The pursuit of a low-carbon transition is central to achieving green development worldwide, and China has embraced carbon emissions trading (CET) with the aim of achieving high-quality economic development. Despite its critical policy importance, the question of whether and how CET promotes carbon efficiency remains unclear. Using unique panel data covering prefecture-level cities in China from 2007 to 2020, this study first fills this gap by constructing the Global-EBM model and taking carbon dioxide as an undesirable output to innovatively evaluate the total factor carbon emission efficiency (TFCEE) of China's cities. Second, as an extension of the existing provincial evidence, we treat the carbon trading scheme in urban China as a quasi-natural experiment and confirm the boosting effect of CET on TFCEE in the pilot cities. Third, the mediating roles of both green technology innovation and industrial structure upgrading in the process of promoting carbon efficiency are identified, further demonstrating the channel influences. Finally, the heterogeneous impact of the CET policy is further investigated and found to be stronger in eastern and developed cities. Our findings have important policy implications for China's green transition.
IsinkaralarOIsinkaralarKYilmazD. Climate-related spatial reduction risk of agricultural lands on the Mediterranean coast in Türkiye and scenario-based modelling of urban growth. Environ Dev Sustain2023; 25: 13199–13217.
2.
RibeiroSLimogesAMasséG, et al.Vulnerability of the North Water ecosystem to climate change. Nat Commun2021; 12: 4475.
3.
Wang G, Deng X, Wang J, et al. Carbon emission efficiency in China: a spatial panel data analysis. China Econ Rev 2019; 56: 101313.
4.
Gao D, Tan L, Mo X, et al. Blue sky defense for carbon emission trading policies: a perspective on the spatial spillover effects of total factor carbon efficiency. Systems 2023a; 11: 382.
5.
IsinkaralarO. Bioclimatic comfort in urban planning and modeling spatial change during 2020–2100 according to climate change scenarios in Kocaeli, Türkiye. Int J Environ Sci Technol2023; 20: 7775–7786.
6.
ZhangYLiSLuoT,et al.The effect of emission trading policy on carbon emission reduction: evidence from an integrated study of pilot regions in China. J Cleaner Prod2020; 265: 121843.
7.
LiGGaoDShiXX. How does information and communication technology affect carbon efficiency? Evidence at China's city level. Energy Environ2023a: 0958305X231156405.
8.
WangQZhangFLiR. Free trade and carbon emissions revisited: the asymmetric impacts of trade diversification and trade openness. Sustain Dev2023a:1–26. doi: https://doi.org/10.1002/sd.2703.
9.
HongQCuiLHongP. The impact of carbon emissions trading on energy efficiency: evidence from quasi-experiment in China's carbon emissions trading pilot. Energy Econ2022; 110: 106025.
10.
CoboSGalán-MartínÁTulusV, et al.Human and planetary health implications of negative emissions technologies. Nat Commun2022; 13: 1–11.
11.
LiGGaoDLiY. Impacts of market-based environmental regulation on green total factor energy efficiency in China. China & World Economy. 2023b.
12.
MielnikOGoldembergJ. Communication the evolution of the “carbonization index” in developing countries. Energy Pol1999; 27: 307–308.
13.
SunJW. The decrease of CO2 emission intensity is decarbonization at national and global levels. Energy Pol2005; 33: 975–978.
14.
WangQWangXLiR. Does urbanization redefine the environmental Kuznets curve? An empirical analysis of 134 Countries. Sustain Cities Soc2022; 76: 103382.
15.
Gao D, Li Y and Tan L. Can environmental regulation break the political resource curse: evidence from heavy polluting private listed companies in China. J Environ Planning Manage 2023b: 1–27.
16.
CaiBGuoHMaZ, et al.Benchmarking carbon emissions efficiency in Chinese cities: a comparative study based on high-resolution gridded data. Appl Energy2019; 242: 994–1009.
17.
MengFSuBThomsonE, et al.Measuring China's regional energy and carbon emission efficiency with DEA models: a survey. Appl Energy2016; 183: 1–21.
18.
LiRLiLWangQ. The impact of energy efficiency on carbon emissions: evidence from the transportation sector in Chinese 30 provinces. Sustain Cities Soc2022; 82: 103880.
19.
Chung YH, Färe R, Grosskopf S. Productivity and undesirable outputs: a directional distance function approach[J]. J Environ Manage 1997; 51: 229–240.
20.
AvkiranNKToneKTsutsuiM. Bridging radial and nonradial measures of efficiency in DEA. Ann Oper Res2008; 164: 127–138.
21.
ToneKTsutsuiM. An epsilon-based measure of efficiency in DEA—the third pole of technical efficiency. Eur J Oper Res2010; 207: 1554–1563.
22.
PastorJTLovellCAK. A global Malmquist productivity index. Econ Lett2005; 88: 266–271.
23.
ZhangSWangYHaoY,et al.Shooting two hawks with one arrow: could China's emission trading scheme promote green development efficiency and regional carbon equality?Energy Econ2021; 101: 105412.
24.
ChenZZhangXChenF. Do carbon emission trading schemes stimulate green innovation in enterprises? Evidence from China. Technol Forecast Soc Change2021; 168: 120744.
25.
LiuYLiuSShaoX,et al.Policy spillover effect and action mechanism for environmental rights trading on green innovation: evidence from China's carbon emissions trading policy. Renew Sustain Energy Rev2022; 153: 111779.
26.
Gao D, Yan Z, Zhou X, et al. Smarter and prosperous: digital transformation and enterprise performance. Systems 2023c; 11: 29.
27.
WangQSunJLiR,et al.Linking trade openness to load capacity factor: the threshold effects of natural resource rent and corruption control. Gondwana Res2023b. doi:https://doi.org/10.1016/j.gr.2023.05.016
28.
AliSAAlharthiMHussainHI, et al.A clean technological innovation and eco-efficiency enhancement: a multi-index assessment of sustainable economic and environmental management. Technol Forecast Soc Change2021; 166: 120573.
29.
ZhangCChenP. Industrialization, urbanization, and carbon emission efficiency of Yangtze River Economic Belt—empirical analysis based on stochastic frontier model. Environ Sci Polluti Res2021; 28: 66914– 66929.
30.
SongMZhaoXShangYP. The impact of low-carbon city construction on ecological efficiency: empirical evidence from quasi-natural experiments. Resour Conserv Recycl2020; 157: 104777.
31.
LiRHanXWangQ. Do technical differences lead to a widening gap in China's regional carbon emissions efficiency? Evidence from a combination of LMDI and PDA approach. Renew Sustain Energy Rev2023; 182: 113361.
32.
SongMAnQZhangW, et al.Environmental efficiency evaluation based on data envelopment analysis: a review. Renew Sustain Energy Rev2012; 16: 4465–4469.
33.
SueyoshiTYuanYGotoM. A literature study for DEA applied to energy and environment. Energy Econ2017; 62: 104–124.
34.
HuangHMoRChenX. New patterns in China’s regional green development: an interval Malmquist–Luenberger productivity analysis. Struct Change Econ Dyn2021; 58: 161–173.
35.
CharnesAWCooperWWRhodesEL. Measuring the efficiency of decision making units. Eur J Oper Res1978; 2: 429–444.
36.
BankerRDCharnesAWCooperWW. Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manage Sci1984; 30: 1078–1092.
37.
ToneK. A slacks-based measure of efficiency in data envelopment analysis. Eur J Oper Res2001; 130: 498–509.
38.
HuYRenSWangY,et al.Can carbon emission trading scheme achieve energy conservation and emission reduction? Evidence from the industrial sector in China. Energy Econ2020; 85: 104590.
39.
HamiltonBHNickersonJA. Correcting for endogeneity in strategic management research. Strategic Org2003; 1: 51–78.
40.
YangQGaoDSongD,et al.Environmental regulation, pollution reduction and green innovation: the case of the Chinese Water Ecological Civilization City Pilot policy. Econ Syst2021; 45: 100911.
41.
XiongSMaXJiJ. The impact of industrial structure efficiency on provincial industrial energy efficiency in China. J Clean Prod2019; 215: 952–962.
42.
LiouJLWuPL. Will economic development enhance the energy use efficiency and CO2 emission control efficiency. Expert Syst Appl2011; 38: 12379–12387.
43.
GaoDLiGYuJ. Does digitization improve green total factor energy efficiency? Evidence from Chinese 213 cities. Energy2022; 247: 123395.
44.
GuoRYuanY. Different types of environmental regulations and heterogeneous influence on energy efficiency in the industrial sector: evidence from Chinese provincial data. Energy Policy2020; 145: 111747.
45.
ZhaoXLiuCSunC,et al.Does stringent environmental regulation lead to a carbon haven effect? Evidence from carbon-intensive industries in China. Energy Econ2020; 86: 104631.
46.
AdamsSKloboduEKM. Financial development and environmental degradation: does political regime matter?J Cleaner Prod2018; 197: 1472–1479.
47.
WangQSunJPataUK, et al.Digital economy and carbon dioxide emissions: examining the role of threshold variables. Geosci Front2023c: 101644. doi:https://doi.org/10.1016/j.gsf.2023.101644
48.
YorkR. Demographic trends and energy consumption in European Union Nations, 1960–2025. Soc Sci Res2007; 36: 855–872.
49.
SunJDuTSunW, et al.An evaluation of greenhouse gas emission efficiency in China’s industry based on SFA. Sci Total Environ2019; 690: 1190–1202.
50.
LiuQQiuLD. Intermediate input imports and innovations: evidence from Chinese firms’ patent filings. J Int Econ2016; 103: 166–183.
51.
HicksJR. The theory of wages. London: Macmillan and Co. Ltd., 1932.
52.
ZhangNWangBLiuZ. Carbon emissions dynamics, efficiency gains, and technological innovation in China’s industrial sectors. Energy2016; 99: 10–19.
53.
MaMShenLRenH, et al.How to measure carbon emission reduction in China’s public building sector: retrospective decomposition analysis based on STIRPAT model in 2000–2015. Sustainability2017; 9: 1744.
54.
MoutinhoVMadalenoMMacedoP. The effect of urban air pollutants in Germany: eco-efficiency analysis through fractional regression models applied after DEA and SFA efficiency predictions. Sustain Cities Soc2020; 59. https://doi.org/10.1016/j.scs.2020.102204
55.
LuYTaoZZhuL. Identifying FDI spillovers. J Int Econ2017; 107: 75–90.
56.
YuYZhangN. Low-carbon city pilot and carbon emission efficiency: quasi-experimental evidence from China. Energy Econ2021; 96: 105125.
57.
XiaoJLiGZhuB, et al.Evaluating the impact of carbon emissions trading scheme on Chinese firms’ total factor productivity. J Clean Prod2021; 306: 127104.
58.
WenSJiaZChenX. Can low-carbon city pilot policies significantly improve carbon emission efficiency? Empirical evidence from China. J Cleaner Prod2022; 346: 131131.
59.
WangQWangLLiR. Trade openness helps move towards carbon neutrality—insight from 114 countries. Sustain Dev2023d. doi:https://doi.org/10.1002/sd.2720
