The Impact of Green Finance on China’s Agricultural Trade

Abstract

Enhancing the effectiveness of green development of the agricultural trade economy with green finance is a practical need to promote the healthy development of agricultural trade. This manuscript empirically analyzes the impact of green finance on China’s agricultural products import and export trade by using provincial-level panel data from 30 Chinese provinces from 2001–2019. The findings show that: (1) Green finance positively impacts China’s agricultural import and export trade at the 1% significant level, expanding the scale of agricultural imports and exports. (2) The positive impact of green finance on China’s agricultural import and export trade is heterogeneous across regions. Accordingly, this paper puts forward policy suggestions such as strengthening the support of green finance to agriculture, focusing on the improvement of green total factor productivity in agriculture, and promoting synergistic regional development through the implementation of differentiation of green finance.

1. Introduction

Since the twenty-first century, China’s rapid economic development has caused the deterioration of environmental resources, and the economic development constraints triggered by ecological damage have become increasingly evident. One crucial manifestation is that China’s total greenhouse gas emissions have been steadily ranked among the world’s highest [1]. If China maintains an economic development model of environmental degradation and resource waste, economic development will fail to be sustainable. Therefore, in recent years, the Chinese government has emphasized the sustainable development approach of protecting the environment and boosting economic growth. Besides, it has been promoting the economic development concept of “green development, circular development, and low-carbon development”, affirming that green development is an essential strategy for implementing sustainable development and promoting green development as a critical goal for China’s future economic development. In order to further implement the green development strategy and promote the sustainable development of China’s economy, China makes efforts to guide all industries to reduce environmental pollution in the production process, enhance the transformation and upgrading of polluting industries, and promote the optimization of green industrial structure. The former China Banking Regulatory Commission emphasized the importance of green financial development for China to achieve a green economy development model as early as 2012. It guided commercial banks to provide green financial services to different enterprises to force the green transformation of industries. In 2016, China included the idea of green finance for the first time in the agenda discussions of the G20 Summit, bringing the importance of green finance to a higher level for healthy economic development. Green finance is proposed to increase the flow of social capital and enhance various capital factors to domestic and foreign markets that are environmentally friendly, clean, and efficient. For the agricultural trade sector with high environmental dependence, the development of green finance provides a new model and opportunity for it.

All the while, the import and export trade of agricultural products occupies an essential position in China’s national economy, which is a necessary driving force for realizing the modernization of agriculture and rural areas and a double stabilizer for the regular operation of the economy and society. Since joining the World Trade Organization(WTO), China’s agricultural trade has become increasingly involved in the international market. It has now become the second-largest importer and fifth-largest exporter of agricultural products globally. In 2021, China’s agricultural imports and exports reached USD 304.17 billion, up 23.2% year-on-year, of which exports were USD 84.35 billion, up 10.9%; imports were USD 219.82 billion, an increase of 28.6%. However, constrained by the tightening of resource and environmental constraints and rising production costs, the production of agricultural products in China has begun to experience a decline in the quality of farm products, low production efficiency and significant price fluctuations, and other problems that need to be solved. Hence, the Chinese government has proposed the need to optimize the development strategy of foreign trade in agricultural products, promote the transformation and upgrading of agricultural import and export trade, optimize the layout of agricultural trade, and implement the diversification strategy of the agrarian business. At this time, the form of financing provided by green finance offers new opportunities for importing and exporting agricultural product enterprises. Green finance has become an essential way of funding import and export enterprises. Specifically, green finance effectively curbs pollution by providing environmental improvements and technological upgrades in the production process of enterprises [2]. The progress of the environment facilitates financial institutions to implement more effective risk management and structural strategies. By optimizing resource allocation and increasing the financing constraints of brown and black economies, high-carbon investments are curbed so that more talent, capital, information, and other resources are diverted away from the highly polluting backward production capacity [3,4]. In addition, these sources could flow to the more environmentally friendly, clean, efficient, and innovative agricultural sector, promoting the development of green and low-carbon agricultural products. What will the impact of green finance, as the practice and innovation of the green low-carbon development concept in the financial sector, be on agricultural product import and export trade? Is the impact on both imports and exports the same? This paper intends to empirically study the impact of green finance on agricultural product import and export trade based on provincial panel data from 30 Chinese provinces from 2010–2019 using a fixed-effect model. Further, we will explore the heterogeneous impact of green finance on foreign trade of agricultural products from multiple perspectives of agricultural development level and location characteristics and propose reasonable and reliable targeted suggestions by analyzing the promotion effect of green finance on agricultural exports and imports. The in-depth study of the above issues is of great theoretical and practical significance to promote the sustainable development of China’s agricultural import and export trade.

Comprehensive literature shows that most scholars have studied the impact on China’s trade from traditional credit in financial development, ignoring green finance in the field of ecological economics to improve the quality of the ecological environment and guide the sustainable development of agricultural trade. Moreover, there are more studies on the total trade of agricultural products, and there is a relative lack of discussion on the classification of agricultural products trade imports and exports. Based on this, this paper may have the following contributions or innovations: First, it is an in-depth analysis of the effects of green finance on the import and export trade of agricultural products, respectively. The second is to extend the study of green finance to agricultural trade and explore the trade effects of green finance to improve the ecological environment to enrich and complement the academic research perspective on international trade. In addition, this paper intends to empirically study the effects of green finance on agricultural product import and export trade using a fixed-effects model based on provincial panel data from 30 Chinese provinces from 2010–2019. The heterogeneous impact of green finance on agricultural import and export trade is further explored from the perspective of agricultural development level and location characteristics. Moreover, targeted suggestions are made by analyzing the promotion effect of green finance on farm import and export trade to ensure the healthy development of agricultural import and export trade.

The remaining sections of this paper are planned as follows: Section 2 presents the literature review. Section 3 provides the mechanistic analysis and research hypothesis. Section 4 indicates the research design. Section 5 shows the empirical results. Section 6 indicates the countermeasures and recommendations.

2. Literature Review

Since the emergence of green finance in the 1980s, it has been given different understandings and connotations by many international organizations, government agencies, and academic organizations, and it does not constitute a unified understanding. Salazar was the first to study green finance, arguing that it is a way to interoperate between the financial and environmental sectors by making specific innovations in the development of traditional finance [5]. Subsequently, academics have researched green finance’s specific concepts and impact mechanisms. In terms of conceptual definition, many scholars consider the development of green finance as a path to connect green development with the finance discipline. They propose that the market is the basis for the research conducted on green finance as a tool for the financial sector that can improve environmental quality as well as reduce environmental risks [6,7]. In addition, Bert Scholtens et al. (2007) focus more on green development and define green finance from the integrated perspective of financial innovation and environmental protection [8]. In the face of increasing environmental degradation, the essence of green finance is to provide enterprises with differentiated exogenous financing based on environmental constraints, using punitive high-interest rates and financing limits as a means to raise the enterprises’ financing threshold, increase financing costs, and create financing pressure [9]. Thus, the development scale of polluting enterprises can be controlled, and their transformation is forced. Wang Yao thought green finance is a concept under the category of “environmental protection,” which aims to achieve environmental protection and ecological diversification through financial means, solving the problems of pollution prevention and control and ecological balance [10]. In 2016, China issued the “Guidance on Building Green Financial System,” which defines green finance as “the financial services provided to support the economic activities of environmental improvement, climate change and efficient use of resources. This basic concept and its definition have been highly recognized by many scholars. In terms of impact mechanisms, numerous studies show a significant relationship between financial development and export trade and that an increase in financial development affects international trade. Early studies have indicated that a country’s financial development can alleviate the financing difficulties faced by the industry to increase the scale of corporate exports. In addition, there is variability in its impact on export trade across countries due to different levels of financial development [11]. At the micro level, financial development can increase firms’ probability of receiving external investment, thus providing additional access to finance [12]. Crino and Ogliari found that financial frictions caused by insufficient financial development not only reduce the quality of firms’ export products but also affect their export size and product prices [13].

Many studies at home and abroad prove a long-term equilibrium relationship between China’s agricultural exports, imports, and agricultural structure. The factors affecting agricultural trade are complex and diverse, and most studies are currently divided into macro- and micro-elements. At the macro level, a study using a gravity model regression test in terms of total agricultural trade found that the degree of cooperation between the two countries is closely related to the development of their bilateral agricultural trade [14]. Improved diplomatic relations between countries can signal confidence in the private investment sector and improve investors’ expectations of future trade activity, further weakening the political shocks’ impediment to bilateral trade [15]. On the micro level, Ding Yibing et al. used social network analysis to analyze the factors influencing interregional differences in China’s agricultural trade. The results manifested that regional economic development level, trade distance, and population size all impact China’s agrarian trade [16]. In terms of the level of financial development, when a region has a high level of financial development, it selects those regions with high external dependence on major agricultural exports, increasing the export trade of major products and boosting the export share [17,18]. Yu Maomao’s study found that promoting the use of green financial products can force the transformation and upgrading of heavily polluting agricultural enterprises and improve green agricultural technology [3]. Similar conclusions were reached by scholars such as Jin et al., who argued that green finance development could promote China’s export trade and bring about ecological improvement [19]. For instance, green credit can significantly improve the quality of manufacturing export products, stimulate corporate R&D investment and alleviate corporate financing constraints [20]. In summary, the previous literature has focused on the impact of traditional credit on China’s foreign trade in financial development but less on green finance, an essential financial credit approach closely related to the environment. In addition, there is a lack of research on the impact of green finance on China’s agricultural import and export trade.

3. Mechanistic Analysis and Research Hypothesis

China has implemented a financial support policy oriented toward increasing production in the issue of agricultural production. This policy has led to a series of problems to some extent, such as the low competitiveness of China’s agriculture and weak capacity for low-carbon green development [21]. Moreover, environmental problems also limit the growth of agricultural import and export trade [22]. For the agricultural sector, under the traditional financial credit model, the import and export of agricultural products in China still face considerable financing constraints and trade barriers. In addition, the development of green finance policy provides a new breakthrough for import and export enterprises under the standard financial exclusion. Implementing green economic policies can improve the functions of the agricultural sector, like optimizing resource allocation, promoting technological innovation, and providing financial support [23]. Furthermore, there is an urgent need for China to vigorously develop green and low-carbon agriculture with the help of green financial tools, improve the green quality of agricultural products, and further establish advantages in the import and export trade of agricultural products. It can be seen that, in this context, it is vital to study the mechanisms through which green finance affects the import and export trade of agricultural products.

3.1. The Impact of Green Finance on Agricultural Exports

Green finance can alleviate the financial needs of agricultural exports. Compared with other industries, agriculture is characterized by high risks, long cycles, low profits, and significant uncertainties, making it more difficult to obtain social financing [24]. Usually, the agricultural sector mainly uses financial subsidies as its primary source of funding, but with the gradual development of agriculture toward scale, mechanization, and greening, financial contributions often cannot meet the financial needs of enterprises for further expansion, upgrading equipment, and talent introduction. The emergence of green finance can solve the problems of low financing and complex financing for agricultural enterprises and greatly alleviate financing constraints [25]. These products, such as green credit, green bonds, green funds, green insurance, and green leasing, can meet the financial demands of production and R&D of green and low-carbon agricultural products, promoting agricultural trade exports.

Green finance can overcome green trade barriers. An important reason for the poor development of China’s agricultural export trade is the existence of green trade barriers in the international market. Green trade barriers are a series of green requirements and restrictions in exporting countries’ production, transportation, and sales of agricultural products. Only if they meet international green standards will they be allowed to export. China’s agricultural production has long relied excessively on high inputs of chemical fertilizers and pesticides, which will not only lead to a large number of carbon emissions during the production of agricultural products but also restrict the development of green agricultural products, making agricultural exports repeatedly hindered by green trade barriers. Green finance, as a policy instrument combining financial and environmental policies, can effectively resolve green trade barriers for agricultural products. On the one hand, the differentiated green credit mechanism could provide financial support for agricultural green development projects, direct the flow of funds to cleaner and more efficient agricultural production sectors, and improve the greening of agricultural production. On the other hand, green financial products such as green bonds and green insurance are used to alleviate the financial constraints encountered by environment-friendly agricultural enterprises’ R&D investments, to force heavily polluting agricultural enterprises to transform and upgrade to upgrade green technology [3], and to reduce agricultural carbon emissions. Moreover, this makes agricultural products comply with international trade regulations and breaks the green trade barriers for agricultural products.

Green finance can enhance the quality of agricultural exports. Green finance can improve agricultural green total factor productivity by expanding the development scale, optimizing financial development structure, and improving development efficiency [26]. With the help of tools such as green securities and green insurance, enterprises can integrate market resources, improve market information, and optimize risk control management using investment portfolios to further strengthen agricultural production management efficiency, thus increasing the added value of agricultural products. From the perspective of the supervision mechanism, introducing a green credit policy can inhibit inefficient investment of enterprises through the supervision mechanism and promote green agricultural production. Besides, from the perspective of the mechanism of elimination of winners and losers, for agricultural enterprises with low-end export products and severe environmental pollution, the green financial policy will eliminate such enterprises from the market by limiting credit. By the above means, it will promote the overall improvement of regional agricultural export quality and enhance the competitiveness of agricultural products in the international market to expand agricultural exports.

Based on the above analysis, this manuscript proposes Hypothesis 1.

Hypothesis 1 (H1).

Green finance has a positive impact on agricultural export trade.

3.2. The Impact of Green Finance on Agricultural Imports

Green finance is able to alleviate the financial needs of agricultural imports. Agricultural firms must explore foreign markets when importing behavior occurs because it is hard to obtain sufficient and reliable information about the other party. There will be problems, such as information asymmetry and adverse selection, which will pay colossal information-gathering costs. At the same time, the existence of transaction risks also makes agricultural businesses face the issue of sunk costs and are more likely to fall into financing difficulties compared to domestic sales enterprises [27]. In contrast, agribusinesses expand the supply of funds with the support of green finance, expanding the sources of funds and alleviating the import funding constraints faced by agribusinesses, which contribute to having a positive impact on their import activities.

In the long term, the green development of agriculture will be beneficial to the sustainable growth of agricultural trade, while in the short time, it will increase the production cost of agricultural products [22]. On the one hand, agricultural enterprises have to face decreased profits due to higher costs. On the other hand, product quality, carbon emissions, and waste emissions have to meet green testing standards. The green improvement of agricultural production often requires a more extended period for staffing, equipment procurement, input research and development, market inspection, and other processes. These offerings may not be able to meet green requirements such as carbon emissions in the short term. In addition, in the face of the dual standards of market demand and green financial institution acceptance, agribusiness prefers to choose import substitution as a short-term solution. Import substitution means that agricultural enterprises change their own product structure to meet the carbon emission requirements of green financial needs, i.e., increase the proportion of production of low-carbon agricultural products and relatively reduce the production of high-carbon agricultural products and meet the supply-demand of high-carbon farm products employing import. Agricultural products like soybeans, rubber, and beef produce many carbon emissions in the production process. If enterprises cannot achieve low-carbon production in the short term, expanding the import of such agricultural products is also one of the low-carbon development strategies.

Based on the preceding analysis, this paper presents Hypothesis 2.

Hypothesis 2 (H2).

Green finance has a positive impact on agricultural import trade.

4. Design of Research

4.1. Sources of Data

This paper intends to use provincial panel data of 30 Chinese provinces from 2001–2019, while Taiwan, Hong Kong, Macao, and Tibetan regions of China are not included in consideration of the availability of data and information. The data are obtained from the China Energy Statistical Yearbook, China Statistical Yearbook, China City Statistical Yearbook, China Insurance Yearbook, the National Bureau of Statistics, the statistical yearbooks of each province, as well as official website analysis reports. It contains detailed information on the import and export of agricultural products, the green financial development index, and various aspects of the national economy, infrastructure, fixed asset investment, finance, resources, and the environment. In order to eliminate the influence of the magnitude between variables, the variables are taken as logarithms to reduce the sample dispersion, which provides a good data environment for this study.

4.2. Selection of Variables

(1)

Explained variables. The import and export value of agricultural trade is selected in 30 Chinese provinces from 2001–2019 as the explanatory variables. Farm products’ total import and export value is converted by using the average exchange rate of RMB to USD in that year to eliminate the exchange rate effect.

(2)

Explanatory variables. The core explanatory variable of the article is green finance. The variable refers to the economic activities to support environmental improvement, combat climate change, and achieve resource conservation and efficient use, i.e., the financial services provided for investment and financing, project operation, and risk management of projects in the fields of environmental protection, energy conservation, clean energy, green transportation, and green buildings [26]. Besides, it is represented by the Green Finance Index (Gfin), which shows the degree of green finance development in each province, obtained by the entropy method based on relevant data.

(3)

Control variables. Since factors such as the scale of agricultural production, human capital, and transportation may have an impact on the study of this paper, the following variables were further controlled to ensure the accuracy of the results: gross agricultural product (Gap), grain production (Gp), years of schooling per capita (Yspc), number of road miles (Nrm), and number of large livestock (Nll). Specifically, the gross agricultural product(Gap) is measured as the gross domestic agricultural product. Grain production(Gp) is measured by a country’s total year-end food production. Years of schooling per capita(Yspc) reflect the population’s education level and are calculated according to the level of education. In other words, a college education is calculated as 16 years, high school as 12 years, middle school as 9 years, elementary school as 6 years, and illiteracy as 0 years. The average number of years of education for the population aged 6 years and above is calculated by this factor. The number of road miles(Nrm) is measured by choosing domestic road mileage access. The number of large livestock(Nll) is portrayed as the number of heads of large livestock at the end of the year. Descriptive statistics for the variables of interest are shown in

Table 1. Variable Statistics.

Symbol	Variable	Mean	Std. Dev.	Min	Max
Import	Agricultural Product Imports	16.822	29.622	0	165.639
Export	Agricultural Product Exports	10.73	17.208	0.039	115.279
Gfin	Green Finance Index	14.065	9.316	4	79
Gap	Gross Agricultural Product	1264.176	1116.658	28.6	5408.6
Gp	Grain Production	1839.706	1495.315	28.8	7506.8
Yspc	Years of Education per Capita	8.619	1.051	6.04	12.78
Nrm	Number of Road Miles	11.863	7.547	0.61	33.71
Nll	Number of Large Livestock	399.015	325.389	1.23	1508.8

.

4.3. Setting of Model

To test the hypothesis proposed, the following two-way fixed effect model is constructed to estimate the influence of green finance on the local trade of agricultural products.

$$\mathrm{Import}={\alpha }_1+{\beta }_1\mathrm{Gfin}+{\displaystyle \sum {\gamma }_j}{x}_j+{\mu }_i+{\mu }_t+{\epsilon }_{it}$$

$$\mathrm{Export}={\alpha }_2+{\beta }_2\mathrm{Gfin}+{\displaystyle \sum {\gamma }_j}{x}_j+{\mu }_i+{\mu }_t+{\epsilon }_{it}$$

where $\mathrm{Import}$ denotes the local import scale in that year, $\mathrm{Export}$ indicates the local export scale in that year, and $\mathrm{Gfin}$ represents the local green financial development index. In addition, $\sum {\gamma }_j{x}_j$ shows a series of control variables, where $j$ displays multiple variables, $i$ implies each province in China, $t$ denotes different years, ${\mu }_i$ and ${\mu }_t$ represent individual effects and time effects in multiple regressions, and ${\epsilon }_{it}$ shows random disturbance terms. ${\beta }_i$ is the parameter to be estimated, and ${\beta }_1$ and ${\beta }_2$ are the coefficients of focus in this paper. If the regression coefficients ${\beta }_1$ and ${\beta }_2$ are significantly positive, it proves that there is a direct positive impact of the improvement of the level of green financial development on the promotion of the local import and export scale.

5. Empirical Results

5.1. Baseline Regression

The setting of the two-way fixed effects model has been explained at the theoretical level in the model set, but the selection of the empirical model still needs to be verified by the Hausman test. The original hypothesis is that the difference in coefficients is not systematic. The results are shown in

Table 2. Hausman specification test.

	Coef.
Chi-square test value	47.169
p-value	0.00

, which rejects the initial hypothesis at the 1% level, indicating that the two-way fixed-effects model has better results in the theoretical validation of this article.

The first and second columns in

Table 3. Benchmark regression results.

Variable	(1)	(2)	(3)	(4)
	Import	Import	Export	Export
Gfin	2.692 ***	2.720 ***	0.273 ***	0.208 **
	(0.143)	(0.153)	(0.0968)	(0.0989)
Gap		0.00890 ***		0.00829 ***
		(0.00180)		(0.00117)
Gp		−0.00326 **		−0.00502 ***
		(0.00145)		(0.000938)
Yspc		−7.077 **		1.877
		(2.972)		(1.926)
Nrm		−1.181 ***		−0.493 ***
		(0.291)		(0.189)
Nll		−0.0127 **		−0.0134 ***
		(0.00629)		(0.00407)
Individual fixed effects	Y	Y	Y	Y
Time Fixed effects	Y	Y	Y	Y
_cons	−18.78 ***	48.57 **	1.112	−0.0574
	(2.436)	(22.20)	(1.645)	(14.39)
N	570	570	570	570
R2	0.5862	0.6238	0.2268	0.3860

Note: *** means significant at the 1% level, ** means significant at the 5% level. The errors in the brackets are robust labels.

show the regression results of the empirical import model, while the third and fourth columns imply that of the empirical export model. Among them, the first and third columns do not introduce control variables, and the second and fourth columns add control variables. The regression results are as follows: from models (1) and (2), it can be seen that green finance on agricultural imports is positive at a 1% significance level, indicating that green finance can promote agrarian imports and the development of green finance boosts import substitution in the short term. It optimizes agricultural import channels to expand the import scale. Thus, hypothesis 1 is proved. As for models (3) and (4), green finance is significantly positive for agricultural exports at the 5% level, manifesting that the growth of green finance can promote the export of agricultural products in the regional context, so hypothesis 2 is proved. This is because, with the policy support of green finance, the relevant subjects utilize green credit and green securities to increase the research and development of green technology and upgrade the appropriate equipment so as to improve the green total factor productivity of agriculture and make the relevant agricultural products produced by them meet the import and export standards of more countries, thus making the export scale expand.

Regarding the effect of control variables on agricultural imports, the impact of the gross agricultural product on imports is sustainability positive at the 1% level, indicating that the larger the gross agricultural product, the greater the agrarian imports. The gross agricultural product is a primary indicator of the scale of agricultural development in a province. The larger the scale of agriculture, the more agricultural products need to be imported to reduce overall carbon emissions and agricultural pollution, hence more imports. The effect of grain production on agricultural imports is significantly negative, implying that the more grain production of a province, the fewer agricultural imports. The possible reason for this is that grains are one of the leading agricultural products imported into China, and the larger the grain-producing province, the lower the import demand for grains. The influence of years of education per capita on agricultural imports is strongly negative, representing that the higher the number of years of education of residents, the lower the agricultural imports of the province. Because the higher the number of years of education of residents, the more likely they are to be employed in secondary and tertiary industries. There will be a decrease in the importance of and participation in agriculture, leading to a reduction in agricultural imports. The considerable negative effect of kilometer-mileage on imports may exist because the main import channel is maritime transport. Generally, provinces with large kilometer-mileage are geographically inland, and the relative cost of import is higher, so there will be a decline in import volume. The impact of the number of large livestock on agricultural imports is similar to the former. Meanwhile, meat is also the primary category of overseas imports, so provinces with a large number of large livestock have less demand for meat imports.

In terms of the effects of the control variables on agricultural exports, the influence of gross agricultural product on agrarian exports is remarkably positive, and the more the number of the gross product, the larger the scale of agricultural production in the province, and then the corresponding exports is getting more. The impact of grain production on exports is significantly negative, probably because large grain-producing areas often bear the burden of domestic grain supply, and the larger the grain production, the more priority is given to supplying the domestic market, and exports will be relatively reduced. The effect of kilometer mileage on exports is considerably negative, as provinces with more enormous kilometer mileage are mostly inland, and the transportation cost for exports are relatively more prominent, so the willingness to export will be reduced. The influence of the number of large livestock on the export of agricultural products is strongly negative, and the reason is similar to the export of cereals. The meat of provinces with extensive livestock development will be supplied to the domestic market as a priority after meeting their own demand, and the export volume may be decreased.

5.2. Robustness Tests

5.2.1. Excluding Municipalities

With small administrative space and high administrative status within the municipality, this type of sample, compared to other provincial samples, will make the estimation results biased, so the regression model with two-way fixed effects is employed after excluding the relevant samples, with the results shown in

Table 4. Baseline regression and exclusion of municipality sample regression results.

Variables	Whole Samples of Import	Non-Municipal Import	Whole Samples of Export	Non-Municipal Export
Gfin	2.720 ***	3.932 ***	0.208 **	1.538 ***
	(0.153)	(0.329)	(0.0989)	(0.271)
Control Variables	Y	Y	Y	Y
Individual Effects	Y	Y	Y	Y
Time Effects	Y	Y	Y	Y
_cons	48.57 **	−17.67	−0.0574	1.733
	(22.20)	(31.32)	(14.39)	(25.83)
N	570	285	570	285
R2	0.6238	0.7036	0.3860	0.4792

Note: *** means significant at the 1% level, ** means significant at the 5% level. The errors in the brackets are robust labels.

. From the regression results, it can be seen that the sign of the regression results does not change after excluding the samples from the municipalities, i.e., green finance has a remarkably positive effect on the development of foreign trade of agricultural products. It confirms that the coefficients of the regression model are robust. When comparing the coefficients of the excluded municipalities with those of the unexcluded municipalities, we find that the coefficients of the non-municipalities are more significant than those of the whole sample, which indicates that green finance has a greater impact on the import and export of agricultural products in the non-municipalities. The reason for this is that, compared with the non-municipality directly under the central government, the municipality directly under the central government is at an absolute advantage in terms of economic development, personnel structure, institutional setup, and information network. Therefore, green finance will direct more resources to the secondary and tertiary industries with higher investment returns and pay less attention to agriculture, which has a smaller scale of development and less influence on agricultural trade.

5.2.2. Endogenous Processing

There may be endogeneity in the results of the benchmark regressions in this paper. On the one hand, green finance and agricultural trade may be causally related. On the other hand, there may be omitted variables. Some unobservable factors may also affect agrarian business. Based on this, each province’s lagged one-period green finance development index is used as an instrumental variable for regression validation. The endogeneity problem can be mitigated to some extent by analyzing the impact of the green finance index of the previous year on the foreign trade of agricultural products in the current year. From

Table 5. Baseline regression with lagged one-period results.

Variables	Import	Import	Export	Export
Gfin	2.692 ***		0.273 ***
	(0.143)		(0.0968)
L.Gfin		2.768 ***		0.192 *
		(0.166)		(0.106)
Control Variables	Y	Y	Y	Y
Individual Effects	Y	Y	Y	Y
Time Effects	Y	Y	Y	Y
_cons	−18.78 ***	43.25 *	1.112	−4.371
	(2.436)	(22.92)	(1.645)	(14.58)
N	570	540	570	540
R2	0.5862	0.6056	0.2668	0.3676

Note: *** means significant at the 1% level, * means significant at the 10% level. The errors in the brackets are robust labels.

, it can be concluded that after regression using the lagged one-period green finance index, the direction of the impact of green finance on agricultural import and export trade remains unchanged, and the estimation is still substantial at the 1% level, showing that the baseline regression results are still robust.

5.2.3. Heterogeneity Analysis

Due to the different geographical resources, uneven levels of agricultural development among regions, and remarkable differences in infrastructure and public services, the impact of green finance on the import and export trade of agricultural products in the different areas may vary. To further explore the effect of green finance on the foreign business of agricultural offerings in the context of various regions. Two dimensions of geographical location and agricultural development level are analyzed, respectively.

First of all, as for the locational heterogeneity, this article groups the samples according to the eastern, central, and western regions and conducts regressions on the grouped samples. In particular, the eastern area includes Hebei, Beijing, Tianjin, Shandong, Jiangsu, Shanghai, Zhejiang, Fujian, Guangdong, and Hainan; the central region contains Shanxi, Henan, Anhui, Hubei, and Jiangxi; the western region covers Sichuan, Yunnan, Guizhou, Chongqing, Shaanxi, Gansu, Qinghai, Xinjiang, Ningxia, Inner Mongolia, and Guangxi. From the regression results in

Table 6. Regional Heterogeneity of Agricultural Product Imports.

Variables	Import	East	Middle	West
Gfin	2.455 ***	5.407 ***	1.698 ***	1.137 ***
	(0.142)	(0.661)	(0.0958)	(0.191)
Control Variables	Y	Y	Y	Y
Individual Effects	Y	Y	Y	Y
Time Effects	Y	Y	Y	Y
_cons	38.85 ***	40.51	−13.06	24.98 ***
	(12.44)	(67.92)	(17.55)	(9.150)
N	570	152	266	152
R2	0.5883	0.7835	0.8023	0.7378

Note: *** means significant at the 1% level. The errors in the brackets are robust labels.

and

Table 7. Regional Heterogeneity of Agricultural Product Exports.

Variables	Export	East	Middle	West
Gfin	0.174 *	0.0737	−0.294 ***	0.236 ***
	(0.0899)	(0.450)	(0.0562)	(0.0826)
Control Variables	Y	Y	Y	Y
Individual Effects	Y	Y	Y	Y
Time Effects	Y	Y	Y	Y
_cons	5.439	15.61	−26.97 ***	10.31 **
	(7.869)	(46.27)	(10.29)	(3.963)
N	570	152	266	152
R2	0.3598	0.6480	0.5540	0.7312

Note: *** means significant at the 1% level, ** means significant at the 5% level, * means significant at the 10% level. The errors in the brackets are robust labels.

, green finance’s impact on agricultural import trade is substantial, and the coefficient is positive in all three regions. However, green finance in the eastern region does not have a significant impact on agricultural export trade. In the central part, it negatively impacts agricultural export trade, and in the western area, it has a positive and significant effect on agricultural export business. Moreover, green finance has different situations on agricultural export trade in different regions. The eastern region is close to the port, and its geographical advantage leads to a more mature development of the foreign trade industry. Hence, the effect of green finance on foreign agricultural trade is not apparent. The central area has a higher economic development and better financial market development than the western region. At the same time, the capital market has diversified financing products, which provides additional financing channels for trade activities in the local market and weakens the credit support of green finance to agricultural enterprises to inhibit the export of farm products.

Secondly, from the perspective of heterogeneity of agricultural development level, this paper considers the outbreak of the “new crown epidemic” in 2019. It divides 30 provinces and cities into advanced agricultural provinces and non-advanced agricultural provinces based on the ranking of the agricultural GDP of each province and city in 2018. The top 10 provinces are advanced agrarian provinces, and the rest 20 are non-advanced ones. The top ten provinces and cities are Henan Province, Shandong Province, Sichuan Province, Jiangsu Province, Heilongjiang Province, Guangdong Province, Hebei Province, Hubei Province, Guangxi Zhuang Autonomous Region, and Hunan Province, while the rest of them are ranked in the bottom twenty. From the estimation in

Table 8. The Impact of Green Finance on Agricultural Product Imports in Advanced Agricultural Provinces and Non-advanced Agricultural Provinces.

Variables	Import	Advanced	Non-Advanced
Gfin	2.455 ***	6.860 ***	2.560 ***
	(0.142)	(0.434)	(0.163)
Control Variables	Y	Y	Y
Individual Effects	Y	Y	Y
Time Effects	Y	Y	Y
_cons	38.85 ***	−73.07	45.94 *
	(12.44)	(44.32)	(24.44)
N	570	95	475
R2	0.5883	0.9927	0.5922

Note: *** means significant at the 1% level, * means significant at the 10% level. The errors in the brackets are robust labels.

and

Table 9. The Impact of Green Finance on Agricultural Product Exports in Advanced Agricultural Provinces and Non-advanced Agricultural Provinces.

Variables	Export	Advanced	Non-Advanced
Gfin	0.174 *	2.726 ***	0.0991
	(0.0899)	(0.172)	(0.108)
Control Variables	Y	Y	Y
Individual Effects	Y	Y	Y
Time Effects	Y	Y	Y
_cons	5.439	−74.41 ***	−0.174
	(7.869)	(17.58)	(16.21)
N	570	95	475
R2	0.3598	0.9338	0.3385

Note: *** means significant at the 1% level, * means significant at the 10% level. The errors in the brackets are robust labels.

, it can be seen that the impact of green finance on agricultural import trade in advanced agricultural provinces and non-advanced ones is significant, and the coefficient is positive, which is the same as that on the farm export business in advanced agrarian provinces. However, the influence of green finance on the agricultural export trade of non-advanced farm provinces is insignificant. The reason is that the non-advanced agricultural provinces have a lower level of agricultural development. The production and quality of farm products need to be improved, coupled with their own limited level of openness to the outside world. Therefore, green finance does not have a significant impact on agricultural trade exports.

6. Countermeasures and Recommendations

The manuscript selects panel data from 30 Chinese provinces from 2001–2019 and empirically analyzes the impact of green finance on agricultural import and export trade, and obtains the following conclusions: first, green finance effectively promotes the development of China’s agricultural foreign trade, expanding both the scale of agricultural imports and exports. Second, there is regional and agricultural development level heterogeneity in green finance on agricultural trade. Green finance development will promote agricultural imports in the eastern, middle, and western regions of China and also improve agricultural exports in the western provinces. Conversely, it will inhibit exports in the central areas, and the effect on the eastern provinces is insignificant. The results of the impacts on advanced agricultural regions and non-advanced farm provinces show that green finance will increase agricultural imports in both advanced agricultural areas and non-advanced ones and will also expand agricultural exports in advanced agrarian provinces. However, the impact on the export of non-advanced agricultural provinces is insignificant. Based on the above findings, the following countermeasures are proposed.

(1)

Strengthen the support of green finance to agricultural production and improve the quality of agricultural trade.

Green finance has an essential role in promoting the import and export trade of agricultural products, which is conducive to expanding the scale of business, strengthening trade exchanges, improving information-sharing mechanisms, and realizing trade progress. Therefore, we should give full play to the driving role of green finance for agricultural trade, develop the upgrading of domestic agrarian production structure, and improve the construction of foreign trade systems of farming products. Relevant departments should thoroughly guide and encourage the specific practice of green finance in the agricultural sector, provide more financial support for green agricultural production through green credit, and encourage technological innovation and industrial upgrading. We could apply green transportation, green equipment, and other infrastructure construction to reduce carbon emissions and promote environmental improvement so that the purpose of enhancing the green efficiency of agriculture can be achieved and the progress of agricultural trade is supposed to be enabled.

(2)

Implement differentiated green financial policies to promote the synergistic development of agricultural trade.

From the perspective of each province’s agricultural development level and location characteristics, it is necessary to use differentiated green financial policies in various regions in accordance with their own characteristics and local conditions. For instance, in provinces where agricultural resources are relatively scarce but with sound economic development, local social networks should be used to integrate the resources of universities and research institutes to strengthen research and development of new green and low-carbon technologies. The government should make use of the mature local market mechanism and give full play to the incentive effect of green finance for agribusiness cooperation. Conversely, in regions rich in agricultural resources but less economically developed, more green financial tools ought to be used to guide the flow of capital to cleaner and more efficient agricultural production sectors and to promote the structural upgrading and green transformation of local agriculture. In short, a large unified market with complementary resources, information sharing, and risk sharing should be formed nationwide to promote synergistic regional agricultural trade development.

(3)

Optimize the production structure of agricultural products and improve the construction of the farming products system.

From the current status of China’s import and export of agricultural products, the overall scale of development continues to expand. On the one hand, in the short term, the domestic market can reduce high carbon production as well as break through the green barrier restrictions utilizing trade substitution. On the other hand, in the long term, firstly, we are supposed to establish a sound market management mechanism, unify green standards for agricultural products, and strict testing procedures. Secondly, we should integrate market resources, unite enterprises, universities, and financial institutions to form a significant alliance for green production, share information, complement resources, and coordinate development. Finally, the government ought to increase policy subsidies and actively implement activities conducive to developing green agriculture, such as agricultural training and publicity, to promote the development of low-carbon green agriculture. Furthermore, it could break through the work of high-carbon agrarian products to reduce emissions and optimize and upgrade the production structure of farm products.

This manuscript not only enriches the study of the mechanism of the role of green finance development on China’s foreign trade in agricultural products from a theoretical perspective, but also provides targeted policy recommendations for China to promote the sustainable development of agricultural import and export trade from a practical perspective. However, there are still some limitations in this paper. Due to the availability of data, the research time frame of this paper ends in 2019, and we will conduct an in-depth examination in future studies. In addition, the research on green financial development can be further examined in more detail in terms of green credit, green bonds, and green leasing in the follow-up, and the impact of different types of green financial instruments or policies on China’s agricultural import and export trade can be studied deeply.