Indicators for Evaluating High-Quality Agricultural Development: Empirical Study from Yangtze River Economic Belt, China

Spatio-temporal dynamics and trend forecasting of urban green high-quality development: An examination of 287 cities in China

Facing the dual challenges of economic growth and environmental conservation, advancing urban green high-quality development (UGHQD) is crucial for sustainable urban development. Rooted in the concept of UGHQD, this study develops a multidimensional evaluation indicator system encompassing economic development, social progress, and ecological civilization. By applying spatial autocorrelation analysis, cold and hot spots analysis, standard deviation ellipse, and Kernel density estimation, it examines the spatial distribution and dynamic evolution of UGHQD across China and its four major regions (Eastern, Central, Western, and Northeastern) from 2003 to 2020. It also forecasts the trajectory of UGHQD from 2021 to 2025. The research findings indicate: (1) A steady annual increase in the overall level of UGHQD, with a geographic pattern showing high levels in the east, moderate in the center, and low in the west. (2) A spatial agglomeration in UGHQD, predominantly in the eastern region, demonstrating spatio-temporal inertia. (3) Varying degrees of a "right-tail" phenomenon in the UGHQD across China and its four sub-regions, indicating a polarization trend or even a weak multi-polarization trend. (4) A forecast of continuous, steady growth in UGHQD from 2021 to 2025, with the eastern region maintaining its leading position. This study offers insights that enhancing our understanding of the fundamental concepts underlying UGHQD, providing a practical foundation and policy guidance for future collaborative efforts in enhancing urban development quality.

Spatial disparities and dynamics in the high quality agricultural development in Heilongjiang Province of China

As a key commodity and strategic reserve grain base in China, evaluating and analyzing the high-quality agricultural development (HQAD) within Heilongjiang Province is crucial for advancing national agricultural quality. We construct a multidimensional evaluation framework with 19 indicators across four dimensions: green agriculture, quality and efficiency improvement of supply, agricultural structural coordination, and shared benefits of development. Using the Entropy Weighted-TOPSIS model, Dagum's Gini Coefficient, and the Markov chain, the study quantifies the HQAD in Heilongjiang from 2013 to 2022, examining regional disparities and development dynamics. The findings indicate that: (1) Heilongjiang's overall HQAD has steadily improved, rising from 0.160 in 2013 to 0.396 in 2022, with an annual average growth rate of 10.595%. Agricultural structural coordination, growing at 2.160% annually, has become the primary constraint. (2) Spatial imbalances are evident. The 12 prefecture-level cities in the province are grouped into four regions based on agricultural endowments. Harbin and Qiqihar in the Songnen Plain, and Mudanjiang in the Mudanjiang Semi-mountainous Areas lead in HQAD, while cities in the Sanjiang Plain lag behind. Intra-regional disparities are narrowing in Sanjiang Plain and Xing'an Mountains Regions except the Songnen Plain (from 0.000 to 0.062 during 2013-2022), increasingly contributing to the overall disparity (from 15.717% to 30.065% during 2013-2022). Inter-regional disparities are decreasing, with their contribution declining from 80.769% in 2013 to 37.481% in 2022. (3) HQAD levels in cities exhibit low mobility, fluctuating between medium-low (57.993%) and medium-high (22.082%). Based on these findings, we recommend strengthening agricultural structural coordination, promoting coordinated HQAD tailored to local conditions, and pursing institutional breakthroughs.

Coupling coordination of digital village construction and high-quality agricultural development in China

This study aims to investigate the coupling coordination relationship between digital village construction and high-quality agricultural development in China, along with influencing factors, in order to provide policy recommendations for fostering the concurrent advancement of these two domains. Utilizing coupling coordination degree model, spatial econometric model and other methods, this paper analyzes the panel data of 31 provinces (municipalities and autonomous regions) in China spanning from 2011 to 2022. The key findings indicate the following: Firstly, there has been an overall enhancement in the levels of digital village construction and high-quality agricultural development across all Chinese provinces, with the eastern region exhibiting a higher developmental status compared to the central and western regions. Secondly, the coupling coordination degree has shown a collective improvement, albeit with variations in coordination levels among different regions; however, the regional disparities are gradually narrowing. Thirdly, the level of economic development and agricultural financial expenditure emerges as significant factors influencing the degree of coupling coordination, demonstrating not only direct positive effects but also positive spatial spillover effects. Finally, this study proposes recommendations to promote sustainable agricultural development, such as setting up agricultural technology innovation platforms, establishing digital agricultural production bases, and training farmers in digital skills in order to mitigate regional disparities and foster mutual advancement across all regions.

Export competitiveness network of Chinese provincial agricultural products: E volution, performance, and influencing factors

The development of top-tier agricultural product bases and demonstration zones aims to propel Chinese agriculture into the global market, form international competitiveness, and advance to the high end of the global industrial and value chain. This study contributes to the existing literature by investigating the performance and factors influencing the competitiveness of Chinese agricultural product exports at the provincial level, using a complex network perspective, and offers recommendations for improvement. In this regard, the article uses agricultural product export data from 2015 to 2022 to create export competitiveness networks of Chinese provincial agricultural products. Our analysis revealed four primary observations. Firstly, significant opportunities exist to improve the competitive edge of agricultural product exports across various Chinese provinces. Secondly, with the exception of Guangdong Province, the types of competitively robust agricultural products exported by each province are inconsistent. Thirdly, international sister-city relationships can foster the development of an export competitiveness network of Chinese provincial agricultural products, while geographic distance may hinder this network. These findings are consistent. Lastly, the development of this competition-focused export network is also influenced by province-level and national characteristics, and these influences have unique differences. All provinces should strive to produce distinctive and globally competitive agricultural goods to build their competitive advantage in international trade. They should also implement strategic regional planning to support the global expansion of their agricultural products.

Exploring the impact of FDI on environmental innovation in China: An empirical investigation

Today, firms face several environmental concerns, including but not limited to: decreasing natural resources, pollution management, and climate change. Little is known about the factors that motivate the many forms of environmental innovation or the effects of these endeavors on the financial success of businesses, despite the growing demand for eco-friendly goods and services. For the first time, this study introduces the core environmental determinants for China's 30 provinces covering the period of 2005-2022. In these determinants, this study considers foreign direct investment (FDI), financial development (FDI), natural resources (NRs), human capital (HC), and green energy (GE). However, to investigate the study objectives, the present study utilizes an advanced series of estimators that can overcome all panel data problems. In these estimators, the Augmented Mean Group (AMG), the Common Correlated Effect Mean Group (CCE-MG), and the Panel Quantile Regression (P-QR) are being considered. However, the results of the long-term investigation obtained interesting outcomes for selected provinces. For example, financial proxies such as economic development and foreign direct investment significantly increase the environmental innovations across the selected regions. Conversely, natural resources negatively affect environmental innovations and become a leading hurdle in the clean & green innovation process. Finally, empirical analysis finds a positive response of ecological regulations and green energy to an explained variable. This article outlined policy proposals for a low-carbon economy that would guarantee environmental innovation in certain provinces by reducing emissions; these proposals included increasing the use of renewable energy sources, sustainable technology, and environmentally friendly technology.

Green industrial policy and green development of agriculture-Quasi-natural experiment based on the Yangtze River Economic Belt in China

Based on the panel data of 30 provinces, municipalities, and autonomous regions in China from 2012 to 2022, from the perspective of harmony between man and nature, this paper selects 20 indicators to measure the level of agricultural green development from five dimensions such as ecological conservation and resource conservation by entropy weight method. On this basis, taking the implementation of green industrial policy in the Yangtze River Economic Belt as a quasi-natural experiment, the policy effect of green industrial policy on agricultural green development was analyzed by using the difference-in-difference method. The study found that: (1) the green development of agriculture is basically increasing year by year in each province, but there are some differences in the green development of agriculture among provinces; (2) Compared with the non-implementation areas of policies, the green development of agriculture in the implementation areas of policies has been significantly improved, and has passed a series of robustness tests; (3) The mechanism analysis shows that the green industrial policy has a crowding-out effect on industrial development, but significantly enhances the ecological construction and protection, thus promoting the green development of agriculture; (4) Heterogeneity analysis shows that the policy has a significant positive incentive effect on the upper and lower reaches of the Yangtze River Economic Belt, and the incentive effect on the middle reaches is not significant; (5) The impact of technological level on agricultural green development shows a positive U-shaped relationship. The improvement of education and information development levels also effectively promotes the green development of agriculture. This paper provides important empirical evidence and factual references for further promoting the green development of agriculture and the improvement of green industrial policies.

Sustainable flood control strategies under extreme rainfall: Allocation of flood drainage rights in the middle and lower reaches of the yellow river based on a new decision-making framework

Climate change has exacerbated the frequency and magnitude of extreme rainfall, which has led to the perpetuation of flooding as a hazard to humans and society. China has begun to consider introducing Flood drainage rights (FDR), a sustainable flood control measure, into non-engineering measures as a complement to engineering measures for flood control. FDR represent the right of regions to discharge regional floodwaters caused by extreme rainfall into the river, and are the primary means of controlling the amount of floodwaters from regions when regional flood capacity is exceeded. However, existing studies on quantitative FDR allocation still have limitations, and some previous methods have resulted in allocation schemes that are not entirely reasonable and fair because they do not comprehensively consider the influencing factors of FDR or the allocation method is unreasonable. This paper explores the impact of flooding on rural and agricultural areas. We incorporate the factors of agricultural economy and security and construct a system of the allocation indicators of FDR composed of five principles: Natural Environmental Endowment, General Economic and Social Development, Agricultural Economy and Security, Macro policy regulation, and Respect for Historical Background. Second, considering the influence of expert judgment and data of different time nodes on the allocation of FDR, we introduce the concepts of expert weight and time weight into the allocation model of FDR, and construct a new set of framework for the allocation of FDR, i.e., "[(expert weight + subjective weight)+(time weight + objective weight)]+decision making model ". To reduce the loss of information during the transformation of subjective judgments, we also introduced triangular fuzzy numbers for the transformation between expert judgments and numbers. Finally, we take the five provinces in the middle and lower reaches of the Yellow River as an example. Using the data from 2010 to 2021, we obtain the final allocation scheme (proportion) of FDR as Henan (33.26%) > Shaanxi (23.08%) > Inner Mongolia (21.31%) > Shanxi (14.44%) > Shandong (7.91%). On this basis, this paper utilizes sensitivity analysis and comparative validation to demonstrate the rationality and effectiveness of the method, and identifies several indicators that have a greater impact on the results of the allocation of FDR. FDR can form part of a set of integrated flood management system together with flood control projects, which greatly alleviates the drainage conflicts arising from flooding caused by extreme precipitation. Under extreme rainfall conditions, FDR improves drainage efficiency and minimizes the overall damage caused by flooding in the watershed. This study can contribute to the sustainable development of the watershed and provide a reference for the promotion and utilization of sustainable flood control measures.

The impact of the digital economy on high-quality agricultural development--Based on the regulatory effects of financial development

The digital economy, as a new economic form with high information density, provides a new driving force for the realization of high-quality agricultural development. Panel data of 31 provinces in China from 2011 to 2020 were selected for analysis. The static panel data interaction effect model and panel threshold model were used to verify the nonlinear influence mechanism and heterogeneity of financial development in the process of the digital economy affecting high-quality agricultural development. The findings are as follows. (1) During the study period, the high-quality development of China's agriculture showed a steady upward trend; however, the regional differences were significant, and the eastern part was larger than the central and western part. (2) The digital economy can promote high-quality agricultural development. (3) The digital economy has a double threshold effect in the process of affecting high-quality agricultural development, which depends on the level of financial development. When the threshold is exceeded, the digital economy has a more significant promoting effect on high-quality agricultural development. (4) The impact of the digital economy on high-quality agricultural development is heterogeneous. From the perspective of different regions, the impact effect is greatest in the eastern region, while the effect is smaller in the central and western regions. From different resource endowments, the positive impact effect is greatest in the major grain-selling areas, followed by the major grain producing areas, but the positive digital economy driving effect is not significant in the balance of production and sales areas. Finally, three policy suggestions are proposed. First, the Chinese government should increase investments in and support for digital technology to promote the integration of the digital economy and agriculture. Second, the Chinese government should promote the development of digital inclusive finance in areas with financial development below the threshold. Third, different regions should implement differentiated digital economies to promote high-quality agricultural development.

Dynamic linkages between tourism development, renewable energy and high-quality economic development: Evidence from spatial Durbin model

There has been a shift in focus toward environmentally and economically sustainable forms of economic growth known as High-quality economic development (HQED). However, this study analyzes the impact of tourism development (TD) and renewable energy consumption on HQED in 30 provinces of China, while covering the time period from 2007 to 2021. TD and HQED has been measured with help of Global Moran Index. This study has used dynamic spatial Durbin model (SDM) to measure the dynamic impact of TD index and renewable energy consumption on HQED along with green finance, foreign direct investment and investment in education. The findings from empirical analysis shows that TD has negative impact on HQED and in more developed regions, the relationship is positive, while in the less developed western part of China, the U-shape has been reversed. Central and northeastern China have a U-shaped connection, while it has been noticed the interaction term of TD and renewable energy endorses HQED. In addition, renewable energy consumption, green finance and increase in education investment have positive and significant impact on HQED while foreign direct investment has negative impact on HQED in China. Therefore, in the light of this study policymakers should focus on the quality of tourism industry, green finance for renewable energy supply and enhancing education investment in China to attain the goal of HQED.

Relationship between the evaluation of agricultural scientific and technological innovation capacity and the influencing factors of green agriculture

China has limited arable land area, and its output value is increased with enhanced agricultural inputs such as machinery, irrigation, fertilizers, and pesticides. However, this mode is accompanied by an increase in agricultural carbon emissions. With the aim to further examine the driving effect of scientific and technological innovation on economic growth and green agriculture, this study uses the Solow growth model coupled with the Cobb-Douglas production function and vector autoregressive models. Then, the agricultural scientific and technological innovation capacity in Guangdong Province during 2006-2020 is evaluated by using the contribution rate of agricultural scientific and technological progress (ASTP) as the assessment index. In addition, the carbon footprints of green agricultural indexes such as machinery, irrigation, fertilizers, and pesticides are measured to analyze the relationship between green agriculture and agricultural scientific and technological innovation capacity. Results demonstrate the gradual increase in the contribution rate of ASTP in Guangdong Province. During the 11th, 12th, and 13th Five-Year Plan periods, the rates were 65.09%, 65.94%, and 70.40%, respectively, indicating that the agricultural scientific and technological innovation ability constantly improved. Among the indexes of green agriculture, the carbon footprints of machinery have a significant impact on agricultural scientific and technological innovation, which is quickly transformed into machinery. Such innovation requires the driving force of science and technology itself, which have relatively significant and rapid effects. On the basis of the results, corresponding policy suggestions are proposed: increasing investments in scientific and technological innovation in the agricultural field, vigorously developing new energy-saving and emission reduction products and processes for fertilizers, and increasing the research and promotion of agricultural machinery. The proposed method provides good prospects for the development of agricultural production towards mechanization, intelligence, efficiency, and greenness.

Can digital inclusive finance promote agricultural green development?

Digital inclusive finance (DIF) provides new momentum for green agricultural development (AGD). This paper measured AGD with entropy weight TOPSIS in five dimensions, including resource conservation, environmental friendliness, ecological conservation, green supply, and economic growth. After that, it estimated the regional spillover effects and threshold impacts of DIF on AGD utilizing China's provincial panel data from 2011 to 2020. The paper shows that (1) DIF and AGD have such a U-shaped complex interrelationship; (2) the AGD is spatially impacted by DIF. The unique manifestation is that as DIF has increased, its effect on AGD has steadily changed from being direct to being indirect, and this effect has regional heterogeneity; and (3) in regions with higher levels of green technology innovation, better development of traditional finance, or relatively concentrated agricultural industries, DIF plays a more prominent role in promoting the AGD.

Environmental regulations, green development of agriculture, and residents' health-empirical analysis of Yangtze River Economic Belt in China

Environmental pollution and food safety have become key public health issues to be addressed in China. Since they are closely related to the green development of agriculture, it is of great practical significance to elucidate the intrinsic relationships between green development of agriculture, environmental regulation and residents' health. Based on the panel data of the Yangtze River Economic Belt from 2011 to 2020, this study investigates the impacts of environmental regulation and green development of agriculture on residents' health and the influencing mechanism by applying fixed effects method, mediating effectsmethod and the spatial Dubin method. Results show that the use of chemical fertilizers, pesticides and agricultural films is harmful to residents' health; environmental regulation has a negative correlation with the green development of agriculture and affect residents' health through mediating effects; the green development of agriculture has negative spillover effects on residents' health, indicating that purchasing finished products instead of producing locally reduces the input of production factors such as chemical fertilizers and pesticides and transfers health risks associated with agricultural production activities to neighboring areas. Intensifying command-and-control environmental regulation will induce the expansion of hidden economic activities and harm local residents' health, while intensifying market-incentive environmental regulation will lead to the 'Pollution Haven' phenomenon because of the 'race to the bottom', in government and is harmful to the health of residents in neighboring areas. Therefore, it is necessary to formulate reasonable and feasible policies and strengthen the control and prevention of agricultural pollution to enhance green development of agriculture and improve residents' health.

Niche Suitability Evaluation and Path Selection for the High-Quality Development of Cities in the Yellow River Basin

The urban development in the Yellow River basin (YRB) varies widely. Therefore, it is necessary to choose a development path that fits the characteristics of each city to achieve high-quality development. The purpose of this paper is to address the problem of how to choose a characteristic path for high-quality development and clarify its suitability for YRB cities. Firstly, based on data from 50 YRB cities from 2011 to 2020, the suitability evaluation was carried out from the perspective of an ecological niche, followed by the measurement of sub-dimensional niche breadth and overlap. The results confirmed the great diversity of development between cities and the intense competition for resources. Then, based on the classification approach using the k-means method, this study proposes a method for selecting a suitable path for high-quality development. It classifies the suitable paths into 3 major types with 7 minor types and recommends policies for the suitable paths for YRB cities. The systematic thinking and specific path selection method for the high-quality development of YRB cities is not only of practical significance for implementing city classification strategies but also provides a reference for the sustainable development of basin cities in other countries.

How Can Digital Financial Inclusion Promote High-Quality Agricultural Development? The Multiple-Mediation Model Research

In order to balance the relationship between economics, society and environment, the Chinese government has stated that China's economy should shift from high-speed growth to high-quality development. Since agriculture is the foundation of the national economy, high-quality development of agriculture plays significant roles in the achievement of food security, social stability and environmental sustainability in China. In practice, the expansion of digital financial inclusion (DFI) seems to provide valuable opportunities for the development of high-quality agriculture. Nevertheless, in theory, the extant literature ignores exploration of the close relationships between DFI and high-quality agricultural development (HQAD). Hence, using Chinese provincial panel data from 2011 to 2020 and structural equation model (SEM) in STATA 16.0, this paper attempts to investigate whether and how DFI can enhance HQAD. Analysis reveals that (1) DFI can directly promote HQAD; (2) DFI can indirectly facilitate HQAD through the mediator of farmland transfer (FLT); (3) DFI can indirectly promote HQAD through the mediator of farmland mechanization level (FML); (4) compared with the benefits brought by "high-mechanization", the benefits brought by "large-scale" farmland transfer policies are much greater. To our knowledge, our research is one of the first to investigate the direct and indirect effecting mechanisms of DFI's influence on HQAD from the perspectives of farmland scale and farmland technology.

Spatial-temporal evolution and convergence analysis of agricultural green total factor productivity-evidence from the Yangtze River Delta Region of China

Measuring regional differences in agricultural green total factor productivity (AGTFP) provides a basis for policy guidance on agricultural green development in the Yangtze River Delta (YRD) region. By constructing a two-period Malmquist-Luenberger index under the carbon emission constraint, we measure the AGTFP of cities in the YRD region from 2001 to 2019. Furthermore, adopting the Moran index method and the hot spot analysis method, this paper analyzes the global spatial correlation and local spatial correlation of AGTFP in this region. Moreover, we investigate its spatial convergence. The results show that the AGTFP of 41 cities in the YRD region is on an increasing trend; the growth of AGTFP in the eastern cities is mainly driven by green technical efficiency, while this growth in the southern cities is mainly stimulated by green technical efficiency and green technological progress. We also find a significant spatial correlation between cities' AGTFP in the YRD region from 2001 to 2019, but with certain fluctuations, showing a U-shaped trend of "strong-weak-strong". In addition, absolute β convergence of the AGTFP exists in the YRD region, and this convergence speed is accelerated with the addition of spatial factors. This evidence provides support for implementing the regional integration development strategy and optimizing the regional agricultural spatial layout. Our findings offer implications for promoting the transfer of green agricultural technology to the southwest of the YRD region, strengthening the construction of agricultural economic belts and agricultural economic circles, and improving the efficiency of agricultural resource use.