Skip to main content

Advertisement

SpringerLink
Log in

The effectiveness and heterogeneity of carbon emissions trading scheme in China

  • Research Article
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

Some developed economies have run emission trading scheme (ETS) to mitigate carbon emissions. However, we know little about the effectiveness and heterogeneity of ETS in a context of developing economy. This paper evaluates the effectiveness and heterogeneity of China’s pilot ETS, the first ETS run in a developing economy. Difference-in-difference (DID) and difference-in-difference-in-difference (DDD) methods are employed to analyze provincial industrial-level data. The heterogeneity of ETS effects is also explored from regional and industrial perspectives. The empirical results show that the pilot ETS can effectively reduce pilot industries’ carbon emissions. The reduction effect of the pilot ETS has a substantial heterogeneity for different pilot provinces and industries. Carbon emissions are reduced by the pilot ETS through technological innovation and the adjustment of industrial structure. The empirical results suggest that policymakers may consider establishing a national ETS and differentiating carbon quota allowance in covered regions and industries in the current pilot ETS.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Notes

  1. The market-based instruments (MBIs) include those instruments that motivates enterprises to reduce pollution emissions via market signals (Tang et al. 2016a, 2016c; Zhang and Jiang 2019), not mandatory restrictions.

  2. http://www.tanjiaoyi.com

  3. Due to the lack of data, Jiangsu, Zhejiang, Shanghai, Tibet, Sichuan, Hong Kong, Macao, and Taiwan are not included in the study.

Abbreviations

ETS:

Emission trading scheme

CTM:

Carbon trading market

DDD:

Difference-in-difference-in-differences

DID:

Difference-in-differences

PSM-DID:

Propensity score matching difference-in-differences

References

  • Albrizio S, Kozluk T, Zipperer V (2017) Environmental policies and productivity growth: evidence across industries and firms. J Environ Econ Manag 81:209–226

    Google Scholar 

  • Allen F, Qian J, Qian M (2005) Law, finance, and economic growth in China. J Financ Econ 77(1):57–116

    Google Scholar 

  • Bel G, Joseph S (2018) Policy stringency under the European Union Emission trading system and its impact on technological change in the energy sector. Energy Policy 117:434–444

    Google Scholar 

  • Cai H, Chen Y, Gong Q (2016a) Polluting thy neighbor: unintended consequences of China’s pollution reduction mandates. J Environ Econ Manag 76:86–104

    Google Scholar 

  • Cai X, Lu Y, Wu M, Yu L (2016b) Does environmental regulation drive away inbound foreign direct investment? Evidence from a quasi-natural experiment in China. J Dev Econ 123:73–85

    Google Scholar 

  • Caparrós A, Pereau JC, Tazdaït T (2013) Emission trading and international competition: the impact of labor market rigidity on technology adoption and output. Energy Policy 55:36–43

    Google Scholar 

  • Cheng Z, Li L, Liu J (2019) The effect of information technology on environmental pollution in China. Environ Sci Pollut Res 26(32):33109–33124

    Google Scholar 

  • Choi Y, Qi C (2019) Is South Korea’s emission trading scheme effective? An analysis based on the marginal abatement cost of coal-fueled power plants. Sustainability. https://doi.org/10.3390/su11092504

  • Deng X, Song X, Xu Z (2018) Transaction costs, modes, and scales from agricultural to industrial water rights trading in an inland river basin, northwest China. Water. 10. https://doi.org/10.3390/w10111598

  • Dong F, Dai Y, Zhang S, Zhang X, Long R (2019) Can a carbon emission trading scheme generate the Porter effect? Evidence from pilot areas in China. Sci Total Environ 653:565–577

    CAS  Google Scholar 

  • Duan Y, Mu H, Li N (2016) Analysis of the relationship between China’s IPPU CO2 emissions and the industrial economic growth. Sustainability. https://doi.org/10.3390/su8050426

  • Ellerman AD, Marcantonini C, Zaklan A (2016) The European Union emissions trading system: ten years and counting. Rev Environ Econ Policy 10(1):89–107

    Google Scholar 

  • Ezzi F, Jarboui A (2016) Does innovation strategy affect financial, social and environmental performance? J Econ Finance Adm Sci 21(40):14–24

    Google Scholar 

  • Gulbrandsen LH, Stenqvist C (2013) The limited effect of EU emissions trading on corporate climate strategies: comparison of a Swedish and a Norwegian pulp and paper company. Energy Policy 56:516–525

    Google Scholar 

  • Hall RE (2018) New evidence on the markup of prices over marginal costs and the role of mega-firms in the US economy (No. w24574). National Bureau of Economic Research. https://www.nber.org/papers/w24574. Accessed 26 July 2020

  • Han Y (2020) Impact of environmental regulation policy on environmental regulation level: a quasi-natural experiment based on carbon emission trading pilot. Environ Sci Pollut Res 27:23602–23615. https://doi.org/10.1007/s11356-020-08658-8

    Article  CAS  Google Scholar 

  • Hasegawa T, Fujimori S, Takahashi K, Yokohata T, Masui T (2016) Economic implications of climate change impacts on human health through undernourishment. Clim Chang 136:189–202

    Google Scholar 

  • He JJ, Tian X (2013) The dark side of analyst coverage: The case of innovation. J Financ Econ 109(3):856–878

    Google Scholar 

  • Hu Y, Ren S, Wang Y, Chen X (2020) Can carbon emission trading scheme achieve energy conservation and emission reduction? Evidence from the industrial sector in China. Energy Econ 85:104590. https://doi.org/10.1016/j.eneco.2019.104590

    Article  Google Scholar 

  • IPCC (2015) Climate change 2014: mitigation of climate change. Cambridge University Press, New York

    Google Scholar 

  • Jaraite-Kažukauske J, Di Maria C (2016) Did the EU ETS make a difference? An empirical assessment using Lithuanian firm-level data. Energy J 37(1):1–23

    Google Scholar 

  • Ji CJ, Hu YJ, Tang BJ (2018) Research on carbon market price mechanism and influencing factors: a literature review. Nat Hazards 92(2):761–782

    Google Scholar 

  • Ji X, Umar M, Ali S, Ali W, Tang K, Khan Z (2020) Does fiscal decentralization and eco-innovation promote sustainable environment? A case study of selected fiscally decentralized countries. Sustain Dev. https://doi.org/10.1002/sd.2132

  • Lee M (2011) Potential cost savings from internal/external CO2 emissions trading in the Korean electric power industry. Energy Policy 39(10):6162–6167

    Google Scholar 

  • Liang W, Gan T, Zhang W (2019) Dynamic evolution of characteristics and decomposition of factors influencing industrial carbon dioxide emissions in China: 1991–2015. Struct Chang Econ Dyn 49:93–106

    Google Scholar 

  • Lin B, Jia Z (2019) What will China's carbon emission trading market affect with only electricity sector involvement? A CGE based study. Energy Econ 78:301–311

    Google Scholar 

  • Liu W, Wang Z (2017) The effects of climate policy on corporate technological upgrading in energy intensive industries: evidence from China. J Clean Prod 142:3748–3758

    Google Scholar 

  • Liu N, Ma Z, Kang J (2015) Changes in carbon intensity in China's industrial sector: decomposition and attribution analysis. Energy Policy 87:28–38

    CAS  Google Scholar 

  • Liu Z, Geng Y, Dai H, Wilson J, Xie Y, Wu R, You W, Yu Z (2018) Regional impacts of launching national carbon emissions trading market: a case study of Shanghai. Appl Energy 230:232–240

    Google Scholar 

  • Liu YD, Tang ZP, Xia Y, Han MY, Jiang SB (2019) Machine learning identification and evolution of key impact factors of China's carbon intensity. J Geogr 74(12):2592–2603

    Google Scholar 

  • Lu H, Ma X, Huang K, Azimi M (2020) Carbon trading volume and price forecasting in China using multiple machine learning models. J Clean Prod 249:119386. https://doi.org/10.1016/j.jclepro.2019.119386

    Article  Google Scholar 

  • Martin R, Muûls M, Wagner UJ (2015) The impact of the European Union Emissions Trading Scheme on regulated firms: what is the evidence after ten years? Rev Environ Econ Policy 10(1):129–148

    Google Scholar 

  • Mi ZF, Pan SY, Yu H, Wei YM (2015) Potential impacts of industrial structure on energy consumption and CO2 emission: a case study of Beijing. J Clean Prod 103:455–462

    CAS  Google Scholar 

  • NBS (National Bureau of Statistics of China) (2009-2018a) China Energy Statistical Yearbook. China Statistic Press, Beijing

  • NBS (National Bureau of Statistics of China) (2009-2018b) China Industry Statistical Yearbook. China Statistic Press, Beijing

  • NBS (National Bureau of Statistics of China) (2009-2018c) China Price Statistical Yearbook. China Statistic Press, Beijing

  • NBS (National Bureau of Statistics of China) (2009-2018d) China Statistical Yearbook. China Statistic Press, Beijing

  • Richter JL, Mundaca L (2013) Market behavior under the New Zealand ETS. Carbon Manag 4(4):423–438

    CAS  Google Scholar 

  • Rogelj J, Huppmann D, Krey V, Riahi K, Clarke L, Gidden M, Nicholls Z, Meinshausen M (2019) A new scenario logic for the Paris Agreement long-term temperature goal. Nature 573(7774):357–363

    CAS  Google Scholar 

  • Segura S, Ferruz L, Gargallo P, Salvador M (2018) Environmental versus economic performance in the EU ETS from the point of view of policy makers: a statistical analysis based on copulas. J Clean Prod 176:1111–1132

    Google Scholar 

  • Shan Y, Guan D, Zheng H, Ou J, Li Y, Meng J, Mi Z, Liu Z, Zhang Q (2018) China CO2 emission accounts 1997–2015. Sci Data 5:170201. https://doi.org/10.1038/sdata.2017.201

    Article  CAS  Google Scholar 

  • Shi X, Xu Z (2018) Environmental regulation and firm exports: evidence from the eleventh Five-Year Plan in China. J Environ Econ Manag 89:187–200

    Google Scholar 

  • Takeda S, Arimura TH, Tamechika H, Fischer C, Fox AK (2014) Output-based allocation of emissions permits for mitigating the leakage and competitiveness issues for the Japanese economy. Environ Econ Policy Stud 16(1):89–110

    Google Scholar 

  • Tang K, Hailu A (2020) Smallholder farms’ adaptation to the impacts of climate change: evidence from China’s Loess Plateau. Land Use Policy 91:104353. https://doi.org/10.1016/j.landusepol.2019.104353

    Article  Google Scholar 

  • Tang K, Hailu A, Kragt ME, Ma C (2016a) Marginal abatement costs of greenhouse gas emissions: broadacre farming in the Great Southern Region of Western Australia. Aust J Agric Resour Econ 60(3):459–475

    Google Scholar 

  • Tang K, Kragt ME, Hailu A, Ma C (2016b) Carbon farming economics: what have we learned? J Environ Manag 172:49–57

    Google Scholar 

  • Tang K, Yang L, Zhang J (2016c) Estimating the regional total factor efficiency and pollutants’ marginal abatement costs in China: a parametric approach. Appl Energy 184:230–240

    CAS  Google Scholar 

  • Tang K, Hailu A, Kragt ME, Ma C (2018) The response of broadacre mixed crop-livestock farmers to agricultural greenhouse gas abatement incentives. Agric Syst 160:11–20

    Google Scholar 

  • Tang K, He C, Ma C, Wang D (2019) Does carbon farming provide a cost-effective option to mitigate GHG emissions? Evidence from China. Aust J Agric Resour Econ 63(3):575–592

    Google Scholar 

  • Tang K, Hailu A, Yang Y (2020a) Agricultural chemical oxygen demand mitigation under various policies in China: a scenario analysis. J Clean Prod 250:119513. https://doi.org/10.1016/j.jclepro.2019.119513

    Article  CAS  Google Scholar 

  • Tang K, Liu Y, Zhou D, Qiu Y (2020b) Urban carbon emission intensity under emission trading system in a developing economy: evidence from 273 Chinese cities. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-020-10785-1

  • Tang K, Qiu Y, Zhou D (2020c) Does command-and-control regulation promote green innovation performance? Evidence from China's industrial enterprises. Sci Total Environ 712:136362. https://doi.org/10.1016/j.scitotenv.2019.136362

    Article  CAS  Google Scholar 

  • Tang K, Xiong C, Wang Y, Zhou D (2020d) Carbon emissions performance trend across Chinese cities: evidence from efficiency and convergence evaluation. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-020-10518-4

  • Tang K, Wang MZ, Zhou D (2021) Abatement potential and cost of agricultural greenhouse gases in Australian dryland farming system. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-020-11867-w

  • Van Vliet MT, Franssen WH, Yearsley JR, Ludwig F, Haddeland I, Lettenmaier DP, Kabat P (2013) Global river discharge and water temperature under climate change. Glob Environ Chang 23(2):450–464

    Google Scholar 

  • Wang Y, Bi Y, Wang ED (2017) Scene prediction of carbon emission peak and emission reduction potential estimation in Chinese industry. China Popul Resour Environ 27:131–140

    Google Scholar 

  • Wang H, Chen Z, Wu X, Nie X (2019) Can a carbon trading system promote the transformation of a low-carbon economy under the framework of the porter hypothesis? Empirical analysis based on the PSM-DID method. Energy Policy 129:930–938

    Google Scholar 

  • Wang Y, Sun X, Wang B, Liu X (2020) Energy saving, GHG abatement and industrial growth in OECD countries: a green productivity approach. Energy. 194:116833. https://doi.org/10.1016/j.energy.2019.116833

    Article  Google Scholar 

  • Wu J, Ma C, Tang K (2019) The static and dynamic heterogeneity and determinants of marginal abatement cost of CO2 emissions in Chinese cities. Energy 178:685–694

    Google Scholar 

  • Xie RH, Yuan Y, Huang JJ (2017) Different types of environmental regulations and heterogeneous influence on “green” productivity: evidence from China. Ecol Econ 132:104–112

    Google Scholar 

  • Yang L, Tang K, Wang Z, An H, Fang W (2017) Regional eco-efficiency and pollutants' marginal abatement costs in China: a parametric approach. J Clean Prod 167:619–629

    Google Scholar 

  • Yang P, Cui C, Li L, Chen W, Shi Y, Mi Z, Guan D (2020) Carbon emissions in countries that failed to ratify the intended nationally determined contributions: a case study of Kyrgyzstan. J Environ Manag 255:109892. https://doi.org/10.1016/j.jenvman.2019.109892

    Article  Google Scholar 

  • Yi L, Bai N, Yang L, Li Z, Wang F (2020) Evaluation on the effectiveness of China’s pilot carbon market policy. J Clean Prod 246:119039. https://doi.org/10.1016/j.jclepro.2019.119039

    Article  Google Scholar 

  • Yuan F, Tang K, Shi Q (2020) Does Internet use reduce chemical fertilizer use? Evidence from rural households in China. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-020-10944-4

  • Zang J, Wan L, Li Z, Wang C, Wang S (2020) Does emission trading scheme have spillover effect on industrial structure upgrading? Evidence from the EU based on a PSM-DID approach. Environ Sci Pollut Res 27:12345–12357

    Google Scholar 

  • Zhang N, Jiang X (2019) The effect of environmental policy on Chinese firm’s green productivity and shadow price: a meta frontier input distance function approach. Technol Forecast Soc Chang 144:129–136

    Google Scholar 

  • Zhang Y, Zhang J (2019) Estimating the impacts of emissions trading scheme on low-carbon development. J Clean Prod 238:117913. https://doi.org/10.1016/j.jclepro.2019.117913

    Article  CAS  Google Scholar 

  • Zhang YJ, Wang AD, Da YB (2014) Regional allocation of carbon emission quotas in China: evidence from the Shapley value method. Energy Policy 74:454–464

    Google Scholar 

  • Zhang C, Zhou B, Wang Q (2019a) Effect of China's western development strategy on carbon intensity. J Clean Prod 215:1170–1179

    Google Scholar 

  • Zhang K, Xu D, Li S, Zhou N, Xiong J (2019b) Has China’s pilot emissions trading scheme influenced the carbon intensity of output? Int J Environ Res Public Health 16. https://doi.org/10.3390/ijerph16101854

  • Zhang W, Zhang N, Yu Y (2019c) Carbon mitigation effects and potential cost savings from carbon emissions trading in China's regional industry. Technol Forecast Soc Chang 141:1–11

    Google Scholar 

  • Zhang W, Li J, Li G, Guo S (2020a) Emission reduction effect and carbon market efficiency of carbon emissions trading policy in China. Energy. 196:117117. https://doi.org/10.1016/j.energy.2020.117117

    Article  Google Scholar 

  • Zhang YJ, Liang T, Jin YL, Shen B (2020b) The impact of carbon trading on economic output and carbon emissions reduction in China’s industrial sectors. Appl Energy 260:114290. https://doi.org/10.1016/j.apenergy.2019.114290

    Article  Google Scholar 

  • Zhou D, Liang X, Zhou Y, Tang K (2020) Does emission trading boost carbon productivity? Evidence from China’s Pilot Emission Trading Scheme. Int J Environ Res Public Health. https://doi.org/10.3390/ijerph17155522

  • Zhu B, Zhang M, Huang L, Wang P, Su B, Wei Y (2020) Exploring the effect of carbon trading mechanism on China's green development efficiency: a novel integrated approach. Energy Econ 85:104601. https://doi.org/10.1016/j.eneco.2019.104601

    Article  Google Scholar 

Download references

Funding

This research was supported by the Humanities and Social Science Fund of Ministry of Education of China (20YJCZH144, 20YJC790191), Guangdong Basic and Applied Basic Research Foundation (2019A1515010884), Natural Science Foundation of Guangdong Province (2018A030310025, 2018A030310044), and Pearl River Talents Plan of Guangdong Province (20170133).

Author information

Authors and Affiliations

  1. School of Economics and Trade, Guangdong University of Foreign Studies, Guangzhou, 510006, China

    Kai Tang

  2. School of Business, Guangdong University of Foreign Studies, Guangzhou, 510006, China

    Ye Zhou & Xiaoyu Liang

  3. School of Mathematics and Statistics, Guangdong University of Foreign Studies, Guangzhou, 510006, China

    Di Zhou

Authors
  1. Kai Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ye Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiaoyu Liang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Di Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: Kai Tang, Ye Zhou, Xiaoyu Liang, and Di Zhou. Methodology: Ye Zhou, Xiaoyu Liang, and Di Zhou. Formal analysis and investigation: Kai Tang, Ye Zhou, Xiaoyu Liang, and Di Zhou. Writing, original draft preparation: Kai Tang, Ye Zhou, Xiaoyu Liang, and Di Zhou. Writing, review and editing: Kai Tang and Di Zhou. Funding acquisition: Kai Tang and Di Zhou. Resources: Kai Tang and Di Zhou. Supervision: Kai Tang.

Corresponding author

Correspondence to Di Zhou.

Ethics declarations

Competing interests

The authors declare that they have no competing interests.

Ethical approval

Not applicable.

Consent to participate

Not applicable.

Consent to publish

Not applicable.

Additional information

Responsible Editor: Philippe Garrigues

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

Table 7 List of pilot industries
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tang, K., Zhou, Y., Liang, X. et al. The effectiveness and heterogeneity of carbon emissions trading scheme in China. Environ Sci Pollut Res 28, 17306–17318 (2021). https://doi.org/10.1007/s11356-020-12182-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-020-12182-0

Keywords

Search

Navigation