui, 2022. "How Natural Gas Infrastructure Affects Carbon Emission Indicators in Guangdong Province?," Sustainability, MDPI, vol. 14(13), pages 1-26, July.
    11. Libin Feng & Zhengcheng Sun, 2023. "The Impact of Green Finance Pilot Policy on Carbon Intensity in Chinese Cities—Based on the Synthetic Control Method," Sustainability, MDPI, vol. 15(15), pages 1-21, July.
    12. Mingjuan Ma & Shuifa Ke & Qiang Li & Yaqi Wu, 2023. "Towards Carbon Neutrality: A Comprehensive Analysis on Total Factor Carbon Productivity of the Yellow River Basin, China," Sustainability, MDPI, vol. 15(8), pages 1-23, April.
    13. Zhang, Weike & Fan, Hongxia & Zhao, Qiwei, 2023. "Seeing green: How does digital infrastructure affect carbon emission intensity?," Energy Economics, Elsevier, vol. 127(PB).

    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. Xu, Bin & Luo, Yuemei & Xu, Renjing & Chen, Jianbao, 2021. "Exploring the driving forces of distributed energy resources in China: Using a semiparametric regression model," Energy, Elsevier, vol. 236(C).
    2. Bin Xu, 2022. "How to Efficiently Reduce the Carbon Intensity of the Heavy Industry in China? Using Quantile Regression Approach," IJERPH, MDPI, vol. 19(19), pages 1-24, October.
    3. Xu, Bin & Lin, Boqiang, 2020. "Investigating drivers of CO2 emission in China’s heavy industry: A quantile regression analysis," Energy, Elsevier, vol. 206(C).
    4. Myo Myo Htike & Anil Shrestha & Makoto Kakinaka, 2022. "Investigating whether the environmental Kuznets curve hypothesis holds for sectoral CO2 emissions: evidence from developed and developing countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(11), pages 12712-12739, November.
    5. Lin, Boqiang & Xu, Bin, 2020. "Effective ways to reduce CO2 emissions from China's heavy industry? Evidence from semiparametric regression models," Energy Economics, Elsevier, vol. 92(C).
    6. Chen, Xing & Lin, Boqiang, 2021. "Towards carbon neutrality by implementing carbon emissions trading scheme: Policy evaluation in China," Energy Policy, Elsevier, vol. 157(C).
    7. Wang, Bo & Zhao, Jun & Dong, Kangyin & Jiang, Qingzhe, 2022. "High-quality energy development in China: Comprehensive assessment and its impact on CO2 emissions," Energy Economics, Elsevier, vol. 110(C).
    8. Xu, Bin & Lin, Boqiang, 2022. "Exploring the spatial distribution of distributed energy in China," Energy Economics, Elsevier, vol. 107(C).
    9. Jiang, Wei & Sun, Yifei, 2023. "Which is the more important factor of carbon emission, coal consumption or industrial structure?," Energy Policy, Elsevier, vol. 176(C).
    10. Lin, Boqiang & Xu, Bin, 2021. "A non-parametric analysis of the driving factors of China's carbon prices," Energy Economics, Elsevier, vol. 104(C).
    11. Bilal Mehmood & Syed Hassan Raza & Mahwish Rana & Huma Sohaib & Muhammad Azhar Khan, 2014. "Triangular Relationship between Energy Consumption, Price Index and National Income in Asian Countries: A Pooled Mean Group Approach in Presence of Structural Breaks," International Journal of Energy Economics and Policy, Econjournals, vol. 4(4), pages 610-620.
    12. repec:zbw:rwirep:0557 is not listed on IDEAS
    13. Ciarlone, Alessio, 2011. "Housing wealth effect in emerging economies," Emerging Markets Review, Elsevier, vol. 12(4), pages 399-417.
    14. Bernstein, Ronald & Madlener, Reinhard, 2011. "Responsiveness of Residential Electricity Demand in OECD Countries: A Panel Cointegation and Causality Analysis," FCN Working Papers 8/2011, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    15. Muntasir Murshed & Seemran Rashid, 2020. "An Empirical Investigation of Real Exchange Rate Responses to Foreign Currency Inflows: Revisiting the Dutch Disease Phenomenon in South Asia," The Economics and Finance Letters, Conscientia Beam, vol. 7(1), pages 23-46.
    16. Apergis, Nicholas & Payne, James E., 2011. "The renewable energy consumption-growth nexus in Central America," Applied Energy, Elsevier, vol. 88(1), pages 343-347, January.
    17. Nicoleta Mihaela Florea & Roxana Maria Bădîrcea & Ramona Costina Pîrvu & Alina Georgiana Manta & Marius Dalian Doran & Elena Jianu, 2020. "The impact of agriculture and renewable energy on climate change in Central and East European Countries," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 66(10), pages 444-457.
    18. Chakraborty, Chandana & Nunnenkamp, Peter, 2006. "Economic reforms, foreign direct investment and its economic effects in India," Kiel Working Papers 1272, Kiel Institute for the World Economy (IfW Kiel).
    19. Shahbaz, Muhammad & Nasreen, Samia & Ahmed, Khalid & Hammoudeh, Shawkat, 2017. "Trade openness–carbon emissions nexus: The importance of turning points of trade openness for country panels," Energy Economics, Elsevier, vol. 61(C), pages 221-232.
    20. Md. Shabbir Alam & Mustafa Raza Rabbani & Mohammad Rumzi Tausif & Joji Abey, 2021. "Banks’ Performance and Economic Growth in India: A Panel Cointegration Analysis," Economies, MDPI, vol. 9(1), pages 1-13, March.
    21. Pradhan, Rudra P. & Arvin, Mak B. & Norman, Neville R., 2015. "The dynamics of information and communications technologies infrastructure, economic growth, and financial development: Evidence from Asian countries," Technology in Society, Elsevier, vol. 42(C), pages 135-149.

    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:energy:v:243:y:2022:i:c:s0360544221033156. 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/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.