Search Results (479)

The research on the effectiveness and mechanism of environmental policy is the focus of ecological policy research. This paper constructs panel data and studies the Eco-efficiency (EE) and influence mechanism of Central Environmental Supervision (CES). The Super Slacks-Based Measure (Super-SBM) model is adopted to measure EE. Difference-in-Differences (DID) methods were used for regression analysis. (1) Research shows that CES can significantly improve EE by 5.11%. A parallel trend test shows that DID is valid. (2) Endogeneity test does not find reverse causality, and Propensity Score Matching and Difference-in-Differences (PSM-DID) test does not find sample selection bias. Variable substitution test shows that the conclusions remain robust. The time bandwidth test finds that the longer CES is implemented, the better the effect. (3) CES can promote EE through industrial upgrading, technological innovation, and promoting green consumption, with relative contributions of 17.52%, 13.78%, and 14.57% respectively. (4) Heterogeneity analysis shows that CES has a significant impact on the EE of the eastern, central, and western cities, with insignificant differences, and the impact is stronger in the core cities. CES only has a significant impact on large- and medium-sized cities with a population of 3 to 10 million. Full article

Against the backdrop of China’s “dual carbon” goals and mounting fiscal pressures at the local level, local governments face a dilemma between offering tax incentives and reducing industrial carbon emissions. This study uses data from 30 Chinese provinces between 2000 and 2022. It employs the Dagum Gini coefficient to characterize regional disparities and spatial heterogeneity in industrial carbon emissions, utilizes the Super-Slack-Based Measure (SBM) model and kernel density estimation to estimate the spatiotemporal evolution of tax competition, constructs a Spatial Durbin Model (SDM) to examine its direct effects and spatial spillover effects, and conducts robustness tests using four different methods. The study finds that: (1) tax competition has a significant positive direct effect on local industrial carbon emissions and generates positive spatial spillovers; bottom-up tax competition exacerbates overall regional carbon emissions; (2) control variables such as economic development level and energy intensity all exhibit significant spatial spillover characteristics; and (3) the carbon emission effects of tax competition exhibit regional heterogeneity, with positive spatial spillovers in the eastern region and predominantly negative spillovers in the central and western regions. From a spatial competition perspective, this paper reveals the underlying mechanisms and regional differences between these two factors. The findings provide empirical insights and policy references to optimize the competitive landscape among local governments, improve the regional collaborative green tax system, promote low-carbon industrial transformation, and achieve the “dual carbon” goals. Full article

Food security and sustainable agriculture, as components of the Zero Hunger goal (SDG 2) under sustainable development, have garnered significant attention from countries worldwide. Enhancing agricultural green total factor productivity (AGTFP) contributes to the achievement of sustainable development. Agricultural socialized services serve as a key means of boosting AGTFP and realizing sustainable development. Based on data from 1534 counties in China from 2007 to 2023, this study employed methods such as the super-efficiency SBM-GML index, a two-way fixed-effects model, and a moderation model to examine the impact of agricultural socialized services on AGTFP, with a particular focus on the moderating role of land scale management. The findings indicate a nonlinear, inverted U-shaped correlation between agricultural socialized services and AGTFP, driven by both the “quantity” and “quality” aspects of these services. Simultaneously, land scale management significantly moderates this relationship. Specifically, the curve’s inflection point shifts leftward and flattens as land scale management intensifies. Furthermore, agricultural socialized services exhibit greater effectiveness in improving AGTFP in major grain-production areas and low regional fiscal pressure regions. These findings provide valuable insights into sustainable agriculture development in China, offering guidance for other developing nations in similar circumstances. Full article

Amid the rapid growth of the aviation sector, carbon reduction presents a significant challenge for airlines. This study investigates the structural characteristics and dynamic evolution of carbon emission efficiency among 18 global airlines from 2015 to 2021 using a two-stage super-efficient slack-based measure model (SBM) and an SBM-based Hicks–Moorsteen productivity index, incorporating absolute β-convergence tests. Key findings include the following: (1) The overall mean static efficiency of the airlines ranged from 0.225 (American Airlines) to 0.662 (Singapore Airlines), with an industry-wide average of 0.44. (2) Dynamic productivity change also exhibited significant variation: the overall mean superefficient SBM-based Hicks–Moorsteen (HM) productivity index was 0.962, but it dropped sharply to 0.526 in 2019–2020 due to the COVID-19 pandemic. After 2020, several airlines demonstrated significant recovery, with Emirates and Singapore Airlines achieving dynamic productivity change indices above 1.5. (3) In 16 out of 18 airlines, operational efficiency exceeded production efficiency, highlighting the importance of technological improvements in production. (4) Limited technological progress was identified as the main factor behind efficiency declines, while absolute β-convergence indicated that inefficient airlines are gradually catching up with efficient peers. These findings provide insights for airlines and policymakers in designing targeted carbon reduction strategies and promoting sustainable aviation development. The empirical scope of this study is limited to 18 major global airlines over the period 2015–2021. Due to data availability constraints, the sample does not fully cover all regions or low-cost carriers. The Hicks–Moorsteen index and its EC/TC components are used for interpretative and heuristic purposes only and should not be understood as a strict mathematical decomposition within the two-stage network SBM framework. Full article

Balancing food security with ecological sustainability is a critical challenge for global agricultural development. This research explores how China’s “three rights separation” reform influences the ecological efficiency of cultivated land use. This institutional innovation separates ownership, contract, and management rights to improve land resource allocation. Utilizing panel data from China spanning from 2005 to 2023, this study employs a super-efficiency SBM model to evaluate ecological efficiency, a continuous difference-in-differences (DID) framework to identify the causal effects of the reform, and a mediation effect model to explore the underlying transmission mechanisms. The results show that the “three rights separation” reform significantly improves the ecological efficiency of cultivated land use, with a regression coefficient of 0.632 that is statistically significant at the 1% level. The findings remain robust across multiple robustness tests. Mechanism analysis reveals distinct hierarchical transmission pathways through the promotion of non-agricultural labor transfer, the optimization of planting structure, and the advancement of agricultural technological progress. Among these pathways, agricultural technological progress emerges as the primary driver. Furthermore, heterogeneity analysis indicates that the positive impact of the reform is more pronounced in non-major grain-producing regions, as well as areas characterized by higher levels of mechanization and land transfer. These results suggest that further deepening land tenure reform is essential, with careful consideration of regional disparities and the mediating role of labor factors, land resource allocation, and technological progress. Full article

Amid the coordinated advancement of the digital economy and rural revitalization, Digital Rural Construction (DRC) has increasingly emerged as a critical catalyst for agricultural modernization and sustainable development. Faced with dual challenges of land resource constraints and agricultural green transformation, improving the Agricultural Land Green Utilization Efficiency (ALGUE) has become essential for achieving high-quality agricultural development. Based on panel data from 29 Chinese provinces from 2012 to 2023, this study employs the super-efficiency SBM model to quantify ALGUE. A comprehensive four-dimensional evaluation system—encompassing digital infrastructure, service capacity, human capital quality, and practical application—is constructed, and the entropy method is used to measure the level of digital rural construction. By applying two-way fixed effects models, mediation analysis, and heterogeneity tests, this study systematically examines the impact of digital rural construction on ALGUE and its underlying transmission pathways. The results demonstrate that: (1) Digital rural construction significantly enhances ALGUE, and this finding remains robust under multiple sensitivity checks. (2) Pronounced heterogeneity exists in two dimensions: the promotion effect is stronger in economically developed regions and in regions with higher agricultural mechanization intensity, while it is weaker in less developed and low-mechanization regions. (3) Mechanism analysis reveals that digital rural construction promotes ALGUE through two channels. The first involves accelerating the transition of the primary industry toward intelligent and high-value-added models, thereby optimizing resource allocation and reducing environmental pressure. The second operates by fostering regional economic growth in an inverted U-shaped nonlinear pattern that supports agricultural green transformation. By integrating DRC and ALGUE into a unified framework, this study identifies two mediating channels and reveals heterogeneity across economic development levels and agricultural structures. These findings provide empirical support and policy implications for digitally driven green agricultural development. Full article

This paper is based on data from 121 cities in China’s ecologically fragile regions from 2008 to 2022; it constructs an indicator system for the efficiency of pollution control and carbon reduction in agricultural practices. This system includes expenditures on agriculture, forestry, and water affairs, arable land area, agricultural laborers, total agricultural output value, agricultural carbon emissions, and agricultural non-point source pollution. It uses a super-efficiency SBM model that incorporates non-desirable outputs to measure the synergistic efficiency and analyzes its dynamic evolution using the Malmquist–Luenberger index to reveal the spatiotemporal characteristics of the synergistic efficiency. A Tobit model identifies the influence of factors, such as the level of rural economic development, crop planting structure, the strength of fiscal support for agriculture, rural education level, urbanization rate, and mechanization level on the synergistic efficiency. The results show that, from a temporal perspective, the average synergistic efficiency was only 0.58, significantly below the effective value of 1, indicating substantial room for overall improvement. Only 10 cities met the benchmark, with distinctly different reasons for compliance, while the remaining 111 cities remained inefficient. Regarding influencing factors, crop planting structure, the strength of fiscal support for agriculture, and urbanization rate significantly and positively drive efficiency; the level of rural economic development and mechanization level significantly inhibit efficiency, and rural education level shows no significant impact. These findings provide targeted policy recommendations for the synergy effect in ecologically fragile areas, as well as for low-carbon agricultural development. Full article

The sponge city pilot policy (SCP) is a green infrastructure initiative that integrates ecological stormwater management, land-use planning, and urban sustainability goals. This study employs the super-efficiency slack-based measure (SBM) model to evaluate the green total factor productivity (GFP) of 278 prefecture-level and above cities in China from 2010 to 2022. It then applies a difference-in-differences (DID) model to identify the causal effect of the SCP on urban GFP while further examining transmission mechanisms and heterogeneous policy effects. The empirical findings show that: (1) the SCP significantly enhances urban GFP, with pilot cities exhibiting an average increase of approximately 6.08% relative to non-pilot cities, indicating broader medium- to long-term ecological–economic co-benefits beyond the policy’s immediate hydrological objectives; (2) the policy effect is more pronounced in cities with stronger economic foundations, larger urban scales, greater environmental governance pressure, weaker resource dependence, and more favorable locational conditions; and (3) the SCP promotes industrial structure transformation (IST) and green technological innovation (GTI), which jointly mediate the relationship between ecological infrastructure and green productivity. Drawing on ecological modernization theory and structural change theory, this study explains how ecological infrastructure, as a techno-structural reform mechanism, can internalize environmental externalities, stimulate innovation, and facilitate sustainable urban transformation. These findings provide evidence that green infrastructure policies can generate both ecological and economic co-benefits, offering useful insights for climate-resilient and sustainable urban planning. Full article

Whether and how digital financial inclusion (DFI) is associated with ecological efficiency (EE) is a critical issue for the sustainable development of the Yangtze River Economic Belt (YREB). Based on panel data from 2011 to 2023, this study measures EE using the PCA-Super SBM model, and employs panel fixed-effects models and mediation models to systematically examine the association, mechanisms, and regional patterns of DFI with EE in the YREB. The findings are as follows: (1) DFI and EE exhibit notable spatiotemporal co-evolution characteristics, with the DFI index increasing nearly 14-fold and the EE level rising by approximately 21.5% over the study period. (2) DFI shows a statistically significant positive association with EE improvement; this finding remains robust after various robustness checks. (3) The association between DFI and EE is partially mediated through four pathways: capital allocation optimization, green technological innovation, industrial structure upgrading, and environmental regulation strengthening, among which green technological innovation is the most prominent mediating pathway. (4) Numerically, the association strength varies across functional zones, being higher in the ecological barrier zone (EBZ) and the coordinated development zone (CDZ) than in the high-quality development zone (HQDZ); however, differences in coefficients across zones are not statistically significant and should be interpreted cautiously. Based on these findings, this study proposes policy recommendations including establishing a DFI-EE linkage platform, implementing differentiated functional-zone strategies, and strengthening cross-basin collaborative governance, thereby providing a reference for the green transformation of the YREB. Full article

This study examines whether and under what conditions the digital economy (DGE) improves the green development efficiency of China’s tourism industry. Drawing on panel data for 30 Chinese provinces from 2012 to 2023, we develop a multidimensional index of the DGE that captures digital infrastructure, digital industrialization, and industrial digitalization. To evaluate tourism green development efficiency, we employ a non-radial, non-angular super-efficiency slacks-based measure (SBM) model that incorporates both desirable outputs and undesirable environmental externalities. From a theoretical perspective, we extend the Cobb–Douglas production framework by embedding DGE-induced technological progress, showing that digitalization can improve green efficiency through two complementary pathways: it expands expected output while reducing carbon intensity. Empirically, the baseline two-way fixed-effects results show that DGE significantly promotes tourism green development efficiency ($\beta$ = 0.0153, p < 0.05), and this result remains robust in instrumental-variable (IV) estimation ($\beta$ = 0.0383, p < 0.05). We further show that this relationship is conditioned by three important external conditions. First, environmental regulation strengthens the enabling effect of digitalization, consistent with a compliance-induced Porter effect. Second, tourism industry agglomeration enhances the benefits of digital transformation by deepening knowledge spillovers and network complementarities. Third, green finance relaxes financing constraints and creates more favorable conditions for digital investment. By integrating a formal theoretical model with panel-data evidence, this study provides a unified explanation of both the mechanism and the boundary conditions through which the DGE promotes tourism green development efficiency. Overall, the findings suggest that the DGE is an important driver of sustainable tourism development and offer useful policy implications for coordinated digital and green transformation. Full article

Against the backdrop of increasing resource and environmental constraints, improving the land use efficiency of state-owned agricultural land is of great significance for promoting sustainable agricultural development. This study measures the land use efficiency of state-owned agricultural land across 29 provinces in China based on data from the China State Farms Statistical Yearbook (2019–2023). The super-efficiency slack-based measure model (Super-SBM), incorporating both desirable and undesirable outputs, is employed, and global and local spatial autocorrelation methods are further applied to analyze the spatiotemporal evolution of land use efficiency. The results indicate the following: (1) from 2019 to 2023, the overall land use efficiency of state-owned agricultural land in China remained below or slightly above the efficiency frontier, exhibiting a fluctuating trend characterized by an initial increase followed by a decline; (2) significant regional disparities exist, with high-efficiency areas mainly concentrated in Northeast China and the eastern coastal regions, while low-efficiency areas are primarily distributed in western regions and parts of central China; (3) spatial autocorrelation analysis reveals that land use efficiency shows an increasingly pronounced spatial clustering pattern at the provincial scale. After 2022, high–high and low–low clustering became more evident, although a certain degree of spatial heterogeneity still persists overall. These findings provide empirical evidence for understanding the spatial differentiation and evolutionary patterns of the land use efficiency of state-owned agricultural land and offer useful insights for optimizing land resource allocation and management. Full article

To address the challenge of balancing economic growth with carbon emission reduction, improving regional Carbon Emission Efficiency (CEE) has emerged as a central pathway to achieving the “dual carbon” goals. While most existing studies focus on inter-regional CEE linkages through pairwise interaction networks, such approaches fall short in capturing the high-order mechanisms of multi-regional collaboration. This study integrates the Super-SBM model with a modified gravity model to construct a CEE correlation network across 30 provincial administrative regions in China from 2007 to 2023. To overcome the limitations of traditional pairwise networks, simplicial complex theory is introduced to establish a high-order topological representation framework. Furthermore, by applying the multiorder Laplacian to assess the synchronization stability of the network, a directed second-order degree swap strategy is proposed to optimize its high-order structure. The findings reveal that the CEE correlation network has evolved from a single-pole aggregation pattern toward a multi-center equilibrium. Provinces with high connectivity play a dominant role in both pairwise and triadic synergies, though their collaborative advantages are gradually diffusing to central and western regions. Notably, with only a limited number (approximately five) of second-order degree swaps among key node pairs, the network’s synchronization stability can be substantially improved. When first-order and second-order interaction strengths reach comparable levels (coupling strength ${\alpha }^{*}\approx 0.5$), the system achieves optimal resistance to external perturbations. This study highlights the pivotal role of high-order collaboration in shaping regional CEE linkages and offers a practical optimization pathway for structurally enhancing CEE through coordinated efforts in pursuit of the “dual carbon” goals. Full article

The rapid expansion of China’s livestock husbandry has boosted the supply of meat, eggs, and dairy products, while concurrently giving rise to environmental pollution issues. Research on the effects of various environmental regulations on the green total factor productivity (GTFP) of the livestock sector and their underlying mechanisms is still lacking, despite the Chinese government’s implementation of corresponding environmental regulatory policies to address this practical challenge. As a key instrument for fostering green economic transformation, examining the relationship between environmental regulation and the green total factor productivity (GTFP) of animal husbandry is crucial for the sector’s sustainable development. In order to estimate the GTFP of China’s livestock sector for the years 2010–2022, this study uses the super-slack-based measure (Super-SBM) methodology. It conducts an empirical analysis to examine the mechanisms through which different environmental regulations influence livestock GTFP, alongside an investigation of regional heterogeneity. The results show that different environmental regulations have different effects on animal husbandry GTFP, with notable regional differences. Specifically, incentive-based environmental regulations enhance livestock GTFP by facilitating technological innovation; however, the level of regional economic development negatively moderates the association between incentive-based environmental regulations and livestock GTFP. The findings confirm that incentive-based environmental regulations are successful in encouraging livestock GTFP through technical innovation. They further emphasize that regions should formulate context-specific environmental regulatory policies to balance environmental protection and industrial development, thereby supporting the green and sustainable growth of China’s livestock industry. Full article

Under the dual strategic imperatives of carbon neutrality and digital transformation, the power industry plays a pivotal role in advancing green and low-carbon development. Green Total Factor Productivity (GTFP) provides a comprehensive measure of efficiency in the power sector under energy and environmental constraints. Using panel data from 31 Chinese provinces over the period 2012–2023, this study employs a super-efficiency Slacks-Based Measure (SBM) model, kernel density estimation, standard deviation ellipse analysis, the Gini coefficient, and fuzzy-set Qualitative Comparative Analysis (fsQCA) to systematically examine the spatiotemporal evolution, regional disparities, and digital-driven improvement pathways of power industry GTFP. The results indicate that national power-sector GTFP exhibits a fluctuating upward trend, accompanied by pronounced regional heterogeneity. A distinct spatial pattern has emerged, characterized by rapid improvement in the western region, relative stability in the eastern region, contraction in the central region, and persistent lagging in the northeastern region. Spatially, the distribution has evolved from an initial east–west dual-core structure to a three-tier gradient pattern led by the west, stabilized in the east, and depressed in the central region. Kernel density estimation reveals a clear multi-peak polarization trend, while standard deviation ellipse analysis shows a relatively stable spatial center with continuously expanding dispersion along the northeast–southwest axis. Further analysis demonstrates that interregional differences remain the primary source of overall inequality, with rapidly widening intraregional disparities in the western region. Configurational analysis identifies five digital-economy-driven pathways to high GTFP, highlighting that no single optimal configuration exists. Instead, multiple combinations of technological, organizational, and environmental conditions jointly facilitate GTFP enhancement. These findings provide empirical evidence to support differentiated and precision-oriented policy design for promoting coordinated digital transformation and green development in China’s power industry. Full article

This study assesses regional science and technology (S&T) innovation efficiency across 30 Chinese provinces from 2011 to 2022, incorporating a sustainable development perspective. Employing a non-oriented global frontier super-slack-based measure (SBM) model that accounts for undesirable outputs, along with kernel density estimation, cluster analysis, and Moran’s I, the research investigates the spatiotemporal evolution of innovation dynamics. The findings demonstrate a marked upward trend, with the national average efficiency score rising from 0.260 to 0.703. Temporally, efficiency advanced through three stages: an initial period of universally low efficiency, a phase of widening disparities, and a final stage of overall improvement and stabilization. Spatial analysis reveals a persistent “strong in the east, weak in the west” disequilibrium; however, absolute β-convergence tests indicate a significant reduction in regional disparities (p < 0.05). Kernel density estimation reveals a shift from a polarized “pyramid” shape to a more balanced “spindle-shaped” distribution. This is evidenced by a decrease in kurtosis and a rightward shift in the median. Spatial autocorrelation, as measured by the Global Moran’s I, evolved from a statistically insignificant distribution in 2011 to a strong positive correlation (0.223, p < 0.05) by 2022. This progression reflects a transition from isolated “unipolar” hubs to integrated “multi-center block linkages.” The results suggest that, although polarization is diminishing and the national innovation baseline is improving, policy efforts should prioritize the development of emerging innovation corridors to address the remaining east–west divide. Full article