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Article

The Impact of Long-Term Security on the Return of Rural Labor Force: Evidence from Rural China

by
Yi Liu
1,
Hanyue Wang
1,
Jie Yang
2,* and
Dingde Xu
1,3,*
1
College of Management, Sichuan Agricultural University, Chengdu 611130, China
2
Committee of the Communist Youth League, Chengdu Agricultural College, Chengdu 611130, China
3
Sichuan Center for Rural Development Research, Sichuan Agricultural University, Chengdu 611130, China
*
Authors to whom correspondence should be addressed.
Agriculture 2024, 14(10), 1727; https://doi.org/10.3390/agriculture14101727
Submission received: 11 September 2024 / Revised: 23 September 2024 / Accepted: 29 September 2024 / Published: 1 October 2024
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
Browse Figures
Versions Notes

Abstract

:
Since the rural revival, the return of the rural labor force has become a trend. Different ways of returning to the rural labor force contain different policy implications. Based on the data of 8209 households in the China Labor Force Dynamic Survey, the probit model was used to explore the impact of long-term security in urban and rural areas on different return ways of the rural labor force. The results show that: (1) 18% of farmers choose to return, of which 3% and 10% choose active return and passive return, respectively, and 10% and 6% choose long-term return and short-term return, respectively. (2) The improvement in urban long-term security will inhibit the return of farmers (including active return and passive return), and the improvement in rural long-term security will promote farmers’ return behavior (including active return, passive return, long-term return, and short-term return). (3) The improvement of rural long-term security will promote the return of the first and second generations of rural households (including active return, passive return, long-term return, and short-term return), and the improvement of urban long-term security will restrain the return of the first generation of rural households (including active returns).

1. Introduction

The return of the rural labor force is the phenomenon of the rural labor force returning to the countryside, with rural laborers migrating to cities for employment and the process of urbanization [1]. The essence of this phenomenon is that farmers, in order to obtain greater benefits, help families maintain their livelihoods and increase the inflow of land and home processes [2]. Since the reform and opening up began in China in 1978, many migrant workers have chosen to work outside rural areas for economic interests [3,4]. However, with the development of the social economy, there has been a phenomenon of labor returning from cities to rural areas since the 1990s [5]. Due to the development of urbanization at that stage, academic and political circles did not pay much attention to the return of the labor force [6,7,8]. They were concerned about how to attract rural laborers (including returning labor) to work and settle down in urban areas [6,7,8]. However, with the implementation of rural revitalization strategies and the guidance of local employment policies, the rural industry is developing continuously and providing a large number of job opportunities, which can effectively attract farmers to choose to return home, leading to the return of rural labor becoming an irreversible trend [9]. According to data from the 2018 China Labor Force Dynamic Survey, about 16.6% of rural labor chose to return from cities to the countryside in 2017, an increase of 3.58 percent compared with 2014. It is noted that the returning labor force will show different characteristics because of the differences in their own resource endowments. As far as the reasons for the return of the labor force are concerned, there are active returns due to seeking opportunities or personal preferences and passive returns due to the inability of farmers to support urban life. In terms of the temporal characteristics of labor returns, there is a short-term return due to repeated round-tripping in search of development opportunities and a long-term return not going out after returning home [10,11,12,13]. In addition, there are significant differences between the new generation and the older generation of migrant workers in terms of the purpose, form, and consideration of whether to return [14,15]. Different forms of return and the intergenerational differences of migrant workers continue to interweave, bringing lots of challenges to social governance after the return of the labor force. Therefore, it is necessary to conduct research on the characteristics of return of different generations (including weather return and the form of return) of migrant workers systematically and reveal its driving mechanism to provide a reference for policy-making and improvement of the return of the labor force.
In fact, labor return is not a new topic. There are a lot of mature theoretical systems in international studies that explain the phenomenon of labor return. For example, life-cycle theory suggests that young migrant workers return home as they become older [16], while new economic migration theory suggests that farmers return because they lack the capital to live in cities and choose to bring the accumulated money and social capital back to the countryside for better development opportunities [17]. In addition to social networks targeting labor mobility, there are also theories that resources such as taxes, policy loans, business services, technical guidance, and families’ natural endowments, which may not actually be available, play an important role in encouraging rural labor to return to their hometowns and creating greater returns [18,19].
Research on domestic labor returns mainly focuses on the following three aspects: First, the spatial and temporal variation characteristics of labor returns. This kind of research is relatively small and mostly concentrated on geography. For example, some scholars have explored the characteristics of labor return transfers from different regions [20,21]. Second, the effect of labor return is revealed. Among them, some studies focus on the employment effect after the return of the labor force (that is, what type of work is engaged in), and some studies focus on the influence of agricultural production on resource allocation and agricultural structure after the return of the labor force [22,23,24,25]. The third is to explore the factors that influence labor return. There are relatively many such studies, and different studies have different perspectives. For example, from the perspective of livelihood capital, some pay attention to the differences between internal and external resource endowments [26,27]. Generally, there are relatively few studies on labor returns from the perspective of long-term security. Long-term security can be divided into urban long-term security and rural long-term security, guaranteeing the ability of rural households to survive in urban and rural areas, respectively, and to maintain their livelihoods after retirement or incapacity for work [28,29]. For example, the purchase of old-age insurance for urban residents and the purchase of old-age insurance for urban residents belong to the long-term urban security system, and the purchase of rural residents’ endowment insurance and rural residents’ medical insurance belong to the long-term rural security system. At present, from the literature that can be retrieved, only Shi Zhilei and other scholars have studied the impact of long-term security on the willingness of labor return [28]. It is noted that although intention is positively related to behavior, it does not represent behavior. At the same time, in theory, the impact of long-term security on different return modes of different generations will be different.
In summary, this research provides a useful reference for the development of this study. However, with the increasing number of rural laborers returning in different ways, the existing research on the formulation and optimization of policies still has the following deficiencies: First, few studies have systematically focused on the impact of long-term security on the different return modes of rural laborers in different generations from the perspective of intergenerational and long-term security. Second, most of the existing research is based on small sample surveys, lacking large sample data across the country.
Based on this, the study used data from the 2018 China Labor Force Dynamic Survey; from the perspective of intergenerational and long-term security, the study divides farmers’ return behavior into active return, passive return, long-term return, and short-term return. Based on depicting the spatial distribution characteristics of labor return, the probit econometric model is used to reveal the mechanism of rural and urban long-term security on different return modes of farmers in different generations to provide a decision-making reference for the formulation and improvement of labor return-related policies.

2. Theoretical Analyses

2.1. Urban-Rural Dual System and Rural Labor Return

After the founding of the People’s Republic of China, to quickly restore national strength and consolidate political power, China referred to Soviet Stalinism and the planned economy. At the same time, the hukou system, an important part of the planned economy system, was also introduced and divided into urban and rural hukou, marking the beginning of the separation between urban and rural areas [30]. Under the household registration system, urban and rural residents each have an independent system of medical care, education, housing, employment, and long-term security. Urban residents also enjoy more rights than rural residents, including access to more resources (for example, urban hukou holders can enjoy higher levels of health insurance and pension insurance, and the government allocates jobs, housing, and food to them, while rural residents need to be self-sufficient) [31]. At the same time, because of the restriction of the household registration system, residents cannot move freely between urban and rural areas during this period, which essentially limits the mobility of the labor force [32]. This situation continued until the reform and opening up occurred in 1978.
In 1978, the Communist Party of China convened its first Third Plenary Session of the 11th CPC Central Committee, which focused on opening up to the outside world and economic development. The hukou system was loosened in 1984 when rural residents were allowed to move to urban areas for employment against the backdrop of economic development. Then, in the 1990s, as the demand for urbanization increased and more labor was needed to move into cities to fill the labor gap, rural residents began to be encouraged to move to urban employment [4]. However, due to the long-term effect of the dual urban-rural system, even though in 2014 China has completely abolished the hukou system of restrictions on urban and rural migration, the rights and interests enjoyed by farmers and the level of social security are still far from those enjoyed by urban residents [33].
In this context, rural households working outside the city will constantly weigh the benefits and long-term security of returning to the countryside and staying in the city against their own and their families’ resource endowments [34]. Specifically, rural households in cities have the opportunity to obtain a higher income than farming and enjoy a higher amount of urban pension insurance and urban health insurance; it can also help families to enjoy more developed medical and educational resources in cities and towns, but all on the basis of farmers’ stable employment in cities and their ability to sustain urban livelihoods; In the countryside, farmers have stable, long-term land contracts and land tenure to make ends meet, access to housing at lower cost, and have access to basic pension and health insurance, to ensure the stability and security of rural households [35,36]. If farmers think that they can obtain more benefits and better long-term security by staying in the city than in the countryside, then settling in the city will become the choice of farmers. On the other hand, if farmers think they cannot meet the conditions of a family’s livelihood in the city, they will return to the countryside.

2.2. Long-Term Urban Security and Rural Labor Return

Since a large number of migrant workers have entered the city, their living conditions and security status in the city have been widely discussed [37]. Good long-term urban security is the basis for migrant workers to take root in the city and contribute to urban development [38]. Studies have found that the improvement of urban living conditions, including the improvement of income and living conditions, will significantly increase their willingness to settle in cities. The improvement of long-term urban security can encourage farmers to settle in cities [39,40].
For the details of urban long-term security, employment is the first thing to pay attention to. Employment is an important way for migrant workers to obtain livelihood capital directly. For a long time, most migrant workers have had ‘informal employment’ caused by low wages and unstable work. In addition, most employers are reluctant to sign labor contracts with migrant workers. These do harm the rights of migrant workers [40]. Signing a labor contract represents stable employment, which can ensure the income stability of migrant workers and the legitimate rights and interests they should enjoy to a certain extent, help migrant workers blend into city life, and promote the willingness of rural laborers to stay in the city [41]. In addition to employment, the purchase of urban medical insurance and pension insurance is an important part of social welfare security and will also significantly encourage farmers to choose to stay in the city [42]. In addition, whether migrant workers have a stable residence in the city (that is, their own house) will also affect their urban settlement. Better housing conditions will encourage migrant workers to choose to stay [43].
In theory, the impact of long-term urban security on the return modes of different generations of migrant workers will also be different. Studies have found that farmers with higher education levels are more likely to choose to settle down in the city, while the second generation of migrant workers is generally younger and more educated [44]. They will be relatively easier and more willing to live in the city. In addition, the second generation of rural laborers has experienced rapid economic development and urbanization, has almost no farming experience, is generally reluctant to live in the countryside all the time, and is more inclined to seek opportunities in the city [45]. In addition, some scholars have found that the second generation of rural laborers pays more attention to urban long-term security because the signing of labor contracts combined with the support of social welfare security can improve the long-term urban security level of migrant workers and help them stay in the city [46]. Based on the above, this study proposes the following hypothesis:
H1. 
The improvement in urban long-term security will inhibit the return behavior of rural households.
H1a. 
The improvement in urban long-term security will inhibit the active return behavior of rural households.
H1b. 
The improvement in urban long-term security will inhibit the passive return behavior of rural households.
H1c. 
The improvement in urban long-term security will inhibit the long-term return behavior of rural households.
H1d. 
The improvement in urban long-term security will inhibit the short-term return behavior of rural households.
H2. 
The second generation of rural labor is more concerned about urban long-term security than the first generation.

2.3. Long-Term Rural Security and Rural Labor Return

It is noted that although many rural migrants work in cities, due to the relative weakness of their own capital endowments and the long-term division of the urban-rural dual system, most rural migrants cannot obtain the same treatment guarantees as urban residents and cannot be completely separated from rural areas [47]. In this context, rural long-term security plays an important role in the return of rural laborers.
Long-term rural security scholars consider that the long-term rural security system consists of rural old-age insurance, rural medical insurance, and a social assistance system [28,48]. Among them, rural endowment insurance and rural medical insurance are the most important parts of the long-term rural security provided by the government. Therefore, having a rural endowment insurance and rural medical insurance can help farmers solve their worries about health and old-age care after returning home, so that they can also enjoy medical and old-age services in the countryside, thus promoting the return of rural households, especially older rural migrants. At the same time, family endowment is also an important factor in ensuring the production and life of farmers, which can determine the development space and platform of farmers in their hometown [49]. Among them, the possession of cultivated land and rural housing (i.e., homestead), as the most important production and living land and an important guarantee for old-age care for farmers in rural areas, will ensure the family endowment that farmers can have in the countryside, help farmers maintain normal production and life after returning, and attract farmers to choose to return home [50,51]. Moreover, social capital is also one of the essential long-term guarantees in rural areas. Compared with the city, the social capital of farmers in rural areas is also an important condition for ensuring a stable life after returning home. The maintenance of social capital can help migrant workers resist risks to the greatest extent possible and quickly find new ways to maintain their livelihoods after returning home [52,53]. The traditional small-scale peasant economy means that interpersonal communication in rural areas generally has the characteristics of strong homogeneity, a stable structure, and more emotional investment. Therefore, maintaining social capital requires a lot of time and money. Studies have found that farmers who often send money to their homes and have their spouses and other family members left behind in their hometowns prefer to return [54].
In addition, in theory, there are intergenerational differences in the behavior of rural long-term security regarding the return of rural laborers. Specifically, the first generation is generally older, and the probability of adapting to new environments, new lifestyles, and making new friends is relatively low [55]. In addition, the relatively low sense of urban identity of these rural laborers, coupled with the persistent local complex, makes it easier for these groups to return. Previous studies have found that the first generation is more inclined to return to rural areas compared with the second generation [56,57]. Based on the above, the study proposes the following hypothesis:
H3. 
The improvement in rural long-term security will promote the return behavior of rural households.
H3a. 
The improvement in rural long-term security will promote the active return behavior of rural households.
H3b. 
The improvement in rural long-term security will promote the passive return behavior of rural households.
H3c. 
The improvement in rural long-term security will promote the long-term return behavior of rural households.
H3d. 
The improvement in rural long-term security will promote the short-term return behavior of rural households.
H4. 
The first generation of rural households is more concerned about rural long-term security than the second generation.

3. Data and Methodology

3.1. Data Sources

The data source comes from the 2018 China Labor Force Dynamic Migration Survey Database. The personal data of the respondents are mainly selected for research, and the variables not involved in the personal database are matched with family data. Because the research only focuses on the return of the labor force, it only focuses on the return status and return mode of individuals from 15 to 60 years old. After cleaning the missing values and extreme outliers of the data, a total of 8029 households in 26 provinces were finally obtained. About 47% of the respondents in the sample were male, with an average age of 42.56. Respondents aged 38 and below accounted for 32.33% of the total, and those over 38 years old accounted for 67.67% of the total. The average years of education of the respondents was 8.11. In addition, about 9% of respondents live in rural areas in the suburbs of large and medium-sized cities, and the average distance between the respondents’ homes and the town or central government is 5.63 km.

3.2. Indicator Selection

3.2.1. Dependent Variables

This research mainly focuses on the return behavior of rural laborers. Referring to the research of some scholars, by setting up “Do you have the experience of working cross county for more than half a year?” and “Where was the main place you worked or farmed last year?” Two questions are used to comprehensively judge whether migrant workers will return [58]. If a farmer has the experience of working outside the county of household registration, and the place where he worked last year is in the county where the farmer is located, that is, the farmer has the return behavior; otherwise, there is no return behavior. Further, according to the return date (period) and the purpose of return, the research divides the return behavior of farmers into long-term return and short-term return, active return and passive return. Specifically, with reference to the classification of scholars such as Xiao Jian, by “When did you return to your hometown this time?” The problem was identified [59]. If the return time of farmers has exceeded 3 years, it is coded as a long-term return; otherwise, it is a short-term return. At the same time, with reference to the research of Zhang Zongyi and other scholars, the question of “Why you intend to stay long-term in your hometown” to determine whether the farmers are actively returning or passively returning [60]. If the purpose of farmers’ return is to return home to find better income work or not adapt to the outside world, it is considered that farmers are actively returning; if the purpose of the farmer’s return is to take care of the family, cannot find a good job outside, or become sick, it is considered that the farmer is a passive return. The selection measures of the final dependent variable are shown in Table 1.

3.2.2. Independent Variables

The independent variable of the study is long-term security, including urban long-term security and rural long-term security (Table 1). For urban long-term security, the setting of indicators mainly refers to the research of scholars, such as Shi Zhilei [28]. Considering that farmers want to survive in the urban area for a long period, they generally need a relatively stable job, a set of housing to purchase urban medical insurance, and urban endowment insurance. Regarding the working situation, the study set the question, “Do you currently sign a written labor contract?” to measure. For urban housing, it is measured by whether farmers have housing in the city. For whether farmers have pension insurance, set the questions “Do you have the basic pension insurance for urban workers?” and “Whether you have a unit pension/purchase pension insurance for government agencies and institutions” to measure. If the farmer has any of these, it is determined that the farmer has pension insurance. For whether farmers have medical insurance, set the questions “Do you have basic medical insurance for urban workers?” and “Do you have basic medical insurance for urban residents?” to measure whether farmers have any of them; it is determined that the farmers have urban medical insurance. Finally, the entropy method is used to combine the above variables into the total index of urban long-term security and substitute it into the model to explore the impact of urban long-term security on farmers’ return behavior.
For rural long-term security, the setting of indicators mainly refers to the research of some scholars [29,61]. If farmers need to survive in their hometown for a long time, in addition to purchasing basic rural medical care and pension insurance, they need to rely more on family resources, such as the area of cultivated land, a set of housing for living, and certain social capital. For the purchase of rural medical insurance, set the questions “Do you have a new rural cooperative medical care?” and “Do you have medical insurance for residents?”, if farmers have one of them, it can be judged that farmers have rural medical insurance. For rural endowment insurance, set the questions “Do you have a new type of rural social endowment insurance?” and “Do you have urban and rural residents’ endowment insurance?” to measure whether farmers have one of them identified as having rural endowment insurance. The area of cultivated land under operation is divided by the size of the family population. Social capital is represented by the per capita number of remittances from migrant workers to their homes. For rural-owned housing, set the question “Do you buy or build a house in the village?” to measure. Finally, the entropy method is used to combine the above variables into the total index of rural long-term security and substitute it into the model to explore the impact of rural long-term security on farmers’ return behavior.

3.2.3. Control Variables

Apart from the independent variables, farmers’ personal characteristics, such as gender, health status, and education level, and family characteristics, such as per capita income and location of farmers, also affect their return behavior. Therefore, with reference to the research of relevant scholars, these variables are controlled in the subsequent regression model [26,31].

3.3. Research Methods

This research aims to explore the impact of long-term security on the return modes of different intergenerational farmers. Among them, urban long-term security and rural long-term security are comprehensive indices of a series of indicators, which are mainly obtained by the entropy method. At the same time, because the dependent variables (different return modes of migrant workers) are binary, the regression model mainly adopts a binary probit model. The model is set as follows:
P Y i = 1 = φ ( α 0 + α 1 · F i + α 2 · X i + α 3 · P i + σ i )
Among them, Y i represents the dependent variable, that is, different return modes of farmers; F i represents the core independent variable, that is, the level of urban long-term security and rural long-term security of farmers; X i denotes the control variable; P i represents the provincial fixed effect; σ i represents the random disturbance term.

4. Results

4.1. Descriptive Statistics Analysis Result

According to the descriptive statistical analysis of farmers’ return behavior, it is found that farmers’ return has occupied a certain proportion, and the return behavior is more passive return than long-term return. Specifically, 18% of the 8209 households chose to return. Among them, 3% and 10% of farmers choose active return and passive return, respectively, and 10% and 6% of farmers choose long-term return and short-term return, respectively (In the original questionnaire, some of the answers to the questions about whether farmers belong to long-term, short-term, active, and passive backflow were missing and marked as 0, so the absence is retained in the analysis). In view of the security situation, this study found that farmers have a higher proportion of rural long-term security, and the score is higher. Specifically, the overall score for rural long-term security is 0.13. Among them, 85% of farmers have purchased rural medical insurance, 49% of farmers have purchased rural endowment insurance, and 82% of farmers have retained arable land in the village. In contrast, the long-term security provided by cities to farmers is relatively scarce, and the overall score of urban long-term security is 0.04. Specifically, only 15% of farmers have signed labor contracts when they are employed in cities, only 8% and 6% of farmers have urban medical insurance and pension insurance, respectively, and only 2% of farmers have their own houses in cities.
Further, the differences between the core variables of different reflux methods are compared (Table 2). Regarding return behavior, the rural long-term security owned by the farmers who choose to return is higher, and the number of rural housing owners, the number of people who have purchased rural medical care and pension insurance, and the amount of money sent to their hometown are significantly higher. For active returns, the long-term security level of farmers in cities is higher, and the proportion of signing labor contracts is larger. In addition, the long-term security level of farmers who choose active return is also higher than that of farmers who do not choose active return, especially in rural housing. For passive return, the urban long-term security level of farmers is lower than that of farmers without passive return, lack of necessary insurance purchases, and stable living places, and the rural long-term security level of farmers who choose passive return is relatively higher. For short-term returns, there is no obvious difference between the long-term urban security level of farmers and the long-term urban security level of farmers who do not choose short-term returns; however, the long-term rural security level of short-term return farmers is higher, especially in rural housing and sending money home. In view of the long-term return, the long-term security ability of farmers in cities is relatively worse, especially the purchase of urban medical insurance, while the long-term security level in rural areas is generally higher.
Based on the location of farmers, the spatial attributes are added, and the five-level classification of the natural breakpoint method is used to analyze the return behavior and long-term security level of farmers (Figure 1, Figure 2, Figure 3 and Figure 4).
Figure 1 shows the provincial statistics of farmers’ return behavior. Farmers who choose to return are mostly concentrated in the western and southern provinces. Among them, Hubei Province, Guizhou Province, Guangxi Zhuang Autonomous Region, and Chongqing City have the highest proportion of farmers who choose to return, while the proportion of farmers who choose to return in the eastern and northern provinces is generally low. The proportion of labor migrants returning from the eastern provinces to the western provinces generally shows a trend of increasing first and then decreasing.
Figure 2 shows the provincial statistics of farmers’ active return, passive return, long-term return, and short-term return. For active return, the farmers who choose active return are mostly concentrated in the southern provinces. The proportion of farmers choosing active returns in the southern provinces is generally higher than that in the northern provinces. Among them, the proportion of farmers choosing active returns in the Guangxi Zhuang Autonomous Region, Guangdong Province, Fujian Province, Jiangxi Province, and Ningxia Hui Autonomous Region is the highest. Regarding the passive return behavior of farmers, the farmers who choose passive return are mainly concentrated in the southern provinces, especially in the Guangxi Zhuang Autonomous Region, Hubei Province, and Chongqing City, and the proportion of farmers choosing passive return in the northern provinces is generally lower than that in the southern provinces. For long-term returns, the proportion of farmers choosing long-term returns in southern provinces is generally higher than that in northern provinces. Among them, Chongqing City, Hubei Province, Jiangxi Province, Guangdong Province, and Guangxi Zhuang Autonomous Region have the largest number of farmers choosing long-term returns. For short-term returns, the proportion of farmers choosing short-term returns is higher in the central provinces, especially in Chongqing City, Guangxi Province, Guizhou Province, Hubei Province, and the Ningxia Hui Autonomous Region, and the proportion of farmers choosing short-term returns in coastal provinces is generally lower than that in inland provinces.
Figure 3 shows the provincial statistics for farmers’ rural long-term security levels. Overall, the level of rural long-term security of farmers increases from east to west, and the level of rural long-term security of farmers in the central and western provinces is generally higher than that in the eastern provinces.
Figure 4 shows the provincial statistics of farmers’ urban long-term security level. In general, the level of urban long-term security of farmers shows a decreasing trend from northwest to southeast, and the level of urban long-term security of farmers in the western and northern provinces is significantly higher than that in other provinces.

4.2. Model Results

Table 3 shows the results of the impact of long-term security on different return modes of farmers. Regarding return behavior, the improvement of urban long-term security will significantly inhibit the return of farmers, while the improvement of rural long-term security will significantly promote the return of farmers; H1 and H3 are established. Whether farmers return depends on the comparison between urban long-term security and rural long-term security. If the city can provide plenty of resources to meet the needs of farmers, they will choose to stay in the city and vice versa. Furthermore, rural households that are older and live in the suburbs are more likely to choose to stay in the city because the resources provided in the city can better meet the needs of these people than those in the countryside. The study also finds that male farmers are more willing to return home than female farmers, and the healthier the farmers, the more willing they are to return home. This is because healthy male farmers have a greater ability to bear risks and are more willing to find opportunities to meet the livelihood needs of their families. For active returns, the improvement in urban long-term security will encourage farmers to stay in the city, and the improvement in rural long-term security will encourage farmers to return; hence, H1a and H3a were established. Most farmers who actively return to the countryside consider that there are more development opportunities in the countryside. After accumulating human, social, and financial capital, they often choose to return home to start a business or develop into large-grain growers. Urban long-term security and rural long-term security will undoubtedly become the thrust and pull of its active return. The study also found that men with higher per capita household income were more likely to actively seek opportunities back in the countryside, as this meant that they were more risk-averse and conducive to the search for better employment opportunities in the countryside. In addition, the older the farmers, the less willing they are to take the initiative to go back. This is because, as they grow older, it is difficult for these farmers to have sufficient ability to withstand pressure and resist risks, and many elderly farmers need better medical resources to protect their health. Therefore, choosing to stay in the city is a better choice for them.
For passive returns, rural long-term security is positively correlated with passive returns, and H3b is established. Although long-term urban security is negatively correlated with passive returns, it is not significant, and H1b is not established. This can be analyzed based on the causes of passive backflow. People who passively return may be because they want to take care of their families and may be gradually excluded by the labor market due to old age and other reasons, so they can only choose to return. For them, rural long-term security is fundamental because they generally do not have the capital to settle in urban areas. In addition, young farmers with higher education, better health conditions, and lower per capita income of their families are more likely to choose passive returns. This may also be due to the fact that these farmers cannot find a way to support their families in the cities, and there are elderly or children in rural households to take care of, which leads them to choose to move back passively to the countryside.
Regarding long-term returns, urban long-term security is negatively correlated with the long-term returns of farmers and rural long-term security is positively correlated with the long-term returns of farmers; thus, H1c and H3c are established. Unlike short-term returns, long-term returns are a very important decision, and farmers will make comprehensive trade-offs based on family capital endowments. If a city’s long-term security is better, it will naturally inhibit its long-term return. On the contrary, if the city cannot stay and rural long-term security is not a problem, it will naturally return for a long time. The study also found that young, healthy, male farmers were more likely to choose long-term returns. This may be because these people form the backbone of the family and generally need to bear the family’s livelihood. When staying in the city cannot meet their personal and family needs, they will choose to return for a long time and find a stable job in their hometown that can meet the needs of the whole family. For short-term returns, rural long-term security can significantly promote the return of farmers, and H3d has been established. Although long-term urban security is negatively correlated with short-term returns, it is not significant, and H1 d is not established. There are many reasons for short-term return, but most of them are family reasons (such as people becoming sick, building houses, etc.). Whether to go out after returning or settle down in the city in the future depends on the specific situation, but it is undeniable that the long-term protection of rural areas is always the foundation of returning farmers, especially those with relatively weak capital endowments. The study also found that young male farmers living on the outskirts of cities with lower per capita income were more likely to choose short-term returns, as they are mostly responsible for meeting the livelihood needs of their families; jobs in the city are more likely to help them achieve this goal, but short-term problems with their families have forced them to return temporarily to their homes and then return to the city to work.

4.3. Heterogeneity Analysis Results

To further study the impact of long-term security on the return behavior of farmers in different generations, referring to the research of relevant scholars, bounded by 1980, migrant workers born before 1980 are divided into the first generation, and migrant workers born after 1980 are divided into the second generations of migrant workers [62,63]. The data of both generations are substituted into the binary probit model for regression. The results are shown in Table 4.
For return behavior, the improvement of rural long-term security will significantly promote the return of farmers, and this promotion effect is more obvious for the first generation. At the same time, the improvement in urban long-term security will significantly inhibit the return of the first generation of migrant workers, and H2 and H4 are not established. This may be because the first generation pays more attention to health and stability due to factors such as age and physical health. Urban medical resources are more abundant than those in rural areas. If there is housing or pension insurance in the city, the first generation is naturally more inclined to stay in the city, while the second generation is in the prime of life and still in the stage of struggle. There are old and young people, and there may not be much thought about whether to stay in the city.
For active returns, the improvement in urban long-term security will significantly inhibit the return of both generations, and the improvement in rural long-term security will significantly promote the return of both generations. However, rural long-term security has a greater impact on the active return of the first generation of migrant workers. For passive return, the improvement of rural long-term security will significantly promote the return of two generations of migrant workers, while the correlation between urban long-term security and passive return is negative but not significant. This may be because the first generation is more inclined toward a stable lifestyle due to capital endowments and physical reasons. The role of long-term security in rural areas is self-evident to them. At the same time, for most migrant workers who lack capital endowments, staying in the city is a distant dream or a dream that needs to be worked hard for. Only a very small number of capable families can stay in the city. Therefore, in the current stage, the long-term security role of the city is far less important than the long-term security role of rural areas.
For long-term returns and short-term returns, the improvement of rural long-term security will significantly promote the return of both generations, and this promotion effect is more prosperous for the first generation. The correlation between urban long-term security and the long-term return and short-term return of the two generations of migrant workers is not significant. Long-term return is different from short-term return because some families can go out and enter the labor market again after short-term return. The constraints are different between the first generation and the second generation. The second generation of rural migrants is in the stage of hard work in their prime years, while some groups of the first generation of rural migrants are forced to return (including long-term return) because of their age, physical health, and other reasons. The long-term security of rural areas is the foundation for migrant workers to leave. When migrant workers do not work smoothly, they can choose to return home without fear. Older groups are more likely to consider returning home for a long time to go in farming for old-age care. In addition to maintaining their own survival, they must strive to support the dream of staying in an urban area for future generations. The second-generation rural households who are in their prime years are in the stage of hard work. Unless there are more opportunities for development, they will not return easily.

5. Discussion

Based on the data of 8209 households from the 2018 China Labor Force Dynamic Survey, this study uses the binary probit model to systematically analyze the impact of long-term security in urban and rural areas on the return mode of different generations of migrant workers and tries to answer the relationship between the return behavior of rural households and long-term security. Compared with existing studies that consider the return of rural migrants from the perspective of their willingness to return (such as Shi & Xue, 2015), this study pays more attention to the actual return behavior of rural migrants [28]. In addition, according to the motivation of migrant workers’ return, we further refine their return modes (active return, passive return, long-term return, and short-term return) and systematically analyze the impact of long-term security in rural and urban areas on different return modes. Compared with existing research, less attention has been paid to the intergenerational differences in the return of rural households (such as Zhang et al., 2020; Y. Yang & Shi, 2012). Combined with the reality of China, this study divides migrant workers into two generations, the first generation and the second generation, and systematically compares the impact of urban long-term security and rural long-term security on the return behavior of rural laborers of different generations [26,60]. The treatment of this study is more in line with the reality of China and can better guide the formulation and optimization of policies related to labor returns and the long-term security of migrant workers.
Due to the different perspectives and research focus, the conclusions of this study are also different from those of the existing research. For example, Shi and Xue found that the improvement of urban long-term security is an important factor hindering the willingness of migrant workers to return, while the improvement of rural long-term security will increase the willingness of farmers to return [28]. This study focuses on the impact of long-term security on the return behavior of migrant workers but finds that the improvement of long-term security in urban and rural areas has a stronger inhibitory and stimulating effect on the return behavior of farmers than the willingness, and the improvement of long-term security in urban areas can effectively inhibit the active and passive return of farmers, but it has no effect on long-term and short-term return, while the improvement of long-term security in rural areas can stimulate all kinds of return behavior. A possible reason for this difference is the difference in the policy environment faced by the study period. Shi and Xue’s research uses survey data from 2013 when China was in the stage of rapid urbanization and needed many migrant workers to enter the city to support urban construction. Therefore, the focus of this research is on how to attract the rural labor force to enter the city and settle down in the city. Even if there is a return of the rural labor force, there is also concern about how to effectively guide the return of migrant workers to the city to continue to support urban construction. Research in the same period as Shi and Xue is basically similar, focusing on the analysis of the influencing factors of rural laborers’ migration and exploring how to encourage them to enter and stay in the city [64,65,66]. At this stage, the long-term security of the city and the long-term security of the countryside are equally important for migrant workers. The former guarantees that migrant workers can stand in the city, while the latter is the last way out for migrant workers if they cannot settle down in the city. However, with the slowdown of urbanization and the proposal of the national rural revitalization strategy in 2017, the resources that the city can provide for rural households can no longer meet the needs of some of them. In addition, many policies have been introduced to encourage rural development and promote rural revitalization and talent revitalization. Large numbers of migrant workers decide to return to the countryside to start a business or develop into a new type of business entity engaged in agricultural production [10,59]. At this stage, due to the gradual improvement of the national security system, the proportion of agricultural operating income in the total household income of farmers gradually decreased, and the long-term security function of rural areas for some migrant workers gradually weakened, and finally, the results of this study appeared.
It is noted that the 2024 Central Document No.1 issued by the General Office of the CPC Central Committee and the State Council proposes to improve the rural public service system, improve the long-term security level of rural areas by strengthening the inclusion of village clinics in rural medical insurance and improving the rural pension insurance mechanism, and ensure the life of farmers after returning to rural areas. Moreover, by promoting the integration of urban and rural development, expanding the employment capacity of the city, and providing a wider coverage of housing security to improve the level of long-term urban security, farmers who do not choose to return to live in the city can be provided. Therefore, current research on the return of rural households is more in the context of urban-rural integration and development to provide adequate long-term protection for returning and remaining farmers in the city to help improve their livelihoods. Urban long-term security and rural long-term security complement each other and are indispensable.

6. Conclusions and Implications

Based on the above, the research mainly draws the following three conclusions:
(1) There are 18% of farmers who choose to return, of which 3% and 10% choose active return and passive return, respectively, and 10% and 6% choose long-term return and short-term return, respectively.
(2) The improvement in urban long-term security will inhibit the return of farmers (including active return and passive return), and the improvement of rural long-term security will promote the return of farmers (including active return, passive return, long-term return, and short-term return).
(3) In terms of intergenerational differences, the improvement of rural long-term security will promote the return of both generations of rural households (including active return, passive return, long-term return, and short-term return), and the improvement of urban long-term security will inhibit the return of the first generation of rural households (including active return).
In view of the above conclusions, this study believes that the long-term urban security level of non-returning farmers should be strengthened. Migrant workers are an indispensable component of urban development. However, their long-term urban security level is not high (only 15% of the labor force has signed labor contracts, only 8% and 6% of the labor force has purchased urban medical insurance and urban pension insurance, and only 2% of farmers have urban housing). It is recommended that the government improve relevant laws and regulations (such as standardizing labor contracts between employers and rural laborers and improving the coverage of rural households’ pensions and medical insurance) and effectively improve the long-term urban security level of rural migrants who stay in the city.
In addition, to improve the level of long-term security in rural areas, protecting the basic rights and interests of passive return rural laborers and attracting more rural laborers who are willing and able to return actively are also necessary. The study found that 10% of farmers return passively. The government should play an essential part in the relevant support work to ensure the basic rights and interests of this part of the rural house who decided to return. In addition, 3% of farmers decided to return actively (more can be expected in the future). The government should devote itself to infrastructure construction, industrial support, and other services to help returnees become rich.

Author Contributions

Conceptualization, Y.L.; methodology, Y.L and H.W.; software, Y.L.; validation, Y.L., H.W. and D.X.; formal analysis, Y.L. and J.Y.; investigation, Y.L.; resources, Y.L. and H.W.; data curation, Y.L., J.Y. and H.W.; writing—original draft preparation, Y.L.; writing—review and editing, D.X.; visualization, Y.L.; supervision, D.X.; project administration, D.X.; funding acquisition, D.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the National Natural Science Foundation of China, grant number 72363014, and the Sichuan Social Science Foundation Youth Fund, grant number SCJJ23ND443.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The data presented in this study are available upon request from the corresponding author.

Acknowledgments

We gratefully acknowledge the anonymous reviewers and editors for their helpful reviews and critical comments.

Conflicts of Interest

The authors declare no conflicts of interest.

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Agriculture 14 01727 g001
Figure 1. Spatial distribution of farmers’ return behavior.
Figure 1. Spatial distribution of farmers’ return behavior.
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Figure 2. Spatial distribution of farmers’ active return, passive return, and long-term and short-term returns.
Figure 2. Spatial distribution of farmers’ active return, passive return, and long-term and short-term returns.
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Figure 3. Spatial distribution of farmers’ long-term rural security levels.
Figure 3. Spatial distribution of farmers’ long-term rural security levels.
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Figure 4. Spatial distribution of farmers’ long-term urban security levels.
Figure 4. Spatial distribution of farmers’ long-term urban security levels.
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Table 1. The definition and data description of the variables.
Table 1. The definition and data description of the variables.
Types of VariablesVariablesDescription
Dependent variablesReturn behavior=1 if farmer decides to return
Long-term return=1 if farmer decides to return for a long time
Short-term return=1 if farmer decides to return for a short time
Active return=1 if farmer decides to return actively
Passive return=1 if farmer decides to return passively
Independent variables of urban long-term securityEmployment contract=1 if farmer signs an employment contract with the employer
Urban medical insurance=1 if farmer has urban medical insurance
Urban endowment insurance=1 if farmer has urban endowment insurance
Urban housing=1 if farmer owns rural housing
Independent variables of rural long-term securityFarmlandLogarithm of cultivated land per capita
Rural housing=1 if farmer owns rural housing
Rural medical insurance=1 if farmer has rural medical insurance
Rural Endowment Insurance=1 if farmer has rural endowment insurance
Send money homeLogarithmic per capita number of remittances sent to the home by an out-of-work workforce
Control variablesAgeIndividual Age (years)
Gender=1 if male
EducationThe years of taking education
Health statusRank 1–5, the higher the rank, the healthier the farmer thinks he or she is
Suburb of a developed city=1 if located in the suburbs of large and medium-sized cities
Net per capita household incomeThe logarithm of household net income per capita last year
Center distanceThe distance between the village and the nearest township government or street office (km)
Table 2. Results of the descriptive statistical analysis by different return models.
Table 2. Results of the descriptive statistical analysis by different return models.
VariablesReturn BehaviorActive ReturnPassive ReturnShort-Term ReturnLong-Term Return
YesNoYesNoYesNoYesNoYesNo
Employment contract0.200.140.300.150.160.150.200.150.190.14
Urban medical insurance0.040.090.080.080.040.080.060.080.030.09
Urban endowment insurance0.030.060.060.060.030.060.040.060.030.06
Urban housing0.020.020.030.020.020.020.020.020.020.02
Farmland0.640.720.660.710.620.720.710.700.600.72
Rural housing0.620.000.660.100.660.050.500.080.690.04
Rural medical insurance0.910.830.890.850.920.840.900.840.920.84
Rural endowment insurance0.500.480.480.490.540.480.460.490.540.48
Send money home0.610.410.480.450.650.430.600.440.640.43
Age41.9342.6942.4642.5643.8742.4137.9742.8744.0142.39
Gender0.600.440.800.460.520.460.650.460.580.46
Education8.328.078.648.108.128.118.618.088.228.10
Health status2.292.222.132.242.402.212.132.242.382.22
Suburb of a developed city0.040.090.070.090.050.090.040.090.050.09
Net per capita household income8.528.699.008.658.448.698.438.688.588.67
Center distance5.315.705.205.655.345.675.585.645.145.69
Observations145467552297980840736953176788487361
Table 3. Results of the impact of long-term security on different return modes of farmers.
Table 3. Results of the impact of long-term security on different return modes of farmers.
VariablesReturn BehaviorActive ReturnPassive ReturnLong-Term ReturnShort-Term Return
Urban long-term security−7.366 ***−10.362 ***−1.529−4.768 ***−4.523
(2.735)(1.842)(2.271)(1.796)(4.142)
Rural Long-term security6.348 ***2.962 ***4.569 ***4.861 ***3.027 ***
(0.176)(0.213)(0.147)(0.197)(0.247)
Age−0.026 ***−0.010 ***−0.009 ***−0.010 ***−0.029 ***
(0.003)(0.003)(0.002)(0.003)(0.003)
Gender0.299 ***0.577 ***−0.0500.116 ***0.336 ***
(0.043)(0.059)(0.049)(0.041)(0.055)
Education0.003−0.0070.013 *0.011−0.007
(0.011)(0.016)(0.007)(0.009)(0.017)
Health status0.082 ***−0.0370.097 ***0.097 ***0.003
(0.019)(0.026)(0.017)(0.018)(0.022)
Suburb of a developed city−0.350 ***−0.093−0.142−0.175−0.408 ***
(0.117)(0.117)(0.129)(0.128)(0.095)
Net per capita Household income−0.0100.066 **−0.021 **0.012−0.025 **
(0.011)(0.027)(0.010)(0.016)(0.012)
Center distance−0.006−0.004−0.002−0.007−0.001
(0.005)(0.006)(0.004)(0.004)(0.005)
Constant−0.810 ***−2.404 ***−1.765 ***−1.996 ***−0.587 *
Chi-square value2350.589799.3782152.396752.132700.846
Observations82098209820982098209
Note: *, **, *** represent the significance level of 10%, 5%, and 1%, respectively.
Table 4. Results of the impact of long-term security on the return mode of different intergenerational migrant workers.
Table 4. Results of the impact of long-term security on the return mode of different intergenerational migrant workers.
VariablesReturn BehaviorActive ReturnPassive ReturnLong-Term ReturnShort-Term Return
First Generation Second GenerationFirst Generation Second GenerationFirst Generation Second GenerationFirst Generation Second GenerationFirst Generation Second Generation
Urban long-term security−6.458 **−1.504−9.302 ***−9.998 **0.0691.252−3.9790.045−0.426−2.565
(2.695)(2.625)(3.461)(4.995)(2.297)(3.825)(2.943)(3.526)(4.160)(5.509)
Rural long-term security7.197 ***4.685 ***3.363 ***1.904 ***5.050 ***3.224 ***5.411 ***3.358 ***3.351 ***2.383 ***
(0.269)(0.254)(0.228)(0.397)(0.148)(0.307)(0.243)(0.274)(0.324)(0.253)
Age−0.049 ***0.028 ***−0.019 ***−0.001−0.026 ***0.038 ***−0.036 ***0.045 ***−0.030 ***0.004
(0.007)(0.005)(0.006)(0.008)(0.006)(0.007)(0.008)(0.008)(0.006)(0.007)
Gender0.429 ***0.165 ***0.607 ***0.510 ***0.063−0.269 ***0.224 ***−0.0850.440 ***0.273 ***
(0.051)(0.062)(0.076)(0.120)(0.074)(0.076)(0.050)(0.082)(0.068)(0.066)
Education0.014−0.000−0.004−0.0230.022 **0.0030.025 **0.003−0.012−0.003
(0.013)(0.011)(0.016)(0.019)(0.011)(0.015)(0.012)(0.018)(0.023)(0.017)
Health status0.114 ***0.077 **−0.024−0.0720.134 ***0.0400.129 ***0.066−0.0030.032
(0.023)(0.039)(0.039)(0.065)(0.026)(0.045)(0.026)(0.048)(0.034)(0.043)
Suburb of a developed city−0.071−0.665 ***0.042−0.315 **0.017−0.3820.004−0.492 **−0.218−0.549 ***
(0.169)(0.133)(0.184)(0.125)(0.126)(0.283)(0.149)(0.224)(0.218)(0.142)
Net per capita household income−0.010−0.0200.0370.184 ***−0.016−0.036 **0.022−0.011−0.025−0.028
(0.011)(0.018)(0.028)(0.050)(0.013)(0.015)(0.019)(0.020)(0.022)(0.019)
Center distance−0.011 *−0.004−0.0090.002−0.0050.002−0.011 **−0.004−0.000−0.002
(0.006)(0.005)(0.009)(0.007)(0.007)(0.005)(0.006)(0.007)(0.007)(0.006)
Constant−0.155−2.069 ***−1.927 ***−3.320 ***−1.396 ***−2.570 ***−1.205 ***−3.080 ***−0.865 **−1.438 ***
Chi-square value1473.146595.591592.42066.8051629.952346.392901.042924.301278.385247.981
Observations5555.0002654.0005555.0002654.0005555.0002654.0005555.0002654.0005555.0002654.000
Note: *, **, *** represent the significance level of 10%, 5% and 1% respectively.
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Liu, Y.; Wang, H.; Yang, J.; Xu, D. The Impact of Long-Term Security on the Return of Rural Labor Force: Evidence from Rural China. Agriculture 2024, 14, 1727. https://doi.org/10.3390/agriculture14101727

AMA Style

Liu Y, Wang H, Yang J, Xu D. The Impact of Long-Term Security on the Return of Rural Labor Force: Evidence from Rural China. Agriculture. 2024; 14(10):1727. https://doi.org/10.3390/agriculture14101727

Chicago/Turabian Style

Liu, Yi, Hanyue Wang, Jie Yang, and Dingde Xu. 2024. "The Impact of Long-Term Security on the Return of Rural Labor Force: Evidence from Rural China" Agriculture 14, no. 10: 1727. https://doi.org/10.3390/agriculture14101727

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