Ecological efficiency in China and its influencing factors—a super-efficient SBM metafrontier-Malmquist-Tobit model study

Abstract

Ecological problem is one of the core issues that restrain China's economic development at present, and it is urgently needed to be solved properly and effectively. Based on panel data from 30 regions, this paper uses a super efficiency slack-based measure (SBM) model that introduces the undesirable output to calculate the ecological efficiency, and then uses traditional and metafrontier-Malmquist index method to study regional change trends and technology gap ratios (TGRs). Finally, the Tobit regression and principal component analysis methods are used to analysis the main factors affecting eco-efficiency and impact degree. The results show that about 60% of China's provinces have effective eco-efficiency, and the overall ecological efficiency of China is at the superior middling level, but there is a serious imbalance among different provinces and regions. Ecological efficiency has an obvious spatial cluster effect. There are differences among regional TGR values. Most regions show a downward trend and the phenomenon of focusing on economic development at the expense of ecological protection still exists. Expansion of opening to the outside, increases in R&D spending, and improvement of population urbanization rate have positive effects on eco-efficiency. Blind economic expansion, increases of industrial structure, and proportion of energy consumption have negative effects on eco-efficiency.

Research on the Structural Features and Influential Factors of the Spatial Network of China’s Regional Ecological Efficiency Spillover

“…Therefore, in this paper, the influential factors of correlation network structure of regional efficiency spillover are considered using two dimensions: geographical proximity and regional differences. While referring to the existing research, the geographic connection matrix was selected as the proxy variable of geographical proximity, while the economic development level, industrial structure, freedom degree of investment, environmental regulation, and technical improvement were selected as influential factors of regional differences on the spatial correlation relation of regional ecological efficiency spillover [52][53][54][55][56]; see Table 2 for further details.…”

Sustainability Governance in China: An Analysis of Regional Ecological Efficiency

“…In order to deal with the relationship between economic development and ecological environment, the government should adhere to the principle of sustainable development, accelerate market-oriented reform, save resources, and protect the environment to improve ecological efficiency [53]. Secondly, the government should control some high-pollution industries, improve energy-saving technologies, encourage and increase investment in new technology, explore clean energy, and ensure balance between the economy and society [54]. Thirdly, the government should strengthen cooperation in regional ecological governance, narrow the regional spatial gap, and promote regional coordinated development of ecological governance [52].…”

Analysis of Driving Factors of Photovoltaic Power Generation Efficiency: A Case Study in China

“…In the Tobit regression model in this study, the explanatory variables x i take the actual observations, and the dependent variable y i takes the overall efficiency of the DEA model and y i is in the interval [0,1]. If y * i < 0, the value of y i is the result of the calculation, which is unlimited; if y * i ≥ 1, the value of y i is 1, which is a restricted dependent variable [23]. The relationship between the explanatory variables and the dependent variable is as follows:…”

“…However, according to the research results in other fields, macro factors also have a significant role in improving efficiency. Ma et al used the ultra-efficiency relaxation-based measurement (SBM) model and Tobit regression to study China's eco-efficiency and found that expanding openness, increasing R&D expenditure, and increasing population urbanization rate have a positive impact on eco-efficiency [23]. Wang used Seiford's linear transformation method to estimate China's water use efficiency, and then used the Tobit model to analyze the influencing factors and found that export dependence, technological progress, and educational value have positive effects on water use efficiency [24].…”