Eco-efficiency In China Research Articles

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.

Dynamic Change and Spatial Correlation of Eco-Efficiency in China

Abstract High-quality economic development has become a goal in China. The measurement of eco-efficiency provides a comprehensive assessment for such development. However, the measurement of eco-efficiency is still based on the traditional data envelopment analysis model, and the analysis of eco-efficiency does not consider spatial correlation. In this study, the SuperSBM model considering undesirable output is used to measure eco-efficiency at the provincial level in China. Then, Moran’s I index is adopted to investigate the spatial correlation of eco-efficiency. Results show that the eco-efficiency in China generally presents a downward trend. In terms of area, the central and western regions have generally declined, except for the eastern region. The reason for the decline in eco-efficiency is the continuous decline in technical efficiency. A significant positive spatial correlation of eco-efficiency exists at the national level. High-high and low-low agglomerations of eco-efficiency exist in China. High eco-efficiency is mainly distributed in Inner Mongolia, Heilongjiang, Hebei, Beijing, Tianjin, Henan, Shandong, Jiangsu, Shanghai, Zhejiang, Fujian, Guangdong, and Hainan. Keywords Spatial correlation; Eco-efficiency; SBM; Technical efficiency; Technological progress

Spatio-temporal evolution and spatial interaction of regional eco-efficiency in China

Spatio-temporal evolution and spatial interaction of regional eco-efficiency in China

Evaluating provincial eco-efficiency in China: an improved network data envelopment analysis model with undesirable output.

In this study, an improved matrix-type network data envelopment analysis (NDEA) model with undesirable output was developed to evaluate the eco-efficiency of China's 30 provinces. The proposed model considered three linked but independent subsystems of the economy-society-environment cyclic system. Additionally, to allocate the weights of the NDEA model among the three subsystems (environment, economy, and society) of the eco-environment, a new relative reduction of the input-based method was proposed. The results show that, from 2003 to 2016, the average eco-efficiency of China's 30 provinces was low, ranging in [0.59, 0.73]. Qinghai and Hainan ranked first and second, respectively, in average eco-efficiencies, while both Shaanxi and Xinjiang had the lowest average eco-efficiencies. Affected by the low social subsystem efficiency, the eco-efficiency of 18 provinces decreased, but the range of the decrease was smaller than that of the increase in 11 other provinces in which the eco-efficiency improved. The average efficiency of the environmental subsystem is the highest among the three subsystems benefiting from reducing the emissions of "three industrial wastes," while economic subsystem owns the lowest average efficiency due to the input redundancy of total fixed assets and energy consumption. Compared with variables' projection, for most provinces, the undesirable output of the three industrial wastes should be reduced by more than 88.0%, while the positive outputs of atmospheric quality and per capita years of education should be increased by at least 61.0%.

Estimating the regional eco-efficiency in China based on bootstrapping by-production technologies

Abstract By-production (BP) technologies, modeled as an intersection of intended production technologies (production efficiency) and nature’s residual-generation technologies (environmental efficiency), was applied in this paper to estimate the regional eco-efficiency in China during 2008–2017. This model is firstly formulated by directional-distance-function (DDF) and Fare-Grosskopf-Lovell (FGL), and then modified by bootstrap sensitivity analysis. The empirical results demonstrate that: (i) BP technologies based on the multiple production relations tend to produce lower efficiency scores than conventional model based on a single production relation. Moreover, BP-FGL can be a better choice for the measurement of efficiency index; (ii) The low economic development level is not necessarily associated with low environmental efficiency. Most of the eastern provinces had superior production efficiencies while inferior environmental efficiencies compared with inland provinces; (iii) At the regional level, a greater improvement in environmental efficiency than in production efficiency can be observed, and the gaps on the latter had widened over time among these regions; (iv) The great efficiency gaps between production efficiency and environmental efficiency appeared in the North Coast and Northwest, which are disadvantage to the inter-regional coordinated development. The results indicate that promoting production performance is crucial to improve the eco-efficiency for sustainable development in China.

Land Use Eco-Efficiency and Its Convergence Characteristics Under the Constraint of Carbon Emissions in China.

By defining the connotation of land use eco-efficiency, land use eco-efficiency from 2003 to 2015 was calculated on the basis of the mixed directional distance function, and its spatial convergence analyzed using a spatial econometric model. Results showed that (1) the land use eco-efficiency in most regions of China was relatively ineffective—only Guangdong and Guangxi were relatively effective—and the spatial distribution of efficiency levels in each region was polarized. (2) Sigma and beta convergences were observed in land use eco-efficiency in China, and land use eco-efficiency in each province had an influence on the other. (3) The convergence rate of the eastern region was the same as that of the national region (0.164). The convergence rates of the central, western, and northeast regions were 0.181, 0.183, and 0.189, respectively, which were all higher than the national convergence rate. (4) Scientific and technological strength and industrial structure significantly promoted the improvement of land use eco-efficiency and steady development of land use in China.

Is metabolism in all regions of China performing well? – Evidence from a new DEA-Malmquist productivity approach

Abstract Economic development is generally accompanied by the consumption of ecosystems, so it is particularly essential to evaluate the operation of the economy-ecosystem quantitatively. In this paper, we explore the emergy evaluation indicators system with 23 indicators and measure the change of eco-efficiency in China from 2009 to 2015 by employing a new DEA Malmquist productivity approach. The results show that the economic-ecosystem operation from 2012 to 2015 is getting worse than that from 2009 to 2012. The Malmquist index is then decomposed into efficiency change (EC) and technology change (TC). The annual average value of EC in the first three years is less than 1, and the annual average value of EC in the last three years is more than 1, which indicates that the relative technical efficiency is increasing year by year. From the perspective of technical change, the growth rates of the first three years and three years after are greater than 1, which shows that technology is not the main factor that restricts the operation of the economy and ecosystem in 26 provincial administrative regions.

NonLinear Effects of Environmental Regulation on Eco-Efficiency under the Constraint of Land Use Carbon Emissions: Evidence Based on a Bootstrapping Approach and Panel Threshold Model.

Eco-efficiency has been receiving attention worldwide, and the effective implementation of environmental regulations (ERs) has become crucial to regional eco-efficiency. This paper uses a method combining mixed directional distance function and bootstrapping approach to investigate the spatial and temporal distribution characteristics of eco-efficiency under the constraint of land use carbon emission in China from 2004 to 2016. The nonlinear relationship between ER and eco-efficiency is observed with a panel threshold model. Results from empirical tests reveal that eco-efficiency in China during the study period has an upward trend, and the spatial and temporal distribution of eco-efficiency is unbalanced and concentrated. Technical innovation and land marketization (LM) shows double threshold, whereas industrial structure (IS) has a single threshold effect. LM has a promotional effect on eco-efficiency, which differs in the promotion before and after promotion across the threshold value. Reasonable ER can reduce cost by stimulating the innovation of green production technology and achieves a win-win situation between environment and output. This finding further verifies that the ER for eco-efficiency under the constraint of land use carbon emission conforms to the Porter hypothesis. The effect of ER on eco-efficiency changes from negative to positive with the increase of IS level. Adjusting the ownership structure and increasing the proportion of green achievements in the promotion and assessment of officials are important measures in the upgrading of eco-efficiency.

Spatial Correlation and Convergence Analysis of Eco-Efficiency in China

In this paper, we first measured the eco-efficiency of 31 provinces in China during 2000–2015 using the SBM (Slack-Based Measure) model, and the spatial character of eco-efficiency was identified based on symmetrical spatial weight matrix. We then proposed a new asymmetrical spatial weight matrix based on the eco-economic transformation index (EETI)-distance reciprocal principle to assess the spatial character of eco-efficiency. Finally, we analyzed the convergence of eco-efficiency’s total factor productivity (EETFPs) in mainland China and in three major regions based on the results of EETFP. The study revealed the following findings: (1) There were some limitations to the spatial autocorrelation of eco-efficiency in mainland China by the symmetrical spatial weight methods based on the spatial proximity principle or spatial distance principle. However, the new spatial weight scheme improved the reliability of the accounting results of the spatial autocorrelation. (2) The clustering effect of eco-efficiency exhibited a downward trend in mainland China during the study period; meanwhile, the significant high-high and low-high clustering areas were located in the eastern, the central, and the western regions. (3) The study of convergence showed that there was a club-convergence phenomenon in mainland China, and except for the western region, all the regions expressed conditional convergence. The results provide a significant reference for ecological-economy management and sustainable development in China.

Metafrontier Eco-Efficiency and Its Convergence Analysis for China: A Multidimensional Heterogeneity Perspective

ABSTRACT This article studies the evaluation, evolution, and convergence of China’s ecological efficiency (eco-efficiency) within a multidimensional (spatial, temporal, and spatiotemporal) heterogeneity framework using a dataset of 191 prefecture and above-prefecture level cities in China over the period of 2003–2015.The results show significant regional disparity of eco-efficiency in China and periodical patterns of σ-and γ-convergence. Estimation results of dynamic spatial Durbin model show that there is global and club β-convergence of eco-efficiency considering spatial, temporal, and spatiotemporal heterogeneity. The findings provide strong evidence for policy makers to take multidimensional heterogeneity into account to improve regional eco-efficiency, promote green development, and realize the “Beautiful China”.

Evaluation of eco-efficiency in China from 1978 to 2016: Based on a modified ecological footprint model

Eco-efficiency has become an important indicator for measuring sustainable development that emphasizes multiple dividends including basic needs, economic growth, resource conservation, and environmental protection. In this paper, we firstly modify the traditional ecological footprint (EF) model through amending the equivalence factors and enriching the account types to estimate the ecological pressure in China. Then, we evaluate the annual eco-efficiency of China based on the modified EF model from the perspectives of biological needs, resource consumption, and environmental pollution from the reform and opening-up until recently. Finally, the decoupling status between resource consumption, pollution emissions and economic growth is explored. The results indicated that: (1) The per capita EF of China increased from 1.83hectares (ha) in 1978 to 6.98ha in 2016, in which EF of energy experienced a significant increase and accounted for the largest proportion of total per capita EF in 2016, followed by air pollution and freshwater; (2) the total eco-efficiency in China increased from 210yuan/ha in 1978 to 1235yuan/ha in 2016, in which biological efficiency performed the best starting from 264yuan/ha in 1978 with an annual growth rate of 7.9% to 2016, resource efficiency roughly presented an upward tendency with a decline during 2002–2005, and environmental efficiency pictured a U-shaped curve; (3) “weak decoupling” between resource consumption, pollution emissions and economic growth is the main characteristic at present after undergoing through large fluctuation. Furthermore, implications towards an eco-friendly society are provided.

Industrial eco-efficiency, regional disparity, and spatial convergence of China's regions

In this study, the industrial eco-efficiency measures of 30 Chinese provinces (municipalities and autonomous regions) from 2001 to 2015 were estimated based on a proposed data envelopment analysis (DEA) model and the non-convex metafrontier-undesirable outputs-super efficiency-slacks-based measure (NCMeta-US-SBM) which simultaneously incorporates non-convex metafrontier technology, undesirable outputs, and super efficiency into slacks-based measure. Subsequently, dynamic spatial econometric models were employed to test the spatial convergence of industrial eco-efficiency. The empirical results show that: 1) the average value of industrial eco-efficiency was the highest in the eastern region (0.67), followed by the western region (0.30) and central region (0.27), indicating the existence of a significant regional disparity. 2) Strong evidence for global and club spatial convergence of industrial eco-efficiency was found. With regard to regional heterogeneity, provinces in the eastern region converged faster than those in the central and western regions; while the convergence speed of industrial eco-efficiency increased after 2008 with respect to temporal heterogeneity. 3) The ownership structure appeared to have a higher impact on industrial eco-efficiency than other controls in the presence of spatial conditional β-convergence. These findings are robust with regard to both spatial econometric model and spatial weighting matrix specifications. Based on the empirical analysis, the following policies promote industrial eco-efficiency in China have been recommended. First, relevant authorities must take effective measures to encourage the central/western regions to adopt clean energy technologies. The energy subsidy policies should strive to break through the technological lock-in and turn to regional green development. Second, full advantage of the spatial effects must be taken and technological exchanges and cooperation among neighboring areas must be strengthened to ensure that the industrial eco-efficiency of the central and western regions converge with those of the eastern coastal areas. Policy implications of multidimensional heterogeneity and adjustment of industrial structure should be highlighted while promoting industrial eco-efficiency. Finally, it is crucial to emphasize factors, such as foreign direct investment (FDI), ownership and industrial structures to attract FDI and optimize the current industrial structure.

Does urban cluster promote the increase of urban eco-efficiency? Evidence from Chinese cities

Abstract In this paper, we first explore the spatial distribution of 273 cities with the index of urban clustering and measure the urban eco-efficiency employing the data envelopment analysis in China from 2003 to 2015. We then comparatively analyze the impacts and mechanisms of urban cluster on urban eco-efficiency under a multidimensional framework. The results demonstrate that the degree of urban clustering and the urban eco-efficiency in China have generally improved, and the improvement of urban cluster is conducive to enhancing urban eco-efficiency. There is a “core-periphery” spatial structure in the process of urban cluster development, and the impact of urban clustering on the eco-efficiency in core cities is stronger than in the periphery cities. Urban cluster benefits urban eco-efficiency through the decentralization effect and structural optimization effect. The decentralization effect is heterogeneous: urban cluster effectively decentralizes the diseconomy of large cities but not small- and medium-sized cities. Similarly, the structural optimization effect is not uniform. For large cities, this effect mainly improves the eco-efficiency by affecting tertiary industry, whereas for small- and medium-sized cities, it mainly improves the eco-efficiency by affecting the secondary industry.

Do technological innovations promote urban green development?—A spatial econometric analysis of 105 cities in China

Abstract Rapid urban economic growth in China has resulted in a number of resource and environmental challenges. Technological innovations are a source of economic growth but act as a double-edged sword in their effects on urban green development. This study aimed to determine whether technological innovations promote or impede the enhancement of urban eco-efficiency in China and also to reveal regional and administrative-level differences in terms of the effects of technological innovations. We selected the number of granted invention patents and the proportion of technology-related revenue in the total revenue of national high-technology industrial development zones (NHTIDZs) as indicators to represent knowledge innovation and product innovation, respectively, and used the spatial autoregressive model to examine the effects of the two innovations on urban eco-efficiency. The results showed that technological innovations, which enhanced urban eco-efficiency, had a greater impact on eastern cities than on central and western cities. The higher was the administrative level of a city, the greater were the effects of invention patents on urban eco-efficiency. Moreover, the higher was the administrative level of a city, the smaller was the role that NHTIDZs played in promoting urban eco-efficiency, which represented a case of diminishing marginal utility.

Exploring the relationship between urbanization and urban eco-efficiency: Evidence from prefecture-level cities in China

Abstract The rapid development of urbanization has had a dramatic impact on the ecological environment in China. In this paper, we first measure the urban eco-efficiency of 281 prefecture-level cities in China during 2006–2013 using the super-efficiency data envelopment analysis (SEDEA) model. We then propose a new comprehensive index system to assess urbanization. Finally, we quantitatively explore the relationship between urbanization and urban eco-efficiency based on a spatial econometric analysis. The results showed that China's average urban eco-efficiency and comprehensive level of urbanization of 281 prefecture-level cities had shown increase during 2006–2013. However, distinct spatial disparities exist among different cities. China's urbanization has significant characteristics of spatial agglomeration and spatial convergence during 2006–2013, with a high-to-low spatial distribution from eastern China to western China. Spatial effects play an important role in the changes of urban eco-efficiency in China through spatial spillover effects and regional replication and competition. Evidence from spatial econometric analysis reveals that an N-shaped relationship exists between urbanization and urban eco-efficiency, indicating that with the improvement of urbanization, urban eco-efficiency first increases, then declines and then increases again. The improvement of the level of technology and the formulation of effective environmental policies will promote the increase in urban eco-efficiency. The results provide significant references for urban ecological management and sustainable urban transformation in China.

Tourism Eco-Efficiency Measurement, Characteristics, and Its Influence Factors in China

As an emerging field of eco-efficiency, tourism eco-efficiency is becoming an important way to measure the sustainable development of tourism. This study calculated and decomposed tourism CO2 emissions in China, explored its evolution and distribution characteristics by using the ratio method of tourism eco-efficiency, and analyzed the influencing factors by adopting a regression model. The results indicate that: (1) tourism CO2 emissions in China have increased significantly, their largest source is transportation. Its characteristics can be divided into carbon emission intensity factor, income structure factor, consumption level factor, and tourist scale factor through utilizing the Logarithmic Mean Divisia Index (LMDI) method, which also shows that the decisive factor of increased of tourism CO2 emissions has been the tourist scale factor. (2) Tourism eco-efficiency is marked by spectacular but unstable growth, which can be divided into three stages: inefficient stagnation stage, fluctuating growth stage, and efficient development stage. (3) Tourism eco-efficiency in China has shown that the remarkable high–high cluster and low–low cluster, and the 31 provinces, can be divided into four groups, namely: a high-efficiency high-growth group, a high-efficiency low-growth group, a low-efficiency high-growth group, and a low-efficiency low-growth group. (4) The main influencing factors of tourism eco-efficiency are the scale effect, the structural effect, the technical effect, and the environmental regulation. Since these four factors have different impacts on the tourism eco-efficiency of different groups according to panel data regression, more effective policies should be adopted for the improvement of tourism eco-efficiency in China. Finally, the significances and deficiencies of this study are discussed.

Industrial eco-efficiency in China: A provincial quantification using three-stage data envelopment analysis

The coordinated development of industrialization and the ecological environment is vital to achieve ecological civilization in China. Integratively considering the economy, energy and resources, and environment, this study aims to measure the industrial eco-efficiency of 30 provinces (autonomous regions and municipalities) in China between 2005 and 2013. A three-stage data envelopment analysis (DEA) modeling approach is adopted to eliminate interference of the external environment and statistical noise with industrial eco-efficiency measurement. The results show that regional industrial eco-efficiency in China is affected by the factors of the environmental regulation, technological innovation, level of economic development and industrial structure. After eliminating the impacts of external environment and statistical noise, China's national average industrial eco-efficiency declines by 30%. Between 2005 and 2013, the industrial eco-efficiency of the 30 provinces increases but at different rates of growth. The variation of overall regional industrial eco-efficiency is primarily caused by scale efficiency. Furthermore, all the 30 provinces are classified into four groups to interpret the causes of variation and differences of regional industrial eco-efficiency. In general, the management and technology level and the economy of scale of industries should be improved simultaneously, even though specific opportunities for industrial eco-efficiency improvement vary across provinces in China.

Assessing regional eco-efficiency from the perspective of resource, environmental and economic performance in China: A bootstrapping approach in global data envelopment analysis

Eco-efficiency has been receiving increasing attention across the world. This paper proposes an extended data envelopment analysis model, which combines global benchmark technology, directional distance function and a bootstrapping approach to investigate the dynamic trends of regional eco-efficiency in China from 2003 to 2014. Moreover, a developed slacks-based measure is utilized to decompose the performance fluctuations into resource, environmental and economic efficiency. Then, the key factors responsible for the changes in eco-efficiency are explored using the global Malmquist–Luenberger index. The empirical results demonstrate an upward trend of eco-efficiency in China. During the study period this trend was high in eastern and northern areas but low in northwestern areas. However, it should be noted that some eco-efficient regions still consume much land, water and energy and emit much environmental pollutants in absolute terms. The whole of China performs well on the economic front, while resource and environmental performances are not encouraging, particularly on environmental efficiency. The eastern and northern regions have experienced the greatest advances in both resource and environmental efficiency, while the undeveloped areas have not shown much progress, which further widens the gaps between developed areas and undeveloped areas. The decomposition of productivity growth indicates that technical progress is the decisive factor in promoting China's eco-efficiency, while decreasing management level is the major obstacle hampering the improvement in eco-efficiency.

Study of spatial patterns and spatial effects of energy eco-efficiency in China

Energy eco-efficiency is a concept integrating ecological and economic benefits arising from energy utilization and serves as a measure of efficiency in the energy–environment–economy system. Using the slacks-based measure (SBM) model considering undesirable output, this study first measures the energy eco-efficiency of provinces in China from 1997 to 2012. It then analyzes the spatial distribution and evolution of energy eco-efficiency from three aspects: scale, intensity, and grain of spatial patterns. Finally, it examines the spatial spillover effects and influencing factors of energy eco-efficiency in different provinces by means of a spatial econometric model. The following conclusions are drawn: (1) The overall energy eco-efficiency is relatively low in China, with energy-inefficient regions accounting for about 40%. Guangdong, Hainan and Fujian provinces enjoy the highest energy eco-efficiency, while Ningxia, Gansu, Qinghai, and Xinjiang are representative regions with low efficiency. Thus, the pattern of evolution of China’s overall energy eco-efficiency is U-shaped. Among local regions, four main patterns of evolution are found: increasing, fluctuating, mutating, and leveling. (2) At the provincial level, China’s energy eco-efficiency features significant spatial agglomeration both globally and locally. High–high agglomeration occurs mainly in the eastern and southern coastal regions and low–low agglomeration in the northwestern region and the middle reaches of the Yellow River. Changes in spatial patterns have occurred mainly in areas with high–low and low–high agglomeration, with the most remarkable change taking place in the Beijing–Tianjin–Hebei region. (3) There exist significant spatial effects of energy eco-efficiency among provinces in China. For the energy eco-efficiency of a given region, spatial spillovers from adjacent regions outweigh the influence of errors in adjacent regions. Industrial structure has the greatest influence on energy eco-efficiency.

An anatomy of China’s eco-efficiency gains: the role of FDI

This paper quantifies the role of FDI in the remarkable fivefold gains in eco-efficiency in China’s manufacturing during the period 1995–2006. We refine the conventional index decomposition method and apply it to China’s emission. We find that (i) foreign-invested enterprises (FIEs) have shifted production toward cleaner industries; (ii) the better abatement technique of FIEs explains 23% of the eco-efficiency gains; and (iii) another 69% of the eco-efficiency gains come from by progress in domestic firms’ abatement technique, which is associated with forward environmental spillovers from FIEs. Findings (ii) and (iii) lend support to the so-called Pollution Halo Hypothesis.