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1

Agricultural environmental efficiency and agricultural environmental Kuznets curve based on technological gap: the case of China

100%

Wang Y. , Shen N.

Polish Journal of Environmental Studies

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2016

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tom 25

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nr 3

EN

With regards to the interchanging features of agricultural pollution and its negative impacts on China’s eco-environment such as environmental degradation, this paper, by fully taking into consideration the gap in environmental technology, incorporated the extended SBM directional distance function and Metaconstraints efficiency function to estimate China’s agricultural environmental efficiency (roughly three regions: eastern, central, and western China), and employed the panel model to study the environmental Kuznets curve’s (EKC) characteristics and the causes of regional differences in agricultural environmental efficiency under levels of different environmental technology. The study showed that, due to the signifi cant differences in agricultural environmental production technology among the three different regions, agricultural environmental efficiency presented a pattern of progressive decline, for instance; eastern China > western China > central China. Although the agricultural environmental technology of eastern China can reach 96.92% of the potential meta-constraint technology level, agricultural environmental technology of central and western China only reach 83.71% and 79.37% of the potential meta-technology constraint, respectively. The EKC curve of agricultural environmental efficiency was proved to be supportive of the circumstances in China; however, as a result of the gap in environmental technology, the EKC curves of different regions presented different turning points and stages. In addition to agricultural economic growth, openness of trade, proportion of agriculture, agricultural technological level, income gap, and fiscal support to agriculture have a significant effect on agricultural environmental efficiency, but both the impact direction and the impact extent of these factors on agricultural environmental efficiency are different.

2

Influence of agglomeration of manufacturing and the producer service sector on energy efficiency

80%

Shen N. , Deng R. , Wang Q.

Polish Journal of Environmental Studies

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2019

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tom 28

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nr 5

EN

Due to the gradual agglomeration of economic activities and the continuous reinforcement of spatial linkages in specific geographic locations, the geospatial factor should become an important starting point to understand the relationship between industrial restructuring and energy conservation and emission reduction. This paper first introduces a non-separable hybrid DEA model that considers undesirable output to measure the energy efficiencies of 285 prefecture or higher-level cities in China during 2003-2016; then, a dynamic spatial panel model is used to investigate the influence of different types of industrial agglomerations and agglomeration modes on energy efficiency. According to the obtained study results, for the investigation period, the overall energy efficiency of China with regard to pollutants remained at a low level and presented a “U-shaped” decreasing-increasing trend. To be specific, China’s energy efficiency distribution presented a trend of “high in the east and low in the west.” The energy efficiency of East China changed relatively gently, while the energy efficiencies of central China and western China changed dramatically. China’s energy efficiency also presented a significant spatial agglomeration effect, i.e., cities with close energy efficiencies are usually adjacent to each other. At the national level, agglomeration of the manufacturing sector significantly inhibited the increase of energy efficiency; the agglomeration of the producer service sector and the co-agglomeration of the manufacturing sector and the producer service sector both facilitated an increase of energy efficiency. The influence of industrial agglomeration on energy efficiency differed across different city scale grades. Based on these conclusions, the paper proposes the following policy implications: 1) make full use of the energy savings and emission reduction effect of agglomeration; 2) accelerate the optimization of industrial layout; 3) develop high-end service industry and productive service industry; and 4) create an agglomeration environment that encourages benign industrial competition.

3

Energy efficiency measures and convergence in China, taking into account the effects of environmental and random factors

80%

Shen N. , Zhou J. , Zou W.

Polish Journal of Environmental Studies

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2015

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tom 24

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nr 1

EN

This paper measures energy efficiency in China using the three-stage data envelopment analysis (DEA) model and then tests the convergence of China’s energy efficiency. The study finds that environmental factors and random factors both have significant impacts on energy efficiency. After eliminating the influences of environmental and random error factors, the results present that the pure technical efficiency improves and the scale efficiency decreases, but pure technical efficiency is far lower than scale efficiency in terms of energy utilization, which indicates that low pure technical efficiency is the main factor constraining China’s energy efficiency. China’s energy efficiency presents obvious regional differences, and the energy efficiency in eastern regions is higher than that in midwestern regions. Based on the matching relationship between energy efficiency and input level, China can be regionally divided into four energy utilization modes: high efficiency and high input mode, high efficiency and low input mode, low efficiency and high input mode, and low efficiency and low input mode. Nationally, the difference in regional energy efficiency should maintain a relatively high level in the short term; divergence occurs in terms of pure technical efficiency and overall technical efficiency, while scale efficiency manifests a significant absolute convergence feature. Differential energy strategy should be carried out according to the features of different districts. Eastern regions should decrease the dependence on external energy, and develop advanced techniques with lower energy consumption. The improvement of energy efficiency in Midwest regions should depend on changing a traditionally highly energy-intensive industrial structure, undertaking clear industrial transfer from the east, excavating latent energy savings with the high-energy industry sector, and accelerating the transformation to an intensive pattern. Strengthening the energy corporation of China not only enhances energy efficiency in eastern regions but also improves energy efficiency in midwestern regions by spillover effect. Accordingly, it could improve energy efficiency balance and robustness.