Environmental regulation influences urban land green use efficiency: Incentive or disincentive effect? Evidence from China

China's crude economic development has led to high pollution and inefficiency of urban land use. Environmental regulation (Er) is crucial for governments to promote green growth and efficient land use. Using a dataset of 271 cities in China from 2011 to 2020, this paper investigates the threshold effect of green innovation in science and technology and industrial structure optimization on Er impacts of urban land green use efficiency (Ulee). The results show that (1) Er positively affects Ulee. (2) There is a threshold effect of green innovation in science and technology (Gin) and industrial structure upgrading (Ind) in Er affecting Ulee, and the force decreases as the threshold value increases. (3) Within the examination of heterogeneity, the impact of Er on Ulee is more significant in eastern, high levels of urbanization and large cities, but the force of action is smaller. Based on the nonlinear force of Er, it is crucial to maximize the effectiveness of green land use by giving full play to the interactive synergistic effect of the "combination box" and dynamically and flexibly adjusting the intensity of Er according to the time, place, and state of urban development.

Can greater openness improve green economy efficiency of countries along the Belt and Road Initiative?

Openness is the core concept of the Belt and Road initiative (BRI), which plays a significant role in promoting the sustainable economic development of countries along the BRI. This study uses the entropy method to measure openness based on six dimensions: trade, investment, finance, tourism, technology, and information. Simultaneously, a super-SBM model with undesired output is proposed to measure green economy efficiency (GEE). Using the panel data of 66 countries along the BRI from 2008 to 2019, we empirically examine the impact of openness on GEE. The results are as follows: (1) The openness level of countries along the BRI is generally increasing, but the relative differences between countries tend to widen. (2) Openness has a significant U-shaped nonlinear effect on GEE, and the conclusion is still valid after considering the robustness test; (3) The spatial econometric model shows that openness not only affects the GEE of the local country, but also has a spillover effect on neighboring countries. Therefore, we believe that BRI countries should strengthen policy communication, break down border barriers, actively promote the orderly flow and diffusion of openness elements, and pay attention to the quantity and quality of openness development, which is key to the high-quality construction of the BRI.

Spatial-temporal differentiation of coupling coordination degree for green finance and green innovation efficiency: a case study in China

Continued investment in finance and innovation is beneficial to economic development, and the joining of green system can accelerate the process of economic recovery from environmental distress. To better enhance the relationship of green finance and green innovation, it is vital to demonstrate the synergy between the two thoroughly. Thirty provinces in China are selected to examine the coupling coordination relationship between the two, specifically testing the spatial aggregation and evolutionary differences in the coupling coordination by adopting the coupling coordination degree (CCD) model, spatial autocorrelation, and kernel density estimation. Conclusions of the paper show that green finance is calculated by the EW-TOPSIS method, and the overall score of provinces is low. Using super-SBM model to evaluate green innovation, the uneven distribution of efficiency is obvious, although it is gradually increasing. The CCD in most provinces is in low-level or basic coordination, with significant regional heterogeneity. The global Moran's index becomes gradually evident with time. The local Moran scatter diagram presents a downward trend from east to west, but with more L-L aggregation provinces emerging in 2020. The center of the national kernel density curve gradually shifts to the right, indicating that the national overall synergy level is improving. Deepening the understanding of the empirical results facilitates the formulation of reasonable policies that fit the four major regions.

The spatiotemporal dynamic and spatial spillover effect of green finance efficiency in China: analysis based on super-SBM model and spatial Durbin model

Green finance is a key institutional framework supporting China's newly publicized "Ecological Civilization Construction" initiative, and studies have analyzed the influencing factors of green growth from multiple perspectives; there are few studies that have examined the effectiveness of China's multidimensional green finance goals. This study analyzes panel data of 30 provinces in China from 2008 to 2020 and uses the Super Slacks-Based Measure (Super-SBM) model to calculate China's green finance efficiency (GFE) and discusses its dynamic evolution characteristics in spatiotemporal dimensions. The main conclusions are as follows: First, there is a steady upward trend in China's overall GFE value, despite a low level of GFE in general. Second, there is a curse of "Hu Huanyong line," with highs in the eastern region and lows in the central and western regions as the overall distribution pattern. Third, GFE has a positive spatial spillover effect, and green finance development in nearby regions is closely related.

Study on eco-efficiency of cultivated land utilization based on the improvement of ecosystem services and emergy analysis

Cultivated land is the result of the cooperation between humans and nature. The utilization of cultivated land hopes to realize a "win-win" situation of food production and ecological protection to promote sustainable development. Previous studies on the eco-efficiency of agro-ecosystem mainly considered material input, agricultural product output and environmental pollution, and did not systematically include the natural input and ecological product output, which had limitations on the study of sustainable development of cultivated land utilization. Therefore, this study initially used emergy analysis and ecosystem service assessment methods to include the natural input and ecosystem service output of cultivated land into the assessment framework of eco-efficiency of cultivated land utilization (ECLU) and used the Super-SBM model to calculate the ECLU in the Yangtze River Delta (YRD) region in China. In addition, we also discussed the influencing factors of ECLU by the OLS model. Here we show that the ECLU was lower in cities with higher agricultural intensive utilization in the YRD. And in cities with better ecological conditions, the ECLU value obtained based on our adjusted ECLU assessment framework was higher than the traditional agricultural eco-efficiency assessment, indicating that the assessment method in this study paid more attention to ecological protection in the application. In addition, we found that crop diversity, paddy/dry land ratio, cultivated land fragmentation and terrain are the factors affecting the ECLU. This study helps provide a scientific basis for decision-makers to improve the ecological function of cultivated land based on ensuring food security and furthermore promote regional sustainable development.

The efficiency of China's freshwater fishery breeding: nonparametric data envelopment analysis based on interprovincial data

Studying the economic efficiency of freshwater fishery breeding is of great significance to the sustainable utilization of freshwater fishery resources. Based on the nonparametric research method, this study combines the super-SBM data envelopment analysis (DEA) model with the global Malmquist index (GMI) to evaluate the total factor productivity of freshwater fishery breeding (FTFP) of China from 2004 to 2019, so as to reflect the economic efficiency of freshwater fishery breeding in China. The empirical results show that (1) in general, FTFP has reached the effective level in China with a fluctuating trend in time, but it lacks a breakthrough value. (2) In China, FTFP shows significant differences in space, and its spatial development pattern has gradually evolved from "high in the south and low in the north" to "high in the north and low in the south." (3) The change of FTFP in China mainly depends on technological progress, while the change of scale efficiency and pure efficiency has no significant impact on it. (4) When environmental factors are taken into account, the FTFP value will decrease as a whole. Therefore, it is very important to optimize the structure of freshwater fishery breeding and strengthen the construction of aquatic science and technology system.

The diminishing marginal contribution of R&D investment on green technological progress: a case study of China's manufacturing industry

One of the ways to fight against global warming is by means of green technological progress. This paper explores the nonlinear relationship between R&D investment and green technological progress based on panel threshold regression model using panel data of 26 manufacturing sub-sectors in China from 2004 to 2017. The results show that the double-threshold model can better explain the nonlinear relationship between the two, and the R&D investment in the three ranges of low, medium, and high levels can significantly promote green technological progress in China's manufacturing industry. However, with the improvement of R&D investment level, the promotion effect of R&D investment on the progress of manufacturing green technology is decreasing, which explains the low R&D intensity of China's manufacturing industry to a certain extent. When the level of R&D investment reaches a certain level, its promoting effect on manufacturing industry's green technological progress will be greatly reduced, and the motivation of enterprises to invest in R&D based on self-interest will decrease, so that the scale of R&D investment will be lower than the optimal scale of society. R&D investment can also improve green technical efficiency change. In addition, environmental regulation can promote green technological progress in manufacturing industry. However, due to the implementation of output-oriented environmental regulation policies, China's environmental regulation can inhibit the improvement of green technical efficiency change. Based on the conclusion, this paper argues that China should implement differentiated R&D subsidy policies for manufacturing enterprises, especially to increase R&D subsidies for enterprises with a medium level of R&D investment, and formulate appropriate environmental regulatory policies, to promote green and low-carbon transformation of China's manufacturing sector.

Analysis of regional vegetable circulation efficiency and its spatial effect considering carbon emission

In order to explore the evolution process of regional vegetable circulation efficiency and its influencing factors, this paper uses Super-SBM model considering unexpected output and GML index to calculate the vegetable circulation efficiency of 13 provinces (cities) in Central China and its surrounding areas from 2015 to 2019, then conducts spatial autocorrelation analysis on the vegetable circulation efficiency in this region through Moran index. Finally, SPDM model is constructed to explore the spatial effect of the influencing factors on the vegetable circulation efficiency in this region. The results show that (1) the vegetable circulation efficiency of most provinces (cities) in this region is low. (2) The Global Moran's I of the vegetable circulation efficiency in this region is positive, that is, the vegetable circulation efficiency in this region shows a certain degree of spatial agglomeration effect. (3) The level of scientific and technological innovation and the degree of government support have significant positive direct and indirect effects on the efficiency of vegetable circulation in the region, the quality of workers has significant positive indirect effects, and the level of economic development and industrial structure have significant negative indirect effects.

Exploring Tourism Efficiency and Its Drivers to Understand the Backwardness of the Tourism Industry in Gansu, China

Gansu Province is rich in tourism resources, and it is the hometown of the "copper galloping horse", which is the logo of China's tourism. However, the scale and revenues of tourism in Gansu province are still at a low level. This paper first evaluated the tourism efficiency of 14 cities and prefectures of Gansu Province in China from 2011 to 2019 using the super-slack-based measure (Super-SBM) and then investigated the internal driving mechanism of the efficiency change through the Global Malmquist-Luenberger (GML) index and its decomposition, and finally analyzed the external influencing elements of tourist efficiency by the Tobit model. The results revealed that the tourism efficiency of Gansu Province had increased rapidly during the study period, especially after 2016, the rising range increased. From 2011 to 2019, the cumulative changes in GML index, technological change (TC), and efficiency change (EC) of tourism efficiency in Gansu Province were 5.053, 4.145 and 1.160, respectively, indicating that the improvement of tourism efficiency in Gansu province is mainly due to technological progress. The regression results of the Tobit model show that the status of the tourism industry, trade openness, information level, and technological innovation level can significantly promote tourism efficiency in the province. At the same time, upgrading the industrial structure and the improvement of greening coverage inhibit tourism efficiency. However, the impact of the economic development level on the tourism efficiency of Gansu Province is not apparent. According to the research results, this paper puts forward corresponding suggestions to promote the development of tourism in Gansu Province. This study is crucial for hospitality, tourism, and policy sectors to understand the underlying factors and promote the healthy development of the tourism industry in Gansu Province.

Spatial-Temporal Pattern and Influencing Factors of Ecological Efficiency in Zhejiang-Based on Super-SBM Method

The traditional meaning of ecological efficiency generally considers only the ratio of economic output to environmental input. This paper expands the meaning and the evaluation system of ecological efficiency from the perspective of improving people's livelihoods. Not only are the discharge of wastewater, waste gas, and solid waste included in the undesired output, but the output index also takes full account of the overall development of the economy, innovation, society and the environment from the perspective of high-quality development. Under the assumption of variable returns to scale, a super-efficiency slack-based measure model based on the undesirable output and Malmquist index is introduced to measure the spatial and temporal variation of ecological efficiency of Zhejiang Province in China, and the panel Tobit method is used to study the key factors affecting ecological efficiency. The results include the four following findings: (1) In the past 12 years, the ecological efficiency of Zhejiang Province has steadily increased, except in 2019 and 2020, when seven cities in Zhejiang Province experienced a decline or near stagnation due to the impact of the economic slowdown and the COVID-19 epidemic. (2) The ecological efficiency of Zhejiang demonstrates a severe regional imbalance, showing a high level in the northeast and a low level in the southwest. (3) Malmquist index analysis shows that the improvement of ecological efficiency in Zhejiang Province has shifted from mainly relying on the dual drivers of pure technical efficiency and scale efficiency in the early stage to relying on technological progress in the later stage. (4) Tobit regression analysis shows that industrialization structure, Theil index, and traffic activity have a significant positive effect on ecological efficiency.

Manufacturing transfer and environmental efficiency: Evidence from the spatial agglomeration of manufacturing in China

Manufacturing transfer is an important factor in optimizing the spatial distribution of resources and promoting regional environmental efficiency. Based on the manufacturing data of 30 provinces in China from 2005 to 2017, the spatial Durbin model is used to investigate the impact of three types of manufacturing transfer and spatial agglomeration effects on environmental efficiency under the spatial weight matrix of economic distance. The results show that the improvement of environmental efficiency is inhibited by the transfer of labor-intensive manufacturing but facilitated by the spatial agglomeration of such manufacturing. The transfer of capital and technology-intensive manufacturing has no significant impact on environmental efficiency. Environmental efficiency is significantly improved by the spatial agglomeration of technology-intensive manufacturing but significantly inhibited by that of capital-intensive manufacturing. Third, the impact of three types of manufacturing transfer on environmental efficiency is analyzed from the perspective of regional heterogeneity. This paper puts forward relevant policy suggestions from the perspectives of manufacturing transfer, the agglomeration effect, so as to further improve the environmental efficiency.

Assessing urbanization efficiency and its influencing factors in China based on Super-SBM and geographical detector models

Improving urbanization efficiency (UE) has gradually become an important requirement for the development of new-type urbanization. In this paper, first, we applied the Super-SBM model with undesirable outputs and Malmquist index to evaluate the UE of 30 provinces in China from 2006 to 2016 based on static and dynamic perspectives. Second, influencing factors were explored using the novel geographical detector model. The results show that China's UE was not high overall and was increasing slowly. Regionally, the UE presented a high-to-low spatial evolution from east to west. Technical change was the main reason for the slow growth in efficiency, and undesirable outputs (pollutant emissions) were the key to efficiency loss. Over the study period, GDP per capita and urbanization rate had the greatest determining power on the UE, but their determination power was declining. Meanwhile, the impact of research and development (R&D) and foreign direct investment (FDI) on UE became increasingly important. Finally, some suggestions for improving the urban ecological environment and UE in China are discussed.

Dynamic Changes, Spatiotemporal Differences and Factors Influencing the Urban Eco-Efficiency in the Lower Reaches of the Yellow River

The measurement of eco-efficiency is an important tool to evaluate the level of urban sustainable development. Therefore; improving urban eco-efficiency in the lower reaches of the Yellow River ensures the implementation of ecological protection and high-quality development strategies in the Yellow River Basin. In this study; the dynamic changes of urban eco-efficiency and spatiotemporal differences in the lower reaches of the Yellow River were investigated using the Super-SBM (Super-Slack measure model) model with undesirable outputs and standard deviation ellipse. The STIRPAT (Stochastic Impacts by Regression Population; Affluence and Technology) model was introduced to analyze the factors affecting the change in urban eco-efficiency. The results showed that the overall urban eco-efficiency in the lower reaches of the Yellow River has not reached the optimal level. The overall eco-efficiency in the lower reaches of the Yellow River in Shandong Province was higher than that in Henan Province but the gap is narrowing. The spatial differentiation of urban eco-efficiency in the lower reaches of the Yellow River showed the following trends: "blooming in the middle and reverse development at both ends" in the high-value area and gradual decrease in the low-value area. From 2007 to 2018; a direction was notable with respect to the development of urban eco-efficiency in the lower reaches of the Yellow River; with the centripetal force weakening. Although the mean center of urban eco-efficiency located in Shandong Province; it notably shifted to the west during the study period. In terms of driving factors; affluence and technological progress play positive roles in driving eco-efficiency; while investment intensity; industrial structure; and foreign investment intensity hindered the optimization and improvement of urban eco-efficiency in the lower reaches of the Yellow River. The results of this study show that urban eco-efficiency in the lower reaches of the Yellow River is improving; but the regional coordination is poor. The main methods promoting the sustainable development in the study area include changing the mode of extensive investments and the introduction of foreign capital; which improve the energy efficiency and promote faster and better economic development.

The Double-Edged Sword of Urbanization and Its Nexus with Eco-Efficiency in China

Urbanization has made tremendous contributions to China's economic development since its economic reforms and opening up. At the same time, population agglomeration has aggravated environmental pollution and posed serious challenges to China's environment. This article empirically investigates the impacts of China's urbanization on eco-efficiency, comprehensively reflecting economic growth, resource input, and waste discharge. We first measured the provincial eco-efficiency in China from 2005 to 2015 using the Super Slack-Based model (Super-SBM). We then constructed a spatial model to empirically analyze the effects of urbanization on eco-efficiency at the national level, and at four regional levels. The results indicated that the regional eco-efficiency in China has fluctuated, but is generally improving, and that a gap between regions was evident, with a trend toward further gap expansion. We observed an effect of spatial spillover in eco-efficiency, which was significant and positive for the whole country, except for the western region. The influence of urbanization on China's eco-efficiency exhibited a U-curve relationship. The changing trend in the eastern, central, and western regions was the same as that in the whole country; however, the trend exhibited an inverted U-curve relationship in the northeastern region. To the best of our knowledge, covering a time period of 2005-2015, this article is the first of its kind to study the impact of urbanization on eco-efficiency in China at both the national and regional levels. This study may help policy-makers to create sustainable policies that could be helpful in balancing urbanization and the ecological environment.