Abstract
Carbon emission trading policy is of great importance for addressing climate change and reducing carbon emissions. Reducing carbon emissions could further affect energy efficiency (EE). Based on the data from 30 provinces in China from 2006 to 2017, this paper first calculated EE by using the super slack-based model (Super-SBM) and then analysed the theoretical mechanism of the impact of carbon emission trading policy on EE. We also used a difference-in-difference (DID) model and mediation effect model for empirical analysis. Finally, we established the spatial difference-in-difference (SDID) model to test the policy spillover effects of carbon emission trading policy. The results showed that the high EE areas have gradually shifted to the central and eastern regions during 2006–2017 in China. The EE value in the pilot area of the carbon emission trading policy was obviously higher than that in the non-pilot area. Carbon emission trading policy had a significant positive effect on improving EE overall. In particular, green technology innovation and energy structure both had positive mediation effects on carbon emission trading policy affecting EE. However, the industrial structuring adjustment had no significant mediation effect in its influencing mechanism. Additionally, the spatial spillover effects test showed that the carbon emission trading policy had a positive effect on the EE of the pilot areas but a negative effect on that of the non-pilot areas.
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Antonietti R, Fontini F (2019) Does energy price affect energy efficiency? Cross-country panel evidence. Energy Policy 129:896–906. https://doi.org/10.1016/j.enpol.2019.02.069
Bayer P, Aklin M (2020) The European Union Emissions Trading System reduced CO2 emissions despite low prices. Proc Natl Acad Sci U S A 117:201918128. https://doi.org/10.1073/pnas.1918128117
Bertrand M, Duflo E, Mullainathan S (2004) How much should we trust differences-in-differences estimates? Q J Econ 119:249–275. https://doi.org/10.2139/ssrn.288970
Čadil J, Petkovová L, Blatná D (2014) Human capital, economic structure and growth. Procedia Economics and Finance 12:85–92. https://doi.org/10.1016/S2212-5671(14)00323-2
Chen Y-J, Li P, Lu Y (2018) Career concerns and multitasking local bureaucrats: evidence of a target-based performance evaluation system in China. J Dev Econ 133:84–101. https://doi.org/10.1016/j.jdeveco.2018.02.001
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. https://doi.org/10.1016/j.scitotenv.2018.10.395
Fang C, Wang S, Li G (2015) Changing urban forms and carbon dioxide emissions in China: a case study of 30 provincial capital cities. ApEn 158:519–531. https://doi.org/10.1016/j.apenergy.2015.08.095
Feng D, Dai Y, Zhang S, Zhang X, Long R (2018) Can a carbon emission trading scheme generate the Porter effect? Evidence from pilot areas in China. Sci Total Environ 653:565–577. https://doi.org/10.1016/j.scitotenv.2018.10.395
Guo J, Gu F, Liu Y, Liang X, Fan Y (2020) Assessing the impact of ETS trading profit on emission abatements based on firm-level transactions. Nat Commun 11:2078. https://doi.org/10.1038/s41467-020-15996-1
Guo R, Yuan Y (2020) Different types of environmental regulations and heterogeneous influence on energy efficiency in the industrial sector: evidence from Chinese provincial data. Energy Policy 145:111747. https://doi.org/10.1016/j.enpol.2020.111747
Cho H, Freyre A, Bürer M, Patel MK (2019) Patel comparative analysis of customer-funded energy efficiency programs in the United States and Switzerland–cost-effectiveness and discussion of operational practices - ScienceDirect. Energy Policy 135:111010–111010. https://doi.org/10.1016/j.enpol.2019.111010
Han F, Xie R, Fang J (2018) Urban agglomeration economies and industrial energy efficiency. Energy 162:45–59. https://doi.org/10.1016/j.energy.2018.07.163
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
Hering L, Poncet S (2011): Environmental policy and trade performance: evidence from China. CEPII.
Hu Y, Ding Y (2020) Can carbon emission permit trade mechanism bring both business benefits and green efficiency? Chinese Journal of Population, Resources and Environment 30:56–64 ((In Chinese))
Jiang J, Ye B (2020) A comparative analysis of Chinese regional climate regulation policy: ETS as an example. Environ Geochem Health 42:819–840. https://doi.org/10.1007/s10653-019-00310-w
Dou J, Han X (2019) How does the industry mobility affect pollution industry transfer in China: empirical test on Pollution Haven Hypothesis and Porter Hypothesis. J Clean Prod 217:105–115. https://doi.org/10.1016/j.jclepro.2019.01.147
Jin T, Kim J (2019) A comparative study of energy and carbon efficiency for emerging countries using panel stochastic frontier analysis. Sci Rep 9:6647. https://doi.org/10.1038/s41598-019-43178-7
Li B, Han S, Wang Y, Li J, Wang Y (2020) Feasibility assessment of the carbon emissions peak in China’s construction industry: factor decomposition and peak forecast. Sci Total Environ 706:135716. https://doi.org/10.1016/j.scitotenv.2019.135716
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. https://doi.org/10.1016/j.eneco.2018.11.030
Lin B, Abudu H (2020) Can energy conservation and substitution mitigate CO2 emissions in electricity generation? Evidence from Middle East and North Africa. J Environ Manage 275:111222. https://doi.org/10.1016/j.jenvman.2020.111222
Liu D, Xiao H (2017) Empirical study on the factors influencing the provincial energy efficiency in Pan Pearl River Delta Region. Soft Science 31:80–84 ((In Chinese))
Liu H, Zhang Z, Zhang T, Wang L (2020a): Revisiting China’s provincial energy efficiency and its influencing factors - ScienceDirect. Energy 208https://doi.org/10.1016/j.energy.2020.118361
Liu S, Hou P, Gao Y, Tan Y (2020b): Innovation and green total factor productivity in China: a linear and nonlinear investigation. Environ. Sci. Pollut. Res. 1-22https://doi.org/10.1007/s11356-020-11436-1
Makarov VI, Khmelinskii IV, Patterson MG (1996) What is energy efficiency? Concepts, indicators and methodological issues. Energy Policy 24:377–390. https://doi.org/10.1016/0301-4215(96)00017-1
Mellon J (2021): Rain, Rain, Go Away: 176 potential exclusion-restriction violations for studies using weather as an instrumental variable. http://dx.doi.org/https://doi.org/10.2139/ssrn.3715610
Nicholson W, Snyder C (2012) Microeconomic theory: basic principles and extensions. Cengage Learning
Ouyang W, Yang J (2020) The network energy and environment efficiency analysis of 27 OECD countries: a multiplicative network DEA model. Energy 197:117161. https://doi.org/10.1016/j.energy.2020.117161
Pan X, Chen M, Ying L, Zhang F (2020) An empirical study on energy utilization efficiency, economic development, and sustainable management. Environ Sci Pollut Res 27:12874–12881. https://doi.org/10.1007/s11356-019-04787-x
Peng J, Xiao J, Wen L, Zhang L (2019) Energy industry investment influences total factor productivity of energy exploitation: a biased technical change analysis. J. Clean. Prod. 237:117847.1-117847.16. https://doi.org/10.1016/j.jclepro.2019.117847
Peng X (2020) Strategic interaction of environmental regulation and green productivity growth in China: green innovation or pollution refuge? Sci Total Environ 732:139200. https://doi.org/10.1016/j.scitotenv.2020.139200
Qi S, Zhou C, Li K, Tang S (2020): Influence of a pilot carbon emission trading policy on enterprises’ low-carbon innovation in China. Clim. Pol. 1–19 https://doi.org/10.1080/14693062.2020.1864268
Qi S, Zhou C, Li K, Tang S (2021) The impact of a carbon emission trading pilot policy on the low-carbon international competitiveness of industry in China: an empirical analysis based on a DDD model. J Clean Prod 281:125361. https://doi.org/10.1016/j.jclepro.2020.125361
Shen W, Wang Y (2019) Adaptive policy innovations and the construction of emission trading schemes in China: taking stock and looking forward. Environ Innov Soc Tr 30:59–68. https://doi.org/10.1016/j.eist.2017.10.009
Shephard RW (1953): Cost and production functions. Cost and Production Functions.
Su K, Lee C (2020) When will China achieve its carbon emission peak? A scenario analysis based on optimal control and the STIRPAT model. Ecol Indic 112:106138. https://doi.org/10.1016/j.ecolind.2020.106138
Tang B, Shen C, Gao C (2013) The efficiency analysis of the European CO2 futures market. Appl Energy 112:1544–1547. https://doi.org/10.1016/j.apenergy.2013.02.017
Tang K, Liu Y, Zhou D, Qiu Y (2020): Urban carbon emission intensity under emission trading system in a developing economy: evidence from 273 Chinese cities. Environ Sci Pollut Res 28https://doi.org/10.1007/s11356-020-10785-1
Tang L, Wu J, Yu L, Bao Q (2017) Carbon allowance auction design of China’s emissions trading scheme: a multi-agent-based approach. Energy Policy 102:30–40. https://doi.org/10.1016/j.enpol.2016.11.041
Trotta G (2020): Assessing energy efficiency improvements and related energy security and climate benefits in Finland: an ex post multi-sectoral decomposition analysis. Energy Econ 86https://doi.org/10.1016/j.eneco.2019.104640
Wang H, Wang M (2019) Effects of technological innovation on energy efficiency in China: evidence from dynamic panel of 284 cities. Sci Total Environ 709:136172. https://doi.org/10.1016/j.scitotenv.2019.136172
Wang J, Wang S, Li S, Cai Q, Gao S (2019) Evaluating the energy-environment efficiency and its determinants in Guangdong using a slack-based measure with environmental undesirable outputs and panel data model. ScTEn 663:878–888. https://doi.org/10.1016/j.scitotenv.2019.01.413
Wong Z (2021) Research on China’s market-oriented emission reduction mechanism to achieve carbon neutral long-term goals. Environ Prot 49:66–69 ((In Chinese))
Wu H, Hao Y, Ren S (2020) How do environmental regulation and environmental decentralization affect green total factor energy efficiency: evidence from China. Energy Econ 91:104880. https://doi.org/10.1016/j.eneco.2020.104880
Xu J, Wang M (2018) Green technology innovation, environmental regulation and energy intensity-an empirical study based on Chinese manufacturing industry. Studies in Science of Science 36:744–753 ((In Chinese))
Xy A, Ping J, Yao P (2020) Does China’s carbon emission trading policy have an employment double dividend and a Porter effect? Energy Policy 142:111492. https://doi.org/10.1016/j.enpol.2020.111492
Yan D, Kong Y, Ren X, Shi Y, Chiang SW (2019) The determinants of urban sustainability in Chinese resource-based cities: a panel quantile regression approach. Sci Total Environ 686:1210–1219. https://doi.org/10.1016/j.scitotenv.2019.05.386
Yan Y, Zhang X, Zhang J, Li K (2020) Emissions trading system (ETS) implementation and its collaborative governance effects on air pollution: The China story. Energy Policy 138:111282. https://doi.org/10.1016/j.enpol.2020.111282
Yang P, Liang X, Drohan PJ (2020) Using Kaya and LMDI models to analyze carbon emissions from the energy consumption in China. Environ Sci Pollut Res 27:26495–26501. https://doi.org/10.1007/s11356-020-09075-7
Yang Z, Wei X (2019) Analysis of the total factor energy efficiency and its influencing factors of the Belt and Road key regions in China. Environ Sci Pollut Res 26:4764–4776. https://doi.org/10.1007/s11356-018-3961-3
Yu B (2020a) Industrial structure, technological innovation, and total-factor energy efficiency in China. Environ Sci Pollut Res 27:1–15. https://doi.org/10.1007/s11356-019-07363-5
Yu B (2020b) Industrial structure, technological innovation, and total-factor energy efficiency in China. Environ Sci Pollut Res 27:8371–8385. https://doi.org/10.1007/s11356-019-07363-5
Yu X, Wu Z, Zheng H, Li M, Tan T (2020) How urban agglomeration improve the emission efficiency ? A spatial econometric analysis of the Yangtze River Delta urban agglomeration in China. J. Environ. Manage. 260:110061.1-110061.8. https://doi.org/10.1016/j.jenvman.2019.110061
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. https://doi.org/10.1007/s11356-020-07818-0
Zhang J (2019) Research on the effect of carbon emission reduction policy in China’s carbon emissions trading pilot. China Popul Resour Environ 29:49–58 ((In Chinese))
Zhang S, Jiang K, Wang L, Bongers G, Li J (2020) Do the performance and efficiency of China’s carbon emission trading market change over time? Environ Sci Pollut Res 27:33140–33160. https://doi.org/10.1007/s11356-020-09168-3
Zhao H, Lin B (2019) Will agglomeration improve the energy efficiency in China’s textile industry: evidence and policy implications. Appl Energy 237:326–337. https://doi.org/10.1016/j.apenergy.2018.12.068
Zhao L, Zhao R, Zhang X (2020): Study on the effectiveness of carbon emission trading policyon the coordinated emission reduction of air pollution in China. Industrial Economic Review 148–160. (In Chinese)
Zhou J, Huo X, Jin B, Yu X (2019a) The efficiency of carbon emission trading market in China: evidence from variance ratio tests. Environ Sci Pollut Res 26:14362–14372. https://doi.org/10.1007/s11356-019-04778-y
Zhou Z, Xu G, Wang C, Wu J (2019) Modeling undesirable output with a DEA approach based on an exponential transformation: an application to measure the energy efficiency of Chinese industry. J. Clean. Prod. 236:117717.1-117717.11. https://doi.org/10.1016/j.jclepro.2019.117717
Zhu L, Wang Y, Shang P, Qi L, Yang G, Wang Y (2019) Improvement path, the improvement potential and the dynamic evolution of regional energy efficiency in China: based on an improved nonradial multidirectional efficiency analysis. Energy Policy 133:110883. https://doi.org/10.1016/j.enpol.2019.110883
Acknowledgements
Thanks to the Natural Science Foundation of China and the Philosophy and Social Science Planning Project of Gansu Province for supporting this project.
Funding
This research was supported by the National Natural Science Foundation of China [Grant No. 71763017; 72063023] and the Natural Science Foundation of Gansu Province [Grant No. 20JR5RA474].
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Conceptualization, X.Z. and F.L.; methodology, F.L.; software, F.L.; validation, X.Z. and F.L.; formal analysis, X.Z.; investigation, X.Z. and F.L.; resources, X.Z.; data curation, F.L.; writing—original draft preparation, X.Z., F.L. and D.X.; writing—review and editing, F.L. and D.X.; visualization, F.L.; supervision, X.Z.; project administration, X.Z.; funding acquisition, X.Z. All authors have read and agreed to the published version of the manuscript.
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Zhang, Xm., Lu, Ff. & Xue, D. Does China’s carbon emission trading policy improve regional energy efficiency?—an analysis based on quasi-experimental and policy spillover effects. Environ Sci Pollut Res 29, 21166–21183 (2022). https://doi.org/10.1007/s11356-021-17021-4
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DOI: https://doi.org/10.1007/s11356-021-17021-4