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.
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Notes
Since the CO2 emissions data from the China Emission Accounts and Datasets are only updated to 2015, for data consistency, the paper uses data from 2008–2015 to measure technical progress bias.
Taking into account data integrity, this paper uses the data of China’s 22 industrial sub-sectors in 30 provinces of mainland China except for Tibet. For detail of the industrial classification for national economic activities of China, see: http://www.stats.gov.cn/tjsj/tjbz/hyflbz/201710/t20171012_1541679.html
The capital-labor substitution elasticity of mining and processing of non-ferrous metal ores and manufacture of chemical fibers are close to 0, so we think they are neutral technical change.
The Eastern region includes Beijing, Tianjin, Hebei, Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Guangdong, Hainan; The Central region includes Shanxi, Liaoning, Jilin, Heilongjiang, Anhui, Jiangxi, Hubei, Hunan; The Western region includes Inner Mongolia, Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang.
References
Acemoglu D (2002) Directed Technical Change. Rev Econ Stud 69(4):781–809. https://doi.org/10.1111/1467-937X.00226
Chen L, Xu L, Yang Z (2017) Accounting carbon emission changes under regional industrial transfer in an urban agglomeration in China’s Pearl River Delta. J Clean Prod 167:110–119. https://doi.org/10.1016/j.jclepro.2017.08.041
Chen J, Xu C, Song M, Liu X (2018) Driving factors of China’s energy productivity and its spatial character: evidence from 248 cities. Ecol Indc 90:18–27. https://doi.org/10.1016/j.ecolind.2018.02.056
Cheng Z, Li L, Liu J, Zhang H (2019) Research on energy directed technical change in China’s industry and its optimization of energy consumption pattern. J Environ Manag 250:109471. https://doi.org/10.1016/j.jenvman.2019.109471
Cheng Z, Liu J, Li L, Gu X (2020) Research on meta-frontier total-factor energy efficiency and its spatial convergence in Chinese provinces. Energy Econ 86:104702. https://doi.org/10.1016/j.eneco.2020.104702
Dong F, Long R, Li Z, Dai Y (2016) Analysis of carbon emission intensity, urbanization and energy mix: evidence from China. Nat Hazards 82(2):1375–1391. https://doi.org/10.1007/s11069-016-2248-6
Fei R, Lin B (2017) Technology gap and CO2 emission reduction potential by technical efficiency measures: a meta-frontier modeling for the Chinese agricultural sector. Ecol Indc 73:653–661. https://doi.org/10.1016/j.ecolind.2016.10.021
IEA (2019) Global Energy & CO2 Status Report 2019, IEA, Paris https://www.iea.org/reports/global-energy-co2-status-report-2019
Jia P, Li K, Shao S (2018) Choice of technological change for China’s low-carbon development: evidence from three urban agglomerations. J Environ Manag 206:1308–1319. https://doi.org/10.1016/j.jenvman.2017.08.052
Jiao J, Yang Y, Bai Y (2018) The impact of inter-industry R&D technology spillover on carbon emission in China. Nat Hazards 91(3):913–929. https://doi.org/10.1007/s11069-017-3161-3
Jin W, Zhang HQ, Liu SS, Zhang HB (2019) Technological innovation, environmental regulation, and green total factor efficiency of industrial water resources. J Clean Prod 211:61–69. https://doi.org/10.1016/j.jclepro.2018.11.172
Jordaan SM, Romo-Rabago E, McLeary R, Reidy L, Nazari J, Herremans IM (2017) The role of energy technology innovation in reducing greenhouse gas emissions: a case study of Canada. Renew Sustain Energy Rev 78:1397–1409. https://doi.org/10.1016/j.rser.2017.05.162
Klump R, McAdam P, Willman A (2007) Factor substitution and factor-augmenting technical progress in the United States: a normalized supply-side system approach. Rev Econ Stat 89(1):183–192. https://doi.org/10.1162/rest.89.1.183
Lee KH, Min B (2015) Green R&D for eco-innovation and its impact on carbon emissions and firm performance. J Clean Prod 108:534–542. https://doi.org/10.1016/j.jclepro.2015.05.114
Li M, Wang Q (2017) Will technology advances alleviate climate change? Dual effects of technology change on aggregate carbon dioxide emissions. Energy Sustain Dev 41:61–68. https://doi.org/10.1016/j.esd.2017.08.004
Li W, Sun W, Li G, Jin B, Wu W, Cui P, Zhao G (2018) Transmission mechanism between energy prices and carbon emissions using geographically weighted regression. Energy Policy 115:434–442. https://doi.org/10.1016/j.enpol.2018.01.005
Miao Z, Chen X, Baležentis T, Sun C (2019) Atmospheric environmental productivity across the provinces of China: joint decomposition of range adjusted measure and Luenberger productivity indicator. Energy Policy 132:665–677. https://doi.org/10.1016/j.enpol.2019.06.019
Miao Z, Baležentis T, Shao S, Chang D (2019) Energy use, industrial soot and vehicle exhaust pollution—China’s regional air pollution recognition, performance decomposition and governance. Energy Econ 83:501–514. https://doi.org/10.1016/j.eneco.2019.07.002
Rojas-Vallejos J, Lastuka A (2020) The income inequality and carbon emissions trade-off revisited. Energy Policy 139:111302. https://doi.org/10.1016/j.enpol.2020.111302
Sanstad AH, Roy J, Sathaye JA (2006) Estimating energy-augmenting technological change in developing country industries. Energy Econ 28(5–6):720–729. https://doi.org/10.1016/j.eneco.2006.07.005
Shafiei S, Salim RA (2014) Non-renewable and renewable energy consumption and CO2 emissions in OECD countries: a comparative analysis. Energy Policy 66:547–556. https://doi.org/10.1016/j.enpol.2013.10.064
Shao S, Luan R, Yang Z et al (2016) Does directed technological change get greener: empirical evidence from Shanghai's industrial green developmenttransformation. Ecol Ind 69:758–770
Shuai C, Shen L, Jiao L, Wu Y, Tan Y (2017) Identifying key impact factors on carbon emission: evidences from panel and time-series data of 125 countries from 1990 to 2011. Appl Energy 187:310–325. https://doi.org/10.1016/j.apenergy.2016.11.029
Sorrell S, Dimitropoulos J (2008) The rebound effect: microeconomic definitions, limitations and extensions. Ecol Econ 65(3):636–649. https://doi.org/10.1016/j.ecolecon.2007.08.013
Subrahmanya MB (2006) Labour productivity, energy intensity and economic performance in small enterprises: a study of brick enterprises cluster in India. Energy Convers Manag 47(6):763–777. https://doi.org/10.1016/j.enconman.2005.05.021
Sun C, Ding D, Fang X, Zhang H, Li J (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 169:637–645. https://doi.org/10.1016/j.energy.2018.12.032
Wang Q, Jiang R (2020) Is carbon emission growth decoupled from economic growth in emerging countries? New insights from labor and investment effects. J Clean Prod 248:119188. https://doi.org/10.1016/j.jclepro.2019.119188
Wang P, Wu W, Zhu B, Wei Y (2013) Examining the impact factors of energy-related CO2 emissions using the STIRPAT model in Guangdong Province. China Appl Energy 106:65–71. https://doi.org/10.1016/j.apenergy.2013.01.036
Wang H, Zhang Y, Lu X, Nielsen CP, Bi J (2015) Understanding China׳ s carbon dioxide emissions from both production and consumption perspectives. Renew Sustain Energy Rev 52:189–200. https://doi.org/10.1016/j.rser.2015.07.089
Wang D, Mugera A, White B (2019) Directed technical change, capital intensity increase and energy transition: evidence from China. Energy J. https://doi.org/10.2139/ssrn.3284258
Watts M (2017) Cities spearhead climate action. Nat Clim Change 7(8):537–538. https://doi.org/10.1038/nclimate3358
Wei T, Liu Y (2017) Estimation of global rebound effect caused by energy efficiency improvement. Energy Econ 66:27–34. https://doi.org/10.1016/j.eneco.2017.05.030
Xiu J, Zhang GX, Hu Y (2019) Which kind of directed technical change does China’s economy have? From the perspective of energy-saving and low-carbon. J Clean Prod 233:160–168. https://doi.org/10.1016/j.jclepro.2019.05.296
Yang Z, Shao S, Yang L, Miao Z (2018) Improvement pathway of energy consumption structure in China’s industrial sector: from the perspective of directed technical change. Energy Econ 72:166–176. https://doi.org/10.1016/j.eneco.2018.04.003
Ye C, Ye Q, Shi X, Sun Y (2020) Technology gap, global value chain and carbon intensity: evidence from global manufacturing industries. Energy Policy 137:111094. https://doi.org/10.1016/j.enpol.2019.111094
Yu J, Zhou K, Yang S (2019) Regional heterogeneity of China’s energy efficiency in new normal: a meta-frontier Super-SBM analysis. Energy Policy 134:110941. https://doi.org/10.1016/j.enpol.2019.110941
Yuan Z, Rao C, Shi S (2019) Balance sheet expansion and economic growth in China: crowd in or crowd out? China Econ Rev 57:101119. https://doi.org/10.1016/j.chieco.2017.10.003
Zha D, Kavuri AS, Si S (2017) Energy biased technology change: focused on Chinese energy-intensive industries. Appl Energy 190:1081–1089. https://doi.org/10.1016/j.apenergy.2016.11.001
Zhang H (2016) Exploring the impact of environmental regulation on economic growth, energy use, and CO 2 emissions nexus in China. Nat Hazards 84(1):213–231. https://doi.org/10.1007/s11069-016-2417-7
Zhang X, Han J, Zhao H, Deng S, Xiao H, Peng H, Zhang Y (2012) Evaluating the interplays among economic growth and energy consumption and CO2 emission of China during 1990–2007. Renew Sustain Energy Rev 16(1):65–72. https://doi.org/10.1016/j.rser.2011.07.137
Zhang Z, Pan SY, Li H, Cai J, Olabi AG, Anthony EJ, Manovic V (2020) Recent advances in carbon dioxide utilization. Renew Sustain Energy Rev 125:109799. https://doi.org/10.1016/j.rser.2020.109799
Zhou X, Zhang J, Li J (2013) Industrial structural transformation and carbon dioxide emissions in China. Energy policy 57:43–51. https://doi.org/10.1016/j.enpol.2012.07.017
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This work was supported by the National Natural Science Foundation of China (grant no. 71673145).
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Liu, L., Li, L. The effect of directed technical change on carbon dioxide emissions: evidence from China’s industrial sector at the provincial level. Nat Hazards 107, 2463–2486 (2021). https://doi.org/10.1007/s11069-020-04437-3
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DOI: https://doi.org/10.1007/s11069-020-04437-3