Tao, Miaomiao and Failler, Pierre and Goh, Lim Thye and Lau, Wee Yeap and Dong, Hanghang and Xie, Liang (2022) Quantify the effect of China's Emission Trading Scheme on low-carbon eco-efficiency: Evidence from China's 283 cities. Mitigation and Adaption Strategies for Global Change, 27 (6). ISSN 1381-2386, DOI https://doi.org/10.1007/s11027-022-10015-8.
Full text not available from this repository.Abstract
The establishment of a carbon trading market is crucial for China to fulfil its carbon emission commitments through a market mechanism. As a market-based environmental regulation instrument, Emission Trading Scheme (ETS) has been attracted increasing attention worldwide, while the effect of ETS on low-carbon economy efficiency (LEE) has not been fully investigated, thus inspiring us to fulfil this research gap. Using the panel data of China's 283 selected prefecture-level cities during 2006-2017, we adopted the difference-in-differences (DID) model, propensity-score-matched DID (PSM-DID) model, and the spatial DID model to model the direct and indirect effects of China's ETS on LEE at national, regional, and local (resource-based cities with different development stages) levels. The robust results yield that ETS directly and significantly improved China's LEE at the national level. Still, the LEE in ETS pilot region will increase by approximately 4.3% compared with untreated cities, while the spatial heterogeneity of this effect is captured at regional and local levels, which emphasises the necessity of a completed market construction and classified supervision. The results of this paper provide important insights for strengthening the policy design of a nationwide carbon market, and a reference point for other regions and countries, especially developing countries, in refining a carbon trading market.
Item Type: | Article |
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Funders: | None |
Uncontrolled Keywords: | Emission trading system; Low-carbon economy efficiency; Quasi-natural experiment; Spatial spillover effect; Spatial heterogeneity |
Subjects: | G Geography. Anthropology. Recreation > GE Environmental Sciences |
Divisions: | Faculty of Business and Economics > Department of Economics and Applied Statistics |
Depositing User: | Ms. Juhaida Abd Rahim |
Date Deposited: | 08 Nov 2023 07:58 |
Last Modified: | 08 Nov 2023 07:58 |
URI: | http://eprints.um.edu.my/id/eprint/41577 |
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