IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v107y2021i3d10.1007_s11069-020-04437-3.html
   My bibliography  Save this article

The effect of directed technical change on carbon dioxide emissions: evidence from China’s industrial sector at the provincial level

Author

Listed:
  • Liang Liu

    (Southeast University)

  • Lianshui Li

    (Southeast University)

Abstract

Technical change has a pivotal role to play in low-carbon development. Recent research has offered different insights regarding the effect of technical change on CO2 emissions but ignored the bias of technical changes which lead to changes in CO2 emissions. To fill the gap, this paper uses the 2008 to 2015 provincial-level data on China’s 22 industrial sub-sectors to investigate both the effect of directed technical change on CO2 emissions and its heterogeneity. We find that the technical change in most industrial sectors in China was capital-biased, although a labor-biased trend was evident. Labor-biased technical change is conducive to CO2 reduction, while capital-biased technical change has the opposite effect. Moreover, this effect is different by developmental periods, industries, and regions. Therefore, we propose that the government promotes labor-biased technical change based on the differentiated characteristics.

Suggested Citation

  • Liang Liu & Lianshui Li, 2021. "The effect of directed technical change on carbon dioxide emissions: evidence from China’s industrial sector at the provincial level," 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. 107(3), pages 2463-2486, July.
    • Handle: RePEc:spr:nathaz:v:107:y:2021:i:3:d:10.1007_s11069-020-04437-3
    DOI: 10.1007/s11069-020-04437-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-020-04437-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-020-04437-3?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. Shuai, Chenyang & Shen, Liyin & Jiao, Liudan & Wu, Ya & Tan, Yongtao, 2017. "Identifying key impact factors on carbon emission: Evidences from panel and time-series data of 125 countries from 1990 to 2011," Applied Energy, Elsevier, vol. 187(C), pages 310-325.
    2. Sorrell, Steve & Dimitropoulos, John, 2008. "The rebound effect: Microeconomic definitions, limitations and extensions," Ecological Economics, Elsevier, vol. 65(3), pages 636-649, April.
    3. Jordaan, Sarah M. & Romo-Rabago, Elizabeth & McLeary, Romaine & Reidy, Luke & Nazari, Jamal & Herremans, Irene M., 2017. "The role of energy technology innovation in reducing greenhouse gas emissions: A case study of Canada," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 1397-1409.
    4. Feng Dong & Ruyin Long & Zhuolin Li & Yuanju Dai, 2016. "Analysis of carbon emission intensity, urbanization and energy mix: evidence from 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. 82(2), pages 1375-1391, June.
    5. Sanstad, Alan H. & Roy, Joyashree & Sathaye, Jayant A., 2006. "Estimating energy-augmenting technological change in developing country industries," Energy Economics, Elsevier, vol. 28(5-6), pages 720-729, November.
    6. Salim, Ruhul A. & Shafiei, Sahar, 2014. "Urbanization and renewable and non-renewable energy consumption in OECD countries: An empirical analysis," Economic Modelling, Elsevier, vol. 38(C), pages 581-591.
    7. Yang, Zhenbing & Shao, Shuai & Yang, Lili & Miao, Zhuang, 2018. "Improvement pathway of energy consumption structure in China's industrial sector: From the perspective of directed technical change," Energy Economics, Elsevier, vol. 72(C), pages 166-176.
    8. Daron Acemoglu, 2002. "Directed Technical Change," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 69(4), pages 781-809.
    9. Dong Wang, Amin Mugera, and Ben White, 2019. "Directed Technical Change, Capital Intensity Increase and Energy Transition: Evidence from China," The Energy Journal, International Association for Energy Economics, vol. 0(The New E).
    10. Mark Watts, 2017. "Cities spearhead climate action," Nature Climate Change, Nature, vol. 7(8), pages 537-538, August.
    11. Miao, Zhuang & Chen, Xiaodong & Baležentis, Tomas & Sun, Chuanwang, 2019. "Atmospheric environmental productivity across the provinces of China: Joint decomposition of range adjusted measure and Luenberger productivity indicator," Energy Policy, Elsevier, vol. 132(C), pages 665-677.
    12. Rojas-Vallejos, Jorge & Lastuka, Amy, 2020. "The income inequality and carbon emissions trade-off revisited," Energy Policy, Elsevier, vol. 139(C).
    13. Cheng, Zhonghua & Liu, Jun & Li, Lianshui & Gu, Xinbei, 2020. "Research on meta-frontier total-factor energy efficiency and its spatial convergence in Chinese provinces," Energy Economics, Elsevier, vol. 86(C).
    14. Wei, Taoyuan & Liu, Yang, 2017. "Estimation of global rebound effect caused by energy efficiency improvement," Energy Economics, Elsevier, vol. 66(C), pages 27-34.
    15. Shafiei, Sahar & Salim, Ruhul A., 2014. "Non-renewable and renewable energy consumption and CO2 emissions in OECD countries: A comparative analysis," Energy Policy, Elsevier, vol. 66(C), pages 547-556.
    16. Huan Zhang, 2016. "Exploring the impact of environmental regulation on economic growth, energy use, and CO2 emissions nexus 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. 84(1), pages 213-231, October.
    17. Zha, Donglan & Kavuri, Anil Savio & Si, Songjian, 2017. "Energy biased technology change: Focused on Chinese energy-intensive industries," Applied Energy, Elsevier, vol. 190(C), pages 1081-1089.
    18. Wang, Ping & Wu, Wanshui & Zhu, Bangzhu & Wei, Yiming, 2013. "Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province, China," Applied Energy, Elsevier, vol. 106(C), pages 65-71.
    19. Jianling Jiao & Yufei Yang & Yu Bai, 2018. "The impact of inter-industry R&D technology spillover on carbon emission 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. 91(3), pages 913-929, April.
    20. Ye, Chusheng & Ye, Qin & Shi, Xunpeng & Sun, Yongping, 2020. "Technology gap, global value chain and carbon intensity: Evidence from global manufacturing industries," Energy Policy, Elsevier, vol. 137(C).
    21. Jiao, Jianling & Jiang, Guili & Yang, Ranran, 2018. "Impact of R&D technology spillovers on carbon emissions between China’s regions," Structural Change and Economic Dynamics, Elsevier, vol. 47(C), pages 35-45.
    22. Li, Wei & Sun, Wen & Li, Guomin & Jin, Baihui & Wu, Wen & Cui, Pengfei & Zhao, Guohao, 2018. "Transmission mechanism between energy prices and carbon emissions using geographically weighted regression," Energy Policy, Elsevier, vol. 115(C), pages 434-442.
    23. Zhang, Zhien & Pan, Shu-Yuan & Li, Hao & Cai, Jianchao & Olabi, Abdul Ghani & Anthony, Edward John & Manovic, Vasilije, 2020. "Recent advances in carbon dioxide utilization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 125(C).
    24. Yuan, Zhigang & Rao, Can & Shi, Shuangshuang, 2019. "Balance sheet expansion and economic growth in China: Crowd in or crowd out?," China Economic Review, Elsevier, vol. 57(C).
    25. Yu, Junqing & Zhou, Kaile & Yang, Shanlin, 2019. "Regional heterogeneity of China's energy efficiency in “new normal”: A meta-frontier Super-SBM analysis," Energy Policy, Elsevier, vol. 134(C).
    26. Sun, Chuanwang & Ding, Dan & Fang, Xingming & Zhang, Huiming & Li, Jianglong, 2019. "How do fossil energy prices affect the stock prices of new energy companies? Evidence from Divisia energy price index in China's market," Energy, Elsevier, vol. 169(C), pages 637-645.
    27. Wang, Haikun & Zhang, Yanxia & Lu, Xi & Nielsen, Chris P. & Bi, Jun, 2015. "Understanding China׳s carbon dioxide emissions from both production and consumption perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 189-200.
    28. Zhou, Xiaoyan & Zhang, Jie & Li, Junpeng, 2013. "Industrial structural transformation and carbon dioxide emissions in China," Energy Policy, Elsevier, vol. 57(C), pages 43-51.
    29. Miao, Zhuang & Baležentis, Tomas & Shao, Shuai & Chang, Dongfeng, 2019. "Energy use, industrial soot and vehicle exhaust pollution—China's regional air pollution recognition, performance decomposition and governance," Energy Economics, Elsevier, vol. 83(C), pages 501-514.
    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. Fan, Fei & Dai, Shangze & Yang, Bo & Ke, Haiqian, 2023. "Urban density, directed technological change, and carbon intensity: An empirical study based on Chinese cities," Technology in Society, Elsevier, vol. 72(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. Wang, Shaojian & Zeng, Jingyuan & Liu, Xiaoping, 2019. "Examining the multiple impacts of technological progress on CO2 emissions in China: A panel quantile regression approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 140-150.
    2. Miao, Zhuang & Chen, Xiaodong, 2022. "Combining parametric and non-parametric approach, variable & source -specific productivity changes and rebound effect of energy & environment," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    3. Li, Ke & Lin, Boqiang, 2015. "Impacts of urbanization and industrialization on energy consumption/CO2 emissions: Does the level of development matter?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1107-1122.
    4. Vélez-Henao, Johan-Andrés & Font Vivanco, David & Hernández-Riveros, Jesús-Antonio, 2019. "Technological change and the rebound effect in the STIRPAT model: A critical view," Energy Policy, Elsevier, vol. 129(C), pages 1372-1381.
    5. Ma, Xuejiao & Jiang, Ping & Jiang, Qichuan, 2020. "Research and application of association rule algorithm and an optimized grey model in carbon emissions forecasting," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    6. Feng Dong & Yue Wang & Xiaojie Zhang, 2018. "Can Environmental Quality Improvement and Emission Reduction Targets Be Realized Simultaneously? Evidence from China and A Geographically and Temporally Weighted Regression Model," IJERPH, MDPI, vol. 15(11), pages 1-22, October.
    7. Dong, Kangyin & Hochman, Gal & Zhang, Yaqing & Sun, Renjin & Li, Hui & Liao, Hua, 2018. "CO2 emissions, economic and population growth, and renewable energy: Empirical evidence across regions," Energy Economics, Elsevier, vol. 75(C), pages 180-192.
    8. Shaozhou Qi & Huarong Peng & Xiujie Tan, 2019. "The Moderating Effect of R&D Investment on Income and Carbon Emissions in China: Direct and Spatial Spillover Insights," Sustainability, MDPI, vol. 11(5), pages 1-19, February.
    9. 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).
    10. Xuejiao Ma & Qichuan Jiang, 2019. "How to Balance the Trade-off between Economic Development and Climate Change?," Sustainability, MDPI, vol. 11(6), pages 1-30, March.
    11. Liu, Jun & Liu, Liang & Qian, Yu & Song, Shunfeng, 2022. "The effect of artificial intelligence on carbon intensity: Evidence from China's industrial sector," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    12. Fan, Fei & Dai, Shangze & Yang, Bo & Ke, Haiqian, 2023. "Urban density, directed technological change, and carbon intensity: An empirical study based on Chinese cities," Technology in Society, Elsevier, vol. 72(C).
    13. Lemoine, Derek, 2020. "General equilibrium rebound from energy efficiency innovation," European Economic Review, Elsevier, vol. 125(C).
    14. Jiancheng Qin & Hui Tao & Minjin Zhan & Qamar Munir & Karthikeyan Brindha & Guijin Mu, 2019. "Scenario Analysis of Carbon Emissions in the Energy Base, Xinjiang Autonomous Region, China," Sustainability, MDPI, vol. 11(15), pages 1-18, August.
    15. Lili Sun & Hang Yu & Qiang Liu & Yanzun Li & Lintao Li & Hua Dong & Caspar Daniel Adenutsi, 2022. "Identifying the Key Driving Factors of Carbon Emissions in ‘Belt and Road Initiative’ Countries," Sustainability, MDPI, vol. 14(15), pages 1-16, July.
    16. Lingyun He & Fang Yin & Zhangqi Zhong & Zhihua Ding, 2017. "The impact of local government investment on the carbon emissions reduction effect: An empirical analysis of panel data from 30 provinces and municipalities in China," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-20, July.
    17. Karel Janda & Binyi Zhang, 2022. "The Impact of Renewable Energy and Technology Innovation on Chinese Carbon Dioxide Emissions," Springer Proceedings in Business and Economics, in: David Procházka (ed.), Regulation of Finance and Accounting, chapter 0, pages 177-189, Springer.
    18. Yang, Zhenbing & Shi, Qingquan & Lv, Xiangqiu & Shi, Qi, 2022. "Heterogeneous low-carbon targets and energy structure optimization: Does stricter carbon regulation really matter?," Structural Change and Economic Dynamics, Elsevier, vol. 60(C), pages 329-343.
    19. Wang, Changjian & Miao, Zhuang & Chen, Xiaodong & Cheng, Yu, 2021. "Factors affecting changes of greenhouse gas emissions in Belt and Road countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    20. Fei Wang & Changjian Wang & Jing Chen & Zeng Li & Ling Li, 2020. "Examining the determinants of energy-related carbon emissions in Central Asia: country-level LMDI and EKC analysis during different phases," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(8), pages 7743-7769, December.

    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:spr:nathaz:v:107:y:2021:i:3:d:10.1007_s11069-020-04437-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.