Search Results (528)

With the global rise in sustainable investment concepts, environmental, social, and governance (ESG) factors have increasingly become important criteria influencing investment decisions. Although institutional investors are paying greater attention to corporate ESG performance, limited evidence exists regarding its impact within the Chinese A-share market. Using panel data from Chinese listed firms during the period 2010–2023, this study employs fixed-effects models with clustered standard errors as the baseline estimation method. To improve the robustness of the findings, Tobit regression, Logit regression, lagged-variable models, heterogeneity analysis, and Hausman tests are further conducted. The empirical findings indicate that the overall ESG score and the individual environmental (E), social (S), and governance (G) dimensions do not exhibit statistically significant effects on institutional ownership in the baseline fixed-effects regressions. The results suggest that ESG performance has not yet become a dominant determinant of institutional investment decisions in China’s capital market. However, the robustness tests based on Tobit and Logit models provide limited evidence that ESG performance may still influence institutional investor behavior under alternative empirical specifications. Furthermore, the heterogeneity analysis reveals that the relationship between ESG dimensions and institutional ownership differs across environmentally related and non-environmentally related firms, although the effects are generally weak and statistically limited. The study contributes to the ESG and institutional investment literature in three important ways. First, it provides updated evidence from the Chinese A-share market over the 2010–2023 period, reflecting the evolving stage of ESG development in emerging economies. Second, it comparatively examines the differentiated roles of environmental, social, and governance dimensions rather than relying solely on aggregated ESG indicators. Third, it highlights the limited and transitional nature of ESG integration among institutional investors in China, where traditional financial indicators continue to play a more important role in investment decisions. The findings provide important implications for policymakers, listed firms, and institutional investors seeking to promote sustainable finance development and improve the effectiveness of ESG disclosure practices in emerging markets. Full article

This present study aims to investigate the influence of board characteristics on the level of climate change disclosures and the extent to which the implementation of the corporate governance code (CGC) moderates these factors. The ordinary least squares statistical method is used to analyze the panel data. In addition, the Tobit regression model is also estimated to check the robustness of the study findings. This study suggests that larger board sizes, more independent directors, and board meeting frequency are positively associated with higher levels of climate change disclosure. However, the study does not find any association between CEO duality, foreign ownership, and climate change disclosure. In addition, it is also observed that CGC can enhance the influence of board characteristics on the likelihood of disclosing climate information. The study offers necessary directions for regulatory authorities, business firms, and practitioners to be more transparent in disclosing climate information and extends guidelines to tackle climate change disclosure issues. Full article

Conservation tillage plays an important role in improving sustainable land use and maintaining food production. Using survey data from 261 agricultural producers in Heilongjiang Province, China, this study examines how conservation tillage policy mixes affect agricultural green total factor productivity (AGTFP). The slack-based measure (SBM) model incorporating undesirable outputs is employed to estimate AGTFP. A Tobit model with interaction terms is applied to analyze the independent and combined effects of three policy instruments: subsidies, regulations, and supporting services, and a mediating effect model is used to verify how these instruments work. The results indicate that: (1) the mean AGTFP value stands at 0.37, reflecting a generally low level of performance, with the largest improvement requirements observed in seed inputs (66.25%), machinery inputs (65.53%), and nitrogen emissions (61.55%); (2) subsidies, regulations, and supporting services all improve AGTFP, while the combinations of subsidies and services, regulations and services, and the full three-policy mix generate significant positive synergistic effects; (3) policy mixes facilitate AGTFP enhancement by increasing agricultural producers’ perceived value of conservation tillage technologies and reducing perceived risks. In particular, the interaction between regulations and supporting services significantly increased perceived value (β = 1.129, p < 0.01) and reduced perceived risk (β = −0.810, p < 0.01); (4) the effects of policy mixes are stronger for producers pursuing green production goals and for small-scale farmers. Based on these findings, the following recommendations are proposed: policy efforts should strengthen the coordination of subsidies, regulations, and services, linking training and inspection results to subsidy eligibility; address efficiency bottlenecks in seeds, machinery, labor, and nitrogen emissions; design differentiated policy packages for various farm types; and build a training system that includes at least two mandatory sessions per season and ties training outcomes to subsequent subsidies. This study contributes a policy mix perspective to the evaluation of AGTFP and provides empirical evidence for coordinated conservation tillage policy design. Full article

Amid China’s “dual carbon” goals and technological transformation, the traditional energy–economy–environment (3E) framework fails to capture evolving urban sustainability patterns, as digitalization and innovation emerge as endogenous drivers. This study constructs an expanded five-system framework (3E-D-T: energy, economy, environment, digitalization, technology) and examines its coupling coordination. Using panel data from 13 Jiangsu cities (2015–2024), we employ entropy weighting, coupling coordination models, Dagum Gini decomposition, spatial autocorrelation, and panel Tobit regression. Results show that incorporating digitalization and technology alters coordination assessments, revealing structural disparities overlooked by the traditional framework. Significant intra-provincial heterogeneity exists across Jiangsu’s regions, with distinct spatial gradients. External factors—economic development, industrial structure, fiscal support, and environmental regulation—exert differentiated regional impacts. Contributions include: (1) expanding 3E to 3E-D-T by endogenizing digitalization and technology; (2) establishing an integrated measurement-evolution-mechanism analytical system; (3) providing empirical evidence on internal heterogeneity and differentiated governance pathways in eastern China. Full article

Background/Objectives: Bone and soft tissue sarcomas frequently affect children, adolescents, and young adults, yet data on chemotherapy-related ovarian reserve decline in this population remain limited. We aimed to characterize anti-Müllerian hormone (AMH) dynamics during treatment and identify factors associated with post-neoadjuvant chemotherapy (post-NACT) ovarian reserve. Methods: We conducted a retrospective, single-center, longitudinal cohort study of 85 female patients with bone and soft tissue sarcoma who underwent serial serum AMH testing during treatment. In the paired cohort with complete baseline and post-NACT AMH measurements (n = 75), post-NACT AMH was defined as the value obtained at the surgery/post-neoadjuvant time point after completion of NACT. Log-transformed multivariable linear modeling and left-censored Tobit regression sensitivity analysis were performed. Results: Median AMH declined from 3.46 ng/mL at baseline to 0.39 ng/mL after the first NACT cycle and to 0.15 ng/mL after the second cycle, corresponding to reductions of 88.7% and 95.7%, respectively. In the paired cohort, median AMH declined from 3.81 ng/mL to 0.19 ng/mL post NACT, with a median absolute decline of 2.75 ng/mL and a median percent decline of 94.4%. In the log-transformed multivariable linear model, log(baseline AMH) was the sole independent predictor of log(post-NACT AMH) (β = 0.735, 95% CI 0.357–1.114, p < 0.001). In Tobit sensitivity analysis, 4 post-NACT AMH values were treated as left-censored at 0.05 ng/mL, and the pattern remained consistent. Conclusions: Ovarian reserve depletion in female sarcoma patients occurred predominantly within the first one to two cycles of NACT. These findings support early, individualized fertility preservation counseling in this population. Full article

Against the backdrop of increasingly severe agricultural labor aging (ALA), the aging process not only threatens food security but also poses challenges to green and sustainable agricultural development. Existing studies have paid insufficient attention to how ALA simultaneously affects grain production efficiency (GPE) and grain eco-efficiency (GEE), and there is a particular lack of systematic investigation into the moderating roles of different crop types and social networks. To address this gap, this study utilizes survey data from 1056 farm households across five major grain-producing provinces in China and employs Tobit regression models to empirically examine the dual effects of ALA on GPE and GEE, while also revealing the moderating mechanisms of formal and informal dual-layer social networks. The main findings are as follows: (1) ALA generally inhibits both GPE and GEE across different grain crops, with a more prevalent negative impact on GEE. (2) The impact of ALA on the two types of efficiency exhibits crop-specific nonlinear characteristics: a positive U-shaped relationship for maize, an inverted U-shaped relationship for rice, and no significant nonlinear relationship for wheat. (3) Social networks play significant linear and nonlinear moderating roles in mitigating the negative effects of ALA, though their effects vary depending on network type, crop system, and efficiency dimension. Based on these findings, it is recommended to implement differentiated intervention strategies tailored to crop characteristics and aging stages, build a multi-tiered social network support system, and strengthen the research, extension, and service support for green technologies targeting middle-aged and older farmers, thereby synergistically enhancing grain production capacity and ecological sustainability. Full article

This paper measures China’s role as an “external market provider” by quantifying, for 168 source countries during 2001–2022, the share of each country’s exports absorbed by China and decomposing that share into extensive (product coverage), quantity, and price margins using the Hummels–Klenow framework. To characterize destination-market concentration, we construct an HHI-based network diversification indicator from export-destination shares and interpret it from a complementary information-theoretic perspective, where higher concentration corresponds to lower diversification and stronger dependence. We document the dynamics of China’s market-provision role and estimate an extended gravity-type model with country- and year-fixed effects. The results show that China’s external market-provider role expanded markedly after WTO accession, with growth driven mainly by the quantity margin and, after 2018, increasingly supported by the price margin. Economic proximity and similarity in global value-chain position are associated with stronger China-absorption shares, while greater destination concentration relative to China is associated with lower China-absorption shares. Free trade agreements are linked to stronger, more extensive, and larger margins. Robustness checks based on lagged covariates, additional controls, higher-dimensional fixed effects, Tobit estimation, and winsorization support the main findings. Overall, the paper provides a replicable framework for measuring destination-market pull and shows how China’s import-side role varies across products, regions, and development groups, while using the information-theoretic perspective as a supplementary interpretation of diversification patterns rather than as a separate empirical tool. 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

Enhancing technical efficiency in food legume production is essential, since the scope for expanding factor inputs is limited under tightening resource constraints. Higher technical efficiency improves resource allocation, ensures food supply stability, and boosts farm income. To strengthen production performance, using survey data from 817 food legume farm households in five major producing regions of China in 2024, this study employs a two-stage DEA-Tobit model to measure farmers’ technical efficiency in food legume production and to empirically identify its driving factors. The results indicate that: (1) technical efficiency in food legume production shows pronounced regional disparities and substantial within-region heterogeneity; (2) technical efficiency in food legume production improves over time, yet substantial space for efficiency gains remains relative to other staple crops; (3) farm households located at different stages of returns to production inputs show distinct production and management patterns. (4) human capital accumulation, full-time farming status, and participation in food legume cooperative economic organizations exert significant positive effects on technical efficiency. Meanwhile, planting scale exhibits a significant inverted U-shaped relationship with technical efficiency. The findings provide household-level empirical evidence to explain disparities in technical efficiency and identify pathways for improving food legume production. Full article

Although the coupling coordination relationship (CCR) between ecological environment and economic development has received extensive scholarly attention, investigations into the underlying mechanisms of this coupling coordination remain insufficient. Taking the Chishui River Basin (CRB) in Southwest China as the study area, this study integrates remote sensing data and county-level statistical datasets. Firstly, the quality of the ecological environment and economic development level of the CRB are systematically evaluated. Secondly, an improved coupling coordination degree model (ICCDM) is adopted to quantify the CCR between the ecological environment and economic development, as well as its spatiotemporal evolution characteristics. Finally, an obstacle degree model and panel Tobit model are employed to explore the influencing factors of the CCR from both intrinsic and extrinsic perspectives. The results show that during the study period, both the ecological environment index (EEI) and the economic development index (EDI) in the CRB exhibited upward trends, with pronounced inter-county disparities. The CCR between ecological environment and economic development was continuously optimized, and the coupling coordination degree (CCD) displayed a distinct spatial gradient pattern of downstream regions > midstream regions > upstream regions. Obstacle degree analysis identifies significant heterogeneity in the obstacle factors for CCR improvement across the basin: Renhuai and Zunyi are dominated by ecological environment constraints, while 11 counties including Chishui and Xishui are mainly restricted by economic development constraints. Industrial structure, ecological endowment, industrialization level and government capacity are vital positive driving factors for the CCR in the CRB, whereas Terrain conditions act as a key negative restraining factor. This study indicates that the overall coupling coordination level between ecological environment and economic development in the CRB is still relatively low and requires further enhancement. Therefore, region-specific differentiated regulation strategies are urgently needed to achieve high-level coordinated development between the ecological environment and economy in the CRB. Full article

Background: Although mega-dams play a significant role in development, providing electricity, irrigation, and flood control, perceptions of their contribution remain mixed, particularly regarding the environmental impacts. Methods: This study jointly determines perceived favorable and adverse environmental impacts of mega-dams by affected residents using a bivariate Tobit model on a clustered random sample of 300 households surveyed from (a) upstream, (b) upstream-relocated, and (c) downstream communities of the Merowe Dam in Sudan. Model diagnostic reveals that the perception of favorable and adverse environmental impacts is significantly and positively correlated, implying that univariate analyses of such perceptions are biased, thereby justifying the use of a bivariate approach. Such joint perception analysis using a bivariate Tobit model confirms that affected residents are well aware of both the positive and negative impacts of the dam, not commonly seen in the literature. Results: Results reveal significant differences in perception among communities on individual indicators of favorable and adverse environmental impacts of the dam. Education, income from farming, and relocation significantly decrease the likelihood of perceiving adverse environmental impacts whereas farmers of all farm types increase it. Selected farming categories and gain in land size after dam’s construction significantly increases the likelihood of scoring high on favorable environmental impacts whereas income from fishing significantly reduces it. Conclusions: Perception towards the favorable and adverse environmental impacts are not independent, rather significantly and positively correlated, confirming that affected residents are aware of both types of impacts of the Merowe Dam. Upstream-relocated residents are less likely to report the significant adverse environmental impacts of the dam, whereas both upstream and upstream-relocated residents are less likely to report significant favorable impacts of the dam. Policy implications: Include establishing educational institutions, allocation of agricultural land, and mitigating adverse environmental impacts by setting up community environmental monitoring programs in affected areas to boost community perception of the favorable environmental impacts of mega-dams. Full article

This paper proposes an innovative research algorithm “measurement—pattern—driving force—synergy” that determines the eco-efficiency of 83 Russian federal subjects (2000–2019) using the Slacks-Based Measure (SBM) model with non-desired outputs (incorporating comprehensive input indicators such as water resources and electricity input, and dual non-desired outputs of waste gas and wastewater). Combined with hot spot analysis, a gravity center model, and panel Tobit regression, we reveal the temporal-spatial evolution and driving mechanisms of eco-efficiency in resource-based economies. The research finds that the overall eco-efficiency of Russia is at a medium level and shows a dynamic correlation with the economic development stage. In the early stage of the period under review, there was a high degree of synergy, but the efficiency declined during the period of rapid economic growth. Later, it rebounded somewhat in tie with technological progress. Spatially, it presents a special pattern of low efficiency in the western European industrialized regions and high efficiency in the Arctic and Far East peripheral regions, reflecting the spatial heterogeneity of resource-dependent economies and the survival-constrained efficiency feature. The analysis of influencing factors indicates that per capita GDP has a significant positive driving effect on eco-efficiency, but the expansion of residents’ consumption, the improvement of education level and the dependence on foreign trade all have inhibitory effects, highlighting the path dependence of the current growth model on the structure of resource consumption. The research suggests that Russia should implement differentiated spatial governance in the future, promote the green transformation of consumption and trade structures, and strengthen the ecological orientation of the education and scientific research system to achieve a fundamental transformation of regional sustainable development from survival constraints to innovation-driven. Full article

Agricultural biomass recycling efficiency is central to advancing the green and sustainable transition of agriculture. Drawing on panel data for 30 Chinese provinces from 2019 to 2023, this study measures recycling efficiency using a three-stage super-efficiency SBM model with undesirable output and examines its determinants with a panel Tobit model. The second-stage SFA indicates that the effects of external conditions on input slacks are input-specific. In particular, GDP is statistically significant only in the biomass-generation slack equation, whereas topographic relief and rural road network density do not show robust associations with any slack measure once controls are included. After removing the influence of environmental factors and random shocks, the overall national level of agricultural biomass recycling efficiency remains moderate. The national mean Stage 3 efficiency decreased from 0.586 in 2019 to 0.427 in 2022 and recovered to 0.543 in 2023. The five-year average was 0.510, which is close to the Stage 1 average of 0.503. Spatial analysis indicates weak global spatial autocorrelation, with only occasional local clustering. The efficiency centroid oscillated during the study period rather than following a one-way migration path, with a total displacement of 70.05 km. The determinant analysis indicates that the number of specialised agricultural machinery has the most stable positive association with recycling efficiency, while other policy, market, and human capital variables do not show robust significance in the short panel. These findings underline the need to align equipment deployment and collection systems with local terrain and transport conditions, expand machinery leasing and service provision, and strengthen capacity building in low-efficiency regions. Establishing a national information sharing and dispatch platform would facilitate cross-regional resource flows and more efficient allocation, while improving local service outlets would make participation more convenient for farmers and reduce transaction costs. Full article

The integration of intangible cultural heritage (ICH) and tourism development (TD) is regarded as a crucial national strategy for China’s sustainable development, as their synergistic relationship is considered pivotal for regional progress. A coupling coordination evaluation system was constructed. Kernel density estimation, entropy method, coupling coordination degree (CCD) and relative development degree (RDD) models, and a tobit model were employed to examine the spatiotemporal characteristics and influencing factors of ICH–TD integration in Sichuan Province. Key findings are as follows: (1) Sichuan is endowed with abundant ICH resources characterized by high heritage value and diverse typologies. However, the distribution is skewed toward traditional skills, exhibiting notable regional disparities. ICH demonstrates a “single-core, belt-shaped and multi-cluster” pattern, which is centered on Chengdu, extends along a north–south high-density belt, and forms several secondary high-density clusters. (2) Temporally, the CCD demonstrates a sustained upward trend, whereas the RDD transitions from ICH-lagged to TD-lagged. Spatially, the number of high coordinated cities increases annually, expanding radially from regional centers, while central-eastern regions consistently outperform the west. (3) Regarding influencing factors, comprehensive economic strength, distribution of industrial structure, overall level of urbanization, and transportation accessibility exert significant positive effects on the CCD, with comprehensive economic strength demonstrating the strongest influence. This study contributes to the theoretical understanding of ICH–TD synergy and provides policy-relevant guidance for integration. Full article

Although higher technical efficiency is theoretically expected to enhance farm sustainability, empirical evidence in livestock systems remains ambiguous. This study investigates the interplay between technical efficiency and sustainability using data from 72 farms in Tokat, Türkiye, selected via stratified random sampling. Technical efficiency was calculated using Data Envelopment Analysis (DEA), while a multidimensional Sustainability Index was constructed using the analytic hierarchy process (AHP) for weighting dimensions. Determinants of inefficiency were estimated using a Tobit model. Results revealed an average technical efficiency of 0.717 and a Composite Sustainability Index of 0.41, classifying the sector as “moderate” but fragile. Crucially, the Kruskal–Wallis test showed no statistically significant difference in sustainability scores across efficiency groups (p > 0.05). This finding confirms a “structural disconnect,” demonstrating that high technical efficiency does not guarantee sustainability because of systemic bottlenecks such as dysfunctional organizations and infrastructure deficits. Furthermore, Tobit results showed that non-farm income and internet access were positively associated with technical efficiency, whereas indebtedness was negatively associated. Consequently, achieving lasting sustainability requires a shift from simple productivity support to structural modernization policies, including the integration of sustainability-oriented criteria such as institutional strengthening, environmental management, and financial capacity into existing support schemes. Full article