Efficiency In China Research Articles

Digital finance, government intervention, and carbon emission efficiency in China.

In accordance with the "dual carbon" objective, China is required to effectively pursue economic expansion and environmental preservation while concurrently enhancing carbon emission efficiency (CEE). This study examines the influence of digital finance on CEE and evaluates the moderating effect of government intervention. The analysis uses panel data collected from 282 cities in China at the prefecture level and above, spanning the period from 2011 to 2021. The findings indicate the following: (1) CEE in China is relatively low, and there are notable regional disparities. Specifically, there is a discernible downward trend in CEE throughout the eastern, central, and western areas. (2) In general, the implementation of digital finance has the potential to enhance the efficiency of carbon emissions. The observed effect is significant in the eastern and central regions but not in the western region. (3) Government subsidies have the potential to amplify digital finance's impact on CEE in the eastern region. Conversely, in the central and western regions, its influence can be increased by environmental regulations. Based on these findings, this study presents recommendations for advancing digital finance, enhancing the targeting and assessment of government subsidies, refining environmental regulations, and encouraging the adoption of green technologies.

Spatial pattern and driving factors of synergistic governance efficiency in pollution reduction and carbon reduction in Chinese cities

This paper is based on the construction of the evaluation system of urban pollution reduction and carbon reduction synergistic governance efficiency indicators. Firstly, we used the NDDF model to measure the efficiency of urban pollution reduction and carbon reduction synergistic governance. We then used the ArcGIS technology and spatial autocorrelation method to explore its spatial distribution pattern, and the spatial econometric model is used to explore its driving factors. The results show that from 2006 to 2020, the synergistic governance efficiency of Chinese cities in terms of pollution reduction and carbon reduction is in a state of continuous improvement, with an increase of 38.07 per cent in 2020 compared with 2006, and overall the synergistic governance efficiency of cities in terms of pollution reduction and carbon reduction shows a pattern of development in which the east is high and the west is low, but there is a tendency for the gap to narrow from one year to the next. There is a positive spatial aggregation of urban pollution reduction and carbon synergistic governance efficiency, which is further shown by the Lisa aggregation diagram that the spatial aggregation of urban pollution reduction and carbon synergistic governance efficiency in China is characterized by urban agglomerations, with the high and high aggregation zones being concentrated in the central and eastern urban agglomerations, such as the urban agglomerations of the middle reaches of the Yangtze River and Guangdong-Fujian-Zhejiang, and the low and low aggregation zones being concentrated in the western urban agglomerations, such as the Lanzhou-Western urban agglomerations and the Guanzhong Plain urban agglomerations. The results of the SDM model indicate that the efficiency of urban pollution reduction and carbon synergistic governance can significantly promote the process of pollution reduction and carbon synergistic governance in neighboring areas. The six drivers, namely, industrial structure, economic development level, innovation level, urbanization rate, population size and foreign direct investment, all have a significant impact on the efficiency of urban pollution reduction and carbon synergistic governance in a local area. The spatial spillover effects of the remaining variables, except for urbanization rate, on the efficiency of urban pollution reduction and carbon synergistic governance are significantly negative. Based on this, corresponding countermeasures are proposed to improve the synergistic governance of urban pollution reduction and carbon reduction.

Does multi-goal policy affect agricultural land efficiency? A quasi-natural experiment based on the natural resource conservation and intensification pilot scheme

With decision-making objects gradually expanding from a single sector to all sectors, it is necessary to clarify the differential impact of the multi-goal land use policy (MGLUP) on subsector land. We defined and measured the agricultural land efficiency in China, and then analyzed the policy effects of the natural resource conservation and intensification pilot scheme on land efficiency based on a quasi-natural experiment. The results showed that (1) agricultural land efficiency presents a spatial replacement process of high-value units and low-value units, and some urban areas with values below 0.8 still have significant room for improvement. (2) The MGLUP reduced agricultural land efficiency by 1% under causal inference analysis. (3) The robustness test results showed that the MGLUP reduced the physical and monetized outputs by 4–15%.

Analysis of spatial correlation characteristics and key factors of regional environmental governance efficiency in China

Analysis of spatial correlation characteristics and key factors of regional environmental governance efficiency in China

Investigating the Effects of Environmental Regulation on Industrial Ecological Efficiency in China Using a Panel Smooth Transition Regression Model

Environmental regulation (ER) is a crucial tool used by governments to intervene in the environmental practices of enterprises, and it is recognized as a significant avenue to impact industrial ecological efficiency (IEE). This study uses the superefficiency SBM model to determine provincial IEE scores. Then, a panel smooth transition regression (PSTR) model is used to explore the effects of ER on IEE transition at different stages of economic growth. The main findings are as follows: Firstly, China’s IEE showed an overall upward trend, with small increments over the past two decades. Regions with higher IEE were mainly located in the east, while those with lower IEE were mostly in the less economically developed west. Secondly, the PSTR model revealed that ER had varying impacts on IEE at different stages of economic growth. ER positively influenced IEE in the early stages of economic growth. However, after surpassing the threshold of economic growth, ER began to contribute to reducing IEE scores. In addition to these findings, this study proposes a series of policy recommendations to strengthen IEE.

An empirical study on the measurement and influencing factors of carbon emission efficiency in China's transportation industry

<p>The severe climate problem has forced the Chinese government to put forward the goal of "carbon peak" and "carbon neutrality", and the transportation industry is a key area of carbon emission reduction. Based on this background, this paper introduces the BCC model and the Malmquist-Luenberger index model to measure the carbon emission efficiency of China's provincial transportation industry from the static and dynamic perspectives from 2014 to 2020. At the same time, the Tobit model is used to estimate the influencing factors of carbon emission efficiency. The results show that: (1) The overall transportation carbon emission efficiency level is low. The comprehensive efficiency of 30 provinces is at [0.6634,0.7154], which needs to be improved urgently. (2) The carbon emission efficiency of transportation is in a growing trend, and the ML index is 1.142, which is significantly higher than 1.0. In addition, the mean value of technical efficiency is 1.015, and the mean value of technological progress efficiency is 1.125. The two factors jointly affect comprehensive efficiency. (3) The carbon emission efficiency of different regions is heterogeneous. The carbon emission efficiency of East China and North China is better than that of Northeast China and South China, while the carbon emission efficiency of Northwest China and Southwest China is at the middle level in China. (4) External environmental factors, such as regional GDP, resident population and consumption level, have a significant impact on the carbon emission efficiency of transportation.</p>

Coupling coordination evaluation and driving path of digital economy and carbon emission efficiency in China: A fuzzy-set qualitative comparative analysis based on 30 provinces.

Enhancing the level of coupling coordination between the digital economy (DIE) and carbon emission efficiency (CEE) is not only an inevitable choice for achieving the goals of energy conservation and emission reduction and promoting green development in China, but also a key path to implementing China's "Double Carbon" strategy. Based on the relevant statistical data of 30 provincial-level regions in China from the period covering 2011 to 2019, this paper empirically analyzed the coupling coordination between the DIE and CEE and its influencing factors. In this study, an improved coupling coordination degree (CCD) model was used to evaluate the degree of the coupling and coordinated development of the DIE and CEE in provincial regions of China. Finally, based on the Technology-Organization-Environment (TOE) framework, a fuzzy-set qualitative comparative analysis (fsQCA) method was employed to identify the realization path of the coupling and coordinated development of the DIE and CEE from the perspective of configuration. The results demonstrated that the coupling coordination between the DIE and CCE in China demonstrated a gradual upward trend, and exhibited regional differences, showing a decreasing trend of east > middle > west. Regarding the influencing factors, no single influencing factor could act as a necessary condition for the high CCD, the coupling and coordinated development of the DIE and CEE is a multifactorial synergy. There were five paths for the high degree of coupling coordination between the DIE and CEE, which were divided into three types: organization-environment-led type, environment-led type, and technology-organization-led type. Furthermore, technological innovation level and industrial structure could substitute for one another in some conditions, and environmental regulation and economic development level were synchronized. These conclusions provide a theoretical basis for countries to formulate policies to promote the coupling and coordinated development of their DIE and CEE.

Government Employment Target Pressure and Labor Investment Efficiency in China: A Political Economy Perspective

Government Employment Target Pressure and Labor Investment Efficiency in China: A Political Economy Perspective

Spatial and temporal evolution of urban carbon emission efficiency in China.

Improving carbon emission efficiency is crucial for achieving carbon peak and carbon neutrality. This paper analyzes the carbon emission efficiency of Chinese cities using panel data from 275 prefecture-level cities between 2006 and 2020. The super-efficiency SBM (undesirable slacks-based measurement) model of undesired output, combined with kernel density estimation and exploratory data analysis, is employed. This study finds, firstly, from 2006 to 2020, the average efficiency of carbon emissions in Chinese cities declined from 0.53 to 0.48, indicating a downward trend. Secondly, from a temporal perspective, the level of dispersion in urban carbon emission efficiency has become increasingly distinct over time, coupled with a decrease in polarization. Thirdly, in terms of spatial analysis, urban carbon emission efficiency in China shows a positive correlation in a global context. In terms of local spatial correlation, it primarily exhibits high-high and low-low clusters, with a few instances of low-high and high-low clusters. Finally, based on the research findings, this paper proposes suggestions to improve urban carbon emission efficiency.

Impact of aging-related consumption trend on carbon emission efficiency in China: mediation effect model based on industrial structure adjustment

With the deepening of China’s aging process, changes in the age structure of the population affect the industrial structure and consumption structure in different ways and have a knock-on effect on the whole economic system. Therefore, aging is one of the objective factors affecting future carbon emissions in China. This study analyzes the impact mechanism of aging-related consumption trend on carbon emission efficiency (CEE) based on panel data of 30 Chinese provinces from 2000 to 2019. The results show that the aging-related consumption trend is conducive to the improvement of regional CEE, and the mediation transmission mechanism of industrial structure adjustment is obvious, with a coefficient of 0.1496. The core industry closely linked to the demand for aging-related consumption is consumer services. The promotion of the consumption demand of the aging in the eastern region on the CEE and the transmission stimulation of the industrial structure adjustment are the most obvious. The mediation effect in the central and western regions is relatively weak, and the aging-related consumption demand has not formed a positive interaction with the aging industry. Therefore, improving the market construction of products and services for the aging is beneficial to achieve a virtuous cycle of aging-related consumption upgrading and carbon emission efficiency. This research can provide insights for China to promote industrial structure transformation within the aging trend and also help China meet its carbon neutrality target on schedule.

Green Total Factor Efficiency in Vegetable Production: A Comprehensive Ecological Analysis of China’s Practices

This study undertakes a comprehensive analysis of vegetable production efficiency in China using input–output data from 30 provinces spanning 2011 to 2017. By incorporating environmental pollution costs as undesirable outputs alongside vegetable output value, we employ Data Envelopment Analysis (DEA) with the Banker, Charnes, and Cooper (BCC) model and the Malmquist index model. Our assessment reveals both annual and inter-period efficiency changes. The findings highlight a modest overall efficiency in China’s vegetable production and significant regional disparities. Technical progress emerges as a pivotal determinant of total factor productivity (TFP). Recognizing these dynamics, we propose policy recommendations that prioritize technical innovation, sustainable practices, rural infrastructure enhancement, and specialized cultivation methods. Implementing these recommendations could bolster China’s position in international trade negotiations due to increased exports and potentially drive broader environmental policy reforms. As vegetable production becomes more efficient and sustainable, there might be a shift in labor needs, potentially leading to migration patterns or changes in employment structures. These insights contribute to the sustainable development of China’s vegetable industry, offering a broader understanding of the dynamics of agricultural efficiency in the context of environmental sustainability.

Spatio-temporal evolution and convergence characteristics of urban digitalization efficiency in China: A perspective on regional coordinated development

ABSTRACT Urban digitalization is a key driver of regional coordinated development in modern times due to its ubiquitous and significant impact on our production, way of life, and ecosystem. Most of the current research has focused on the economic and social impacts of digitalization, while little work has been done on the efficiency of digitalization. This study investigates urban digitalization efficiency (UDE) employing the super-efficient EBM model from a viewpoint of regional coordinated development. The dynamic evolution of UDE is revealed by the Markov chain method. The convergence properties of UDE in each region are examined using the β convergence models. The findings indicate that: (1) The UDE of each city and each of the eight integrated economic zones has increased to some extent. (2) The UDE is relatively likely to remain stable, with a greater probability of shifting to a neighbouring type than to a non-neighbouring type. (3) While UDE exhibits absolute and conditional β-convergence across all areas, the causes affecting UDE convergence in various economic zones vary. The results presented in this study can help clarify the laws and characteristics of UDE and serve as a reference for developing countries to promote coordinated regional development through urban digitalization.

How do R&D capital market distortions affect innovation efficiency in China? Some evidence about spatial interaction and spillover effects

Improving innovation efficiency (IE) and refining capital market distortions are important considerations for promoting national innovation strategies. This study uses the dynamic spatial Durbin model and mechanism tests to explore the direct impacts, spatial effects, and influencing mechanisms of R&D capital market distortions on IE based on Chinese provincial panel data from 2009 to 2019. The main results can be summarized as follows. First, China’s IE is characterized by temporal inertia and spatial agglomeration. In both the spatial and temporal dimensions, IE in neighboring areas in the previous period can inhibit local IE in the current period. Second, R&D capital market distortions have a weakening effect on IE in the short- and long-term. Third, R&D capital market distortions have significant spatial interaction and persistent positive spatial spillover effects on IE. Finally, R&D capital mismatch and technology lock-in effects are essential mechanisms related to R&D capital market distortions that can inhibit IE. Based on these results, policy recommendations have been proposed to improve IE.

Agricultural tridimension pollution emission efficiency in China: An evaluation system and influencing factors

We innovated traditional one-sided agricultural carbon emission efficiency research, comprehensively explored the agricultural tridimension pollution emission efficiency (ATPEE), constructed an ATPEE evaluation system considering technological heterogeneity characteristics based on the meta-frontier nonradial directional distance function (NDDF) model in a total-factor framework, evaluated the ATPEE in 30 mainland China provinces from 1997 to 2021 for the first time, and empirically studied the factors influencing the ATPEE in China with the Tobit model. The results showed the following: (1) ATPEE improvement potentials of 75.16 % and 50.88 % occur under the meta and group frontiers, respectively. (2) The eastern region represents the potential optimal agricultural tridimension pollution emission technology, while the central and western regions exhibit a large gap with the national potential optimal technology level. (3) The ATPEE loss in the eastern and western regions mainly results from management inefficiency, while that in the central region largely results from technology gap inefficiency. (4) The effects of the industrialization rate, urban–rural income gap, agricultural production structure, financial support for agriculture, natural conditions and effective irrigation rate on the ATPEE in the different regions vary.

Evaluation and spatial convergence of carbon emission reduction efficiency in China's power industry: Based on a three-stage DEA model with game cross-efficiency

Reducing carbon emissions is essential for achieving sustainable development in China. In this study, we developed a framework for measuring carbon emission reduction considering both thermal power and clean energy generation perspectives. Subsequently, we constructed a three-stage data envelopment analysis (DEA) model with game cross-efficiency to eliminate the influence of external environmental factors, random factors, and regional competition. Thereafter, we calculated the carbon emission reduction efficiencies (CEREs) of the power industries of 30 provinces in China from 2010 to 2020. Based on this, we conducted temporal and spatial analyses of the carbon emission reduction amount (CERA), evaluated CERE, compared different DEA models, and assessed spatial convergence effects. The evaluation results of CERE across 30 provinces, cities, and autonomous regions in China showed that: (1) although China's CERA increased, substantial regional differences exist in the carbon emission reduction structure. (2) The overall average CERE ranged from 0.485 to 0.737. Since 2016, the highest CERE values have been observed in southwest China, followed by the eastern coastal and central regions, while the northwestern region experienced notable fluctuations. (3) The three-stage DEA model with game cross-efficiency, which eliminates the influence of competition and external environmental factors, can be used to accurately measure CERE. (4) CERE has a spatial convergence effect on China's power industry and is promoted by energy structure, upgrading of industrial structure and government interventions. These findings provide important insights for optimizing the carbon emissions reduction structure and improving CERE.

Influential Effect and Mechanism of Digital Finance on Urban Land Use Efficiency in China

With the acceleration of urbanization, the carrying capacity of urban land resources is increasingly being challenged. Thus, urban land use efficiency (ULUE) has been a crucial issue in sustainable development, and digital finance (DF) has been thought to be an effective solution for solving this dilemma. Based on panel data from 283 cities in China spanning from 2011 to 2020, this study first utilized the super-efficiency SBM model to assess ULUE across China. Then, the panel Tobit model was employed to empirically examine the overall impact of DF on ULUE, while the intermediary effect model was utilized to analyze the indirect impact of DF on ULUE. Additionally, the threshold effect model was employed to investigate the non-linear characteristics of the impact of DF on ULUE. The findings indicate that: (1) DF can enhance ULUE, with the dimension of application depth of DF exerting the most significant impact, followed by the dimensions of coverage breadth and digitization degree of DF; (2) DF can boost ULUE by promoting industrial structure upgrading (ISU); (3) the promotional effect of DF on ULUE exhibits regional variations, with a stronger impact observed in the western region and provincial capital cities, but weaker effects noted in the eastern and central regions as well as non-provincial capital cities; (4) with the improvement of economic development and DF, the impact of DF on ULUE exhibits a slightly increasing nonlinear trend. The research findings presented in this paper offer valuable insights for enhancing ULUE in emerging economies.

The Synergy of Water Resource Agglomeration and Innovative Conservation Technologies on Provincial and Regional Water Usage Efficiency in China: A Super SBM-DEA Approach

China is currently facing the significant task of effectively managing its water resources to satisfy the rising needs while grappling with the growing worries of water shortage. In this context, it becomes crucial to comprehend the importance of resource agglomeration and technological adoption. Thus, this research examines the relationship between water resource agglomeration and the adoption of innovative conservation technologies in enhancing water usage efficiency at provincial and regional levels in China (2006–2020). In the first stage, the study utilizes a super SBM-Data Envelopment Analysis (DEA) methodology to evaluate the water usage efficiency of China’s provinces and regions. In the second stage, we find the dynamic nexuses between water resources, water technologies (recycling, sprinkler irrigation) and water usage efficiency by applying a systematic econometric approach. SBM-DEA analysis revealed that Beijing (1.08), Shaanxi (1.01), Shanghai (1.23) and Tianjin (1.01) remained the higher efficient over the years. Six provinces (Guangdong, Shandong, Jiangsu, Inner Mongolia, Hebei, and Zhejiang) are in the middle ranges (0.55–0.83). In contrast, nineteen provinces have the lowest water usage efficiency (0.21–049). Qinghai and Ningxia are on the lowest rank (0.21) and (0.22), respectively. The findings recommended that the water resources impact is negative. In comparison, the impact of water-saving mechanisms on the efficiency of water usage seems to be positive, as recycling technology significantly enhances the water usage efficiency in China’s province. The study found that GDP growth has a negative impact on water usage efficiency in the early stages of economic development. Still, as economies mature, this negative impact diminishes, indicating a tendency to allocate more resources to water conservation and efficiency. Water recycling technology, the modernization of irrigation methods, and water resource management can enhance water efficiency.

Calculation of carbon emission efficiency in China and analysis of influencing factors.

Carbon emissions have risen in line with China's economic expansion. The key to sustainable development is finding a way to strike a balance between economic expansion and environmental protection, so improving carbon emission efficiency is vital. This paper uses provincial data from 2010 to 2020 to account for total carbon emissions using the emission factor method and obtains carbon emission efficiency data on this basis. A dynamic spatial Durbin model is then used to empirically test the possible influencing factors. The results show that, firstly, the growth rate of total carbon emissions is generally in line with the growth rate of GDP, indicating that there is no 'decoupling' in the economic system. Second, regional carbon emissions and carbon emission efficiency are not necessarily related. Thirdly, there is a clear spatial effect on carbon emission efficiency. The eastern region has the highest carbon emission efficiency, the western region has the lowest, and the northeastern and central regions have little difference in carbon emission efficiency. Further spatial and temporal migration analysis reveals that five provinces have made the migration between 2010 and 2020. Fourthly, in the short term, the direct and indirect effects of the factors affecting carbon emission efficiency are insignificant, but in the long term, most of the factors have significant direct and indirect effects on carbon emission efficiency. Finally, based on the above research findings, this paper makes policy recommendations.

Developing a low-carbon hybrid of ammonia fuel cell and internal combustion engine for carbon neutrality

With global warming and an increase in extreme weather, reducing carbon emissions in response to climate change has become a global consensus. Compared with traditional fuel vehicles, hybrid vehicles have the benefits of energy savings, low grid-load, and low emissions. The hybrid vehicles use the internal combustion engine and lithium-ion batteries as the hybrid power source to achieve the best match between the engine and the motor. However, the current commercial hybrid vehicle still has such defects as high dependence on fossil fuels, high carbon emissions, poor safety, etc. As such, it is necessary to explore and develop the next generation low-carbon hybrid vehicles. Herein, we propose a new-type hybrid of ammonia fuel cell and internal combustion engine with high-energy conversion efficiency and low-carbon emissions. Considering the advantages of low-carbon emissions, high mileage, fast refueling, low-cost, high-energy conversion efficiency, and high safety, a green low-carbon concept of the ammonia fuel cell-internal combustion engine hybrid vehicle (AFC-ICE HV) is proposed. This will help improve the scale and efficiency of China's green energy conversion, establish a green, low-carbon and sustainable economic system, provide new impetus for tackling climate change and environmental protection recovery, and help China and the world to achieve the Carbon Peak and Carbon Neutrality goal.

Spatiotemporal dynamics and anthropogenic drivers of geological hazard prevention efficiency in China

Rapid socio-economic development and the large-scale anthropogenic activities aggravated the risk of geological hazards, endangering human life and property safety. Understanding the geological hazard prevention efficiency (GHPE) and driving factors is important for promoting the sustainable development, there are few quantitative studies have investigated the GHPE and anthropogenic drivers in China. This study employed the super-efficiency slack based measure-data envelopment analysis (SBM–DEA) model with undesirable outputs and Malmquist–Luenberger (ML) index to investigate the spatiotemporal distribution of GHPE from static and dynamic perspectives. Additionally, the geographically and temporally weighted regression (GTWR) model was utilized to identify the spatial heterogeneity of anthropogenic drivers on GHPE in China. Results showed that GHPE showed a spatial difference of eastern > central > western China, with only 38.71 % provinces were in an optimal prevention condition of the GHPE. An average annual growth rate of GHPE was 5.8 % in China, with a distribution pattern characterized by central > eastern > western China. Furthermore, the spatial heterogeneity of anthropogenic drivers affecting GHPE varied greatly across different regions. Our findings highlighted investment in environmental protection had obviously positive effects on the GHPE, whereas urban population density had markedly inhibited effects in most provinces. Low GHPE was more prevalent in regions with relatively backward economic and technological levels. Effective measures were proposed to promote regional high-quality and sustainable development.