Search Results (42)

Enhancing agricultural green total factor productivity (AGTFP) under ecological and environmental constraints is essential for advancing green agricultural development in the Beijing–Tianjin–Hebei (BTH) region. Using panel data from 13 prefecture-level cities from 2001 to 2022, this study applies a super-efficiency EBM model incorporating undesirable outputs together with the Malmquist–Luenberger index to measure AGTFP. Global and local Moran’s I indices as well as the spatial Durbin model are then employed to examine the temporal evolution, spatial disparities, and spatial interaction effects of AGTFP during 2001–2022. The findings indicate that: (1) From 2001 to 2022, the AGTFP in the BTH region grew at an average annual rate of 7.7%. This trend reflects a growth pattern primarily driven by green technological progress in agriculture, while substantial disparities in AGTFP persist across different subregions. (2) the global Moran’s I values show frequent shifts between positive and negative spatial autocorrelation, suggesting that a stable and effective regional coordination mechanism for green agricultural development has yet to be formed; (3) the determinants of AGTFP exhibit pronounced spatiotemporal heterogeneity, and the fundamental drivers of the region’s green agricultural transition increasingly rely on endogenous growth generated by technological innovation and rural human capital; (4) policy recommendations include strengthening benefit-sharing and policy coordination mechanisms, promoting cross-regional cooperation in agricultural science and technology, and implementing differentiated industrial layouts to support green agricultural development in the BTH region. These results provide valuable insights for promoting coordinated and sustainable green agricultural development across regions. Full article

This research explores the digital economy’s impact on high-quality agricultural development, with a particular focus on its effect on Agricultural Green Total Factor Productivity (AGTFP). By integrating Dynamic Qualitative Comparative Analysis (QCA) and Necessary Condition Analysis (NCA) on data spanning from 2011 to 2023 across 31 Chinese provinces, the study produces the following results: (1) No single element of the digital economy alone is indispensable for enhancing AGTFP. Instead, its driving force stems from the synergistic interactions among multiple elements. Configuration analysis identifies four effective pathways to boost AGTFP: the financial–government dual-driver model, the infrastructure–government dual-driver model, the financial–resource dual-driver model and the industry-led driver model. (2) Regional disparities exist in the approaches to achieving high-quality agricultural development. The eastern region prioritizes the integration of finance and policy, while the central and western regions emphasize the synergy between infrastructure and government initiatives. (3) The identified pathways demonstrate temporal stability, with digital finance pathways exhibiting particularly high consistency over the study period, maintaining a temporal stability exceeding 0.85 in most years. This study combines the TOE framework with configuration analysis to enrich the theoretical framework of agricultural digitalization, revealing key pathways through which the digital economy can propel green agriculture development and offers empirical evidence to inform tailored digital agriculture policies. Full article

Digital literacy (DL) among farmers serves as a vital link between digital technology and green sustainable development, significantly enhancing agricultural green total factor productivity (AGTFP). This study employs panel data from the China Family Panel Studies (CFPS) covering 2014–2020, applying a two-way fixed effects model and machine learning techniques to examine the influence of farmers’ digital literacy on AGTFP. The results indicate that DL positively contributes to AGTFP. Further heterogeneity analysis shows stronger effects among male farmers, households with low trust, and those within the working-age population. Mechanism analysis indicates that social capital accumulation mediates the relationship, whereas agricultural socialization services strengthen the positive impact of DL on AGTFP. Additional analysis using machine learning models reveals that the impact of farmers’ digital literacy on AGTFP changes over time. Specifically, entertainment and learning-oriented network use enhances AGTFP, whereas work-related, social, and lifestyle-related use suppresses it. This study offers a more nuanced understanding by shifting from traditional macro-level frameworks to a micro-level perspective focused on farmers’ digital literacy. Moreover, the innovative application of explainable machine learning provides empirical evidence for the underlying drivers of AGTFP. Full article

Using a balanced provincial panel of 31 Chinese regions (2014–2022), this study examines how Digital Inclusive Finance (DIF) and Rural E-Commerce (RE) jointly shape the urban–rural income gap. Two-way fixed effects and instrumental-variable estimators mitigate confounding. Both DIF and RE are associated with narrower gaps, and the interaction term is negative and robust across specifications. Mechanism evidence indicates that the coupling operates through higher Agricultural Green Total Factor Productivity, expanded rural credit supply, and stronger entrepreneurship. Effects are larger in Central/Western provinces and are most pronounced when DIF’s usage-depth and digital-support components are salient. For policymakers and managers, the findings support bundled investments in digital rails, platform logistics, and e-commerce–linked credit, with priority to lagging regions and programs that deepen usage. Overall, the results provide a tractable systems approach to aligning finance and markets for inclusive rural transformation. Full article

Accurate assessment of green productivity is essential for advancing sustainable agriculture in ecologically fragile regions. This study examined the evolution of agricultural green total factor productivity (AGTFP) in Tibet over the period 2002–2021 by applying a super-efficiency SBM-GML model that accounts for undesirable outputs. We decompose AGTFP into technical change and efficiency change, conduct redundancy analysis to identify sources of inefficiency and explore its spatiotemporal dynamics through kernel density estimation and convergence analysis. Results show that (1) AGTFP in Tibet grew at an average annual rate of 0.78%, slower than the national average of 1.6%; (2) labor input, livestock scale, and agricultural carbon emissions are major sources of redundancy, especially in pastoral regions; (3) technological progress is the main driver of AGTFP growth, while efficiency gains have a limited impact, reflecting a technology-led growth pattern; (4) AGTFP follows a “convergence-divergence-reconvergence” trend, with signs of conditional β convergence after controlling for regional heterogeneity. These findings highlight the need for region-specific green agricultural policies. Priority should be given to improving green technology diffusion and input allocation in high-altitude pastoral areas, alongside strengthening ecological compensation and interregional coordination to enhance green efficiency and promote high-quality development across Tibet. Full article

This study employs a Super-SBM model to construct a comprehensive evaluation framework—encompassing input factors, desirable outputs, and undesirable outputs—to measure agricultural green total factor productivity (AGTFP) in the Tibet Autonomous Region in the period 2002–2021. We then apply kernel density estimation and Dagum Gini coefficient decomposition to examine its spatiotemporal evolution. The main findings are as follows: (1) AGTFP in Tibet rose overall from 0.949 in 2002 to 1.068 in 2021, with a compound annual growth rate of 0.78%, yet remained below the national average; (2) significant regional heterogeneity emerged, with three typical evolution patterns identified: continual improvement (Nagqu, Qamdo), stable fluctuation (Lhasa, Xigazê), and risk of decline (Lhoka, Nyingchi, Ngari); (3) gains in pure technical efficiency were the primary driver of AGTFP growth, while insufficient scale efficiency was a key constraint; (4) AGTFP exhibited a “convergence–divergence–reconvergence” dynamic, with interregional disparities widening but structural patterns stabilizing; and (5) interregional inequality was the main source of overall disparity—its importance grew over the study period, with the largest gap observed between agrarian and pastoral zones. On this basis, we recommend a “gradient advancement” strategy that prioritizes pure technical efficiency and regional coordination, while promoting zone-specific support tools tailored to local ecological conditions and institutional capacities to ensure inclusive green productivity growth. Full article

This paper investigates the impact of carbon emissions trading schemes (CETSs) on agricultural green total factor productivity (AGTFP) using a multi-temporal DID model. Using Chinese prefecture-level city data collected from 2004 to 2022, we find that CETSs enhance AGTFP through technological innovation, with stronger effects in eastern and western regions and positive spillover to neighboring cities. These findings underscore the significant role of CETSs in influencing agricultural productivity and highlight the various factors that contribute to improving AGTFP. Full article

To further promote rural revitalization strategies and achieve common prosperity, it is necessary to clarify the relationships among public expenditure for agriculture, agricultural green total factor productivity (AGTFP), and the urban–rural income gap (URIG). On the basis of panel data for 30 provincial regions in China from 2012 to 2022, this study constructs a panel vector autoregression (PVAR) model and explores their mutual interaction and influence from both dynamic and static perspectives through the Granger causality test, impulse response analysis, and variance decomposition methods. The research results show that public expenditure on agriculture, AGTFP, and URIG exhibit significant self-reinforcing trends. There is a significant two-way interaction effect between public expenditure on agriculture and URIG, indicating that these factors promote and complement each other. In addition, both improving AGTFP and increasing public expenditure on agriculture can help narrow URIG, but the positive impact of AGTFP exhibits greater magnitude and sustainability. In conclusion, from a long-term perspective, to develop the rural economy and promote rural revitalization, it is necessary not only to increase public expenditure on agriculture continuously, but also to focus on enhancing AGTFP. Full article

The digital economy’s development has been significantly influenced by data, which have emerged as a new propelling force for the promotion of high-quality and environmentally friendly agricultural development. This paper employs panel data from 30 provinces in China, spanning from 2000 to 2022. We construct a multi-period difference-in-differences model to investigate the impact of data elements on agricultural green total factor productivity (AGTFP) by utilizing the launch of public data open platforms as a quasi-natural experiment. AGTFP is substantially improved by public data openness, as indicated by the findings. Cross-sectoral labor transfer and green technological innovation are critical pathways through which public data openness enhances AGTFP, according to the mechanism analysis. Furthermore, heterogeneity analysis indicates that the beneficial impact of public data openness on AGTFP is more pronounced in regions with high levels of environmental regulation and non-major grain-producing regions. The results of this study have significant policy implications for the evaluation of the economic impacts of data elements and the promotion of sustainable and environmentally friendly agricultural development. Full article

Based on endogenous growth theory and technological innovation theory, this paper uses panel data from 30 provinces in China from 2011 to 2022 to investigate the impact of digital village construction on agricultural green total factor productivity (AGTFP). AGTFP was measured by the EBM-GML method, and mediated effects and heterogeneity analysis were used to reveal its conduction pathway. The findings are as follows: (1) AGTFP showed an overall upward trend during the sample period, and most provinces peaked in 2018. Among them, the AGTFP index value of the eastern coastal provinces (such as Tianjin and Beijing) is between 1.059 and 1.129, maintaining the leading position. The western region fluctuates greatly; e.g., the AGTFP value of Qinghai Province fluctuates between 0.915 and 1.047. (2) Digital village construction significantly improves AGTFP by promoting green technology progress (coefficient 0.105, significant at the 5% level) but has no significant impact on technical efficiency. (3) Agricultural informatization (coefficient 0.040, significant at the 5% level) and rural human capital (coefficient 0.115, significant at the 5% level) are important intermediary channels for digital village construction to affect AGTFP. (4) Regional heterogeneity analysis showed that the effect of digital village construction in the eastern region (coefficient 0.151, significant at the 5% level) and the southern provinces (coefficient 0.170, significant at the 1% level) was more significant. The digital village construction in the main producing areas (coefficient 0.113, significant at the 1% level) also significantly promoted AGTFP. Based on the research results, it is suggested that the promotion and application of digital technology be strengthened, the land transfer system improved, an agricultural information platform built, rural human capital improved, and regional differentiated development strategies implemented. Full article

Agricultural green total factor productivity (AGTFP) is vital to sustainable agricultural development (SAD), which plays a pivotal role in achieving high-quality economic growth in China. The current research quantified China’s AGTFP from 2007 to 2019 with the Super-SBM model and the GML index. Subsequently, it examined the impact of environmental regulation (ER) on AGTFP and its heterogeneity. Finally, this study developed a mediating effect model and a panel threshold model to investigate the role of technological innovation (TI) in affecting environmental regulation (ER) on AGTFP. The findings indicate that the following: (1) The average annual growth rate of AGTFP is 7.84%, which is mostly driven by green technological innovation progress. (2) ER has a significant positive impact on AGTFP with noticeable regional differences. The eastern and central regions experience a more substantial promotion effect compared to the western region. Additionally, the prominent grain-producing areas and main grain-marketing areas have a more significant promotion effect compared to the grain-balanced areas. The promotion effect of heterogeneous ER on AGTFP varies, with the effects of command-and-control environmental regulation (ERC), market-based incentives for environmental regulation (ERM), and public participation regulation (ERP) decreasing in magnitude. (3) The mechanism analysis reveals that promoting TI is a crucial way to enhance AGTFP through ER. There exists a notable dual threshold for TI in ER, encompassing both ERC and ERM. Moreover, AGTFP becomes increasingly pronounced. This study presents a novel perspective for promoting SAD, with a focus on the rise in AGTFP and the path to achieving it. Full article

Agricultural production faces the dual challenge of increasing output while ensuring efficient resource utilization and environmental sustainability amid escalating global climate change and relentless increases in human demand. This study used provincial panel data from China from 2001 to 2022 to address these challenges. It systematically evaluated the dynamic evolution of agricultural green total factor productivity (AGTFP) by selecting “resources” and “energy” as core input factors and adopting a dual-output approach focused on “economic” and “low-carbon” outcomes. This study thoroughly analyzed the synergistic mechanisms of factors such as natural endowment, agricultural technology, economic development, and environmental regulation, exploring their impact on AGTFP enhancement through the innovative application of the dynamic fuzzy-set qualitative comparative analysis (fsQCA) method. There was a significant upward trend in AGTFP across China, indicating notable progress in green agricultural development. Additionally, three pathways promoting AGTFP improvement were identified: resource–economy-driven, technology–policy-guided, and multifactor-synergy. Simultaneously, two modes constraining AGTFP enhancement were uncovered: economy–policy suppression and human capital–economy suppression, highlighting the pivotal role of regional economic development and the conditionality of converting natural resource advantages. Moreover, the contributions of these pathways to AGTFP exhibited notable temporal dynamics. Major economic events, such as the 2008 financial crisis and policy shifts, including the 2012 “Ecological Civilization” strategy, significantly altered the effectiveness of existing configurations. Our analysis of regional heterogeneity revealed distinct geographical patterns, with the resource–economy-driven model predominantly observed in central regions and the technology–policy-guided and multi-factor-synergy models more prevalent in central and eastern regions. These findings highlight the importance of formulating differentiated policies tailored to the specific needs and stages of development in different regions. Specifically, enhancing the synergy between resource management and economic development, optimizing technology–policy integration, and promoting coordinated multisectoral development are critical to fostering sustainable agricultural practices. This research provides crucial empirical evidence for shaping targeted policies that can drive green agricultural development across diverse regional contexts. Full article

The inefficient allocation of resources in agricultural production not only affects the quality of agricultural development and the efficiency of resource utilization but also represents a pivotal issue that constrains the sustainable progress of agriculture. Considering the urgent societal need for the optimization and advancement of industries, investigating the issue of resource misallocation within agricultural production and its specific losses on AGTFP is profoundly important in advancing the pursuit of high-quality and sustainable agricultural development. This study employs the Cobb–Douglas function and the theory of price distortion to establish a model for quantifying losses in Agricultural Green Total Factor Productivity (AGTFP). Drawing on provincial panel data from North China spanning the years 2006 to 2022, we analyze the characteristics of resource allocation and the corresponding losses in AGTFP. The findings suggest that AGTFP in North China has been gradually rising, accompanied by notable regional disparities in both the level of AGTFP and its growth rate. Nevertheless, due to the varying effects of distorted agricultural input factors, there exists different resource misallocation across North China. Despite some improvement in resource misallocation, this improvement has not been significant. Consequently, there is a loss of AGTFP in the North China region. If resource misallocation is effectively addressed, AGTFP losses could be reduced by at least 29%. It is anticipated that over the course of the next decade, AGTFP will rise and resource misallocation and AGTFP losses will diminish slightly, and it is crucial to step up efforts to enhance resource allocation. By ensuring adequate agricultural funding, enhancing agricultural efficiency, and optimizing energy inputs, it is possible to mitigate resource misallocation, thereby effectively diminishing AGTFP losses and fostering the sustainable advancement of agriculture. Full article

Promoting the role of green finance (GF) in agricultural green transformation is essential for easing resource constraints and achieving sustainable agricultural development. Based on provincial-level data from 2006 to 2022, this study considers the China GF reform and innovation pilot zone as a quasi-natural experiment. It empirically examines the impact and mechanism of GF on agricultural green total factor productivity (AGTFP). The following results are obtained: (1) GF exerts a significant enhancement effect on AGTFP. (2) GF can improve AGTFP by increasing the degree of land transfer (LT). (3) The effect of GF on AGTFP is heterogeneous, and GF has a significant enhancement effect on high-environmental-regulation provinces, the eastern region, and nonmajor grain-producing regions. From these findings, this study suggests accelerating the development level of GF, improving LT policies, continuously stimulating rural entrepreneurial vitality, and further leveraging the role of GF in promoting agricultural green transformation through coordinating regional economic development. Full article

The key to sustainable agricultural development is the transition to an environmentally friendly economic growth model. The development of agricultural credit (AC) plays an important role in promoting the shift of agricultural economic growth toward a green and low-carbon direction. In this context, a key question that needs to be addressed is the theoretical basis for how AC development affects agricultural green total factor productivity (AGTFP), and whether this relationship can be empirically tested. This article analyzes the impact mechanism of China’s AC development on AGTFP and conducts empirical testing using provincial panel data from 2009 to 2019. The results show that AC development significantly contributes to improving AGTFP. In terms of the underlying mechanism, AC development primarily fosters agricultural green technology innovation, thereby enhancing AGTFP. Full article