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Article

The Impact of Industrial and Commercial Capital Influx on Sustainable Agricultural Development: Evidence from 30 Provinces in China from 2013 to 2022

by
Hongli Yang
and
Fengjuan Wang
*
Business School, Liaocheng University, Liaocheng 252000, China
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(1), 312; https://doi.org/10.3390/su17010312
Submission received: 15 December 2024 / Revised: 31 December 2024 / Accepted: 2 January 2025 / Published: 3 January 2025
Browse Figure
Figure 1
<p>Framework diagram of the mechanism of the impact of industrial capital and commercial capital on the sustainable development of agriculture.</p> ">
Versions Notes

Abstract

:
Promoting the sustainable development of agriculture is the basis of reducing the poverty rate, ensuring food security, and promoting common prosperity. In order to explore the impact of industrial capital and commercial capital on the sustainable development of agriculture, this paper starts from the perspective of agriculture and conducts empirical tests based on the panel data of 30 provinces in China (except Tibet) from 2013 to 2022, using the fixed-effect model and spatial spillover effect model. The results included the following: (1) industrial capital and commercial capital can significantly promote the sustainable development of agriculture, and this conclusion was still valid after endogenous test and robustness test; (2) a heterogeneity test showed that industrial capital and commercial capital has a stronger role in promoting the sustainable development of agriculture in non-major grain producing areas, areas with high marketization level and central and western regions; (3) the test of the transmission mechanism showed that industrial capital and commercial capital can promote the sustainable development of agriculture by optimizing agricultural production conditions, improving rural environment and promoting farmers’ poverty reduction and common prosperity; (4) further research showed that industrial and commercial capital has a positive spillover effect on the sustainable development of agriculture in neighboring areas while promoting the sustainable development of agriculture in this region. Based on the above conclusions, this paper puts forward some countermeasures and suggestions, such as improving rural infrastructure construction, strengthening efforts to guide industrial and commercial capital to the countryside, and paying attention to the differentiation of industrial and commercial capital investment development.

1. Introduction

With the rapid growth of the global population, the acceleration of urbanization, and the continuous development of the economy, ensuring food security, protecting natural resources, and promoting sustainable agricultural development have become the focus of social attention at home and abroad. As a country with a large population, China attaches great importance to the sustainable development of agriculture. As early as 2015, the Chinese Central Government promulgated the “National Agricultural Sustainable Development Plan (2015–2030)”, which made plans to guide the work of agricultural sustainable development. In 2024, the Chinese Central Government issued the “Guiding Opinions of the Ministry of Agriculture and Rural Affairs on Vigorously Developing Smart Agriculture”, aiming at promoting the development of smart agriculture, improving agricultural total factor productivity and the efficiency of agricultural and rural management services and thus promoting the sustainable development of agriculture. It can be seen that the realization of agricultural sustainable development requires advanced technology, excellent talents, and a large amount of capital and other production factors to invest in agriculture and rural areas. However, based on China’s early development strategy and urban–rural dual-development structure, a large number of production factors flowed to cities, which led to a lack of production factors for agricultural development, especially a shortage of capital factors. According to the data from the “Three Rural Issues” Internet Finance Blue Book of the Chinese Academy of Social Sciences, the gap in China’s “Three Rural Issues” finance reached 3.05 trillion yuan, which makes it difficult to meet the capital demand of rural development only by the government supporting agriculture and farmers’ own accumulation. In view of this, since 2013, the Chinese Government has issued the Central No.1 Document many times to guide industrial and commercial capital to go to the countryside so as to promote the transformation of agricultural modernization and realize rural revitalization. At present, China is in a critical period of forming a new type of relationship between workers and peasants and between urban and rural areas, which is “promoting agriculture through industry, bringing rural areas through cities, benefiting workers and peasants and integrating urban and rural areas” (Zhou and Zhong, 2024) [1]. Industrial capital and commercial capital are regarded as an important way to promote agricultural modernization and coordinated urban and rural development. Industrial capital and commercial capital not only bring scarce resources such as capital, technology, and talents but also drive farmers to increase their income and become rich through technology demonstration and market guidance, which improves the economy and environment in rural areas (Zhou et al., 2023) [2]. It plays an important role in developing modern agriculture and promoting the sustainable development of agriculture.
Industrial capital and commercial capital are still in the initial stage, and the relevant policies and systems are not yet perfect, which has brought some problems to agricultural development to some extent. First, the profit-seeking nature of industrial and commercial capital makes investment in cash crops with high returns, which is not conducive to food production; secondly, industrial capital and commercial capital are used to invest and build factories, and a large number of mechanical operations are used, which will cause pollution, affect the fertility of cultivated land, and harm the sustainable use of farmland (Shi and Tong, 2023) [3]; finally, industrial capital and commercial capital may weaken farmers’ dominant position, squeeze the living space of small farmers, and turn them into “marginal people”, which is not conducive to farmers’ development [4]. However, it is still impossible to draw a clear conclusion as to whether the impact of industrial and commercial capital on agricultural sustainable development is more beneficial than harmful or harmful than beneficial. Therefore, it is of great theoretical and practical significance to explore how industrial and commercial capital affects the sustainable development of agriculture for realizing agricultural modernization, ensuring national food security, and increasing farmers’ income. Especially in the context of the current global food safety challenge and the increasing constraints of resources and the environment, how to realize the sustainable development of agriculture through the intervention of industrial and commercial capital is a problem worthy of in-depth study.

2. Literature Review

At present, there is little discussion on the relationship between industrial and commercial capital and agricultural sustainable development in academic circles, but there are many studies on the effect of industrial capital and commercial capital based on agricultural sustainable development. For example, Gao and Ren (2020) analyzed the impact of industrial capital and commercial capital on farmers’ income and found that industrial capital and commercial capital can significantly promote farmers’ income [5]. Shao et al. (2024) once again proved that industrial capital and commercial capital can increase farmers’ income and further found that industrial capital and commercial capital mainly increased farmers’ non-agricultural operational income and wage income [6]. Yuan et al. (2023) discussed the influence of industrial and commercial capital on the development of agricultural industry from the perspective of the relationship between government and enterprises and made an empirical study by using the survey data of industrial and commercial enterprises in Jiangsu Province [7]. Jia et al. (2024) studied the influence of industrial capital and commercial capital on the development of geographical indications of agricultural products from the perspective of the development of rural characteristic industries and found that industrial and commercial capital can promote the development of geographical indications of agricultural products [8]. Huang and Chen (2022) explored the influence of industrial capital and commercial capital on farmers’ farmland transfer behavior based on the farmers’ survey data [9]. Jiang and Hu (2021) used CLDS data to analyze the influence of industrial capital and commercial capital on the “non-food” of agricultural land production from two perspectives: farmland circulation and mechanical substitution [10]. Ying et al. (2019) studied the development of industrial and commercial capital in China to promote rural economic growth [11]. Ramakumar (2012) studied India and found that public capital has a significant effect on poverty reduction on agricultural investment [12]. Prayitno et al. (2022) found that social capital will affect the quality of life of farmers [13]. In addition, some scholars have analyzed the impact of industrial capital and commercial capital on the improvement of rural human settlements (Zheng et al., 2022; Shao et al., 2024) [14,15]. It can be seen that scholars’ evaluation of industrial capital and commercial capital mainly focuses on farmers’ income, agricultural industry development, cultivated land utilization, the agricultural economy, farmers’ lives, and the rural environment. However, there is relatively little in-depth attention on how industrial capital and commercial capital specifically affect the sustainable development of agriculture.
On the other hand, the discussion of agricultural sustainable development focuses on its measurement standards and development status. Tang and Liu (2022) measured the ability of agricultural sustainable development by constructing an evaluation index system of agricultural sustainable development level from five aspects, namely population, society, economy, environment, and resources, and they found that the level of agricultural sustainable development in the Yangtze River Economic Belt rose slowly at first and then quickly [16]. Miao et al. (2021) measured the agricultural sustainable development ability by using the weighted comprehensive evaluation model from the four dimensions of agricultural economy; resources and environment; culture, science, and technology; and rural society and found that the comprehensive ability of agricultural sustainable development in the hilly and mountainous areas of southern China was in a benign growth trend [17]. Wang and Yu (2021) used the principal component analysis method to measure the level of agricultural sustainable development in China and found that the comprehensive index of agricultural sustainable development changed greatly from year to year, with obvious differences in regional development [18]. Cao (2020) used the ecological footprint model to analyze the sustainable development of agriculture and found that the ability of agricultural sustainable development in Guangxi Province was poor [19]. Zhang et al. (2019) studied China’s agricultural sustainable development ability by using the entropy method based on provincial panel data and found that China’s agricultural sustainable development index generally showed a trend of fluctuation and decline, then continued to rise, and then continued to decline [20]. In summary, the academic research on agricultural sustainable development has been relatively solid. Therefore, the present paper is based on the concept of sustainable agriculture, that is, adopting a certain method to ensure the sustainable development of agricultural products required by contemporary humans and their descendants through technological changes and institutional reforms, combined with the policy of the National Agricultural Sustainable Development Plan (2015–2030) promulgated by the central government in 2015. According to the research of Tang and Liu (2022), the index evaluation system of agriculturally sustainable development ability is constructed from five levels: the population system, social system, economic system, resource system, and environmental system [16]. It is worth noting that the recent research of Luo and Wu (2024) on rural capital and high-quality development of agricultural economy is closely related to this research [21]. Agricultural sustainable development is the basis of the high-quality development of agriculture, but this research focuses on the high-quality development of the agricultural economy, which is a part of the economic system in the agricultural sustainable development system, and this research has not been extended to the study of agricultural sustainable development.
Compared with the existing research, the possible marginal contributions of this paper are mainly the following: from the research perspective, focusing on the research on the relationship between industrial capital and commercial capital and agricultural sustainable development enriches the relevant research on the effect of industrial capital and commercial capital; on the transmission mechanism, from the perspective of optimizing agricultural production conditions, improving rural living environment, and realizing poverty reduction and common prosperity for farmers, the mechanism of industrial and commercial capital affecting agricultural sustainable development is sorted out, which expands the existing research mechanism; in the research content, the fixed-effect model and spatial econometric model were constructed to empirically study the influence effect and spatial effect of industrial and commercial capital on agricultural sustainable development and to clarify the difference of the influence of industrial capital and commercial capital on local and neighboring regions’ agricultural sustainable development.

3. Transmission Mechanism Analysis and Research Hypothesis

3.1. Analysis of the Direct Impact of Industrial Capital and Commercial Capital on the Sustainable Development of Agriculture

Capital is an important factor in agricultural production and management activities. The impact of industrial capital and commercial capital on the sustainable development of agriculture is mainly reflected in two aspects. First, industrial capital and commercial capital optimize the allocation of production factors, promote the transformation of traditional agriculture, and promote the sustainable development of agriculture. Industrial capital and commercial capital alleviate the problem of shortage of funds for agricultural development; bring modern production factors such as advanced technology, high-quality talents, and mature management experience to agricultural development; promote the transformation of traditional agricultural industries to modern agriculture (Wang, 2021) [22]; improve agricultural efficiency; and promote the sustainable development of agriculture. Secondly, industrial capital and commercial capital bring economies of scale and promote the sustainable development of agriculture. The economies of scale brought by the industrial capital and commercial capital are mainly reflected in two aspects: production scale and service scale (Zhao et al., 2024) [23]. Industrial capital and commercial capital have promoted land transfer, revitalized idle land, changed the scale diseconomies caused by land fragmentation (Yan and Zheng, 2022) [24], formed large-scale and intensive production, reduced agricultural production costs, improved agricultural economic benefits, and promoted sustainable agricultural development. With the transfer of the backbone labor force in rural areas, the remaining elderly, women, and children are unable to engage in agricultural production, and a large amount of arable land is idle. Industrial capital and commercial capital have promoted the internal and social division of labor in agriculture by investing in agricultural social services (Hu et al., 2021) [25], improved agricultural production efficiency, and achieved service scale economies. Therefore, the following research hypothesis is proposed:
Hypothesis 1. 
Industrial capital and commercial capital promote the sustainable development of agriculture by optimizing the allocation of production factors, achieving scale economies, and improving agricultural production benefits.

3.2. Analysis of the Transmission Mechanism of Industrial Capital and Commercial Capital Affecting Sustainable Development of Agriculture

Industrial capital and commercial capital can promote the optimization of agricultural production conditions, thus promoting the sustainable development of agriculture. Science and technology are the primary productive forces, and industrial capital and commercial capital provide strong support for the innovation and application of agricultural science and technology. Industrial capital and commercial capital usually have strong financial strength, which can invest in agricultural science and technology research and development, promote the upgrading and transformation of agricultural technology, and greatly improve agricultural production conditions (Feng et al., 2022) [26]. The development of agricultural science and technology can significantly improve agricultural production efficiency and reduce production costs, thus enhancing the overall competitiveness of agriculture. For example, by introducing intelligent agricultural technologies such as precision irrigation, automatic monitoring, and automatic harvesting, the fine management of agriculture is realized (Cao and Huang, 2022) [4], which reduces the waste of resources and environmental pollution and lays the foundation for the sustainable development of agriculture. Secondly, industrial capital and commercial capital have accelerated the improvement of agricultural mechanization (Zhang, 2016) [27], thus optimizing agricultural production conditions. By investing in agricultural machinery and facilities, such as tractors, harvesters, and irrigation systems, industrial and commercial capital can significantly improve the mechanization level of agricultural production (Jiang and Hu, 2021) [13], promote large-scale agricultural production, improve the efficiency and quality of agricultural production, and thus promote the sustainable development of agriculture.
Industrial capital and commercial capital have promoted the sustainable development of agriculture by optimizing agricultural production conditions. Specifically, industrial capital and commercial capital have promoted the development of agricultural science and technology and accelerated the level of agricultural mechanization, thus improving the efficiency and quality of agricultural production, reducing agricultural production costs and resource consumption, and promoting the sustainable development of agriculture. Therefore, the following research hypothesis is proposed:
Hypothesis 2a. 
Industrial capital and commercial capital promote the sustainable development of agriculture by promoting the optimization of agricultural production conditions.
Industrial capital and commercial capital can improve the rural environment, which is conducive to the sustainable development of agriculture. First, in the process of industrial capital and commercial capital, they provide certain financial support for the construction of environmental protection infrastructure such as sewage treatment. By promoting the construction of rural environmental protection infrastructure, industrial and commercial capital goes to the countryside, which effectively improves sewage treatment (Li et al., 2022) [28], protects rural water resources, and improves rural environmental quality. This not only improves farmers’ living conditions but also provides clean and safe water resources for agricultural production, ensuring the stability and sustainability of agricultural production. Secondly, while industrial capital and commercial capital boost rural economic development, it also improves the rural ecological environment. Industrial capital and commercial capital are used to invest in the development of circular sustainable agriculture such as ecological agriculture and sightseeing agriculture, which promotes rural greening management, improves the rural greening rate, and provides a good ecological environment for agricultural production. At the same time, the improvement of the rural greening rate is also helpful to improve rural climate, reduce the occurrence of natural disasters and reduce the risk of agricultural production, and it is conducive to the sustainable development of agriculture.
Industrial capital and commercial capital have created favorable conditions for the sustainable development of agriculture by improving the rural environment. On the one hand, by improving the sewage treatment capacity, the stability of agricultural water use is guaranteed, which provides a reliable water resource guarantee for agricultural production. On the other hand, by increasing the rural greening rate, the rural ecological environment is improved, and the self-repair ability of agricultural ecosystem is enhanced, which is conducive to the sustainable development of agriculture. Therefore, the following research hypothesis is proposed:
Hypothesis 2b. 
Industrial capital and commercial capital promote the sustainable development of agriculture by promoting the improvement of rural environment.
Industrial capital and commercial capital are used to build factories, which increase non-agricultural employment opportunities, improve farmers’ consumption structure, reduce farmers’ Engel coefficient, promote farmers’ realization of poverty reduction and common prosperity, and then promote the sustainable development of agriculture. Industrial and commercial capital’s investment in agriculture in the countryside has promoted the extension of agricultural industrial chain, created more non-agricultural employment opportunities (Cui et al., 2008) [29], promoted the transfer of the rural labor force (Feng, 2021) [30], and promoted the optimal allocation of agricultural labor force and the transformation and upgrading of agricultural structure. A large number of rural surplus labor forces have been liberated from traditional agricultural production and transferred to non-agricultural industries, which has improved the production efficiency and income level of labor forces and promoted farmers to reduce poverty. With the decrease in employment in the primary industry, agricultural production has gradually realized intensification and specialization, and the utilization efficiency of agricultural resources has improved, which has created favorable conditions for the sustainable development of agriculture. At the same time, industrial capital and commercial capital can improve farmers’ property income (Tian, 2017) [31]. The increase in farmers’ income will change the consumption structure, and farmers’ expenditure on basic living needs such as food will decrease, while more resources will be invested in higher-level consumption such as education, medical care, and entertainment, which will improve farmers’ well-being and promote the sustainable development of agriculture.
Industrial capital and commercial capital not only improve the efficiency of resource allocation by promoting the transfer of rural labor force but also adjust the consumption structure of farmers by increasing their income, thus achieving the effect of reducing poverty and achieving common prosperity for farmers and promoting the sustainable development of agriculture. Therefore, the following research hypothesis is proposed:
Hypothesis 2c. 
Industrial capital and commercial capital promote the sustainable development of agriculture by promoting farmers’ poverty reduction and common prosperity.

3.3. Analysis of the Spatial Spillover Effect of Industrial Capital and Commercial Capital on Sustainable Agricultural Development

According to the first law of geography, everything has spatial correlation, and industrial capital and commercial capital and sustainable agricultural development are no exception. Therefore, while industrial capital and commercial capital affect the sustainable development of local agriculture, it is very likely to have the characteristics of cross-regional diffusion and mainly manifest in two effects. The first is the spillover effect. The high-quality talents, advanced technology, and management knowledge brought by industrial capital and commercial capital have spillover effects (Yan and Zheng, 2022) [24]. Agricultural workers in neighboring areas will learn and imitate through explicit or implicit communication channels and improve the level of agricultural production management in “learning by doing” (Zhang et al., 2014) [32], thereby promoting the sustainable development of agriculture in neighboring areas. The second is the siphon effect. The profit-seeking nature of capital will cause production factors between regions to flow to regions with high demand and high remuneration for these production factors. For this reason, the vigorous development of industrial capital and commercial capital in a certain region will attract agricultural production resources from surrounding areas to gather locally, resulting in a siphon effect and hindering the sustainable development of agriculture in neighboring areas. Therefore, the following hypothesis is proposed:
Hypothesis 3. 
The impact of industrial capital and commercial capital on agricultural sustainable development has a spatial spillover effect.
To sum up, this paper studies the influence of industrial capital and commercial capital on agricultural sustainable development from the perspectives of agriculture, rural areas and farmers, and puts forward five research hypotheses. The specific transmission path is shown in Figure 1.

4. Research Design

4.1. Model Selection

4.1.1. Benchmark Regression Model

In order to test the impact of industrial capital and commercial capital on agricultural sustainable development, referring to the research of Wang et al. (2025) [33], this paper first constructs the following benchmark model:
A s u s i , t = α + β B c a p i , t + γ C o n t r o l i , t + μ i + ε i , t
In the formula, Asus represents the agricultural sustainable development ability, Bcap represents the level of industrial capital and commercial capital, Control represents the control variable, μ represents the unobservable individual fixed effect, i represents the province, t represents the year, and ε represents the random disturbance term.

4.1.2. Mediating Effects Model

Based on Formula (1), in order to explore the mechanism of industrial capital and commercial capital affecting the sustainable development of agriculture, referring to the research of Wen and Ye (2014), this paper construct the following mediation effect model [34]:
z i , t = α + β B c a p i , t + γ C o n t r o l i , t + μ i + ε i , t
A s u s i , t = α + β B c a p i , t + z i , t + γ C o n t r o l i , t + μ i + ε i , t
where z represents the mediating variable, and the meanings of the other variables are the same as those in Formula (1). At the same time, in order to ensure the accuracy of the regression results of mediation effect, this paper refers to the research method of He et al. (2019) [35] and further tests the mediation variables by the Sobel method and bootstrap method.

4.1.3. Spatial Metrology Model

In view of the spatial correlation between industrial capital and commercial capital and agricultural sustainable development in different provinces, in order to further test whether the influence of industrial capital and commercial capital on agricultural sustainable development has spatial spillover effect and referring to the research of Su and Xing (2024) [36] this paper constructs the following spatial Durbin model:
A s u s i , t = α + ρ W i , t A s u s i , t + β B c a p i , t + λ W i , t B c a p i , t + γ C o n t r o l i , t + φ W i , t C o n t r o l i , t + μ i + ε i , t
In Formula (4), ρ represents the spatial autoregression coefficient, which reflects the impact of the sustainable development of agriculture in neighboring regions on the sustainable development of local agriculture. λ represents the coefficient of the spatial explanatory variable, which reflects the impact of the inflow of industrial and commercial capital from neighboring regions on the sustainable development of local agriculture. The meanings of the other variables are the same as those in Formula (1). W is the spatial adjacency matrix.

4.2. Variable Description

4.2.1. Explained Variables

Referring to the research of Tang and Liu (2022) [16] and combining relevant policy documents, this paper constructs a comprehensive indicator evaluation system of sustainable agricultural development from five levels, namely the population system, social system, economic system, resource system, and environmental system (Table 1), and it uses the entropy method to weight each indicator. Finally, the comprehensive score of sustainable agricultural development in each province is calculated, symbolized as Asus.

4.2.2. Core Explanatory Variables

Based on the research of Jia et al. (2024) [7] and Huang et al. (2023) [37], this paper uses the number of agricultural enterprises in operation to represent the level of industrial capital and commercial capital, symbolized as BCap.

4.2.3. Mediating Variables

The transmission mechanism of this paper starts from three levels: agriculture, rural areas, and farmers. Each level has two measurement indicators, with a total of six mediating variables. Referring to the research of Guo et al. (2024) and Li and Liu (2024) [38,39], the agricultural production conditions indicators are replaced by the agricultural science and technology development level (Atec) and the agricultural mechanization level (Amec), and the specific reference is the number of agricultural science and technology patents and the mechanical harvesting area for measurement; the rural environmental governance indicators are measured by the rural sewage treatment level (Awat) and the rural greening level (Agre), and the specific reference is the proportion of administrative villages that treat domestic sewage and the rural greening rate for measurement; the farmers’ poverty reduction and common prosperity indicators are measured by the rural Engel coefficient (Aeng) and the number of people employed in the primary industry (Fpio).

4.2.4. Control Variables

In addition to industrial capital and commercial capital, it is also necessary to control the interference of other potential factors on the sustainable development of agriculture. Referring to the research of Wang et al. (2025) [33], combined with the research purpose of this paper, the degree of government intervention, the level of technological progress, the level of infrastructure, and the level of informatization were selected as the control variables of this paper. Among them, the degree of government intervention (Ginter) is measured by the ratio of general fiscal expenditure to GDP; the level of technological progress (Tadv) is measured by the ratio of internal expenditure of R&D funds to GDP; the infrastructure level (Infra) is measured by logarithm of highway mileage; the informatization level (Infor) is measured by the ratio of total post and telecommunications business to GDP.

4.3. Data Sources

According to the research purpose of this paper, the panel data of 30 provincial administrative regions in China from 2013 to 2022 (limited to the availability of data, excluding Hong Kong, Macao and Taiwan regions, and Tibet) were used, and there were no missing values in the original data. The indicators of industrial capital and commercial capital, that is, the data of agricultural enterprises in operation, were derived from the Zhejiang University Carter-Enterprise Research China Agricultural Research Database (CCAD), and other data were derived from the “China Statistical Yearbook”, “China Rural Statistical Yearbook”, “China Population and Employment Statistical Yearbook”, and provincial regional statistical yearbooks. The descriptive statistical results of the related variables are shown in Table 2.
From the perspective of core variables, the average level of agricultural sustainable development is only 0.305, the maximum value is 0.514, and the minimum value is 0.120, which shows that the level of agricultural sustainable development in China is low, and there are great differences in its regional development. The average value of the index of industrial capital and commercial capital is 0.171, the maximum value is 0.9197, and the minimum value is 0.008, which shows that the development level of industrial capital and commercial capital in China is low, and there is a big difference.

5. Results

5.1. Benchmark Regression Analysis

The benchmark regression results of the impact of industrial capital and commercial capital on agricultural sustainable development are shown in Table 3. Column (1) only regresses industrial and commercial capital to the countryside. Column (2) adds control variables based on column (1). Column (3) fixes individual effects based on column (2). The results show that regardless of whether introducing control variables and controlling individual effects, industrial capital and commercial capital have a significant positive impact on agricultural sustainable development at the 1% significance level, indicating that industrial capital and commercial capital can promote agricultural sustainable development, and research Hypothesis 1 is preliminarily verified. In order to conduct an in-depth study of the impact of industrial capital and commercial capital on the level of sustainable agricultural development at different levels of development, quantile regression was used to test. The results are shown in columns (4), (5), and (6) of Table 3. The estimated coefficient of indicator of capital going to the countryside is always significantly positive, indicating that the impact of industrial capital and commercial capital on the level of sustainable agricultural development at different levels of development is promotion, and research Hypothesis 1 is further verified. This conclusion provides a theoretical basis for orderly guiding of industrial and commercial capital to the countryside and for promoting the integration of industrial and commercial capital into agriculture and rural areas.
In terms of each control variable, government intervention has a significant negative impact on agricultural sustainable development. The possible reason is that excessive government protection and subsidies may reduce the efficiency of resource allocation and are not conducive to sustainable agricultural development. The estimated coefficient of infrastructure level is significantly positive, indicating that a higher level of infrastructure can promote sustainable agricultural development. The estimated coefficients of technological progress and informatization level are positive but not significant, indicating that technological progress and informatization development have the potential to promote sustainable agricultural development.
In order to further explore the specific impact of industrial capital and commercial capital on agricultural sustainable development, the components of agricultural sustainable development, namely the population system, social system, economic system, resource system, and environmental system, were regressed by fixed-effect model, and the results are shown in Table 4. The results show that industrial capital and commercial capital have a significant positive impact on the population system, economic system, resource system, and environmental system, and the estimation coefficients of the impact are 0.0124, 0.0307, 0.0161, and 0.0175, respectively, through the 1% significance test, but the impact of industrial capital and commercial capital on social system is not significant, which may be due to industrial and commercial capital’s limited improvement in rural poverty, electricity consumption, and housing. Industrial capital and commercial capital mainly invest in specific fields, and the improvement of infrastructure is limited; housing conditions are restricted by multiple factors, which are not determined by a single capital; the causes of poverty are complex, and many efforts are needed to effectively reduce the poverty rate, so the impact of industrial capital and commercial capital on the rural social system is not significant.

5.2. Endogenous Test

First of all, although the factors affecting the sustainable development of agriculture and the development of industrial and commercial capital in the countryside are included in the econometric model as much as possible, there are inevitably missing variables, which leads to the correlation between the missing variables and the disturbance term, thus generating endogeneity problems and making the research results biased. Secondly, there may be a two-way causal problem between industrial capital and commercial capital and agricultural sustainable development; that is, industrial capital and commercial capital may interact with agricultural sustainable development, which will lead to deviation of results. In order to try to solve the errors caused by the above endogeneity problems, this paper uses the panel instrumental variable method to test the endogeneity, selects the digital inclusive finance index as the instrumental variable, and uses the two-stage least square method (2SLS) to identify the causal relationship between industrial capital and commercial capital and agricultural sustainable development. This instrumental variable meets two constraints: on the one hand, the development level of digital inclusive finance (IV) is closely related to the development of industrial capital and commercial capital, which satisfies the correlation conditions between instrumental variables and endogenous explanatory variables; on the other hand, the development level of digital inclusive finance (IV) satisfies the condition of exogenous relationship with random disturbance term.
Column (1) and column (2) of Table 5 show the regression results of tool variables, and tool variable IV passed the weak tool variable test and unidentifiable test, which shows that the selected tool variable is reasonable and can effectively solve the endogeneity problem of variables. From column (2), after considering the possible endogeneity problems between industrial capital and commercial capital and agricultural sustainable development, the estimation coefficient of industrial capital and commercial capital is still significantly positive, indicating that industrial capital and commercial capital can significantly promote agricultural sustainable development, which is completely consistent with the previous results.

5.3. Robustness Test

In order to ensure the reliability of the conclusion, the next test is based on the following three methods: First, in order to prevent extreme values from interfering with the regression results, all continuous variables were truncated by 1%, and the results are shown in column (3) of Table 5. Secondly, considering that it takes some time for capital to go to the countryside to exert its effect, a regression test was performed on the core explanatory variable industrial capital and commercial capital by four periods with reference to Shao’s research [2], and the results are shown in column (4) of Table 5. Finally, considering that the development of agricultural industry will be affected by the level of opening to the outside world (Xiong et al., 2023) [40], the benchmark regression was re-tested by increasing the control variables of the level of external development, and the results are shown in column (5) of Table 5. It can be seen from Table 5 that the core explanatory variable of industrial capital and commercial capital is still significant at the level of 1% significance after tail-shrinking, lagging, and changing the measurement model, and the sign of the estimation coefficient is consistent with the benchmark regression, which confirms the robustness of the benchmark regression results.

5.4. Heterogeneity Analysis

5.4.1. Heterogeneity Analysis Based on Agricultural Resource Endowment

Based on China’s basic national conditions of more people and less land, the Chinese government has divided 31 provinces into main grain-production areas, main grain-sales areas, and grain balance areas in order to optimize the layout of agricultural production and focus on advantageous production areas. In view of the different natural endowments and policy implementation and other development conditions of the three regions, which may have an impact on the level of industrial capital and commercial capital and the sustainable development of agriculture, this article draws on the research of Feng and Zou (2024) [41] and divides 30 research samples into major grain-producing areas and non-major grain-producing areas for empirical testing. The regression results are shown in columns (1) and (2) of Table 6. Overall, whether in major grain-producing areas or non-major grain-producing areas, the flow of industrial capital and commercial capital has a significant role in promoting sustainable agricultural development. However, in non-major grain-producing areas, the flow of industrial capital and commercial capital has a more significant role in promoting sustainable agricultural development. This may be because the main grain-producing areas have already established a relatively complete production system, so the impact of industrial capital and commercial capital is relatively small. In contrast, non-major grain-producing areas are relatively deficient in production factors, so the decline of industrial and commercial capital and the production factors brought by the countryside have a greater impact on it.

5.4.2. Heterogeneity Analysis Based on Marketization Level

In view of the fact that the market-oriented environment in different regions of China may have an impact on the effect of industrial and commercial capital in promoting the sustainable development of agriculture, this study divides the total sample into high-level and low-level market-oriented regions according to the market-oriented index of Fan Gang and China so as to explore the impact of industrial capital and commercial capital on the sustainable development of agriculture under different market-oriented levels. The related results are shown in columns (3) and (4) of Table 6. Overall, under different marketization levels, industrial and commercial capital have a significant positive impact on the sustainable development of agriculture, but the regression coefficient is larger in areas with a high marketization level, indicating that the impact is greater. The possible reason is that the business environment in areas with a high marketization level is higher, which can attract more industrial and commercial capital to participate, so the impact is greater. Therefore, it is necessary to accelerate the process of marketization, improve relevant policies and measures, and promote the development of industrial and commercial capital in the countryside.

5.4.3. Heterogeneity Analysis Based on Economic Development Level

Given that China is a vast country, the economic development conditions of different regions vary, which may affect the effect of industrial and commercial capital on agricultural sustainable development. Therefore, this study divides 30 provinces into an eastern region and central and western regions based on differences in economic and social development to explore the regional heterogeneous effects of industrial and commercial capital on agricultural sustainable development. The relevant results are shown in columns (5) and (6) of Table 6. Overall, the development of industrial capital and commercial capital in the eastern, central, and western regions can promote agricultural sustainable development, but the degree of impact of industrial capital and commercial capital on agricultural sustainable development in different regions is different, with the greatest impact on the central and western regions, followed by the eastern region. The possible reason is that the eastern region has a relatively developed economy, relatively rich agricultural production factors, relatively advanced technology, and a good level of agricultural development, so industrial capital and commercial capital have a relatively small role in promoting it. In contrast, the economic development of the central and western regions is relatively lagging, and industrial capital and commercial capital can play a greater role. In particular, the central region lacks production factors for agricultural development, so the impact of industrial and commercial capital on agricultural sustainable development is the greatest.

5.5. Mediation Effect Analysis

5.5.1. Test of Transmission Mechanism Based on Optimization of Agricultural Production Conditions

The test results of the mechanism of industrial capital and commercial capital to promote sustainable agricultural development through optimizing agricultural production conditions are shown in Table 7. First, columns (1) and (2) of Table 7 show the regression results of the intervening variable of agricultural science and technology development level. The development of industrial capital and commercial capital will significantly promote the level of agricultural science and technology development. After adding the variable of agricultural science and technology development level to the baseline regression, it was found that the movement of industrial and commercial capital into the countryside still has a significant positive impact on the sustainable development of agriculture. Secondly, columns (3) and (4) of Table 7 show the regression results of the intermediary variable of agricultural mechanization level. The development of industrial capital and commercial capital will have a significant positive impact on the level of agricultural mechanization. After adding the agricultural mechanization level variable to the baseline regression, it was found that the movement of industrial and commercial capital into the countryside still has a significant positive impact on the sustainable development of agriculture. In summary, the estimated coefficients of industrial capital and commercial capital, the level of agricultural science and technology development, and the level of agricultural mechanization all passed the significance test. The level of agricultural science and technology development and the level of agricultural mechanization have a significant positive impact on the sustainable development of agriculture. All of the above results were gained through the Sobel test and bootstrap test; this shows that the optimization of agricultural production conditions is an important path that affects the flow of industrial and commercial capital to the countryside to promote sustainable agricultural development, and the research Hypothesis 2a is verified.

5.5.2. Test of the Transmission Mechanism Based on the Effect of Rural Environment Optimization

The test results of the intermediary mechanism of industrial capital and commercial capital to promote sustainable agricultural development by improving the rural environment are shown in Table 8. First, columns (1) and (2) of Table 8 show the regression results of the intermediary variable rural sewage treatment level. The development of industrial capital and commercial capital will significantly improve the level of rural sewage treatment. After adding the variable of rural sewage treatment level in the baseline regression, it was found that sending industrial and commercial capital to the countryside still has a significant positive impact on the sustainable development of agriculture. Secondly, columns (3) and (4) of Table 8 show the regression results of the intermediary variable of the rural greening level. The development of industrial capital and commercial capital will have a significant positive impact on the level of rural greening. After adding the variable of the rural greening level to the baseline regression, it was found that the movement of industrial and commercial capital into the countryside still has a significant positive impact on the sustainable development of agriculture. In summary, the estimated coefficients of industrial capital and commercial capital, rural sewage treatment level, and agricultural greening level all passed the significance test. The above results all passed the Sobel test and bootstrap test, which shows that industrial capital and commercial capital promote the development of rural areas by improving the rural environment. The action path of sustainable agricultural development is established, and the research Hypothesis 2b is verified.

5.5.3. Test of Transmission Mechanism Based on the Effect of Farmers’ Poverty Reduction and Common Prosperity

The mechanism test results of industrial capital and commercial capital to promote the sustainable development of agriculture by promoting farmers’ poverty reduction and common prosperity are shown in Table 9. First of all, column (1) and column (2) of Table 9 show the regression result of the rural Engel coefficient, an intermediate variable. The development of industrial capital and commercial capital will significantly reduce the rural Engel coefficient; after adding the rural Engel coefficient variable to the benchmark regression, the industrial capital and commercial capital still have a significant positive impact on the sustainable development of agriculture. Secondly, column (3) and column (4) of Table 9 show the regression results of the primary industry labor force as an intermediary variable. The development of industrial capital and commercial capital will significantly reduce the labor force in the primary industry, and then, it was found that the industrial capital and commercial capital still have a significant positive impact on the sustainable development of agriculture after adding the variables of labor force in the primary industry in the benchmark regression. In summary, the estimated coefficients of industrial capital and commercial capital, the rural Engel coefficient, and the primary industry labor force all passed the significance test, and the above results all passed the Sobel test and bootstrap test, which shows that the action path of industrial capital and commercial capital can promote the sustainable development of agriculture by promoting farmers’ poverty reduction and common prosperity, and the research Hypothesis 2c is verified.

5.6. Further Analysis

According to the previous theoretical analysis, there may be spatial spillover effects between industrial capital and commercial capital and sustainable agricultural development. Therefore, in order to verify whether this hypothesis is true, it is necessary to empirically analyze the impact of industrial capital and commercial capital on sustainable agricultural development by constructing a spatial econometric model. Before that, it is necessary to test the spatial correlation between the industrial capital and commercial capital and the sustainable development of agriculture in each province. This article uses Moran’s I index to test the two separately. From the test results in Table 10, it can be seen that during the sample period, the Moran’s I index of each industrial and commercial capital was significantly positive, indicating that there is a significant positive spatial autocorrelation in the industrial capital and commercial capital in each province; the Moran’s I index of agricultural sustainable development is significantly positive in most years, indicating that there is positive spatial autocorrelation in sustainable agricultural development. Therefore, it is necessary to further use spatial econometric models to study the spatial spillover effects of industrial capital and commercial capital on sustainable agricultural development.
It is crucial to choose an appropriate spatial econometric model to examine the spatial spillover effects of industrial capital and commercial capital on sustainable agricultural development. First, the fixed-effects model was determined through the Hausman test; secondly, through the LM and RobustLM tests, it was found that the p-values are both less than 1%, which indicates that both the SEM model and the SLM model were suitable choices. Therefore, this study initially chose the SDM model that combines the two. Finally, through the Wald test, it was found that the spatial Durbin model was not transformed into a spatial error model and a spatial lag model; that is, the spatial Durbin model is more suitable for this study. The estimation results are shown in Table 11.
According to Table 11, the estimated value of the spatial autoregressive coefficient value is 0.361 and is significant at the 1% level, which further confirms that there is a positive spatial correlation in agricultural sustainable development. The estimated coefficient of industrial capital and commercial capital is significantly positive, indicating that even if a spatial econometric model is used, industrial capital and commercial capital will still significantly promote sustainable agricultural development. The spatial weighting coefficient of industrial and commercial capital is also significantly positive, indicating that the development of industrial and commercial capital in neighboring areas will have a significant promotion effect on the sustainable development of local agriculture. The previous research Hypothesis 3 is preliminarily verified. According to the previous theoretical analysis, the reason may be that the development of industrial capital and commercial capital has a strong spillover effect, thus promoting the sustainable development of agriculture in neighboring areas.
To further study the marginal impact of industrial capital and commercial capital on agricultural sustainable development, referring to the research of Lesage and Pace [42], this study decomposed the spatial effect of industrial capital and commercial capital on agricultural sustainable development, and the results are shown in Table 12. Judging from the decomposition results, the direct effect of industrial capital and commercial capital on agricultural sustainable development is 0.0274, and it passed the significance test at the level of 5%, indicating that every 1% increase in the development level of industrial capital and commercial capital will increase the level of agricultural sustainable development in this area by 0.0274%. The indirect effect of industrial capital and commercial capital is 0.0787, which shows that every 1% increase in the development level of local industrial capital and commercial capital will promote the sustainable development level of agriculture in neighboring areas by 0.0787%; that is, the development of industrial capital and commercial capital in this area will have a significant positive spatial spillover effect on the sustainable development of agriculture in neighboring areas, and the research Hypothesis 3 is further verified.

6. Conclusions and Policy Recommendations

6.1. Conclusions

Sustainable agricultural development is not only related to contemporary and future human survival but is also the basis for realizing the harmonious unity of economy, society, and environment. This study selected panel data from 30 provinces in China from 2013 to 2022 to test the impact of industrial capital and commercial capital on sustainable agricultural development from both theoretical and empirical aspects. The study found the following:
First, industrial capital and commercial capital can significantly promote the sustainable development of agriculture. This conclusion is still valid after endogenous tests and robustness tests, such as dealing with extreme values and changing measurement models.
Second, the impact of industrial capital and commercial capital on agricultural sustainable development is heterogeneous. Industrial capital and commercial capital have a great influence on the sustainable development of agriculture in China’s non-grain-producing areas, areas with a high marketization level, and the central and western regions.
Thirdly, industrial capital and commercial capital affect the sustainable development of agriculture by optimizing agricultural production conditions, improving rural environment, and promoting farmers’ poverty reduction and common prosperity. First of all, industrial capital and commercial capital promote the optimization of agricultural production conditions by improving the level of agricultural science and technology and mechanization, thus affecting the sustainable development of agriculture; next, industrial capital and commercial capital promote rural environmental governance by improving the level of rural sewage treatment and rural greening, thus affecting the sustainable development of agriculture; finally, industrial capital and commercial capital reduce the Engel coefficient in rural areas, promote the transfer of agricultural labor force, and enhance the effect of reducing poverty and common prosperity for farmers, thus affecting the sustainable development of agriculture.
Fourthly, industrial capital and commercial capital have a significant positive spatial spillover effect on the sustainable development of agriculture. Every 1% increase in the development level of local industrial and commercial capital will promote the sustainable development level of agriculture in neighboring areas by 0.079%.
Generally speaking, industrial capital and commercial capital are conducive to promoting the sustainable development of agriculture. This can have an impact on the sustainable development of agriculture by affecting agricultural production conditions, the rural environment, and farmers’ lives. However, the impact on the sustainable development of agriculture in different areas is heterogeneous, and it has a positive spillover effect on the sustainable development of agriculture in neighboring areas.

6.2. Policy Recommendations

First, the policy environment should be optimized to guide industrial capital and commercial capital. The government should establish and improve relevant policies to encourage industrial and commercial capital to flow into the field of agricultural industrialization. At the same time, it should regulate the entry of industrial and commercial capital into the agricultural field, adhere to the legal bottom line of land-use control, and lower the threshold and barriers for industrial capital and commercial capital to enter. Secondly, policies should strengthen rural infrastructure construction and improve supporting services by introducing industrial capital and commercial capital, increasing investment in agricultural and rural infrastructure, speeding up the filling of rural infrastructure shortcomings, promoting the interconnection of urban and rural infrastructure, strengthening the construction of rural transportation and logistics facilities, and laying a solid foundation for attracting high-quality resources into rural areas. Finally, attention should be paid to the development differences among regions, building on their own advantages and attracting industrial capital and commercial capital to invest in characteristic agriculture. Regional cooperation should be strengthened, with exchanges to promote the formation of characteristic agricultural industry clusters and improve agricultural production efficiency but avoid homogeneity problems.

6.3. Discussion

Through theoretical analysis and empirical tests, this study found that the influence of industrial capital and commercial capital on agricultural sustainable development is comprehensive and far-reaching. They optimize the production conditions by improving the scientific and technological level and mechanization of agricultural production, benefit the rural environment by improving the level of rural sewage treatment and greening, enhance the effect of poverty reduction and common prosperity of farmers by reducing Engel coefficient and promoting the transfer of agricultural labor force, and promote the agricultural development in neighboring areas through positive spatial spillover effect. The conclusion of this paper emphasizes the important role of capital in agricultural modernization and rural revitalization and provides the basis for policymakers to optimize the policy environment, strengthen rural infrastructure construction, and pay attention to regional development differences so as to realize the long-term stable development of agriculture.

6.4. Research Limitations and Future Research Directions

Future research may be carried out in two different ways. First, the accuracy of industrial capital and commercial capital index measurement may be improved. In this paper, the industrial and commercial capital index is measured by the number of agricultural enterprises in operation, which can only be measured from the macro quantity and not from the micro indexes such as capital quota and time to enter agriculture. With the improvement of the availability of relevant data, the measurement of industrial capital and commercial capital variables in future research can be more comprehensive and detailed. Second, the research conclusions drawn by using provincial data are more universal, and future research can better reflect the micro differences between industrial capital and commercial capital and agricultural sustainable development by using farmers’ survey data.

Author Contributions

H.Y., investigation, supervision, and writing—review and editing; F.W., conceptualization, methodology, data curation, software, visualization, and writing—original draft preparation. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by China Social Science Fund’s key project “Effect Evaluation, Mechanism Test and Dynamic Contract Regulation of Industrial and Commercial Capital Participating in Rural Revitalization”, funding number: 24AJY027.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The datasets supporting this study’s findings are available on request from the corresponding author. The dataset is not publicly available due to privacy or ethical restrictions.

Acknowledgments

The authors are grateful to the editor and the anonymous referees for their helpful comments and suggestions.

Conflicts of Interest

The authors declare no conflicts of interest.

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Sustainability 17 00312 g001
Figure 1. Framework diagram of the mechanism of the impact of industrial capital and commercial capital on the sustainable development of agriculture.
Figure 1. Framework diagram of the mechanism of the impact of industrial capital and commercial capital on the sustainable development of agriculture.
Sustainability 17 00312 g001
Table 1. Evaluation Index System of Sustainable Agricultural Development.
Table 1. Evaluation Index System of Sustainable Agricultural Development.
Primary IndexWeightSecondary IndexWeightUnitAttributes of
Indicators
Population system0.0509Average education level of villagers0.0168YearP
Natural population growth rate0.0254%N
Regional population density0.0087People/square kilometer N
Social system0.2533Rural electricity consumption0.1601100 million kWhP
Rural housing area0.0468square meterP
Rural poverty rate0.0464%N
Economic system0.2463Gross agricultural output value0.0682100 million yuanP
Farmers’ income level0.0458YuanP
Agricultural fixed asset investment0.0658100 million yuanP
Agricultural output value per unit of sown area0.0665100 million yuan/1000 hectares P
Resource system0.2791Per capita cultivated land area0.0480Hectares/10,000 peopleP
Agricultural land productivity0.044010,000 tons/1000 hectares P
Total mechanical power per unit cultivated land area0.059010,000 kilowatts/1000 hectaresP
Agricultural water consumption0.0791100 million cubic metersP
Effective irrigation rate0.0490%P
Environmental system0.1704Fertilizer use intensity0.011310,000 tonsN
Pesticide use intensity0.018310,000 tonsN
Plastic film use intensity0.01231000 hectaresN
Soil and water loss control area0.074210,000 tonsP
Forest coverage rate0.0490%P
Agricultural disaster rate0.0053%N
Table 2. Descriptive statistics of variables.
Table 2. Descriptive statistics of variables.
Variable NameSymbolSample SizeMeanStandard
Deviation		MinimumMaximum
Agricultural sustainable developmentAsus3000.3050.0750.1200.514
Industrial capital and commercial capitalBcap3000.1710.1470.0080.919
Government interventionGinter3000.2600.1100.1050.753
Technical progressTadv3003.4566.8170.01255.398
Infrastructure levelInfra30011.7260.8529.44412.913
Informatization levelInfor3000.0750.1520.0152.520
Table 3. Benchmark regression results of the impact of industrial capital and commercial capital on agricultural sustainable development.
Table 3. Benchmark regression results of the impact of industrial capital and commercial capital on agricultural sustainable development.
(1)(2)(3)(4)(5)(6)
VariableAsusAsusAsus25%50%75%
Bcap0.163 ***0.106 ***0.0726 ***0.0533 ***0.0733 ***0.0677 ***
(0.0172)(0.0163)(0.0147)(0.0187)(0.0194)(0.0237)
Ginter −0.324 ***−0.193 ***−0.167 ***−0.197 ***−0.291 ***
(0.0447)(0.0469)(0.0596)(0.0616)(0.0754)
Tadv 0.000481 *0.000197−8.58 × 10−5−0.0001130.000437
(0.000263)(0.000231)(0.000293)(0.000303)(0.000371)
Infra 0.0523 ***0.187 ***0.206 ***0.177 ***0.170 ***
(0.00914)(0.0160)(0.0203)(0.0210)(0.0257)
Infor 0.008420.007110.001990.01190.0133
(0.00902)(0.00782)(0.00992)(0.0103)(0.0126)
Individual fixed effectsNoNoYesYesYesYes
Constant term0.278 ***−0.244 **−1.857 ***−1.746 ***−1.433 ***−1.308 ***
(0.0116)(0.109)(0.190)(0.206)(0.213)(0.261)
Observations300300300300300300
R20.2430.4520.5640.7740.7630.776
Note: Standard errors are in parentheses; ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.
Table 4. Regression results of the influence of industrial capital and commercial capital on various systems.
Table 4. Regression results of the influence of industrial capital and commercial capital on various systems.
(1)(2)(3)(4)(5)
VariablePopulation SystemSocial
System		Economic SystemResource
System		Environmental System
Bcap0.0124 ***−0.003930.0307 ***0.0161 ***0.0175 ***
(0.00235)(0.0106)(0.00536)(0.00476)(0.00238)
Ginter−0.0305 ***−0.0387−0.0770 ***−0.0385 **−0.00813
(0.00748)(0.0339)(0.0171)(0.0152)(0.00759)
Tadv0.000168 ***−0.000308 *5.26 × 10−50.000212 ***7.53 × 10−5 **
(3.68 × 10−5)(0.000167)(8.40 × 10−5)(7.46 × 10−5)(3.73 × 10−5)
Infra0.0230 ***0.0217 *0.0720 ***0.0396 ***0.0311 ***
(0.00255)(0.0115)(0.00581)(0.00516)(0.00258)
Infor0.0005810.0004120.00461−0.0003690.00179
(0.00124)(0.00565)(0.00284)(0.00253)(0.00126)
Individual fixed effectsYesYesYesYesYes
Constant term−0.237 ***−0.187−0.762 ***−0.380 ***−0.288 ***
(0.0303)(0.137)(0.0691)(0.0615)(0.0307)
Observations300300300300300
R20.5290.0340.6010.3850.593
Note: Standard errors are in parentheses; ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.
Table 5. Endogeneity treatment and robustness test regression results.
Table 5. Endogeneity treatment and robustness test regression results.
(1)(2)(3)(4)(5)
VariableFirst StageSecond StageShrinkageLag Four PeriodsAdd Control Variables
Bcap 0.332 ***0.0897 *** 0.0707 ***
(0.0810)(0.0152) (0.0147)
IV0.000611 ***
(8.92 × 10−5)
L4.Bcap 0.0847 ***
(0.0284)
Kleibergen-Paaprk LM10.390 ***
Cragg–Donald Wald F46.972 (16.380)
Control variablesYesYesYesYesYes
Individual fixed effectsYesYesYesYesYes
Constant term −1.591 ***−1.538 ***−1.8096 ***
(0.198)(0.351)(0.1901)
Observations300300300180300
R2 0.0540.5840.5290.571
Note: Standard errors are in parentheses; *** indicate significance at the 1% level.
Table 6. Heterogeneity test results.
Table 6. Heterogeneity test results.
(1)(2)(3)(4)(5)(6)
VariableMajor Grain-Producing AreasNon-Grain-Producing AreasLow Level of MarketizationHigh Level of MarketizationEastern RegionCentral and Western Regions
Bcap0.0636 ***0.0954 ***0.0638 **0.0741 ***0.0590 **0.0847 ***
(0.0195)(0.0244)(0.0262)(0.0194)(0.0285)(0.0151)
Control variablesYesYesYesYesYesYes
Individual fixed effectsYesYesYesYesYesYes
Constant term−2.065 ***−1.498 ***−2.066 ***−1.192 ***−1.300 ***−2.034 ***
(0.353)(0.228)(0.227)(0.355)(0.387)(0.206)
Observations130170145155130170
R20.5270.6190.6610.4850.3620.737
Note: Standard errors are in parentheses; ***, ** indicate significance at the 1%, 5% levels, respectively.
Table 7. Test results of transmission mechanism: optimization of agricultural production conditions.
Table 7. Test results of transmission mechanism: optimization of agricultural production conditions.
(1)(2)(3)(4)
VariableAtecyAmecy
Bcap5.827 ***0.0586 ***0.159 ***0.00490 ***
(1.128)(0.0152)(0.0309)(0.00147)
Atec 0.00240 ***
(0.000790)
Amec 0.0148 ***
(0.00279)
Sobel test (p-value)0.00889230.000217
Ind_eff test (p-value)0.0360.008
Ind_eff test confidence interval[0.0008794, 0.0270645][0.0060638, 0.0411095]
Control variablesYesYes
Individual fixed effectsYesYesYesYes
Constant term−52.61 ***−1.730 ***−31.15 ***−1.394 ***
(14.56)(0.192)(3.983)(0.201)
Observations300300300300
R20.2610.5780.3930.606
Note: Standard errors are in parentheses; *** indicate significance at the 1% level.
Table 8. Test results of transmission mechanism: improvement of rural environment.
Table 8. Test results of transmission mechanism: improvement of rural environment.
(1)(2)(3)(4)
VariableAwatyAgreey
Bcap4.468 ***0.0452 ***2.353 ***0.0535 ***
(0.793)(0.0147)(0.498)(0.0148)
Awat 0.00613 ***
(0.00108)
Agree 0.00811 ***
(0.00175)
Sobel test (p-value)0.00006340.00094351
Ind_eff test (p-value)0.0050.024
Ind_eff test confidence interval[0.0082768, 0.0465157][0.0024695, 0.356953]
Control variablesYesYesYesYes
Individual fixed effectsYesYesYesYes
Constant term−69.71 ***−1.429 ***−38.03 ***−1.548 ***
(10.24)(0.195)(6.424)(0.195)
Observations300300300300
R20.4570.6110.3940.596
Note: Standard errors are in parentheses; *** indicate significance at the 1% level.
Table 9. Test results of transmission mechanism: farmers’ poverty reduction and common prosperity.
Table 9. Test results of transmission mechanism: farmers’ poverty reduction and common prosperity.
(1)(2)(3)(4)
VariableAengyFpioy
Bcap−1.167 ***0.0427 ***−0.632 ***0.0498 ***
(0.200)(0.0147)(0.0872)(0.0158)
Aeng −0.0256 ***
(0.00425)
Fpio −0.0360 ***
(0.0102)
Sobel test (p-value)0.000027640.00146254
Ind_eff test (p-value)0.0060.006
Ind_eff test confidence interval[0.0087257, 0.0510885][0.0066695, 0.0388606]
Observations300300300300
Control variablesYesYesYesYes
Individual fixed effectsYesYesYesYes
Constant term28.53 ***−1.125 ***8.285 ***−1.558 ***
(2.579)(0.216)(1.125)(0.204)
R20.4180.6160.4640.583
Note: Standard errors are in parentheses; *** indicate significance at the 1% level.
Table 10. Moran index under spatial adjacency matrix.
Table 10. Moran index under spatial adjacency matrix.
YearBcapAsus
20130.1862 *
(1.8197)		0.1493
(1.5041)
20140.2442 **
(2.3181)		0.1892 *
(1.8331)
20150.2440 ***
(2.6430)		0.1813 *
(1.7729)
20160.2126 ***
(2.7355)		0.2242 **
(2.1299)
20170.2726 ***
(2.6818)		0.1650
(1.6399)
20180.2671 ***
(2.5878)		0.2511 **
(2.3508)
20190.1969 **
(2.1295)		0.2058 **
(1.9704)
20200.1994 **
(2.1240)		0.2141 **
(2.0368)
20210.2597 ***
(2.5790)		0.0398
(0.6008)
20220.2585 **
(2.4038)		0.0463
(0.6532)
Note: Parentheses indicate Z value; ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.
Table 11. Empirical results of spatial Durbin model.
Table 11. Empirical results of spatial Durbin model.
(1) (2)
VariableCoefficientVariableCoefficient
Bcap0.0219 *W × Bcap0.0443 *
(0.0126) (0.0269)
Ginter−0.0648W × Ginter−0.224 **
(0.0406) (0.0900)
Tadv−0.000372 **W × Tadv0.000338
(0.000183) (0.000352)
Infra0.0583 ***W × Infra0.00690
(0.0164) (0.0377)
Infor−0.00263W × Infor−0.00217
(0.00586) (0.0121)
ρ 0.361 ***
(0.0731)
σ 2 0.000189 ***
(0.0000157)
Individual fixed effectsYes Yes
Time fixed effectsYes Yes
Observations300 300
R20.290 0.290
Note: Standard errors are in parentheses; ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.
Table 12. Spatial effect decomposition results.
Table 12. Spatial effect decomposition results.
(1)(2)(3)
VariableDirect EffectIndirect EffectTotal Utility
Bcap0.0274 **0.0787 **0.106 **
(0.0131)(0.0395)(0.0450)
Ginter−0.0939 **−0.369 ***−0.462 ***
(0.0374)(0.131)(0.153)
Tadv−0.000345 *0.000205−0.000140
(0.000198)(0.000485)(0.000561)
Infra0.0621 ***0.03860.101
(0.0190)(0.0590)(0.0691)
Infor−0.00416−0.00601−0.0102
(0.00738)(0.0199)(0.0241)
Individual fixed effects YesYesYes
Time fixed effectsYesYesYes
Observations300300300
R20.2900.2900.290
Note: Standard errors are in parentheses; ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.
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Yang, H.; Wang, F. The Impact of Industrial and Commercial Capital Influx on Sustainable Agricultural Development: Evidence from 30 Provinces in China from 2013 to 2022. Sustainability 2025, 17, 312. https://doi.org/10.3390/su17010312

AMA Style

Yang H, Wang F. The Impact of Industrial and Commercial Capital Influx on Sustainable Agricultural Development: Evidence from 30 Provinces in China from 2013 to 2022. Sustainability. 2025; 17(1):312. https://doi.org/10.3390/su17010312

Chicago/Turabian Style

Yang, Hongli, and Fengjuan Wang. 2025. "The Impact of Industrial and Commercial Capital Influx on Sustainable Agricultural Development: Evidence from 30 Provinces in China from 2013 to 2022" Sustainability 17, no. 1: 312. https://doi.org/10.3390/su17010312

APA Style

Yang, H., & Wang, F. (2025). The Impact of Industrial and Commercial Capital Influx on Sustainable Agricultural Development: Evidence from 30 Provinces in China from 2013 to 2022. Sustainability, 17(1), 312. https://doi.org/10.3390/su17010312

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