Search

After the concept of ecological efficiency (eco-efficiency) was put forward and constantly supplemented, it generally refers to the maximization of economic benefits with minimum energy consumption and environmental damage. In a new eco-efficiency model proposed by this paper, the input indexes take into account the consumption of capital, human, resources and energy, and the environmental load caused by them. The output indexes take into account GDP, income, and tax revenue. An optimal weighted cross-evaluation efficiency (OWCE) model based on data standardization is proposed, by improving the traditional data envelopment models of CCR and BCC. The OWCE model not only objectively weights but also unifies the comparison scale, and facilitates the establishment of the super-efficiency decomposition model, which is conducive to further exploring the reasons for the difference of eco-efficiency in various regions. Empirically, the eco-efficiencies of 11 provinces (municipalities) along the Yangtze River Economic Belt (YREB) were analyzed based on the data from 2008 to 2019. The results show that there has been a serious imbalance in the 11 provinces, showing a trend of high in the east and low in the west, although the eco-efficiency has been improving continuously in the past 10 years. Shanghai, Zhejiang, and Jiangsu, which are located in the traditional Yangtze River lower delta region, are the top in terms of eco-efficiency, among which Shanghai ranks the first place with absolute advantage, and also is far ahead in sub-efficiencies of basic input, energy consumption, capital and human input, and environmental cost. Geographical location, especially whether it is close to the ocean, and the length of river flow have a certain positive impact on eco-efficiency. Through in-depth analysis, high-energy consumption, high pollution, and low economic output are the main reasons for low eco-efficiency in the middle and upper reaches of the Yangtze River.

Environmental regulations affect employment through productivity output and factor substitution. This paper employs a difference-in-differences (DID) method to investigate the effect of China's Two Control Zones (TCZ) policy on the urban employment in 287 cities from 1994 to 2009. We apply the DID method to two time points: 1998 for policy issuance and 2000 for the policy implementation. From the results of analyses on full-sample cities, the TCZ policy did not contribute to increasing total urban employment. Moreover, a negative impact on employment resulted from sulfur dioxide and acid rain controls in secondary and tertiary industries, respectively. In the acid rain control zone, the TCZ policy increased the average wage of urban workers. Negative effects on employment were observed in larger cities. The policy triggered labor migration from larger to smaller cities, resulting in significant increases in primary and tertiary industry employment in smaller cities, although the effects on mid-size cities were insignificant. This study provides important empirical evidence and insight into the impact of the TCZ policy on urban employment.