IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v73y2021ics0301420721002373.html
   My bibliography  Save this article

The effects of technical change on carbon intensity in China’s non-ferrous metal industry

Author

Listed:
  • Zhong, Mei-Rui
  • Xiao, Shun-Li
  • Zou, Han
  • Zhang, Yi-Jun
  • Song, Yi

Abstract

China is the world’s largest producer and consumer of non-ferrous metals. With a characteristic of energy-intensive, China’s non-ferrous metal industry is under enormous pressure to reduce carbon emissions. Accelerating the process of technical change is an effective way to reduce the carbon intensity of the non-ferrous metal industry. Based on industry data from 30 Chinese provinces during 2005–2017, this study calculated the technical change and corresponding decompositions utilising the slacks-based measure method and the Malmquist-Luenberger index. Subsequently, the impact of technical change on carbon intensity in terms of magnitude and direction is discussed, and the mediation effects among three technical change indexes and carbon intensity are analysed. The research results show that (1) during 2005–2017, the technical change of China’s nonferrous metal industry presented an overall growth trend, mainly contributed by the magnitude technical change. Simultaneously, there was variation in the technical change among the provinces. (2) The progress of magnitude technical change could continuously reduce carbon intensity in China’s non-ferrous metal industry, whereas with a characteristic of energy-using, the biased technical change will weaken the positive impact of technical change. (3) The technical change can reduce the carbon intensity of the non-ferrous metal industry by reducing energy consumption and optimising the energy structure. These findings suggest that effective promotion of technical change requires more targeted polices to reduce regional heterogeneity. The government should also encourage non-ferrous metal enterprises to reduce overcapacity, accelerate the process of high-end industry, strengthen the secondary recycling of materials and promote the use of clean energy.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:jrpoli:v:73:y:2021:i:c:s0301420721002373
    DOI: 10.1016/j.resourpol.2021.102226
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420721002373
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.resourpol.2021.102226?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. Lin, Boqiang & Zhang, Guoliang, 2013. "Estimates of electricity saving potential in Chinese nonferrous metals industry," Energy Policy, Elsevier, vol. 60(C), pages 558-568.
    2. 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.
    3. Sorrell, Steve & Dimitropoulos, John, 2008. "The rebound effect: Microeconomic definitions, limitations and extensions," Ecological Economics, Elsevier, vol. 65(3), pages 636-649, April.
    4. 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).
    5. Fare, Rolf, et al, 1997. " Biased Technical Change and the Malmquist Productivity Index," Scandinavian Journal of Economics, Wiley Blackwell, vol. 99(1), pages 119-127, March.
    6. Rolf Färe & Emili Grifell‐Tatjé & Shawna Grosskopf & C. A. Knox Lovell, 1997. "Biased Technical Change and the Malmquist Productivity Index," Scandinavian Journal of Economics, Wiley Blackwell, vol. 99(1), pages 119-127, March.
    7. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali & Shadman, Foroogh, 2014. "Power industry restructuring and eco-efficiency changes: A new slacks-based model in Malmquist–Luenberger Index measurement," Energy Policy, Elsevier, vol. 68(C), pages 132-145.
    8. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    9. Shao, Liuguo & He, Yingying & Feng, Chao & Zhang, Shijing, 2016. "An empirical analysis of total-factor productivity in 30 sub-sub-sectors of China's nonferrous metal industry," Resources Policy, Elsevier, vol. 50(C), pages 264-269.
    10. Khan, Ali Nawaz & En, Xie & Raza, Muhammad Yousaf & Khan, Naseer Abbas & Ali, Ahsan, 2020. "Sectorial study of technological progress and CO2 emission: Insights from a developing economy," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    11. Huang, Junbing & Liu, Qiang & Cai, Xiaochen & Hao, Yu & Lei, Hongyan, 2018. "The effect of technological factors on China's carbon intensity: New evidence from a panel threshold model," Energy Policy, Elsevier, vol. 115(C), pages 32-42.
    12. Yang, Yuan & Cai, Wenjia & Wang, Can, 2014. "Industrial CO2 intensity, indigenous innovation and R&D spillovers in China’s provinces," Applied Energy, Elsevier, vol. 131(C), pages 117-127.
    13. Fare, Rolf & Shawna Grosskopf & Mary Norris & Zhongyang Zhang, 1994. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries," American Economic Review, American Economic Association, vol. 84(1), pages 66-83, March.
    14. Li, Qiang & Zhang, Wenjuan & Li, Huiquan & He, Peng, 2017. "CO2 emission trends of China's primary aluminum industry: A scenario analysis using system dynamics model," Energy Policy, Elsevier, vol. 105(C), pages 225-235.
    15. Wang, Miao & Feng, Chao, 2018. "Decomposing the change in energy consumption in China's nonferrous metal industry: An empirical analysis based on the LMDI method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2652-2663.
    16. Emrouznejad, Ali & Yang, Guo-liang, 2016. "A framework for measuring global Malmquist–Luenberger productivity index with CO2 emissions on Chinese manufacturing industries," Energy, Elsevier, vol. 115(P1), pages 840-856.
    17. González Palencia, Juan C. & Furubayashi, Takaaki & Nakata, Toshihiko, 2013. "Analysis of CO2 emissions reduction potential in secondary production and semi-fabrication of non-ferrous metals," Energy Policy, Elsevier, vol. 52(C), pages 328-341.
    18. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    19. Silva, Thiago Christiano & Tabak, Benjamin Miranda & Cajueiro, Daniel Oliveira & Dias, Marina Villas Boas, 2017. "A comparison of DEA and SFA using micro- and macro-level perspectives: Efficiency of Chinese local banks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 216-223.
    20. Lin, Boqiang & Chen, Yufang & Zhang, Guoliang, 2017. "Technological progress and rebound effect in China's nonferrous metals industry: An empirical study," Energy Policy, Elsevier, vol. 109(C), pages 520-529.
    21. Wang, Zhaohua & Zhang, Bin & Liu, Tongfan, 2016. "Empirical analysis on the factors influencing national and regional carbon intensity in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 34-42.
    22. Wu, Yunna & Ke, Yiming & Zhang, Ting & Liu, Fangtong & Wang, Jing, 2018. "Performance efficiency assessment of photovoltaic poverty alleviation projects in China: A three-phase data envelopment analysis model," Energy, Elsevier, vol. 159(C), pages 599-610.
    23. Tan, Xianchun & Dong, Lele & Chen, Dexue & Gu, Baihe & Zeng, Yuan, 2016. "China’s regional CO2 emissions reduction potential: A study of Chongqing city," Applied Energy, Elsevier, vol. 162(C), pages 1345-1354.
    24. Jiayu Wang & Ke Wang & Xunpeng Shi & Yi-Ming Wei, 2019. "Spatial heterogeneity and driving forces of environmental productivity growth in China: Would it help to switch pollutant discharge fees to environmental taxes?," CEEP-BIT Working Papers 123, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    25. Shao, Yanmin, 2017. "Analysis of energy savings potential of China's nonferrous metals industry," Resources, Conservation & Recycling, Elsevier, vol. 117(PA), pages 25-33.
    26. 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.
    27. 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.
    28. Feng, Chao & Huang, Jian-Bai & Wang, Miao, 2018. "The driving forces and potential mitigation of energy-related CO2 emissions in China's metal industry," Resources Policy, Elsevier, vol. 59(C), pages 487-494.
    29. Song, Yi & Cheng, Jinhua & Zhang, Yijun & Dai, Tao & Huang, Jianbai, 2021. "Direct and indirect effects of heterogeneous technical change on metal consumption intensity: Evidence from G7 and BRICS countries," Resources Policy, Elsevier, vol. 71(C).
    30. Ren, Shenggang & Hu, Zhen, 2012. "Effects of decoupling of carbon dioxide emission by Chinese nonferrous metals industry," Energy Policy, Elsevier, vol. 43(C), pages 407-414.
    31. Li, Tingting & Wang, Yong & Zhao, Dingtao, 2016. "Environmental Kuznets Curve in China: New evidence from dynamic panel analysis," Energy Policy, Elsevier, vol. 91(C), pages 138-147.
    32. Zhang, Ning & Zhou, Peng & Kung, Chih-Chun, 2015. "Total-factor carbon emission performance of the Chinese transportation industry: A bootstrapped non-radial Malmquist index analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 584-593.
    33. Sonia I. Seneviratne & Markus G. Donat & Andy J. Pitman & Reto Knutti & Robert L. Wilby, 2016. "Allowable CO2 emissions based on regional and impact-related climate targets," Nature, Nature, vol. 529(7587), pages 477-483, January.
    34. Zhang, Chunhong & Liu, Haiying & Bressers, Hans Th.A. & Buchanan, Karen S., 2011. "Productivity growth and environmental regulations - accounting for undesirable outputs: Analysis of China's thirty provincial regions using the Malmquist–Luenberger index," Ecological Economics, Elsevier, vol. 70(12), pages 2369-2379.
    35. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "Multilateral Comparisons of Output, Input, and Productivity Using Superlative Index Numbers," Economic Journal, Royal Economic Society, vol. 92(365), pages 73-86, March.
    36. Yi, Ming & Wang, Yiqian & Sheng, Mingyue & Sharp, Basil & Zhang, Yao, 2020. "Effects of heterogeneous technological progress on haze pollution: Evidence from China," Ecological Economics, Elsevier, vol. 169(C).
    37. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2017. "Energy consumption, CO2 emissions, and economic growth: An ethical dilemma," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 808-824.
    38. Li, Hai-ling & Zhu, Xue-hong & Chen, Jin-yu & Jiang, Fei-tao, 2019. "Environmental regulations, environmental governance efficiency and the green transformation of China's iron and steel enterprises," Ecological Economics, Elsevier, vol. 165(C), pages 1-1.
    39. 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.
    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. Song, Yi & Ruan, Shengzhe & Cheng, Jinhua & Zhang, Yijun, 2023. "Technological change in critical metallic mineral sub-sectors and its impacts on mineral supply: Evidence from China," Resources Policy, Elsevier, vol. 85(PA).
    2. Yujian Jin & Lihong Yu & Yan Wang, 2022. "Green Total Factor Productivity and Its Saving Effect on the Green Factor in China’s Strategic Minerals Industry from 1998–2017," IJERPH, MDPI, vol. 19(22), pages 1-20, November.
    3. 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).
    4. 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).
    5. Pan, Minjie & Zhao, Xin & lv, Kangjuan & Rosak-Szyrocka, Joanna & Mentel, Grzegorz & Truskolaski, Tadeusz, 2023. "Internet development and carbon emission-reduction in the era of digitalization: Where will resource-based cities go?," Resources Policy, Elsevier, vol. 81(C).
    6. Li, Yonglin & Zuo, Zhili & Cheng, Yue & Cheng, Jinhua & Xu, Deyi, 2023. "Towards a decoupling between regional economic growth and CO2 emissions in China's mining industry: A comprehensive decomposition framework," Resources Policy, Elsevier, vol. 80(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. Song, Yi & Ruan, Shengzhe & Cheng, Jinhua & Zhang, Yijun, 2023. "Technological change in critical metallic mineral sub-sectors and its impacts on mineral supply: Evidence from China," Resources Policy, Elsevier, vol. 85(PA).
    2. Feng, Chao & Huang, Jian-Bai & Wang, Miao, 2019. "The sustainability of China’s metal industries: features, challenges and future focuses," Resources Policy, Elsevier, vol. 60(C), pages 215-224.
    3. 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).
    4. Lei, Ming & Yin, Zihan & Yu, Xiaowen & Deng, Shijie, 2017. "Carbon-weighted economic development performance and driving force analysis: Evidence from China," Energy Policy, Elsevier, vol. 111(C), pages 179-192.
    5. Zaijun Li & Xiang Zheng & Dongqi Sun, 2021. "The Influencing Effects of Industrial Eco-Efficiency on Carbon Emissions in the Yangtze River Delta," Energies, MDPI, vol. 14(23), pages 1-19, December.
    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. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    8. Cheng, Zhonghua & Li, Lianshui & Liu, Jun & Zhang, Huiming, 2018. "Total-factor carbon emission efficiency of China's provincial industrial sector and its dynamic evolution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 330-339.
    9. Pei-Pei Jiang & Yuan Wang & Jin Luo & Lin Zhu & Rui Shi & Song Hu & Xiaodong Zhu, 2023. "Measuring static and dynamic industrial eco-efficiency in China based on the MinDS–Malmquist–Luenberger model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(6), pages 5241-5261, June.
    10. Zhou, Di & Yin, Xiaoshuo & Xie, Dongchun, 2023. "Local governments’ environmental targets and green total factor productivity in Chinese cities," Economic Modelling, Elsevier, vol. 120(C).
    11. Yao, Xin & Guo, Chengwen & Shao, Shuai & Jiang, Zhujun, 2016. "Total-factor CO2 emission performance of China’s provincial industrial sector: A meta-frontier non-radial Malmquist index approach," Applied Energy, Elsevier, vol. 184(C), pages 1142-1153.
    12. Liu, Guangtian & Wang, Bing & Zhang, Ning, 2016. "A coin has two sides: Which one is driving China’s green TFP growth?," Economic Systems, Elsevier, vol. 40(3), pages 481-498.
    13. Valentin Zelenyuk, 2023. "Productivity analysis: roots, foundations, trends and perspectives," Journal of Productivity Analysis, Springer, vol. 60(3), pages 229-247, December.
    14. 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).
    15. Wenhan Ren & Jing Ni & Wen Jiao & Yan Li, 2023. "Explore the key factors of sustainable development: A bibliometric and visual analysis of technological progress," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(1), pages 492-509, February.
    16. Ben Lahouel, Béchir & Taleb, Lotfi & Ben Zaied, Younes & Managi, Shunsuke, 2022. "Does primary stakeholder management improve competitiveness? A dynamic network non-parametric frontier approach," Economic Modelling, Elsevier, vol. 116(C).
    17. Minyoung Yang & Jinsoo Kim, 2022. "A Critical Review of the Definition and Estimation of Carbon Efficiency," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    18. Chen, Xiang & Chen, Yong & Huang, Wenli & Zhang, Xuping, 2023. "A new Malmquist-type green total factor productivity measure: An application to China," Energy Economics, Elsevier, vol. 117(C).
    19. 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).
    20. Xiao, Yi & Qi, Guanqiu & Jin, Mengjie & Yuen, Kum Fai & Chen, Zhuo & Li, Kevin X., 2021. "Efficiency of Port State Control inspection regimes: A comparative study," Transport Policy, Elsevier, vol. 106(C), pages 165-172.

    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:jrpoli:v:73:y:2021:i:c:s0301420721002373. 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/30467 .

    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.