The establishment of a carbon trading market is crucial for China to fulfill its carbon emission commitments through a market mechanism. As a market-based environmental regulation instrument, 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 fulfill 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 examine 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.
|Number of pages||33|
|Journal||Mitigation and Adaptation Strategies for Global Change|
|Publication status||Published - 27 Jul 2022|
- Emission trading system
- Low-carbon economy efficiency
- Quasi-natural experiment
- Spatial spillover effect
- Spatial heterogeneity
FingerprintDive into the research topics of 'Quantify the effect of China’s emission trading scheme on low-carbon eco-efficiency: Evidence from China’s 283 cities'. Together they form a unique fingerprint.
Supplementary material for 'Quantify the effect of China’s emission trading scheme on low-carbon eco-efficiency: Evidence from China’s 283 cities'.
Tao, M. (Creator), Failler, P. (Creator), Goh, L. T. (Creator), Lin, X. (Creator), Dong, H. (Creator) & Xie, L. (Creator), University of Portsmouth, 7 Jul 2022