The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
How does emission trading reduce China's carbon intensity? An exploration using a decomposition and difference-in-differences approach
Abstract
Emission trading is a market-driven method to more quickly reduce carbon intensity, and has been widely used in countries with significant carbon emissions. In 2013, the Chinese government established pilot carbon emission trading programs in seven provinces. However, there is incomplete research on the effect and influencing channels of emission trading on carbon intensity reduction. To explore these problems, this study conducted an empirical analysis, using a decomposition and difference-in-differences approach. The main conclusions are as follows: (1) Overall, China's emission trading pilots have driven a significant decline in the carbon intensity, resulting in an average annual decline of approximately 0.026 tons/10,000 yuan in the pilot provinces. (2) In the sample period, emission trading pilots had a sustained and stable effect on carbon intensity with no time lag. (3) Emission trading pilots reduce the carbon intensity by adjusting the industrial structure. In contrast, energy structure and energy intensity channels have not yet been realized.
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Cites
Pollution, welfare, and environmental policy in the theory of Comparative Advantage
Pethig, R. (1976) · Journal of Environmental Economics and Management · doi:10.1016/0095-0696(76)90031-0 · Cited by 429
Zhang, W., Zhang, N., & Yu, Y. (2019) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2018.12.014 · Cited by 157
Cited by
Does carbon emissions trading promote green technology innovation in China?
Zhang, W., Li, G., & Guo, F. (2022) · Applied Energy · doi:10.1016/j.apenergy.2022.119012 · Cited by 419
Evaluation of effectiveness of China's carbon emissions trading scheme in carbon mitigation
Gao, Y., Li, M., Xue, J., & Liu, Y. (2020) · Energy Economics · doi:10.1016/j.eneco.2020.104872 · Cited by 398
Shi, B., Li, N., Gao, Q., & Li, G. (2022) · Journal of Environmental Management · doi:10.1016/j.jenvman.2022.115650 · Cited by 386
Review of recent progress of emission trading policy in China
Huang, W., Wang, Q., Li, H., Fan, H., Qian, Y., & Klemeš, J. J. (2022) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2022.131480 · Cited by 238
Self-citationWang, X., Huang, J., & Liu, H. (2022) · Journal of Environmental Management · doi:10.1016/j.jenvman.2021.114357 · Cited by 210
Metadata
- Authors
- Zhou, B., Zhang, C., Song, H., & Wang, Q.
- Venue
- Science of The Total Environment
- Publisher
- Elsevier BV
- Published
- 2019-08
- Volume
- 676
- Pages
- 514-523
- ISSN
- 0048-9697 (ISSN-L)
- OpenAlex
- W2941384101
- Cited by
- 284
- References
- 2
- FWCI
- 42.70
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zhou, B., Zhang, C., Song, H., & Wang, Q. (2019). How does emission trading reduce China's carbon intensity? An exploration using a decomposition and difference-in-differences approach. Science of The Total Environment. https://doi.org/10.1016/j.scitotenv.2019.04.303
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
