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Environmental efficiency and economic growth of China: A Ray slack-based model analysis
Abstract
The Chinese economy has been experiencing rapid growth since the implementation of the reform and opening-up policy. However, at the same time, it faces issues regarding resource savings and environmental protection, which are important aspects of the new industrialization. Therefore, this study conducts data envelopment analysis (DEA) to evaluate the environmental efficiency of Chinese regions. Certain existing DEA models account for undesirable outputs and do not elucidate the weak disposable relationship between undesirable and desirable outputs. Thus, polar theory is introduced among the DEA modeling in this study. First, drawing on stochastic frontier analysis, Ray stochastic frontier analysis, and DEA, we propose a Ray slack-based model (RSBM) to evaluate provincial environmental efficiencies in China from 2004 to 2012. Subsequently, an RSBM-Malmquist–Luenberger (total factor productivity) index is structured. Finally, economic growth, environmental efficiency, and energy consumption are analyzed using spatial panel econometrics. As this study treats industrial waste as undesirable outputs, the RSBM results show that the environmental efficiencies in the east are the highest, while those in the central regions are the lowest. The spatial econometric analysis reveals that the ratios of direct to total elasticity and those of direct to total effect for capital, labor, and energy input variables are fixed. Furthermore, the study provides policy implications and suggestions for future research.
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Citations
Cites
Hsiao, C. (2014) · doi:10.1017/cbo9781139839327 · Cited by 7,869
A slacks-based measure of super-efficiency in data envelopment analysis
Tone, K. (2002) · European Journal of Operational Research · doi:10.1016/s0377-2217(01)00324-1 · Cited by 3,576
Cited by
Mardani, A., Streimikiene, D., Cavallaro, F., Loganathan, N., & Khoshnoudi, M. (2019) · Science of The Total Environment · doi:10.1016/j.scitotenv.2018.08.229 · Cited by 630
The survey of economic growth, energy consumption and carbon emission
Waheed, R., Sarwar, S., & Wei, C. (2019) · Energy Reports · doi:10.1016/j.egyr.2019.07.006 · Cited by 440
Testing the fluctuations of oil resource price volatility: A hurdle for economic recovery
Xiuzhen, X., Zheng, W., & Umair, M. (2022) · Resources Policy · doi:10.1016/j.resourpol.2022.102982 · Cited by 407
Combating desertification in China: Monitoring, control, management and revegetation
Zhang, Z., & Huisingh, D. (2018) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2018.01.233 · Cited by 284
Baz, K., Cheng, J., Xu, D., Abbas, K., Ali, I., Ali, H., & Fang, C. (2021) · Energy · doi:10.1016/j.energy.2021.120357 · Cited by 265
Metadata
- Authors
- Song, M., Peng, J., Wang, J., & Zhao, J.
- Venue
- European Journal of Operational Research
- Publisher
- Elsevier BV
- Published
- 2018-08
- Volume
- 269
- Issue
- 1
- Pages
- 51-63
- ISSN
- 0377-2217 (ISSN-L)
- OpenAlex
- W2605693365
- Cited by
- 217
- References
- 2
- FWCI
- 21.28
- Type
- journal article
- Language
- en
- Open access
- closed
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- Song, M., Peng, J., Wang, J., & Zhao, J. (2018). Environmental efficiency and economic growth of China: A Ray slack-based model analysis. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2017.03.073
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