This study tries to determine whether or not agricultural insurance has a substantial influence on farmers' increases in revenue. For the test, we've utilised the system generalized moment estimation (GMM), panel fixed effects, and ordinary least squares technique (OLS). The findings demonstrate a strong beneficial influence on farmers' income growth from increased agricultural insurance density and per capita pay. The indices used in this study to gauge the growth of agricultural insurance are per capita compensation and insurance density. Therefore, it can be said that Guangdong Province's (China) growth of agricultural insurance would successfully raise farmers' income levels. This study eventually offers pertinent countermeasures and recommendations based on the findings of theoretical and empirical research, as well as the present state of agricultural insurance development in Guangdong Province. From the viewpoints of applicable system design, subsidy strategies, insurance innovation, service level, and publicity, it offers some suggestions for maximising the contribution of agricultural insurance to improving farmers' income.
- Initialization
The foundation of China's national economy is agriculture, which has a crucial strategic role in the country's transition from a small agrarian nation to an economic superpower. Leading the nation's reform and opening up is the province of Guangdong. With established industry and high levels of urbanisation, the province's economic growth is among the finest in the nation, but there is also the issue of unequal development within the area. The three agricultural difficulties have not been totally handled in terms of the province. The topic of agricultural development cannot be disregarded since agriculture is crucial to the growth of secondary and tertiary industries in the rapidly expanding Guangdong Province.
The province of Guangdong is situated along the southeast coast Area. Bai emphasised that Guangdong is a typical "climate fragile area" with frequent natural catastrophes, freezing calamities, and droughts in the winter mountains in addition to strong convective weather like typhoons and heavy rains in the summer. And the intensity is strongest in the country's front regions, having a significant negative influence on agricultural output. Agricultural insurance is a useful instrument for transferring risk and is important for enhancing the robustness of agricultural output, Minimising the losses brought on by natural catastrophes to agricultural production, and safeguarding farmers' total income. Additionally, it is important for transferring financial risks, economic compensation, and agricultural hazards.
The most important of the measured effects is a decrease in the volatility of farmers' income. What effect will agricultural insurance have on farmers' income growth despite the fact that it plays a part in fostering agricultural development and Stabilising farmers' income? What is the impact's method and scope? It is still unclear how the government and insurance providers should handle agriculture insurance. The study of Guangdong Province's economic growth is receiving more attention from academics. Even little research has been done on the connection between farmer income. This article establishes the study subject by taking into account the modern themes of agricultural development and the significance of agricultural insurance in resolving the three rural challenges.
In Guangdong Province, agricultural insurance has been tested since 1985 and has through a protracted development process. Guangdong Province started investigating the growth of farm insurance in 1985; at the time, it was being held by Chinese private insurance firms. During the five-year period, the average yearly premium for agriculture insurance in Guangdong Province was close to 4.2 million yuan, and the comprehensive loss rate approached 95%, making operation difficult. Guangdong Agricultural Insurance has offered 78.2 billion yuan in risk protection for agricultural output as of 2019, and there are now 23 types that are covered at the province level. with the size of agricultural insurance premiums totaling 6.222 billion yuan, the depth of agricultural insurance at more than 1.2%, and the density at 500 yuan per person. From 53 million in 2007 to 1.882 billion yuan in 2019, the revenue from agricultural insurance premiums has grown dramatically, showing that the expansion of agriculture insurance with financial subsidies has produced good benefits. It has been shown that local government revenue from farm insurance premiums varies substantially.
Except for Guangzhou, the revenue from agriculture insurance premiums is modest throughout the Pearl River Delta area. The revenue from farm insurance premiums is larger in Shaoguan, Meizhou, Qingyuan, Zhanjiang, Maoming, and other cities, amounting to 100 million to 300 million yuan. Due to the abundance of agricultural resources in these five cities, there is room for the growth of agricultural insurance. Jiangmen, Yangjiang, Zhaoqing, Heyuan, and Yunfu all get agricultural insurance premium income in the second tier, with premium ranges ranging from 60 million to 8000 yuan. Additionally, Foshan, zhongshan, Dongguan, Chaozhou, Jieyang, and other places have significantly less advanced agriculture insurance development.
Many academics have recently focused on the issues of agricultural insurance and agricultural output, and they have produced particular research findings that provide some inspiration and illumination for the study of this article. However, this article's study also contains several unique breakthroughs. Due to the absence of attention for autocorrelation difficulties, the majority of the research findings of predecessors employed time-series data for study and mostly static panel model analysis. This study chooses 20 Guangdong Province cities' panel data for the period 2010–2019, builds a panel model with fixed effects and system generalised moments, and corrects the estimate bias brought on by the endogenous information issue of the explained variable's lag term. In this study, the Zhou approach is combined with the Shi threshold effect model, which enriches the threshold to some level. The study on farm insurance at the provincial level in Guangdong Province is supplemented by the notion of the impact. Few studies have looked at this topic from the viewpoint of Guangdong Province; the majority of earlier studies have been done on the national or regional level. In certain ways, the study in this paper has met the high standards for Guangdong farm insurance.
This article provides a theoretical basis for effectively playing the role of agricultural insurance. Many scholars in China and abroad have paid attention to agricultural insurance issues, mainly focusing on the nature of agrarian insurance, influencing demand factors, impact on farm output and income of farmers, etc. But, research on the impact of Guangdong agricultural insurance on farmers’ income is temporarily limited. Based on previous studies, this paper uses the agricultural insurance data of 20 cities in Guangdong Province in the past ten years as the research basis and uses empirical research methods to test the impact of agricultural insurance on farmers’ income. It enriches the research ideas of agricultural insurance issues at the provincial level to a certain extent.
This paper is constructed as follows: the first section is the introduction, which includes the research gap, research significance, and key research questions. The next part is a literature review where we have added related previous studies from Chinese and international scholars. Chapter three discusses the research methodology. Chapter four presents the empirical analysis, and the next chapter explains the results of the investigation. In the last chapter in the conclusion, we have added the study’s summary, limitations, and future scope.
2. Literature review
2.1. Research on the influencing factors of agricultural insurance demand
The determinants of farmers' need for agricultural insurance have been studied by academics. They mostly hold the view that the demand for agricultural insurance is influenced by factors other than only farmer income. In their study, Abraham et al. chose 120 rural homes using a three-stage selection method. Age, education, and agricultural income may all have an impact on farmers' propensity to enrol in agricultural insurance, according to a questionnaire poll. According to Moschini and Hennessy, whether or not farmers engage in agricultural insurance will depend on their risk preferences. Farmers with a high risk tolerance tend to assume the majority of the risk themselves, whilst those who are more risk averse may not utilise agricultural insurance to transfer risks. King & Singh discovered that access to private transfers replaces the requirement for insurance. But being a member of a farmer's union helps one appreciate why farmers value index insurance. According to Coble et al., a single economic factor—which takes into account farmers' risk awareness and crop risk status—usually determines whether they choose to participate in agricultural insurance. According to the research by Sujarwo et al., factors influencing farmers' readiness to take agrarian insurance include the size of their farming operations, their prior experience with buying agricultural insurance, and even their attendance at farmers' group meetings. Additionally, involvement in the insurance policy seems to be supported by age, female gender, and past insurance experiences.
2.2. Research on the impact of agricultural insurance on farmers’ income
When analysing how agricultural insurance affects farmers' income, scholars' opinions may be broadly split into two camps. Contrary to popular belief, some people think that agricultural insurance negatively impacts farmers' income and agricultural productivity. Yamauchi employed Japanese rice farmers who had acquired insurance in the Aomori Prefecture as his study subject as early as the 1980s. He discovered that mandatory crop insurance, particularly in the case of catastrophic calamities, helped stabilise farmers' income. Farmers that bought crop insurance in southern India were successfully able to raise their revenue, according to research by Xavier et al. Agrarian insurance may significantly lessen the volatility of farmers' incomes and boost farmers' income, according to Hosseini & Gholizadeh and Enjolras. Researchers like Leatham examined the growth of agricultural insurance in North Dakota, United States, and came to the conclusion that farmers' total income would rise by $1.03 for every dollar of agrarian insurance payout. Barry came to the statistical conclusion that farmers' income surpasses more than half of the average production years in years when they are exposed to agricultural risks, demonstrating the beneficial effects of agricultural insurance on farmers' revenue. Babcock and Hart, Glauber et al. believe that although agricultural insurance increases agricultural output, it will shift the supply curve to the right, resulting in a decrease in the price of agricultural products but not necessarily an increase in farmers' income in the long run. The influence of crop insurance on farmers' income is not always considerable, and in certain years, the two can have a negative connection, according to research by Robert et al.
2.3. Research on the nature of agricultural insurance
For the research on the nature of agricultural insurance, many scholars believe that agricultural insurance has the attribute of public goods. For example, in Tuo and Wang’s study, agricultural insurance has both the attributes of private goods and public products, a quasi-public product. Feng & Su also believe that agricultural insurance is not a personal good; it has apparent externalities. Zhang proposed that the failure of the agricultural insurance market is precisely due to its positive externalities. Zhang and Chen proposed that agricultural insurance should be carried out as a government’s beneficial agricultural project rather than a purely commercial operation. Zhang further proposed that the government should adopt diversified subsidy methods to support the healthy development of agricultural insurance. Liu and Sun also believe that implementing premium subsidies can further promote farmers’ willingness to participate in agricultural insurance.
2.4. Research on the impact of agricultural insurance on agricultural output
Many scholars have researched agricultural insurance and agricultural output. Most scholars believe there is a significant positive correlation between agricultural insurance and agricultural output. akinrinola & Okunola evaluated the success of the Nigerian Agricultural Insurance Scheme’s goals in Ondo State. The study demonstrates that the farmers’ participation in the insurance program was solely motivated by their ability to get financing. On the other hand, the farmers claimed that more investments had led to higher gains in output. Scholars such as Feng and fei believe that agricultural insurance can promote agrarian output to a certain extent. Zhou & Zhao and Wang used a dynamic panel model to conduct empirical analysis and concluded that agricultural insurance has largely promoted agricultural production. Scholars such as Huang & Pu, Cheng et al. , and Jiang & Zhang also believe that agricultural insurance can increase agricultural output.
In contrast, some scholars do not believe there is a strong relationship between these two. For example, Zhang et al. assume that under the condition that the level and proportion of agricultural insurance subsidies are low, the total production of agricultural products will not significantly change. Hu analyzed the impact of agricultural insurance on agricultural production capacity by hypothesis testing, and the results showed that the impact is almost non-existent, and there is no significant correlation between agricultural insurance and food production.
2.5. Research on the direction and path of agricultural insurance’s impact on farmers’ income
Some scholars have researched the issue of agricultural insurance on farmers’ income. Jiang believes that agricultural insurance under financial subsidies significantly affects farmers’ income. Yuan et al. Sun & Chen analyzed based on the data of Jilin Province and found that agricultural insurance also promoted the income growth of local farmers to a certain extent. Zhang & Sun used panel data from 31 provinces across the country to perform a cluster analysis and found that agricultural insurance played a certain role in promoting the growth of farmers’ income from a national perspective. However, other scholars believe that the impact of agricultural insurance on farmers’ income is not necessarily noticeable. For example, through cluster analysis, Yang and Shi found that china’s agricultural insurance did not significantly increase farmers’ income. hou et al. also pointed out that agricultural insurance plays a small role in promoting farmers’ income growth. Zhu & Tao tested the impact of agricultural insurance on farmers’ income through panel data and found that agricultural insurance not only does not Promote the increase of farmers’ income but also has a significant negative effect.
Scholars have different opinions regarding agricultural insurance’s impact on farmers’ income. Zhou et al. believe that agricultural insurance can protect farmers’ income, but this protective effect only appears in post-disaster compensation. Zhang & Sun used cluster analysis to divide 31 provinces into six regions and used the Hausman test method and generalized least squares (GLS) estimation method to conduct empirical research and found that agricultural insurance can significantly increase farmers’ operating income. According to them, the effect of agricultural insurance on financial subsidies is more prominent. Fei et al.believe that agricultural insurance reduces the fluctuation of farmers’ income through the payment of indemnities and the promotion of agricultural technology by insurance companies. Lu et al.Stated that agricultural insurance is carried out through financial subsidies in the form of transfer payments to increase farmers’ income, and there are obvious differences in the internal mechanisms of farmers’ income increase in eastern and western China.
3. Research methodology
This article analyzes many Chinese and foreign agricultural insurance documents on agricultural production and farmers’ income and documents on the development of agricultural insurance in Guangdong Province. It sorts out the mechanism and path of agricultural insurance’s impact on farmers’ income and further analyzes the impact of agricultural insurance on farmers’ income. At the same time, it also analyzes other related factors affecting farmers’ income, which provides a certain basis for the selection of control variables in the empirical analysis of this article. In addition, we have considered related theories, such as expected utility theory, welfare economics affect approach, and non-Walrasian equilibrium theory, to explore their application in agricultural insurance and provide a foundation for a thorough understanding of the nature of agricultural insurance. That helped us for improving the theoretical level of this article.
Considering the availability and completeness of the data, the per capita disposable income of farmers reflecting the income level of farmers is selected as the explanatory variable. The relevant indicators of the development level of agricultural insurance are used as the explanatory variables. The urbanization rate, mechanization level, industrial structure, and agricultural investment level are added as control variables. The data studied in this paper are all from the China Insurance Yearbook from 2011 to 2020, the Guangdong Statistical Yearbook from 2009 to 2020, the Guangdong Rural Statistics Yearbook, the China Rural Research Database, and the Chinese Rural Research Database.
The empirical analysis is an important research method for this article. After referring to the practice of Zhou (2018) and other scholars, this article uses ordinary least squares, fixed effects, and system generalized moment estimation methods to analyze whether agricultural insurance impacts farmers’ income. On this basis, referring to Shi and Li , a panel threshold model was established to test the characteristics of the impact of agricultural insurance on farmers’ income. First, by collecting and sorting out the relevant data of 20 cities in Guangdong Province (except Shenzhen) from 2009 to 2019, establish a static panel model, use Stata 15 software to operate, and compare the results obtained with the estimated results of the dynamic panel model. Next stage, we analyzed the test results of the system GMM that considers the endogenous problem. Subsequently, a panel threshold model was established to test whether there is a threshold value for agricultural insurance density and per capita compensation. Finally, an objective, standardized, and rigorous empirical analysis conclusion can be drawn to test whether the hypothesis in this article is correct, and this article is summarized research conclusions accordingly.
A statistical income probability distribution method is adopted to explore further the role of agricultural policy insurance in guaranteeing farmers’ income. After analyzing, we have made the following four hypotheses:
(1) The risk hazards faced in the agricultural production process are lucid; the hazards either occur or do not occur. The probability of occurrence is set to P, and the likelihood of non-occurrence is 1-P. And 0<P≤1.
(2) The income of farmers in production and operation obeys the binomial distribution: either no loss occurs, and the income is Y at this time, or there is a loss, and the loss causes the current production and operation income to be 0.
(3) Assuming that farmers’ proficiency in production technology, crop quality, and other factors are consistent, there are two ways for farmers to avoid production risks: participating in agricultural insurance (M) and not participating in agricultural insurance (N).
(4) assuming that the premium of agricultural insurance is B. The government subsidy ratio for agricultural insurance is L. When the loss does not occur, the farmer’s income is Y. Otherwise, it is 0, but at this time, the actual income obtained by the farmer who purchases agricultural insurance is A, 0<A≤Y.
Therefore, the income probability distributions of farmers who purchase policy-based agricultural insurance and those who do not purchase policy-based agricultural insurance are obtained when risks occur and when risks do not occur, as follows :
Table 1Income probability distribution of farmers buying and not buying agricultural insurance when risks occur and when they do not occur.
| Whether to purchase agricultural insurance Risk | Accident occurred (P) | No risk accident occurred (1-P) |
|---|---|---|
| purchase M | A-B | Y-B |
| No purchase N | 0 | Y |
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From Table 1, it can be concluded that the expected benefits of farmers who purchase agricultural insurance and those who do not purchase agricultural insurance are :E(M)=P(A−B)+(1−P)(Y−B)=(1−P)Y+PA−B=(1−P)Y+ϕ(1)
E(N)=Y(1−P)(2)
Let ϕ = PA−B, where PA is the insurance compensation farmers who purchase agricultural insurance expect to receive. If the amount is equal to the premium B paid when buying agricultural insurance, the farmers believe that there is no need to participate in the insurance, so the enthusiasm for buying agricultural insurance is not high. However, since most of the existing agricultural insurance in Guangdong Province is policy-based, the government subsidizes farmers’ premiums relatively. Therefore, the premiums paid by farmers themselves must be lower than the expected indemnity PA, ϕ = PA− The existence of B = PA−(1−L)B>0 means that farmers’ participation in agricultural insurance can increase their expected income. Therefore, theoretically, agricultural insurance can increase farmers’ expected income.
To study the impact of agricultural insurance on farmers’ income, we must first sort out the mechanism of agricultural insurance’s effect on farmers’ income. The impact of agricultural insurance on farmers’ income is complex to a certain extent. After sorting out and thinking about the previous research results, this paper believes that the effect of agricultural insurance on farmers’ income is mainly transmitted through direct and indirect paths. For reference, Zhou , Wang , and Li put forward the idea which summarizes the impact of agricultural insurance on farmers’ income into direct and indirect mechanisms, as shown in .
A road map of the impact of agricultural insurance on farmers’ income.
Source: authors’ elaboration.
This paper studies the impact of agricultural insurance in Guangdong Province on farmers’ income. Considering the availability and completeness of the data, the per capita disposable income of farmers, which reflects the income level of farmers, is selected as the explanatory variable, and indicators related to the level of agricultural insurance development are used as the explanatory variable. Then add urbanization rate, mechanization level, industrial structure, agricultural investment level, etc., as control variables. The data studied in this article are from the "China Insurance Yearbook" from 2011 to 2020, the "Guangdong Statistical Yearbook" and "Guangdong Rural Statistical Yearbook" from 2009 to 2020, the China Rural Research Database and AREMOS China Agricultural Statistics Database collects and sorts out the required data indicators.
4. An empirical analysis of the effect of Guangdong agricultural insurance on farmers’ income increase
This article uses agricultural insurance density (ind), Per capita income of farmers (y), and per capita compensation expenditure (ex) to express the development level of agricultural insurance, which are measured by agricultural insurance premium income/rural population and agricultural insurance indemnity expenditure/rural population, respectively. Agricultural insurance density refers to farmers’ expenditure in a certain area to transfer risks during the production process, that is, the average insurance premium paid by farmers, which can reflect the level of agricultural insurance development in a region. The greater the agricultural insurance density, the greater the level of agricultural insurance development in the region. The higher the value, the more obvious the role of agricultural insurance in protecting farmers’ income. Per capita indemnity expenditure refers to the insurance indemnity compensation received by farmers due to disasters—the post-disaster effect of agricultural insurance to help farmers resume reproduction and stabilize farmers’ income. Generally speaking, the larger the value, the higher the development of agricultural insurance. However, when the insurance compensation expenditure is large, it also means that there are many risk accidents and the farmers suffer a lot. Therefore, from the perspective of theoretical analysis, the direction of this indicator’s impact on farmers’ income levels cannot be determined.
To study the impact of agricultural insurance on farmers’ income and consider the core variables, to be rigorous in the empirical analysis, it is also necessary to consider other factors affecting farmers’ income. Based on the existing research results of the predecessors and considering the actual situation that affects farmers’ income, this paper selects the other five control variables, which are as follows: (1) The level of urbanization (urb). Based on the particularity of China’s urban-rural dual structure, although Guangdong Province has a highly developed economy, there is still a gap between urban and rural areas. Urbanization is an inevitable process of local social development. Wang found that the level of urbanization is related to farmers’ income. Wang’s research directly proposed that the urbanization rate can effectively increase farmers’ income. (2) The level of agricultural mechanization (mec). The level of agricultural mechanization refers to the proportion of machinery and equipment used in agricultural production in the total workload. Traditional production methods require substantial labor costs, while advanced production technology can save agricultural production costs, improve agricultural production efficiency, and increase farmers’ income to a certain extent. (3) Industrial structure (ins). In economic accounting, the gross product value of a country or a region is mainly composed of the output value of the primary, secondary, and tertiary industries, and the industrial structure refers to the proportion of each industry’s three major industries. (4) Agricultural investment level (inv). The level of agricultural investment represents the degree of importance the government and social capital attach to agricultural production. The more significant the value, the more fixed assets are used in agricultural production, including modern machinery and equipment, high-quality seeds, fertilizers, etc., which can positively promote agricultural output. (5) The per capita planting area of crops (area). Taking this indicator as one of the control variables, it is mainly considered that the planting area of crops is one of the important factors affecting agricultural output. Zhou believes that under certain production technologies, the larger the per capita planting area of crops, the greater the value of agricultural output.
