Super-efficiency Data Envelopment Analysis Research Articles

Quantitative analysis of spatiotemporal disparity of urban water use efficiency and its driving factors in the Yangtze River Economic Belt, China

Study regionYangtze River Economic Belt, China Study focusAs the major national strategic development area of China, there have always been vital problems about imbalance of the water resources distribution and the disparity of economic levels in YREB. Quantitative analysis of water use efficiency (WUE) is essential to the rational use of water resources, as well as the sustainable development. In this study, a WUE evaluation index system for prefecture-level cities in the YREB was constructed, and Super-Efficiency Data envelopment analysis Slacks-Based Measure (DEA-SBM) model, Global Malmquist-Luenberger productivity index, combined with geographically weighted regression model were utilized to measure and identify the spatiotemporal evolution characteristics of WUE and its influencing factors. New hydrological insights for the regionFrom the temporal perspective, the WUE manifests a significant upward trend from 2005 to 2020, and the growth presents lower reach > middle reach > upper reach; in the spatial pattern, the WUE has significant spatial divergence characteristics, high WUE mainly occurred in developed leading cities, while developing cities in the midstream and upstream tended to be inefficient; various effects on WUE were also analyzed, highlighting that technical advancement was the key driver of WUE evolution. Then the negative effects of industrial structure and urban environment was becoming more and more significant. Finally, effective measures for upstream, middle and downstream cities in the YREB were discussed.

Assessment of truck driver safety efficiency based on data envelopment analysis

This paper introduces a safety efficiency evaluation framework that integrates Data Envelopment Analysis (DEA) and Super-Efficiency Data Envelopment Analysis (SE-DEA) for quantitatively assessing the safety of truck drivers. The framework utilizes data from onboard equipment to capture drivers’ dangerous behaviors and poor driving states. Subsequently, it evaluates safety efficiency using the DEA combination model, providing safety rankings. Improvement suggestions are offered to underperforming drivers based on slack variable values. The proposed method is compared with EWM-Topsis and Critic-Topsis models using fixed weights, demonstrating better stability. The study’s outcomes enable freight companies to identify high-risk drivers and offer personalized, targeted safety training.

A [formula omitted]-Number Slacks-Based Measure DEA model-based framework for sustainable supplier selection with imprecise information

The focus of this study is to develop a decision-making framework for selecting sustainable suppliers with imprecise information. Sustainable supplier selection poses a significant challenge for managers and decision-makers seeking a long-term competitive edge. Due to the presence of unreliable, or partially reliable imprecise information in practice, incorporation of the reliability degree of imprecise information in the decision models becomes necessary. Since Z-numbers can incorporate the reliability degree of imprecise information, the Z-number-based “Data Envelopment Analysis (DEA)” approach can be used for decision-making. The current study introduces a super-efficiency DEA approach, namely “Z-number Slacks-Based Measure (ZN-SBM)”, which is further used to construct a framework for selecting sustainable suppliers. Unlike the existing Z-number-based DEA approaches, the proposed ZN-SBM model can assume “constant returns-to-scale”, “variable returns-to-scale”, “non-increasing returns-to-scale”, and “non-decreasing returns-to-scale” conditions. Moreover, the developed framework is free from strategic weight manipulation. To demonstrate the efficacy of this framework in sustainable supplier selection, we present a case study of the automotive industry. Further, the robustness of the proposed framework is investigated through a sensitivity analysis. The results of this study reveal that the proposed framework can be effectively applied as a high-performing decision-support tool for decision-making under imprecision in the domain of sustainable supplier selection.

Evaluation of Ecological Efficiency and Analysis of Its Influencing Factors in Provincial Coastal Regions Using Integrated Super-Efficiency DEA and Tobit Models

Abstract With the rapid development of the Chinese economy, the demand for resources has increased significantly, putting the environment under increasing pressure. Effectively using various resources has become crucial. This study employs the Super-Efficiency Data Envelopment Analysis to assess ecological efficiency during the same period and conducts a residual analysis on cities with high efficiency but not efficiently analyzed by Data Envelopment Analysis. The primary objective of this approach is to investigate the potential ecological development of these regions. The dynamic assessment of ecological efficiency is done using the Malmquist index, which takes into account changes in the total factor output growth rate. To investigate factors that affect ecological efficiency and their magnitudes, a Tobit model is being established using panel data. From 2017 to 2022, there were changes in ecological benefits among cities in Zhejiang Province due to intense competition between high-efficiency cities and frequent position changes, as evidenced by the results. The gap between cities with middle to low efficiency is narrowing, which suggests that ecological benefits are being balanced in the province despite a decreasing trend. Both the degree of openness and the proportion of asset investment have a significant and positive impact on ecological efficiency. Enhancing interregional communication, optimizing resource allocation, increasing openness, and adjusting industrial layout is essential to sustain technological innovation and progress.

Rural revitalization helps rural e-commerce level development efficiency-Based on DEA model

Abstract The rural revitalization strategy is underway and can provide the promotion of high-quality growing rural e-commerce as well as supply the facilities and industrial support required for its growth. The complete score of the rural e-commerce development level was assessed using the entropy value technique by analyzing data from 31 Chinese provinces, municipalities, and autonomous regions. The efficiency of rural e-commerce growth was evaluated using the BCC model and the super-efficient DEA model within the DEA model. The study examined the effects of rural revival on the effectiveness of electronic commerce in rural development. Both input and output views were considered when selecting the related factors. After that, the productivity value was examined by merging information on the growth of rural e-commerce between 2016 and 2020. The research indicates that between 2015 and 2022, the comprehensive score of rural e-commerce growth experienced a high-quality increase of 173.50%. Furthermore, 8 out of 31 provinces, municipalities, and autonomous areas had DEA-achieved e-commerce development efficiency, with a mean complete efficiency score of 0.700. However, the mean value of total efficiency decreased by 35.29% when the progress level of rural rejuvenation was eliminated. Apart from providing support for infrastructure construction, rural revitalization can also provide policy assurances and an industrial base for the expansion of rural electronic commerce.

Research on the Water Environment Governance of Hangzhou Bay Based on the DEA–Tobit Model

With rapid urbanization and industrialization, Hangzhou Bay faces significant pressure in water environment governance. This study, based on panel data from 2011 to 2021 in Zhejiang’s Hangzhou, Jiaxing, Shaoxing, and Ningbo, employs the Super-Efficiency DEA model to assess water environment governance performance. The Tobit model analyzes external environmental factors. Findings reveal fluctuating water governance efficiency during the study period, with inefficiencies from 2012 to 2019, followed by significant improvement from 2019 to 2021. Key factors impacting governance include urban water environment performance in Hangzhou, urban residents’ disposable income, population density, and secondary industry GDP development. A higher urban income enhances environmental awareness and governance performance, while population density and industrial GDP intensify resource use, energy consumption, and wastewater discharge, worsening governance pressures and performance. This research offers insights for enhancing water environment governance in Hangzhou Bay, aiding in the formulation of protection plans and management policies. Additionally, it provides valuable experiences for watershed governance globally.

Analysis of the Spatial Correlation Network Structure of Agricultural Water Use Efficiency in Northwest China

There are some problems in Northwest China, such as the fragile ecological environment, poor basic conditions of agricultural production, low efficiency of agricultural water use, and difficulty in clarifying the path of agricultural water use efficiency (AWUE) improvement. Based on the superefficiency data envelopment analysis (DEA) model, this study increases the amount of ‘green water’ resources in the agricultural water consumption index of the input index and increases the wastewater pollutants (total chemical oxygen demand emissions; total ammonia nitrogen emissions) in the undesired output index to measure the AWUE in the northwest region. Based on the calculation results of AWUE, combined with the modified gravity model, the connection strength of AWUE between any two provinces in Northwest China is calculated, and the spatial structure and network characteristics of AWUE in this area are analysed via the social network analysis (SNA) method. The results show that the average AWUE in 2020 is nearly two times higher than that in 2011. From the situation of the northwest provinces, the average AWUE of the five provinces is in the order of Qinghai > Shaanxi > Gansu > Ningxia > Xinjiang. The AWUE value, total population, real GDP and per capita GDP of the capital cities of the five provinces in Northwest China are the key factors for the improvement of the connection intensity of AWUE. From 2011 to 2020, the connection intensity and closeness of AWUE in Northwest China increased, and there was a clear network hierarchy. The improvement in overall AWUE in the region is mainly due to the radiation and driving effect of the central province on other provinces. Based on this, the study proposes policy recommendations for gradually realising the AWUE improvement path of the central province (Shaanxi; Gansu)—cooperation circle (Shaanxi–Ningxia; Gansu–Qinghai)—the whole region. The results provide theoretical support and a quantitative basis for optimising the spatial pattern of agricultural water resources and improving AWUE in Northwest China.

Research on Forest Ecological Product Value Evaluation and Conversion Efficiency: Case Study from Pearl River Delta, China

Exploring an effective scientific method to measure the economic benefits of ecological products is of great significance for green development. Based on the InVEST model, this paper, taking the Pearl River Delta (PRD) as an example, evaluated the FEPs value in the PRD from 2000 to 2015; using a super-efficient DEA model, the conversion efficiency of ecological products was estimated, and its temporal and spatial variation characteristics were analyzed using the Malmquist index. The results showed that the value of FEPs in the PRD shot up during 2000–2015, and that the regulation services value is the main part of FEPs, followed by the value of cultural service. The overall conversion efficiency of FEPs is improving. However, cities differ greatly. Technical efficiency is the key driving factor for improving forest product conversion efficiency. The main reasons for the current efficiency loss are redundant inputs and insufficient outputs. This paper also suggests that conversion efficiency is a convincing method to evaluate the degree of transformation of ecological environment resources into economic benefits and the degree of ecological and economic coordinated development.

Research on the Influencing Factors of The Green Coordinated Development of Productive Service Industry and Manufacturing Industry Under the Background of Dual Carbon

Under the dual-carbon background, along with the process of the two-wheel drive development strategy, the industrial synergistic agglomeration has quietly become the "new normal" of urban industrial spatial layout, and the green total factor productivity has become an essential measure of the quality of economic development of cities in China. This project takes the synergistic agglomeration at the factor level between the productive service industry and manufacturing industry as the perspective and analyzes the realization mechanism of green total factor productivity growth under the synergistic agglomeration of the manufacturing industry and productive service industry from the current situation of China's industrial development, which is also a deepening and expanding of the theory of agglomeration economy. This project first discusses the "greening" issue in the development process of the productive service industry and manufacturing industry, and applies the super-efficient DEA model to account for the green total factor productivity of the productive service industry and manufacturing industry according to the difference of industrial characteristics, and then expounds the inner mechanism of green total factor productivity growth under the synergistic agglomeration of industries. Then, the panel data of 24 provinces in China are used to modify the existing indexes for measuring the level of industrial synergistic agglomeration and analyze the impact factors of the synergistic evolution of the productive service industry and the manufacturing industry on the green total factor productivity. Finally, through scenario simulation analysis, different policy scenarios with different policy incentives are set up to study the impact of policy incentives further and propose corresponding policy recommendations.

Multi-step impacts of environmental regulations on green economic growth: Evidence in the lens of natural resource dependence

Whether and how environmental regulation and resource dependence contribute to green economic growth has been a focus of academic discussion. This paper analyzes the multi-stage transmission mechanism based on environmental regulation to promote green economic growth, especially the important transmission mechanism of resource dependence. The green economic growth and environmental regulation indicators of 286 Chinese cities were measured from 2003 to 2018 using the Metafrontier Global Slack-Based Measure (SBM) super-efficient Data Envelopment Analysis (DEA) approach and Fuzzy Comprehensive Evaluation (FCE) method. In addition, resource dependence indicators are investigated. Spatial panel and multiple mediator models are used to test the one- and two-step transmission mechanisms of resource dependence concerning the effect of environmental regulation on green economic growth. The results show that resource dependence plays a mediating role in the one-step transmission mechanism. Resource dependence further affects green economic growth by influencing the industrial structure, quality of the government system, foreign investments, technological innovation, manufacturing development, and physical capital, thus constituting a two-step transmission mechanism. Finally, we suggest a new method based on the environmental regulation policy in China, which can be used to break the “curse” of urban resources and realize green economic growth.

What Type of Energy Structure Improves Eco-Efficiency? A Study Based on Statistical Data of 285 Prefecture-Level Entities in China

Increasing environmental pollution, resource depletion, and climate change have led to policymakers paying increased attention to the environmental and ecological impacts of economic activities. To establish which type of energy structure is most conducive to improving eco-efficiency, we use the super-efficiency data envelopment analysis (DEA) model to quantify the relationship between the two, based on the panel data of 285 prefecture-level cities in China from 2005 to 2016. The heterogeneity and spatial spillover effect on different types of cities are further discussed. Our findings suggest that energy structure optimization by reducing the proportion of coal energy is beneficial to improving ecological efficiency. However, the effect is nonlinear, showing an inverted U-shaped nonlinear change. The influence of energy structure optimization on ecological efficiency has a stronger effect on its improvement of resource-based and old industrial cities. Moreover, it has an obvious “local–neighborhood” spatial spillover effect. Additionally, the energy structure could be improved according to local conditions in different regions, such as the level of economic development, industrial structure, and resource endowment conditions. Furthermore, regional cooperation and coordination should be strengthened and consolidated, along with the positive spatial effects of high eco-efficiency cities. Especially in city clusters and metropolitan areas, the strengthening of cross-city cooperation in emission trading, environmental governance, and compensation is vital.

An integrated approach of discrete event simulation and a non-radial super efficiency data envelopment analysis for performance evaluation of an emergency department

An emergency department (ED) has been considered as one of the most congested department in a hospital. The congestion is typically contributed by long waiting time to get medical service, primarily caused by insufficient resource allocation or improper resource configurations. However, how various resource allocation configurations affect ED performance and how their efficiency can correctly be evaluated, using an integrated approach is rarely discussed. This paper thus integrates discrete event simulation (DES) and data envelopment analysis (DEA) to measure ED performance and evaluate the efficiency of potential resource allocation configurations for future performance improvement. For this, a DES model for an ED is first designed and developed. Its performance improvement is then tested using 35 potential resource allocation configurations, and their impacts on the performance are measured. To evaluate their efficiency and identify the optimal configuration, a mixed integer super efficiency of slacks-based measure data envelopment analysis (SE-SBM-DEA) approach dealing with undesirable outputs is proposed. The model utilizes resource allocation as inputs and simulation performance measures as outputs. All inputs were considered as integer, while the outputs were classified into desirable and undesirable in mixed integer-valued data. The desirable real outputs are the utilization of receptionists, nurses and doctors. The undesirable real outputs are the average of patient cycle time and time spent in queues, while the undesirable integer output is average number of patients in queues. The desirable integer output is average number of patients received treatment. The results obtained from the DEA approach show that 21 efficient resource configurations have the capability to increase their inputs, undesirable outputs and/or decrease desirable outputs simultaneously without affecting their efficiency status. The integrated approach helps decision makers manage their healthcare facilities by identifying the sources of inefficiency and (the maximum levels of inputs-undesirable outputs and minimum levels of desirable outputs) to improve and (retain) efficiency.

Analysis of regional differences in green energy efficiency in countries along “the Belt and Road” Initiative zone—Based on super efficiency DEA model and Malmquist index method

This study uses the super-efficiency DEA model and Malmquist index analysis to evaluate the green energy efficiency of 58 countries along “the Belt and Road” Initiative zone from 2012 to 2021 and uses Tobit regression to analyze the external environmental influences on their green energy efficiency. The results of the study show that in the static analysis, The overall green energy efficiency of 58 countries along the “the Belt and Road” initiative area is low, and there are obvious regional differences; In terms of dynamic analysis, the Malmquist Index shows a slight fluctuation trend from 2012 to 2021. Tobit regression models show that external factors such as economic strength, energy consumption structure, industrial structure, and R&D expenditure are significantly and positively related to green energy efficiency. Based on this, this study proposed that countries should make good use of their resource advantages to improve the overall green energy efficiency of “the Belt and Road” Initiative zone according to local characteristics; strengthen inter-regional cooperation and exchange among countries, and implement outbound strategies to create a favorable development environment for green energy efficiency in “the Belt and Road” Initiative zone. Create a favorable development environment for green energy efficiency in “the Belt and Road” Initiative region.

A study on the measurement of operational efficiency of commercial banks--Analysis based on super-efficient DEA model and Malmquist index

The banking sector has a risk-intensive character and early warning of the risk of commercial bank failures is particularly important. In order to measure the efficiency of commercial banks in Poland and provide a cut-off line for bank failure efficiency, this paper firstly adopts the dichotomous method to pre-process the existing data, then selects three representative input indicators and two output indicators to construct an evaluation index system for bank efficiency, and uses the super-efficiency DEA model to measure the efficiency of banks, and concludes that comprehensive technical efficiency inhibits the rise of bank efficiency, and the efficiency of banks in 2017 -2021 banks' efficiency showed a zigzag fluctuation trend; secondly, based on the static analysis of super-efficient DEA, the dynamic efficiency of banks was estimated and decomposed based on the Malmquist index method; finally, the failure cut-off was determined by testing whether there was a significant difference in the mean values.

Efficiency of zakat institutions in Indonesia: data envelopment analysis (DEA) vs free disposal hull (FDH) vs super-efficiency DEA

PurposeZakat is an important Islamic economic instrument that plays significant role in Sustainable Development Goals. Accordingly, Zakat Institutions must manage zakat in a proper and efficient manner. This study aims to examine the efficiency of Zakat Institutions based on their clusters which are government, business and social organizations.Design/methodology/approachThis study uses three quantitative methods: data envelopment analysis (DEA), free disposal hull and super-efficiency DEA. The analytical method is based on production approach, variable return to scale assumption and output orientation. The sample consists of 14 Zakat Institutions from three clusters: Zakat Institutions managed by government, Zakat Institutions managed by corporation and Zakat Institution managed by social organizations.FindingsThe results revealed that all of three techniques culminate the same ranking order of efficiency. Zakat Institution managed by the government is the most efficient Zakat Institution, with the average value of 0.87 by using three approaches combined. Meanwhile, Zakat Institutions owned by company and social institutions cluster are in second and third position, with the average value of 0.65 and 0.4, respectively, based on the results of the three approaches. This study contends that the level of efficiency of Zakat Institutions may be supported by clusters (affiliations) in their management.Research limitations/implicationsThis study’s limitation is the inadequacy of the required data. Nonetheless, this study provides insights to improve the efficiency of Zakat Institutions based on their clusters. Zakat Institutions in each cluster can improve their efficiency by optimizing inputs to produce multiple outputs.Originality/valueThis study enhances research on the efficiency of Zakat Institutions using three methods to assess the consistency and strength of Zakat Institutions’ efficiency values. In addition, this study examines the efficiency level of Zakat Institutions based on their clusters.

Regional Allocation Design and Efficiency Improvement of Rural Water Conservancy Project in China

Different development levels and speeds in different regions in China leads to the great difference in the allocation of rural water conservancy projects and the inefficiency. In order to improve the services function and configuration efficiency of rural China water conservancy infrastructure from water engineering, water supply engineering, reservoir engineering, the work chose the Chinese provincial panel data from 2017 to construct input-output indicator evaluation system with super-efficiency DEA. Then we designed the rural area of configuration of water conservancy projects for comparative analysis and China’s current rural water conservancy project region configuration system of geographical network coverage. Finally, based on the configuration in the grid lines, the method was proposed for efficiency. In order to analyze the regional difference in input-output efficiency of rural water conservancy construction, the panel data of 2017 was selected to establish the input-output indicator system of management efficiency. The results of super efficiency DEA show the general situation of input-output efficiency of rural water conservancy construction in China is not good, while there are some differences among input-output efficiency of rural water conservancy construction in East, West, Middle of China. Besides, Qinghai, Beijing, Hainan and Tibet are located in the last four. Finally, the four regions are all relatively effective with less than 100% super efficiency value, and four regions has redundant input in hydropower investment.

Efficiency Evaluation and the Impact Factors of Sustainable Forestry Development in China: Adoption of Super-Efficiency Data Envelopment Analysis and Malmquist Index Methods

Forestry is the underpinning of economic and environmental civilization for sustainable economic development. Forestry benefits ecosystems and local dwellings; thus, transforming and advancing forest products in a civilized society is critical to building a progressive community. This research aims to analyze the merits of forest products based on static, dynamic, and scale efficiency. It employed the super-efficient data envelopment analysis—Charnes, Cooper and Rhodes, and Malmquist index methods with an enhanced robustness check by applying the Stochastic Frontier Analysis. The results show that, first, from the perspective of static efficiency, the forestry industry’s operating performance is maintained at a relatively high level, with a minimal fluctuation range; however, the scale efficiency is observed at a deficient level. Limited by the scale efficiency results, the aggregate comprehensive technical efficiency was at a low standard. The average total factor productivity of dynamic efficiency for each company reached 1.029, indicating that the resource allocation of listed companies is relatively reasonable, operating efficiency is on the rise, and technical level changes are a substantial source of total factor productivity growth. Furthermore, the super efficiency DEA findings indicated that 11 of the most high-performance companies attained an efficiency value above criterion value one after re-ranking. The comprehensive efficiency value of Sun Paper reached 1.438 in 2019, Sophia 1.393, Hexing Packaging 1.383, Fujian Jinsen 1.326, Bunny 1.271, Meike Home Furnishing 1.235, Jingxing Paper 1.222, Zhongshun Jiezou 1.116, Meiying Sen 1.099, Chenming Paper 1.064, Da Ya Dekor 1.015. Second, the comprehensive efficiency value of Fujian Jinsen’s company has a more significant impact on the overall average efficiency of the forestry listed companies. After excluding Fujian Jinsen, the average comprehensive efficiency of 2018–2019 indicated an upward trend for the listed companies. This study suggests that policymakers should strengthen the forestry industry development plan and policy implementation regulations to focus on the forward-looking and guiding principles of industrial and technological innovation policies.

DOES ENERGY EFFICIENCY MATTER FOR POVERTY ALLEVIATION AND ECONOMIC GROWTH? A FRESH EMPIRICAL INSIGHT FROM AN ASIAN PERSPECTIVE

Globally, everybody deals with poverty as a shared societal issue. It is still unclear how to investigate its causes and create new paradigms for policy, but it offers many promising directions for academic study. The use of technological innovation in this environment for social change to address poverty reduction is also an important issue. Consequently, this study investigates how effective poverty reduction may be accomplished in Asia through technological innovation and financial development. The super-efficiency data envelopment analysis model and system generalized method of moments were utilized in the present study together with data from 2010 to 2020 for an empirical estimate. The data show that different areas have effectively reduced poverty over time. However, Asia’s overall effectiveness in reducing poverty is rather unevenly distributed geographically. The significance of poverty reduction in Asia is positively impacted by technical advancement and financial prosperity. The effects of globalization on the efficacy of poverty reduction are negligible. This study presents some policy insights for decision makers based on the empirical findings.

Assessing the eco-efficiency of industrial parks recycling transformation: Evidence from data envelopment analysis (DEA) and fuzzy set qualitative comparative analysis (fsQCA)

Industrial parks are essential for promoting regional economic development, yet their linear growth model has become unsustainable. Hence, implementing the industrial park recycling transformation (IPRT) is necessary and urgent. However, the current literature on IPRT performance evaluation and improvement has not kept up with practical developments. This study aims to evaluate the eco-efficiency of IPRT and identify the variables and configurations that affect its enhancement. To achieve this, the authors employed super-efficiency data envelopment analysis and fuzzy set qualitative comparative analysis to analyze data collected from 21 IPRT demonstration pilot parks. Drawing on the Technology-Organization-Environment framework, this study identified three configurations with high eco-efficiency and two configurations with non-high eco-efficiency for IPRT. The findings indicate that eco-efficiency varies significantly among different parks and is the result of multiple factors and interactions, with environmental supervision playing a pivotal role. Additionally, the results suggest that the local economic development level and the technological capacity of parks are substitutable. Parks in regions with modest economies tend to focus on environment-technology-oriented transformations, while external factors drive IPRT of parks in areas with developed economies. These findings offer guidance for parks to adopt appropriate strategy profiles and provide policy options for governments.

Effect of Fiscal Expenditure for Supporting Agriculture on Agricultural Economic Efficiency in Central China—A Case Study of Henan Province

The policy guidance and financial support for industrial development from public finance provide an important guarantee for practicing green and circular development of agriculture. By sorting out the development context of fiscal support for agriculture in Henan province in different historical stages, this paper analyzes the development status of fiscal support for agriculture and the agricultural circular economy in the province. Relying on data envelopment analysis (DEA), it measures the efficiency of the agricultural circular economy in Henan province in 2013–2019 using the Charnes, Cooper, and Rhodes (CCR) model, the Banker, Charnes, and Cooper (BCC) model, and super-efficiency DEA models and empirically analyzes the effect of the fiscal expenditure for supporting agriculture on the efficiency of the agricultural circular economy using the fixed effect model. According to the results, (1) the expenditure on comprehensive agricultural development of Henan Province was mainly supported by the government’s fiscal funds to such a degree that the proportion of fiscal funds from the central government exceeded 40% throughout the year. Particular stress was laid on the land governance projects of comprehensive agricultural development in the province. (2) The overall development level of the agricultural circular economy in Henan Province was low, and there were considerable gaps between cities (counties). Under the super-efficiency DEA model, only Hebi City, which ranked first in terms of average efficiency, achieved relative efficiency. (3) The fiscal expenditure for supporting agriculture had a positive incentive effect on the efficiency of the agricultural circular economy in Henan province, and the incentive effect became more significant after the time effect was controlled. Accordingly, this paper puts forward some targeted policy suggestions, which enrich the existing research on fiscal support for agriculture and agricultural circular economy at both theoretical and practical levels.