Financial Support For Agriculture Research Articles

Unveiling the Dynamics of Rural Revitalization: From Disorder to Harmony in China’s Production-Life-Ecology Space

This study utilizes provincial panel data from China spanning the period from 2011 to 2020 to assess the coupled and coordinated development of spatial functions related to production, life, and ecology (PLE) in rural areas. The assessment is based on quantifying the spatial function indices for PLE in China’s rural regions. Additionally, it examines the characteristics of their spatial and temporal evolution, spatial correlation, and driving factors. The findings indicate a modest upward trend in the spatial coupling and coordination levels of these functions across rural China, although a significant proportion of provinces still exhibit a near-disordered decline. Exploratory spatial data analysis reveals a geographical disparity, with higher levels of coupled and coordinated development observed in the eastern regions, lower levels in the west, and noticeable spatial clustering. By employing the spatial Durbin model to investigate the determinants of coupling degrees, we discovered that factors such as regional economic development, urbanization, the urban–rural income gap, financial support for agriculture, science and technology investment level, and agricultural structural adjustments significantly influence the spatial coupling of rural PLE functions. Furthermore, using the geographic detector model, the analysis identifies science and technology investment level, economic development, and financial support for agriculture as key drivers influencing the spatial coupling and coordination of these functions. These findings provide valuable reference points for policies and strategies related to rural management.

Financial Support for Agriculture, Agricultural Mechanization Service and Agricultural Economic Development -- An Empirical Study Based on Provincial Panel Data

Financial Support for Agriculture, Agricultural Mechanization Service and Agricultural Economic Development -- An Empirical Study Based on Provincial Panel Data

Can the digitalization level of agriculture improve its ecological efficiency under carbon constraints: Evidence from China

The interplay between digitalization and economic development constitutes a pivotal global issue, yet empirical research on agricultural ecological efficiency in developing countries remains limited. This study initially establishes a measurement system and a comprehensive index for the level of agricultural digitalization. Subsequently, it delineates the relationship between agricultural digitalization level and agroecological efficiency using the spatial Durbin model, and ultimately explores the enhancing effect of agricultural digitalization level on agroecological efficiency using China as a case study. Research reveals that the agricultural ecological efficiency across the 31 mainland Chinese provinces demonstrates a generally linear upward trajectory, embodying both agglomeration and heterogeneity. The level of agricultural digitization exerts a significant, positive direct impact and facilitates a spatial spillover effect on agricultural ecological efficiency. Other control variables, such as financial support for agriculture and local economic development, impart a positive direct impact on regional agricultural ecological efficiency, while rural household operating income propels a positive spatial spillover effect on adjacent areas. The findings furnish guidance for developing countries to adeptly execute digital rural construction, aiming to enhance agricultural ecological efficiency amidst carbon constraints.

The Impact of Internet Use on Land Productivity: Evidence from China Land Economy Survey

Enhancing land productivity is a crucial strategy for addressing key sustainable development issues, such as poverty reduction and ensuring food security. Farmers’ Internet use behavior offers the potential to improve land productivity. However, relatively little is known about the association between Internet use and land productivity. To fill this void, this study examines the impact of Internet use on land productivity and its mechanisms. The results indicate that farmers’ use of the Internet has a positive impact on improving agricultural land productivity. Internet use increases land productivity by 12.3%, and the conclusion still holds after a series of robustness tests and endogeneity tests. Heterogeneity analysis indicates that Internet use significantly enhances land productivity in the central and northern parts of Jiangsu Province, while it does not have the same effect in the province’s southern regions. Without the addition of county fixed effects, the central sample regression results show that the coefficient for Internet use is 0.165 and significant at the 10% confidence level. When county fixed effects are added, the coefficient decreases to 0.117 and is not significant. The coefficient on Internet use for the northern sample is 0.128 and is significant at the 5% confidence level. Mechanistic analyses demonstrate that Internet use also enhances land productivity primarily by expanding the cultivated land area, facilitating mechanized production, and strengthening farmers’ social networks. The results of the study indicate that the positive effects of Internet use in improving land productivity should be fully released by strengthening the communication infrastructure, further enhancing farmers’ Internet use capacity, improving the land transfer system, upgrading the socialized service level of agricultural machinery, and strengthening agricultural financial support.

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

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

How do environmental regulations and financial support for agriculture affect agricultural green development? The mediating role of agricultural infrastructure

Environmental regulations and financial support for agriculture have been respectively proved as important means to break through the dilemma of agricultural green development in China. While their interactive influences on agricultural green development are rarely focused, as well as the mediation mechanism. This paper provides an interactive perspective by exploring the direct and indirect mechanisms affecting the relationship between environmental regulations, financial support for agriculture, and agricultural green development, among which the mediating effects of agricultural infrastructure, are further discussed. Based on the provincial panel data for China from the year 2000 to 2021, this paper constructs a fixed effect model, mediating effects model, and threshold panel model to empirically test the direct and indirect effects of environmental regulations and financial support for agriculture on agricultural green development. The results show that: (1) The full sample of agricultural green development in China shows an M-shaped trend, environmental regulations and financial support for agriculture show spatial and temporal heterogeneity among regions. (2) Environmental regulations, financial support for agriculture, and their interaction all have positive effects on agricultural green development, while their interactive effect is greater. (3) Agricultural power facilities not only significantly mediate the relationship between financial support for agriculture and agricultural green development, but also play a mediating role in the positive effect of the interaction between environmental regulations and financial support on agricultural green development. While rural transportation facilities only significantly mediate the positive effect of the interaction between environmental regulations and financial support for agriculture on agricultural green development. (4) Heterogeneity analysis results show that the effect of the interaction between environmental regulations and financial support for agriculture on agricultural green development is greatest in agricultural optimized developing areas; however moderate developing areas are insignificant. This research contributes to understanding how environmental regulations and financial support for agriculture affect agricultural green development and extends the mediating role of agricultural infrastructure in their relationships.

Analyzing the Impact of Digital Inclusive Finance on Poverty Reduction: A Study Based on System GMM in China

This study investigates the potential of digital financial inclusion to reduce regional poverty in China, an issue that has received varying opinions from the academic community. Using panel data from 31 provinces, municipalities, and autonomous regions (2011–2020) and employing the system GMM, this paper analyzes the dynamic relationship between regional poverty and the growth of digital financial inclusion, as measured by the ‘Peking University Digital Financial Inclusion Index’. Controlling for factors such as the Gini coefficient, industrial structure, financial support for agriculture and education, and economic openness, this research finds that digital financial inclusion has a marked ability to reduce poverty rates. Moreover, our results indicate an intergenerational transmission characteristic in poverty, where prior levels significantly influence current poverty incidence. The study concludes that the recent acceleration of digital financial inclusion can be harnessed for meaningful poverty reduction. This study’s policy recommendations highlight the need for financial development to foster industrial and social growth and stress the importance of financial education for low-income populations. Additionally, it calls for increased management and oversight of inclusive and agricultural digital financial products and services.

The influence of agricultural policy on carbon emissions in selected OECD countries

Global agriculture is actively impacted by policies which affect the composition and location of produce and the production methods. This paper examines how agricultural policy affects carbon emissons in 27 OECD countries over the period 2000 to 2020. This research deploys the Generalised Methods of Moments (GMM) and Pooled Mean Group (PMG) to analyse panel data. The study findings demonstrate that the indicators of agricultural policy (agricultural financial support and producer protection ratio) predominantly display a significantly positive relationship with emissions in the short term. Still, that link is mostly significantly negative in the long run. As such, agricultural policy is a driver of emissions in the short run, which is in line with the extended STIRPAT model, although in the long run, the variable seizes to be a driver. Economic growth, transport services and human capital support that their association is positively significant in the short run, chiefly negative and significant in the long run. There is overwhelming evidence that renewable energy is negatively and significantly associated with emissions in both periods. This research analysis is imperative to create vital cornerstones towards a complete understanding of the effects of agricultural policy on developing green economies.

Analysis of the spatial-temporal evolution of Green and low carbon utilization efficiency of agricultural land in China and its influencing factors under the goal of carbon neutralization

Agricultural land is the most basic input factor for agricultural production and an essential component of terrestrial ecosystems, which plays a vital role in achieving carbon neutrality. Giving full play to the carbon-neutral contribution of agricultural land is a crucial part of China's economic transformation and green development. It incorporates carbon and pollution emissions from agricultural land use into the unexpected outputs of the Green and Low-carbon Utilization Efficiency of Agricultural Land (GLUEAL) evaluation system. The study utilized several advanced analytical tools, including the super-efficient Slacks-Based Measure (SBM) model, Exploratory Spatial-Temporal Data Analysis (ESTDA) method, Geodetector, and Geographically and Temporally Weighted Regression (GTWR) model. The objective was to examine the spatial-temporal evolution of GLUEAL and identify the factors that influenced it in all 31 provinces of China from 2005 to 2020. The results show that: (1) The overall spatial-temporal evolution of GLUEAL showed an increasing trend, but the disparity between provinces and regions became wider. (2) Most provinces have not yet made significant spatial and temporal jumps. They have high spatial cohesion with specific "path-dependent" characteristics. (3) The Geodetector results reveal that the Number of Rural Labor Force with Higher Education (NRLFHE) and Technology Support for Agriculture (TSA) have insufficient explanatory power on average for GLUEAL. Agricultural Economic Development Level (AEDL), Urbanization Level (UL), Multiple Crop Index (MCI), Planting Structure (PS), Degree of Crop Damage (DCD), Financial support for agriculture (FSA), and Agricultural mechanization level (AML) had stronger explanatory power on average for GLUEAL and were important factors influencing GLUEAL levels. (4) The average influence of AEDL, UL, FSA, and AML on GLUEAL changed from negative to positive. The average influence of MCI and DCD on GLUEAL was negative, and the average influence of PS on GLUEAL changed from positive to negative. This study provides a comprehensive description of the spatial and temporal evolution of GLUEAL in China. It reveals the key factors influencing GLUEAL and analyzes their spatial variations and impact patterns. These findings offer robust evidence for government policymakers to formulate policy measures for sustainable agricultural development and optimized resource allocation, promoting the transformation of agricultural land towards green and low-carbon practices and advancing the achievement of sustainable development goals.

Improvement of Agricultural Supply Quality in China: Evidence from Jiangsu Province

Promoting the reform of the agricultural supply side and its quality improvement are crucial for realizing agricultural modernization. This paper tests the varied trajectory of agricultural total factor productivity (ATFP) in Jiangsu Province over the past 21 years. The paper used the three-stage DEA empirical analysis method—Stochastic Frontier Approach (SFA), to address the uncertainty in the development of the agricultural industry. The paper introduces environmental variables such as urbanization level, import and export trade, financial support for agriculture, and transportation convenience. The research results show that: (1) the ATFP growth in Jiangsu Province presents a fluctuating trend; (2) The further sub-index research of ATFP in Jiangsu Province shows that the average rate of growth for agricultural technology efficiency (AEC) in Jiangsu is negative, indicating that the input cost of agricultural factors in Jiangsu increases and marginal efficiency decreases; (3) The empirical analysis of ATFP growth by region shows that there are still large differences in agricultural economic development level, the level of modern agricultural technology and ATFP in the southern, the central and the northern parts of Jiangsu. (4) Stage III: DEA empirical results showed that improving urbanization level, net export trade, and transportation convenience is conducive to improving agricultural production efficiency; financial support for agriculture is weakly conducive to improving agricultural production efficiency. On this basis, the paper puts forward countermeasures and suggestions to promote agricultural structural reform.

Spatiotemporal evolution and convergence of agricultural eco-efficiency in the middle reaches of the Yangtze River

In the context of regional coordinated development, exploring the spatiotemporal evolution characteristics of agricultural eco-efficiency(AEE) in the middle reaches of the Yangtze River(MRYR) can provide decision support for the coordinated development of regional agriculture. This study proposes a theoretical hypothesis of AEE spatial convergence at the input-output level and uses the Super-SBM model, kernel density estimation, spatial autocorrelation and β-convergence model to calculate the spatiotemporal evolution and convergence characteristics of AEE in the MRYR from 2005 to 2020. The results show that (1) from 2005 to 2020, the AEE of the study area increased from 0.665 to 0.864, with the average efficiency of Hubei, Jiangxi, and Hunan reaching 0.794, 0.767, and 0.724, respectively; and (2)the overall spatial convergence rate of AEE is 0.045, and there is a phenomenon of “club convergence” between regions. The spatial convergence rates of Jiangxi, Hubei, and Hunan are 0.053, 0.063, and 0.048, respectively. The convergence rate slows down over time, (3) The farmers' living standards, per capita GDP, and technological level have promoted the improvement of AEE. Multiple planting indices and financial support for agriculture have not had a positive effect on the improvement of AEE. The region should strengthen the exchange and cooperation of agricultural production and pay attention to the pollution discharge problem of agricultural production.

Temporal and Spatial Effects of Heavy Metal-Contaminated Cultivated Land Treatment on Agricultural Development Resilience

Heavy metal-contaminated cultivated land treatment (HMCLT) plays an essential role in the realization of sustainable utilization of cultivated land resources and sustainable agricultural development. Evaluating this policy’s impact on agricultural development resilience (ADR) has great practical significance. This paper reveals the impact HMCLT has on ADR from the perspectives of time and space, utilizing data from Hunan province between 2007 and 2019. The synthetic control method (SCM) and spatial Durbin model (SDM) are employed for investigating the temporal and spatial effects HMCLT has on ADR. The results demonstrate that the HMCLT policy has effectively improved the pilot cities’ ADR and can enhance ADR in adjacent areas from a spatial perspective. In addition to HMCLT policy, financial support for agriculture, farmers’ per capita disposable income, and rural population density are key factors affecting ADR. However, they all have a crowding-out effect on the ADR in neighboring areas. Due to these circumstances, while the governments make efforts in promoting the policy design and improvement of HMCLT, increasing the disposable income of farmers, narrowing regional differences in government financial support and human capital, and promoting regional interactions are essential to enhance ADR. This study formulates valuable insights for policymakers and researchers in the field of sustainable agricultural development.

The carbon emission reduction effect of agricultural policy——Evidence from China

China has a high agricultural output and is a significant carbon emitter; thus, reducing carbon emissions in the agricultural sector is crucial for achieving carbon neutrality. To address this, China implemented the National Agricultural Sustainable Development Experimental Demonstration Zone policy in 2018, in which reducing agricultural carbon emissions (ACE) is a subject of concern. We explore the impact of the policy on agricultural carbon emissions reduction (ACER) using the propensity score matching and differences-in-differences (PSM-DID) methods with a series of robustness tests based on the panel data of prefecture-level cities in China from 2011 to 2020. The results indicate that: (1) the policy significantly reduces carbon emissions and impacts carbon emission sources, with the results passing the robustness tests. (2) According to the mechanism test, agricultural financial support mediates carbon emissions reduction, and the policy reduces these emissions by decreasing the intensity of fiscal support. (3) The heterogeneity analysis illustrates that the carbon emissions reduction effect is more evident in cities with a small urban-rural income gap and a high proportion of agricultural output value. Finally, we provide suggestions to reduce carbon emissions from the perspective of national and local governments. This paper is particularly relevant for achieving sustainable agriculture development.

Green-Biased Technical Change and Its Influencing Factors of Agriculture Industry: Empirical Evidence at the Provincial Level in China

The continued expansion of agriculture must contend with the dual pressures of changing factor endowment structure and constrained resources and environments. The main purpose of this paper is to provide feasible ideas for high-quality agricultural development in the transition period through the research on the green-biased technical change in Chinese agriculture. This paper selects China's provincial panel data of the agriculture industry from 1997 to 2017, combining the DEA-SBM model and Malmquist-Luenberger index decomposition method to calculate the green-biased technical change (BTC) index; second, the influence mechanism of BTC is empirically investigated by using the panel data regression analysis approach. The results show that: (1) in China's agriculture industry, BTC is the driving force behind long-term and steady improvement of technological advancement. Specifically, input-biased technical change (IBTC) has a substantial enhancing effect on agricultural green total factor productivity (GTFP), whereas output-biased technical change (OBTC) has a certain inhibiting effect. (2) On the whole, the tendency of capital substituting for labor and land is very evident, whereas the biased advantage of desirable output is not particularly prominent. (3) The BTC index in Chinese agriculture varies regionally. The eastern region has the highest IBTC index but the lowest OBTC index. (4) The degree of marketization, urbanization, capital deepening, financial support for agriculture, and other factors have a promoting effect on IBTC, whereas most of them have a restraining effect on OBTC. There is evident regional heterogeneity in the effect of environmental regulation intensity on BTC. The following are the primary contributions of this paper: based on national conditions in China, this paper empirically explores the changes and internal rules of green-biased technical change in China's agriculture industry from various regional viewpoints. It provides an empirical foundation for the regional diversification of agricultural green transformation.

Evaluating the Spatiotemporal Characteristics of Agricultural Eco-Efficiency Alongside China's Carbon Neutrality Targets.

Agriculture has the dual effect of contributing to both carbon emissions and sequestration, and thus plays a critical role in mitigating global climate change and achieving carbon neutrality. Agricultural eco-efficiency (AEE) is an important measurement through which we can assess the efforts toward reduced emissions and increased sequestration. The purpose of this study was to understand the relationship between China's target of carbon neutrality and AEE through an evaluative model, so as to improve AEE and ultimately achieve sustainable agricultural development. The Super-SBM model scientifically measures the AEE based on provincial panel data collected between 2000 and 2020. We selected kernel density function and spatial distribution to explore the spatial and temporal evolutionary trends, and used a Tobit model to identify the drivers of AEE. The research shows that (1) China's agricultural system functions as a net carbon sink, with all provinces' agricultural carbon sequestration levels recorded as higher than their carbon emissions from 2000 to 2020. (2) Despite sequestration levels, the level of AEE in China is not high enough, and the average efficiency level from 2000 to 2020 is 0.7726, showing an overall trend where AEE decreased at first and then increased. (3) The AEE of each province is clearly polarized; there are obvious core-periphery characteristics and spatial distribution of clustered contiguous areas. Central provinces generally have lower efficiency, eastern and northeastern provinces have higher efficiency, and northeastern provinces always remain in the high-efficiency group. (4) Influencing factors show that urbanization, upgrading of industrial structure, financial support for agriculture, and mechanization have a significant positive impact on AEE. These findings have important implications for the promotion of the low-carbon green development of Chinese agriculture.

The Dual Effects of Environmental Regulation and Financial Support for Agriculture on Agricultural Green Development: Spatial Spillover Effects and Spatio-Temporal Heterogeneity

Environmental regulation and financial support for agriculture are regarded as important means to promote agricultural green development. Based on provincial panel data of 31 provinces in China between the years 2000 and 2020, this paper explores the interactive effect, spatial spillover effect and spatio-temporal heterogeneity of environmental regulation and financial support for agriculture on agricultural green development. The empirical conclusions are as follows: (1) The level of agricultural green development increases year by year with a spatial characteristic of high in the east and low in the west. Moreover, there is a spatial spillover effect of agricultural green development with spatiotemporal heterogeneity. (2) Environmental regulation would not only reduce the level of local agricultural green development but also inhibit the adjacent regions, which is contrary to the impact of financial support for agriculture. (3) The interactive relationship of environmental regulation and financial support for agriculture has a spatial spillover effect on agricultural green development, which is more significant in the systematization stage of agricultural green development and most significant in the east-middle region.

Research on the Impact of Agricultural Financial Support on Agricultural Carbon Compensation Rate

Based on the consideration of the dual attributes of agricultural carbon emission and carbon sink, this study measures the agricultural carbon compensation rate (ACCR) of 31 provinces in China from 2006 to 2019, the impact of agricultural financial support on ACCR and its transmission mechanism are empirically analyzed using a spatial econometric model and intermediary effect model. The results show that: (1) a significant spatial correlation between agricultural financial support and ACCR; (2) increased agricultural financial support is conducive to the improvement of ACCR; (3) agricultural financial support has the most significant effect on the ACCR in the eastern region; (4) the effect of agricultural financial support on ACCR has a spatial spillover effect but is not significant; (5) agricultural technological progress is the intermediary variable that agricultural financial support affecting ACCR. Therefore, it is suggested to promote agricultural emission reduction through collaboration, innovative financial support mechanisms, implementation of differentiated financial support strategies, exerting the radiation effect of financial support to agriculture, and pushing up the level of agricultural mechanization.

Spatial correlations and driving mechanisms of low-carbon agricultural development in china

Low-carbon agricultural development in China is a prerequisite for rural revitalization and a key to achieving socio-economic green transformation. This paper used agricultural data from 30 Chinese provinces from 2001 to 2020, considering both carbon emissions from farming and livestock, agricultural low-carbon total factor productivity (ALTFP) was measured using the RSBM-GML index. Based on this, the network characteristics and driving mechanisms of low-carbon synergistic development in agriculture were explored with the help of an improved gravity model and social network analysis, and the dominant provinces in low-carbon synergistic development in agriculture are identified. The study revealed that the spatially linked network of ALTFP in China exhibits multi-threaded characteristics of spillover to non-adjacent provinces, and the whole network has a sparse structure and hierarchy. The eastern regions such as Beijing, Tianjin, Shanghai, Jiangsu, and Zhejiang are at the core of the network, with closer ties to other regions and a stronger role in allocating resources. While the western regions such as Xinjiang, Qinghai, and Gansu are located at the periphery of the network, with weaker access to the resources. Meanwhile, the spatial proximity of provinces, the widening of differences in urbanization levels and differences in financial support for agriculture, and the narrowing of differences in the educational attainment of rural labor have significantly contributed to the formation of provincial spatial linkages. This study reveals that China’s government needs to give full play to the role of core regions as “leaders”, and promote the balanced and coordinated regional development of low-carbon agriculture in China. In addition, policy makers should further optimize the spatial allocation of agricultural resource elements between provinces. The findings of the study provide reference suggestions for the development of regionally differentiated agricultural low-carbon development plans.

The Impact of Fiscal Support for Agriculture on Economic Development: Evidence from Fujian Province

Since the strategy of rural revitalization was put forward for the first time, it is necessary to deal with the issues related to the "three rural areas" in order to realize socialist modernization, and the government has focused on the financial expenditure on agriculture, so reasonable planning of financial support for agriculture is crucial to stabilize the development of agriculture. Agriculture, one of the most basic industries in the economic development, plays an important role in the growing economy. It has strong externalities, but its vulnerability dictates that it must be supported by government policies. Effective fiscal measures are essential to promote agricultural and economic development. In this sense, this paper collects the data of Fujian Province from 2010 to 2019. Firstly, the paper analyzes the current situation of financial support for agriculture in Fujian Province through the absolute scale and relative scale of financial support for agriculture and the differences in economic development of various cities in the province, and explores the problems of economic growth; secondly, we conduct the trend and correlation analysis of the scale of financial support for agriculture expenditure, and examine the impact of agricultural financial support on economic growth. Finally, we propose some feasible policy recommendations regarding financial support for agriculture to promote economic growth.

Spatial Analysis of Agriculture Ecological Efficiency and Its Influence on Fiscal Expenditures

The faster development of the agriculture sector has led to the excessive waste of agriculture resources and that development causes serious damage to the ecological environment. So, ecological agriculture has become an important topic to understand the relationship between agriculture and the environment. This study tries to examine the impact of agricultural fiscal expenditures on agricultural ecological efficiency. In the first step, the researcher found the ecological efficiency of agriculture. The second step tries to examine the agricultural fiscal expenditure impact on agriculture’s ecological efficiency. The study used data from 30 provinces of China from 1998 to 2018. For the empirical results, the researcher used the super-efficiency DEA window analysis in the first step. Moreover, we used the spatial Durbin model in the second step. The results of the study revealed that China’s agricultural ecological efficiency shows a downward trend to an upward trend. The efficiency value of the eastern region is higher than the central region’s efficiency value, which is lower than the national average level. The western region’s efficiency value is equal to the national average level, and the differences between regions vary with the time period. The nuclear density of agricultural eco-efficiency in China showed a trend of “left-shift rising—double peaks—right-shifting decline”. In terms of space, China’s agricultural ecological efficiency has a significant positive spatial spillover effect, especially in the eastern and western regions. The results of the spatial Durbin model revealed that agricultural fiscal expenditures have a significant role in promoting China’s agricultural ecological efficiency. While agricultural governance has shown a significant spatial crowd-out effect. Therefore, it is proposed to promote the development of inter-provincial agricultural cooperation, and the formulation of agricultural financial support strategies should be green-oriented and should consider regional heterogeneity.