Financial Support Efficiency of Rural Revitalization: Based on Three-Stage DEA Model and Malmquist Index Model

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper titled “Efficiency of Financial Support to Rural Revitalization: Based on Three-Stage DEA Model and Malmquist Index Model” presents a quantitative analysis of financial support efficiency in rural revitalization across Chinese provinces. The paper yields methodological rigor, specifically the application of the three-stage DEA model and Malmquist index to assess both static and dynamic efficiency but it also need some revisions in order to improve its scope and value-added. I have the following comments and suggestions for the authors:

1. The authors need to clearly connect the paper’s findings to the broader context of sustainable development goals (e.g., SDG 1: No Poverty, SDG 8: Decent Work and Economic Growth) and sustainability concept in general.

2. It would be useful to highlight how financial efficiency improvements can directly promote sustainable rural livelihoods, environmental protection, and inclusive economic growth.

3. The Literature review needs to be extended. The authors might want to incorporate global studies on financial support efficiency and rural sustainability to contextualize findings within international frameworks.

4. It would be useful to include references discussing financial systems' role in achieving rural resilience and environmental sustainability.

5. Policy recommendations need to be extended. The authors need to provide actionable strategies to address regional disparities in financial support efficiency. For instance, how to enhance digital financial infrastructure for remote regions, or or how to introduce sustainability-linked financial incentives.

6. It would be useful to summarize the three-stage DEA and Malmquist methods concisely while retaining technical appendices for readers interested in details.

7. It would also be useful to extend the list of references. Some key studies on rural revitalization and sustainability should be added, such as works on rural financial development, sustainable agriculture, and digital financial tools.

8. Last but not least, the authors need to make sure that the paper is proofread and all minor flows in English are corrected.

Author Response

1. The authors need to clearly connect the paper’s findings to the broader context of sustainable development goals (e.g., SDG 1: No Poverty, SDG 8: Decent Work and Economic Growth) and sustainability concept in general.

We appreciate the reviewer’s comment. We have made changes in the revised version. (Section 1, Page No 2).

“In summary, the current research lacks an in-depth analysis of the efficiency of financial support for rural revitalization. Compared to poverty alleviation, measuring the efficiency of rural revitalization proves more challenging because of its multifaceted nature, which encompasses dimensions such as industrial prosperity, ecological livability, rural civilization, effective governance, and life affluence \cite{renEfficiencyFundingRural2024}. Therefore, to gain insights into the efficiency of financial support for rural revitalization, this study selects 30 provinces in China as measurement units, based on the "Rural Revitalization Strategy Planning (2018-2022)". Taking the period from 2011 to 2020 as the evaluation period, this study employs the entropy method to measure the comprehensive level of rural revitalization in these 30 provinces. Subsequently, the three-stage Data Envelopment Analysis (DEA) and Malmquist index models are applied to evaluate the efficiency of China's financial support for rural revitalization from both static and dynamic perspectives. This study further enriches the theory and methodology for evaluating the effectiveness of financial support for rural revitalization. The results of this study provide a decision-making basis for China's financial support for the sustainable development of rural areas.”

2. It would be useful to highlight how financial efficiency improvements can directly promote sustainable rural livelihoods, environmental protection, and inclusive economic growth.

Reply: Thank you for your valuable comments. We have made the appropriate changes in the revised version (Section 1, Page No 2).

“Improving the efficiency of financial support is key to promoting sustainable rural development. Enhanced financial efficiency ensures that financial resources flow more precisely and efficiently into the key areas of rural development. Wang et al. [14] discovered that the expansion of bank branches resulted in increased financial penetration, which consequently raised the income of rural households and decreased the likelihood of them falling back into poverty. Qian et al. [2] noted that, in comparison to traditional financial services, emerging financial services exhibit a notably more favorable impact on the income and consumption patterns of rural residents. Lin and Peng’s [15] findings show that digital finance can significantly contribute to rural development.”

• Qian, Z.; Tu, Y.; Zhou, Z. The Impact of Financial Development on the Income and Consumption Levels of China’s Rural Residents. JOURNAL OF ASIAN ECONOMICS 2022, 83, 101551. https://doi.org/10.1016/j.asieco.2022.101551.
• Wang, X.; Wang, Y.; Zhao, Y. Financial Permeation and Rural Poverty Reduction Nexus: Further Insights from Counties in China. China Economic Review 2022, 76, 101863. https://doi.org/10.1016/j.chieco.2022.101863.
• Lin, H.; Peng, P. Impacts of Digital Inclusive Finance, Human Capital and Digital Economy on Rural Development in Developing Countries. Finance Research Letters 2025, 73, 106654. https://doi.org/10.1016/j.frl.2024.106654.

3. It would be useful to include references discussing financial systems' role in achieving rural resilience and environmental sustainability.

Thank you for your valuable comments. We have revised in the revised version (Section 1, Page No 2).

“Finance is an essential factor in driving rural revitalization. As the lifeblood of real economic development, it plays a crucial role in fostering rural resilience and promoting environmental sustainability [ 11 – 13].”

• Xu, Q.; Zhong, M.; Dong, Y. Digital Finance and Rural Revitalization: Empirical Test and Mechanism Discussion. Technological Forecasting and Social Change 2024, 201, 123248. https://doi.org/10.1016/j.techfore.2024.123248.
• Gong, Q.; Zhang, R. Digital finance as a catalyst for energy transition and sustainable rural economic growth. Finance Research Letters 2025, 71, 106405.https://doi.org/10.1016/j.frl.2024.106405.
• Wu, Y.; Zhang, J. Digital inclusive finance and rural households’ economic resilience. Finance Research Letters 2025, 74, 106706. https://doi.org/10.1016/j.frl.2024.106706.

4. The Literature review needs to be extended. The authors might want to incorporate global studies on financial support efficiency and rural sustainability to contextualize findings within international frameworks.

Reply: We appreciate the reviewer’s comment. We have revised Section 1 in the revised version (Section 1, Pages No 1-2).

Since its inception, China’s rural revitalization strategy has emerged as a pivotal national development priority. As a crucial pillar of the modern economic landscape, finance holds significant importance in fostering rural economic growth, enhancing farmers’ living standards, and driving agricultural modernization [1-3]. High-quality and effective financial resource allocation is a prerequisite and foundation for giving full play to the effectiveness of financial support for rural revitalization. A full understanding of the effectiveness of financial support for rural revitalization is the only way to allocate financial resources in a scientific and reasonable manner, better assist rural revitalization, and achieve sustainable development in villages. However, owing to the unique characteristics of rural areas, including their remote geographical locations, diverse economic development levels, and underdeveloped financial service systems, notable regional disparities exist in the efficiency of financial resource allocation [4]. Thus, developing effective means to gauge the effectiveness of financial support for rural revitalization and ensuring the optimal allocation and efficient utilization of financial resources remain key challenges.

Rural revitalization has rich connotations, covering five aspects: industrial prosperity, ecological livability, rural civilization, effective governance, and life affluence [5]. Since the concept of rural revitalization was put forward, academics have explored its multiple dimensions of rural revitalization in depth, including the construction of an evaluation system and the analysis of influencing factors [6-8]. However, many scholars have pointed out that despite the significance of the rural revitalization strategy, it still faces many challenges in its implementation. These challenges include the monolithic nature of the rural industrial structure, lack of capital, backwardness of technology, and lack of human resources [9,10].

Finance is an essential factor in driving rural revitalization. As the lifeblood of real economic development, it plays a crucial role in fostering rural resilience and promoting environmental sustainability [11-13]. Improving the efficiency of financial support is key to promoting sustainable rural development. Enhanced financial efficiency ensures that financial resources flow more precisely and efficiently into the key areas of rural development. Wang et al. [14] discovered that the expansion of bank branches resulted in increased financial penetration, which consequently raised the income of rural households and decreased the likelihood of them falling back into poverty. Qian et al. [2] noted that, in comparison to traditional financial services, emerging financial services exhibit a notably more favorable impact on the income and consumption patterns of rural residents. Lin and Peng’s [15] findings show that digital finance can significantly contribute to rural development.

Data envelopment analysis (DEA), a non-parametric approach for efficiency evaluation, has been extensively utilized to assess the efficiency of public sectors, enterprises, and specific policies or projects[16-19]. Its advantage is that it does not require knowledge of a specific production function while efficiently managing multiple inputs and outputs. In recent years, this approach has received much attention in studies on the efficiency of rural poverty alleviation as well as the efficiency of financial support. Yang et al. [20] evaluated the effectiveness of anti-poverty policies in China using a two-stage data envelopment analysis model. Chen et al. [21] employed a type-2 fuzzy data envelopment analysis (DEA) model to quantify the relative efficiency of rural poverty reduction initiatives in Hainan Province. Wang et al. [22] utilized the Super-SBM model to evaluate the effectiveness of tourism-based poverty alleviation programs in 40 districts and counties in the Liupan Mountain region of Gansu Province, China, over a period of 10 years from 2009 to 2018. Xiao et al. [23] conducted a dynamic evaluation of poverty reduction efforts in China based on the non-convex global two-stage Data Envelopment Analysis (DEA) and the Malmquist index model. Wang et al. [24] used a two-stage dynamic DEA model to measure and analyze the spatio-temporal evolution of agricultural production efficiency and poverty reduction in China. Xue and Li [25] applied the DEA-Malmquist index to evaluate the efficiency of financial support for agricultural industrialization. Lu and Zhang [26] evaluated the efficiency of financial support for high-tech industries using the DEA model and the DEA-Malmquist index.

5. It would also be useful to extend the list of references. Some key studies on rural revitalization and sustainability should be added, such as works on rural financial development, sustainable agriculture, and digital financial tools.

Reply: Thank you for your valuable comments. We have extend the list of references in the revised version.

“Rural Financial Development:

[2] Qian, Z.; Tu, Y.; Zhou, Z. The Impact of Financial Development on the Income and Consumption Levels of China’s Rural Residents. JOURNAL OF ASIAN ECONOMICS 2022, 83, 101551. https://doi.org/10.1016/j.asieco.2022.101551.

[4] Fan, S.; Jiang, M.; Sun, D.; Zhang, S. Does Financial Development Matter the Accomplishment of Rural Revitalization? Evidence from China. INTERNATIONAL REVIEW OF ECONOMICS & FINANCE 2023, 88, 620–633. https://doi.org/10.1016/j.iref.2023.06.041.

• Wang, X.; Wang, Y.; Zhao, Y. Financial Permeation and Rural Poverty Reduction Nexus: Further Insights from Counties in China. China Economic Review 2022, 76, 101863. https://doi.org/10.1016/j.chieco.2022.101863.

Sustainable Agriculture:

• Li, Y.; Wu, W.; Liu, Y. Land consolidation for rural sustainability in China: Practical reflections and policy implications. Land Use Policy 2018, 74, 137–141. https://doi.org/10.1016/j.landusepol.2017.07.003.

[12] Gong, Q.; Zhang, R. Digital finance as a catalyst for energy transition and sustainable rural economic growth. Finance Research Letters 2025, 71, 106405. https://doi.org/10.1016/j.frl.2024.106405.

[19] Guo, C.; Zhang, R.; Zou, Y. The Efficiency of China’s Agricultural Circular Economy and Its Influencing Factors under the Rural Revitalization Strategy: A DEA-Malmquist-Tobit Approach. AGRICULTURE-BASEL 2023, 13, 1454. https://doi.org/10.3390/agriculture13071454. 457

[24] Wang, J.; Tong, J.; Fang, Z. Assessing the Drivers of Sustained Agricultural Economic Development in China: Agricultural Productivity and Poverty Reduction Efficiency. SUSTAINABILITY 2024, 16, 2073. https://doi.org/10.3390/su16052073.

[30] Wei, L.; Wang, Y.; Zhou, Z.; Luo, J. Unlocking the Effects and Optimization Path of Financial Support for Improvement in Environmental Quality and Rural Revitalization Development: An Empirical Analysis Based on Provincial Data of Shaanxi Province. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2023, 30, 46795–46812. https://doi.org/10.1007/s11356-023-25569-6.

Digital Financial:

• Xu, Q.; Zhong, M.; Dong, Y. Digital Finance and Rural Revitalization: Empirical Test and Mechanism Discussion. Technological Forecasting and Social Change 2024, 201, 123248. https://doi.org/10.1016/j.techfore.2024.123248.
• Gong, Q.; Zhang, R. Digital finance as a catalyst for energy transition and sustainable rural economic growth. Finance Research Letters 2025, 71, 106405.https://doi.org/10.1016/j.frl.2024.106405.
• Wu, Y.; Zhang, J. Digital inclusive finance and rural households’ economic resilience. Finance Research Letters 2025, 74, 106706. https://doi.org/10.1016/j.frl.2024.106706.
• Lin, H.; Peng, P. Impacts of Digital Inclusive Finance, Human Capital and Digital Economy on Rural Development in Developing Countries. Finance Research Letters 2025, 73, 106654. https://doi.org/10.1016/j.frl.2024.106654.

[29] Liu, Y.; Wan, Q.; Chen, W. Digital Inclusive Finance as a Catalyst for Rural Revitalization: An Empirical Analysis from the County Development Perspective in Hubei Province. JOURNAL OF THE KNOWLEDGE ECONOMY 2023. https://doi.org/10.1007/s13132-023-01493-5.

[30] Xiong, M.; Fan, J.; Li, W.; Xian, B.T.S. Can China’s Digital Inclusive Finance Help Rural Revitalization? A Perspective Based on Rural Economic Development and Income Disparity. FRONTIERS IN ENVIRONMENTAL SCIENCE 2022, 10, 985620. https://doi.org/10.3389/fenvs.2022.985620.

[31] Xiong, M.; Fan, J.; Li, W.; Xian, B.T.S. Can China’s Digital Inclusive Finance Help Rural Revitalization? A Perspective Based on Rural Economic Development and Income Disparity. FRONTIERS IN ENVIRONMENTAL SCIENCE 2022, 10, 985620. https://doi.org/10.3389/fenvs.2022.985620.

[32] Xia, D.s.; Kong, C.L. The Impact of Digital Inclusive Finance on Rural Revitalization: Evidence From China. JOURNAL OF ORGANIZATIONAL AND END USER COMPUTING 2024, 36, 337970. https://doi.org/10.4018/JOEUC.337970. ”

6. Policy recommendations need to be extended. The authors need to provide actionable strategies to address regional disparities in financial support efficiency. For instance, how to enhance digital financial infrastructure for remote regions, or or how to introduce sustainability-linked financial incentives.

Reply: Thanks for your valuable suggestion. We have made the appropriate changes in the revised version (Conclusions, Pages No 13)

“Based on the results analyzed in this paper, the following policy recommendations are made. First, tailor financial products to meet the risk tolerance of groups vulnerable to returning to poverty in remote rural areas with low levels of education, low incomes, and weak risk tolerance. Second, create a service model that integrates online and offline services to empower rural residents in remote areas to access financial services through online channels. Finally, utilize digital financial instruments to integrate agriculture-related data, encompassing rural construction projects, rural land rights, land transfers, agricultural insurance, agricultural subsidies, farmers' deposits, and farmers' borrowing and lending activities. Efforts should be made to accelerate the construction of national agriculture-related public data and information-sharing platforms, aiming to establish a unified national public data platform and enhance the convenience and efficiency of data utilization.”

7. It would be useful to summarize the three-stage DEA and Malmquist methods concisely while retaining technical appendices for readers interested in details.

Reply: We appreciate the reviewer’s comment. We have made the appropriate changes in the revised version (Section 2.2, Page No 4).

8. Last but not least, the authors need to make sure that the paper is proofread and all minor flows in English are corrected.

Reply: We appreciate the reviewer’s comment. We rechecked the manuscript and corrected all the linguistic problems found.

Reviewer 2 Report

Comments and Suggestions for Authors

1. We suggest replacing Figure 1 with a bar chart to avoid cluttered connections.
2. The author's first conclusion, 'The distribution of efficiency generally adheres to the pattern' East>Central>West>Northeast, 'with both the Western and Northeastern regions displaying efficiency levels below the national average,' is trivial and does not add any new insights. This conclusion is consistent with common sense and should not be considered a new discovery in the manuscript.
3. In the second conclusion, the author points out that "the overall efficiency of financial support for rural revitalization is declining, especially in the Northeast region." The author needs to clarify whether this trend is a monotonic decline? And we suggest that the author use more detailed indicators to analyze the reasons for the efficiency decline rather than simply describing the phenomenon. And the author needs to explain whether the decline in financial support efficiency is due to a decrease in government efficiency.
4. We suggest that the author add specific plans to improve the efficiency of financial support in the manuscript and simulate the effects of following these plans separately.

Author Response

1. We suggest replacing Figure 1 with a bar chart to avoid cluttered connections.

Reply: Thank you for your suggestion to replace Figure 1 with a bar chart to improve clarity. However, upon further consideration and attempts to implement this change, we found that even a bar chart would not adequately address the issue of cluttered connections in our original figure. Therefore, we decided to present the data in tabular format instead. This format allows for a more straightforward and organized presentation of information, facilitating easier understanding and analysis for readers. We hope that this change meets your approval and enhances the overall readability of our manuscript. (Section 4.3, Page No 10).

2. The author's first conclusion, 'The distribution of efficiency generally adheres to the pattern' East>Central>West>Northeast, 'with both the Western and Northeastern regions displaying efficiency levels below the national average,' is trivial and does not add any new insights. This conclusion is consistent with common sense and should not be considered a new discovery in the manuscript.

Reply: We appreciate the reviewer’s comment. We have made the appropriate changes in the revised version (Abstract, Conclusions).

“abstract

Financial resources play a crucial role in rural revitalization. Understanding the efficiency of financial support is essential for the scientific and rational allocation of these resources. Therefore, we conducted an assessment over the period 2011-2020, utilizing the three-stage DEA model and the Malmquist index model to measure the efficiency of financial support for rural revitalization across 30 Chinese provinces (excluding Hong Kong, Macao, Taiwan, and Tibet) from both static and dynamic perspectives. The results indicate the following: (1) Despite an overall downward trend, efficiency increased during specific intervals, namely 2012-2013, 2015-2016, and 2018-2019. (2) Regionally, the decline in the efficiency of financial support for rural revitalization is particularly notable in the northeast region. The eastern and central regions also experienced this trend to a lesser extent, whereas the western region experienced a more moderate decrease. However, a detailed analysis revealed that 10 provinces experienced efficiency gains. (3) Stochastic Frontier Analysis (SFA) regression results suggest that environmental variables have a measurable impact on the efficiency of financial support for rural revitalization.

Conclusions

Financial resources are crucial for rural development and constitute a significant factor in rural revitalization. A thorough understanding of the efficiency of financial support is essential for the scientific and rational allocation of financial resources, which in turn improves the utilization rate of these resources during rural revitalization. Based on this, we chose the years 2011-2020 as the assessment period, employing the entropy method to quantitatively evaluate the level of rural revitalization across 30 Chinese provinces  (excluding Hong Kong, Macao, Taiwan, and Tibet). Subsequently, we utilized the three-stage DEA and Malmquist index models from both static and dynamic perspectives to measure the efficiency of financial support for rural revitalization. The results of this study are as follows:

First, although there is an overall downward trend, the efficiency of financial support for rural revitalization has increased during specific intervals, namely the periods 2012-2013, 2015-2016 and 2018-2019.

Second, from a regional perspective, the decline in the efficiency of financial support for rural revitalization is particularly notable in the northeast region. The eastern and central regions have also experienced this trend to a lesser extent, whereas the western region has seen a more moderate decrease. However, upon closer examination of the specific situations in individual provinces, it becomes evident that the decline in the efficiency of financial support is not universal. Specifically, ten provinces experienced efficiency gains: Fujian, Hainan, and Shanghai in the East; Anhui and Hubei in the Central region; and Gansu, Guizhou, Qinghai, Xinjiang, and Yunnan in the West.

Third, the regression results from the Stochastic Frontier Analysis (SFA) suggest that environmental variables exert a measurable impact on the efficiency of financial support for rural revitalization.”

3. In the second conclusion, the author points out that "the overall efficiency of financial support for rural revitalization is declining, especially in the Northeast region." The author needs to clarify whether this trend is a monotonic decline? And we suggest that the author use more detailed indicators to analyze the reasons for the efficiency decline rather than simply describing the phenomenon. And the author needs to explain whether the decline in financial support efficiency is due to a decrease in government efficiency.

Reply: Thanks for your valuable suggestion. We have made the appropriate changes in the revised version (Conclusions, Page No 13).

• The author needs to clarify whether this trend is a monotonic decline?

“First, although there is an overall downward trend, the efficiency of financial support for rural revitalization has increased during specific intervals, namely the periods 2012-2013, 2015-2016 and 2018-2019.

Second, from a regional perspective, the decline in the efficiency of financial support for rural revitalization is particularly notable in the northeast region. The eastern and central regions have also experienced this trend to a lesser extent, whereas the western region has seen a more moderate decrease. However, upon closer examination of the specific situations in individual provinces, it becomes evident that the decline in the efficiency of financial support is not universal. Specifically, ten provinces experienced efficiency gains: Fujian, Hainan, and Shanghai in the East; Anhui and Hubei in the Central region; and Gansu, Guizhou, Qinghai, Xinjiang, and Yunnan in the West.”

• we suggest that the author use more detailed indicators to analyze the reasons for the efficiency decline rather than simply describing the phenomenon. And the author needs to explain whether the decline in financial support efficiency is due to a decrease in government efficiency.

The questions of the causes of the decline in efficiency and whether the decline in the efficiency of financial support is due to a decline in government efficiency are relatively complex and require more detailed and comprehensive analysis. To answer this question more accurately, we plan to specifically address it in a follow-up study, with a view to providing more detailed and in-depth insights into the field.

“This study has certain limitations. It primarily focuses on analyzing the change in the efficiency of financial support for rural revitalization, but the specific reasons behind this change have not yet been analyzed in depth. In view of this, we intend to further deepen our research to explore not only the specific reasons for the change in financial support efficiency for rural revitalization, but also to investigate whether this change is correlated with changes in government efficiency.”

4. We suggest that the author add specific plans to improve the efficiency of financial support in the manuscript and simulate the effects of following these plans separately.

Reply: Thank you for your valuable comments. We have made the appropriate changes in the revised version (Conclusions).

“Based on the results analyzed in this paper, the following policy recommendations are made. First, tailor financial products to meet the risk tolerance of groups vulnerable to returning to poverty in remote rural areas with low levels of education, low incomes, and weak risk tolerance. Second, create a service model that integrates online and offline services to empower rural residents in remote areas to access financial services through online channels. Finally, utilize digital financial instruments to integrate agriculture-related data, encompassing rural construction projects, rural land rights, land transfers, agricultural insurance, agricultural subsidies, farmers' deposits, and farmers' borrowing and lending activities. Efforts should be made to accelerate the construction of national agriculture-related public data and information-sharing platforms, aiming to establish a unified national public data platform and enhance the convenience and efficiency of data utilization.”

 

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The authors tackled my comments and suggestions in a sufficient way. All points have been taken on board. I think that the paper now deserves to be recommended to be accepted for publication.