Abstract / Description of output
Comprehensive evaluation and identification of the critical regulatory determinants of carbon emission efficiency (CEE) are very important for China’s low-carbon transition. Accordingly, this paper first employs an undesirable global super-hybrid measure approach to calculate the CEE of China’s iron and steel industry (ISI). We then further use spatial error and threshold regression models to examine the spatial and non-linear effects of heterogeneous environmental regulations on CEE, respectively. Our empirical results show that (1) CEE varies significantly across China’s regions, with the eastern region having the highest CEE score, followed by the western and central regions, with the northeast region ranking the lowest; (2) command-and-control and market-incentive regulations both promote CEE, whereas the public participation approach does not significantly contribute to performance gains; (3) all three types of environmental regulations exhibit a non-linear threshold effect on CEE; (4) openness level, technological progress, and industrial concentration enhance efficiency gains, while urbanization level exerts a negative impact on CEE. Our findings have important implications for the design of environmental regulations.
Original language | English |
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Number of pages | 27 |
Journal | Annals of Operations Research |
Early online date | 24 Jul 2023 |
DOIs | |
Publication status | E-pub ahead of print - 24 Jul 2023 |
Keywords / Materials (for Non-textual outputs)
- environmental regulation
- carbon emission efficiency, low-carbon transition, iron and steel industry
- spatial error model
- panel threshold analysis