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Article

To Stay or to Migrate: Driving Factors and Formation Mechanisms of Rural Households’ Decisions Regarding Rural–Urban Student Migration in China

1
Research Institute for Ecological Civilization, Sichuan Academy of Social Sciences, Chengdu 610072, China
2
Rural Development Institute, Chinese Academy of Social Sciences, Beijing 100732, China
3
School of Agricultural Economics and Rural Development, Renmin University of China, Beijing 100872, China
*
Author to whom correspondence should be addressed.
Societies 2025, 15(8), 226; https://doi.org/10.3390/soc15080226
Submission received: 30 June 2025 / Revised: 30 July 2025 / Accepted: 15 August 2025 / Published: 17 August 2025

Abstract

Rural–urban student migration during the compulsory education stage is a transitional phenomenon in China’s socio-economic development and a crucial issue for achieving the goal of urban–rural integration. This paper, grounded in theoretical analysis, constructs a “willingness-capacity-behavior” framework. Based on field survey data from 916 rural households and in-depth interview materials from County D, Province X, China, this study employs a bivariate Probit model and qualitative analysis methods to explore the driving factors and formation mechanisms of rural households’ rural–urban student migration decisions. The results indicate that rural households’ decisions regarding rural–urban student migration are jointly influenced by migration willingness and migration capacity. Only households with both migration willingness and migration capacity can actualize migration behavior. Migration willingness is derived from a cost–benefit analysis and involves joint decision-making by both parents, significantly influenced by parental personal characteristics and the student’s individual characteristics. The intermediate barriers to rural–urban student migration require certain migration capacities to be overcome, which are mainly influenced by family resource endowment and parental personal characteristics.

1. Introduction

Large-scale rural–urban population migration is a common phenomenon in the industrialization, modernization, and urbanization processes of countries worldwide. Over the past forty years, China has also experienced rapid rural–urban population migration alongside continuous economic and social progress. China’s rural–urban population migration can be roughly divided into two stages. The first stage involved rural laborers migrating to cities individually, resulting in a large group of migrant workers. The second stage saw a shift towards family migration, leading to a growing number of migrant children. Since Lewis (1954) proposed the dual economy model, rural–urban labor migration has garnered extensive attention, establishing a well-developed theoretical system and analytical framework [1,2]. However, the focus on rural–urban student migration remains insufficient.
Rural–urban student migration (“Rural-urban student mobility” in this study specifically refers to student mobility during the compulsory education stage, which, in the Chinese context, includes primary and junior secondary education (typically covering ages 6–16)) in China is not a naturally occurring phenomenon; it is restricted by the household registration system (hukou) and the corresponding compulsory education management system [3]. Rural households in China face three main institutional barriers when migrating their children to urban schools: the hukou-based territorial management system, the hukou-based financial allocation system, and the conditional access system [4]. Among these, the hukou-based territorial management system presents the most significant obstacle to rural–urban student migration. The hukou-based financial allocation system leads to an unreasonable division of expenditure responsibilities between the origin and destination areas of migrant children, resulting in inadequate educational funding in the destination areas. Additionally, the conditional access system creates further implicit barriers to entry [5]. As these institutional barriers gradually diminish, the freedom for rural households to decide between staying in their village or moving to a city for education purposes increases, and the occurrence of rural–urban student migration becomes more common [6,7]. According to national representative data from China Family Panel Studies (CFPS), the proportion of rural–urban student migration during the compulsory education stage has shown an increasing trend, rising from 16.05% in 2012 to 30.22% in 2020.
Most studies on China’s rural–urban migration start with the urban–rural dual structure. Consequently, many discussions focus on the institutional exclusion faced by rural households from a macro perspective, considering factors such as the household registration system and compulsory education system [8]. These studies undoubtedly provide important macro perspectives to explain rural–urban student migration. However, the limitation of these perspectives lies in them treating rural households as passive recipients of macro institutional changes, thereby neglecting these households’ subjective agency. Some observed behaviors of China’s rural households engaged in rural–urban student migration cannot be fully explained by macro institutional factors alone. For instance, during the reform process of the urban–rural dual system, many rural households choose to send their children to urban schools; however, the majority still choose to have their children educated in their village, including many children of migrant labors. From 2000 to 2010, the ratio of migrant children to left-behind children changed from 1:1.71 to 1:2.12, indicating that, despite the relaxation of urban enrollment policies, the rate of left-behind children did not decrease, but instead increased [9]. Similarly, in the eastern regions of China with a significant influx of migrant populations, there are often high thresholds for urban settlement, property purchase, and enrollment policies for migrant children. Nonetheless, the proportion of rural–urban migrant children in four eastern provinces—Guangdong, Jiangsu, Zhejiang, and Fujian—accounts for 44.51% of the total rural–urban migrant children. Conversely, in small county towns in the central and western regions of China with serious population outflow, more relaxed policies on household registration, housing purchase, and enrollment of migrant children are often introduced to attract rural population inflow. However, the results are often contrary to expectations [10]. These phenomena indicate that macro-institutional factors are not the sole important factors influencing rural households’ decisions regarding rural–urban student migration in China. As decision-makers in rural–urban student migration, the subjective agency of rural households should not be ignored.
Recognizing the subjective agency of China’s rural households, a micro-family perspective has gradually been introduced into related research. In the micro-family perspective, rural–urban student migration is considered a rational decision-making process by parents based on comprehensive considerations of individual characteristics, family conditions, and external environments [11]. The decision-making of rural–urban student migration is essentially a school choice issue. Attention is mainly focused on parents’ choices between public and private schools, local and non-local schools, and the different choices of local residents and immigrants [12,13]. The literature studying compulsory education in China has long focused on the significant gap in educational resources between urban and rural areas and among different regions, as well as the resulting school-choice-related behaviors within cities [14]. Studies of rural–urban student migration mostly limit the research subjects to migrant workers [15,16], overlooking the fact that rural–urban student migration in China shows a unique trend feature of de-synchronization with rural–urban labor migration [17], leading to sample bias. Moreover, existing research often conflates migration willingness with migration behavior. In reality, although migration willingness can promote the occurrence of migration behavior, these two factors are not entirely consistent. The migration willingness of rural households does not necessarily equate to actual migration behavior, and there can be significant differences. The ability of rural households to convert migration willingness into migration behavior is increasingly constrained by their capacity. Therefore, research on the driving factors of rural households’ decisions regarding rural–urban student migration in China should also focus on the differences between migration willingness and migration behavior, as well as the limiting role of migration capacity.
Why do some rural households in China experience rural–urban student migration while others do not? Rural–urban student migration is a significant phenomenon in China, driven by disparities in educational resources and opportunities between rural and urban areas [8]. Despite the potential benefits of urban education for rural students, many rural households face substantial barriers that prevent them from pursuing this option [18]. This paper views rural households as active agents, examining how they make proactive decisions about whether to keep their children in their village or migrate them to a city for education, considering their own family endowments within the given macro-social context. This study constructs a research framework based on the “willingness-capacity-behavior” model. By identifying the factors influencing rural households’ willingness and capacity for rural–urban student migration, this study aims to clarify the decision-making mechanisms of rural households in China and the key factors limiting the transformation of willingness into behavior. This study not only provides a theoretical explanation that integrates urban–rural migration theories into the Chinese context, but also helps us to understand how different rural households adapt and make differentiated decisions regarding rural–urban student migration under the common constraints of internal and external factors.
Based on theoretical analysis and empirical data from rural households in County D, Province X, China, this paper explores the driving factors and formation mechanisms of rural households’ decisions regarding rural–urban student migration in China. The rest of the paper is structured as follows: Section 2 constructs a theoretical analysis, constructing a mathematical model to derive the key factors that influence rural households’ migration willingness and behavior, and proposes a series of theoretical propositions. Section 3 presents the empirical research design, introducing the study area, data sources, econometric model setting, and variable definitions, and develops an identification framework for migration willingness and capacity based on the theoretical propositions. Section 4 provides the empirical results and analysis, quantitatively testing the theoretical hypotheses using survey data, and supplementing the findings with qualitative insights from in-depth interviews. Section 5 concludes this paper, offering key discussions, policy implications, and the limitations of the study.

2. Theoretical Analysis

The theoretical model of this paper assumes that China’s rural households have two choices for the educational location of their children: staying in rural areas or migrating to urban areas. The goal of rural households is to maximize net utility. The subsequent model derivation focuses on how migration willingness and migration capacity affect rural–urban student migration behavior, as well as the key factors influencing migration willingness and migration capacity.

2.1. Basic Model

The basic assumptions of the model are set as follows:
  • There are two administrative regions in the economic system: rural areas and urban areas. Rural areas engage in agricultural production activities, while urban areas engage in industrial and service production activities (collectively referred to as non-agricultural production activities).
  • Residence is specified to the county-level administrative region, and the household registration types are divided into urban hukou and rural hukou. The initial place of residence for the representative rural household i is located in rural areas, and household members have rural hukou status.
  • Each adult laborer is assumed to have 1 unit time endowment, and, post-childbirth, time is allocated between market labor and child care.
  • Family is the basic decision-making unit, and key decisions within the family are made by the adult laborers (parents).
  • The utility function is additive and separable, with a first derivative greater than 0 and a second derivative less than 0.
  • The quality of public education resources varies significantly by location, with urban areas generally offering higher-quality resources than rural areas.

2.1.1. Two-Sector Production Functions

1.
Urban sector. The urban sector includes both high-skilled and low-skilled labor. Its production function follows a CES form:
Y u = A u F N H + Ψ h ,   N L
where Y u is total urban output; A u > 0 is urban productivity; N H and N L represent high-skilled and low-skilled labor; Ψ is the constant endowment in the urban area; and h is the human capital level of high-skilled labor, which can be considered as labor quality determined by years of education.
Assuming equal pay for urban residents and migrant workers (rural hukou holders working in urban areas), wage rates are determined by marginal productivity:
w H U = Y u [ N H + Ψ h ] = A u F H
w L U = Y u N L = A u F L
where F H = F / [ N H + Ψ h ] , F L = F / N L . The wage ratio is
w H U h w L U = h F H F L
2.
Rural sector. The production function of the rural sector is
Y r = A R F N R ,   L R
where Y r is total rural output; A R > 0 is the total factor productivity in the rural sector; N R is the quantity of labor; and L R is the land area. Rural wages are also determined by marginal labor productivity:
w R = Y r N R = A R F R
where F R = F / N R . In summary, the urban sector offers two wage levels ( w H U   and w L U ) depending on labor skills, while the rural sector offers a single wage rate w R .

2.1.2. Education Production Function

The education production function (EPF) incorporates public education input, family education investment, and individual endowments of students [19]. Family education investment comprises both explicit monetary investment and implicit investment through caregiving. Assuming a Cobb–Douglas production form, the EPF for rural household i is
h i c e = z i c Q i θ e i η t c i 1 η 1 θ
where h i c e represents the offspring’s human capital; z i c is offspring’s learning talent; e i   is the cash education investment; t c i   is the caregiving time investment—that is, the time family members spend caring for their offspring; Q i is the quality of school education; θ and 1 θ represent the output elasticity of public and family education investment, respectively; and η and 1 η represent the output elasticity of monetary and time investment in family education. This paper assumes that the learning talent is innate, uncorrelated across generations, and heterogeneous across individuals.

2.1.3. Family Utility Function

The representative rural household i is altruistic, deriving utility from both current consumption and the expected income determined by the human capital of its offspring. The maximum family utility of rural household i   is
U i ( M i ) = max u c i + β E x v ( i i c ) + u ¯ ρ
s . t .     I i c i + e i + σ i U E  
T i t u i + t r i + t c i
In Formula (8), u ·   and v ·   represent the utility obtained from current consumption c i and expected offspring income i i c , respectively; β represents the parent’s altruistic tendency towards the offspring; i i c = f h i c e , depends on the offspring’s human capital level; and M i represents the educational choice, with M i = 1 if the offspring migrate for urban compulsory education, and M i = 0 if they stay in rural areas. To capture the disutility from parent–child separation common in rural–urban migration [20], u ¯ < 0 represents the non-monetary or psychological cost, activated when ρ = 1 ; otherwise, ρ = 0 [18].
Formula (9) is the income constraint. It is assumed that the current income I i is entirely used for family consumption c i , education investment e i , and the cost of rural–urban student migration σ i U E , with no saving or borrowing behavior. Formula (10) is the time constraint. It is assumed that the parent’s current time T i (based on the number of workers J ) is allocated among urban work t u i , rural work t r i , and childcare t c i , with no leisure time.

2.2. Key Decisions of Rural Households

2.2.1. Migration Willingness

Rural–urban student migration results in differentiation in the offspring’s education investment expenditure and incurs additional migration costs. Assuming that the basic education expenditure required when the offspring stays in rural areas is i , then e i | ( M i = 0 ) = i . The additional education expenditure required when the offspring migrates to urban areas is x i , then e i | ( M i = 1 ) = x i + i . The income constraint can be further expressed as
I i = c i + M i ( x i + σ i U E ) + i
The talent level of the offspring is denoted as z i c , with distribution G z i c . It is assumed that even offspring with the lowest talent level can achieve a level of low-skilled labor when educated in rural areas. Therefore, the benefit of rural–urban student migration is to increase the probability of the offspring becoming a high-skilled laborer through human capital investment. The probabilities of the offspring obtaining high-skilled and low-skilled jobs in urban areas when rural–urban student migration occurs are denoted as φ H U E and φ L U E , respectively, while the probability of returning to rural areas for farming is 1 φ H U E φ L U E . The probabilities of finding high-skilled and low-skilled jobs in urban areas without rural–urban student migration are denoted as φ H R E and φ L R E , respectively, while the probability of returning to rural areas for farming is 1 φ H R E φ L R E . These probabilities must satisfy the condition φ H U E   >   φ H R E and ( φ H U E + φ L U E ) >   ( φ H R E + φ L R E ) . This indicates that children with rural–urban migration have a higher probability of obtaining non-agricultural and high-skilled jobs in urban areas compared to those without rural–urban migration. The expected incomes of the offspring under the two scenarios are given by
i i c | ( M i = 1 ) = φ H U E w H U h i c e + φ L U E w L U + 1 φ H U E φ L U E w R
i i c | ( M i = 0 ) = φ H R E w H U h i c e + φ L R E w L U + 1 φ H R E φ L R E w R
The family utility functions under the two scenarios are
U i | ( M i = 1 ) = u I i x i σ i U E i + β E x v [ φ H U E w H U h i c e + φ L U E w L U + 1 φ H U E φ L U E w R ] + u ¯ ρ
U i | ( M i = 0 ) = u I i i + β E x v [ φ H R E w H U h i c e + φ L R E w L U + 1 φ H R E φ L R E w R ] + u ¯ ρ
The net utility obtained from rural–urban student migration is Δ U i = U i | M i = 1 U i | ( M i = 0 ) . Thus,
Δ U i = u I i x i σ i U E i u I i i + β E x v [ φ H U E w H U h i c e + φ L U E w L U + 1 φ H U E φ L U E w R ] v [ φ H R E w H U h i c e + φ L R E w L U + 1 φ H R E φ L R E w R ] + [ u ¯ ρ M i = 1 u ¯ ρ M i = 0 ]
Formula (16) can be further simplified to
Δ U i = u I i x i σ i U E i u I i i c o n s u m p t i o n   e f f e c t + β E x v ( i i U c v ( i i R c ) } i n t e r g e n e r a t i o n a l   e f f e c t + u ¯ ρ M i = 1 u ¯ ρ M i = 0 s e p a r a t i o n   e f f e c t
From Formula (17), the net utility of rural household i’s decision on rural–urban student migration can be decomposed into three components: the consumption effect, the intergenerational effect, and the separation effect. The consumption effect is always negative because rural–urban student migration increases education investment expenditure for the offspring, thereby reducing parents’ final product consumption. The intergenerational effect is always positive because rural–urban student migration increases the probability of the offspring obtaining non-agricultural and high-skilled jobs in urban areas, thus raising the expected income level of the offspring. The direction of the separation effect is uncertain. If rural–urban student migration leads to a shift from parent–child co-residence to separation, it generates non-monetary negative utility, making the separation effect negative. If rural–urban student migration leads to a shift from parent–child separation to co-residence, it generates non-monetary positive utility, making the separation effect positive. If rural–urban student migration does not change the spatial distance between parents and children—for instance, when the parents work in both rural and urban areas, respectively, and the child moves from living with one parent to living with the other—then the separation effect is neutral and equals zero. Therefore, the net effect of rural–urban student migration for different rural households can be positive or negative. The key factor influencing rural household i’s migration willingness is the comparison of the relative magnitudes of the consumption effect, intergenerational effect, and separation effect. Based on this analysis, Proposition 1 is proposed:
Proposition 1.
A positive net utility of rural–urban student migration is a necessary condition for rural households to engage in such migration.
Continuing with the static analysis of Formula (16), the following conclusions can be drawn:
d Δ U i d σ i U E < 0 ,     d Δ U i d ρ > 0 ,     d Δ U i d w H U >   0 ,     d Δ U i d φ H R E < 0 ,     d Δ U i d β > 0
Based on this, proposition 2 is proposed:
Proposition 2.
Rural households are more likely to have migration willingness under the following conditions:
(1)
When the cost of rural–urban student migration is lower  ( σ i U E ) ;
(2)
When rural–urban student migration enables a transition from parent–child separation to co-residence (ρ changes from 0 to 1);
(3)
When the expected wage rate of high-skilled labor in urban areas is higher  ( w H U ) ;
(4)
When the probability of becoming high-skilled labor is lower if rural–urban student migration does not occur  ( φ H R E ) ;
(5)
When the parent’s altruistic tendency towards the offspring is stronger  ( β ) .
The critical parameters ( σ i U E ,     ρ ,     w H U ,     φ H R E ,     β ) in Proposition 2 are directly or indirectly related to the characteristics of rural households. As a result, rural households with different characteristics exhibit varying levels of migration willingness. Therefore, Proposition 2 helps to identify the key factors that influence the migration willingness of rural households:
(1)
The impact of family resource endowment on migration willingness: From formula (16), it can be seen that when rural households make rural–urban student migration decisions, the predetermined family income I i does not affect Δ U i , and therefore does not influence the migration willingness. This implies that family resource endowments, as represented by family income, do not impact migration willingness.
(2)
The impact of parental individual endowment on migration willingness: Parental individual endowment can influence σ i U E ,   ρ ,   w H U , consequently affecting migration willingness. Firstly, the parent’s workplace affects the cost σ i U E of rural–urban student migration and the parameter ρ for parent–child separation. When the parent’s workplace is in the city, the offspring are more likely to meet the enrollment conditions for urban migrant workers, which reduces the cost of rural–urban student migration. Additionally, when the parent’s workplace is in the city, the offspring are more likely to live together with the parents after migration, reducing the negative utility generated by parent–child separation. Secondly, parental occupational background and personal income shape the amount of exposure they have to urban labor market information, which then influences how accurately they expect high-skilled wages w H U . Studies have shown that rural farmers—with very limited access to urban wage information—tend to underestimate city wage levels. In contrast, white-collar parents—through their work experience or social network—possess more accurate expectations, whereas blue-collar workers fall somewhere in between [21]. In the context of rural China, empirical findings confirm that parents’ occupations and incomes influence their educational return expectations [22]. Thus, parents with white-collar occupations or higher personal income have a stronger migration willingness. Finally, the parents’ levels of education indirectly influence migration willingness by affecting their workplace, occupation type, and personal annual income. The higher the parents’ levels of education, the stronger the migration willingness.
(3)
The impact of the student’s individual characteristics on migration willingness: The student’s individual characteristics can influence φ H R E and β , consequently affecting migration willingness. Firstly, the student’s learning talent impacts the probability of becoming a high-skilled labor φ H R E   when rural–urban student migration does not occur. In rural areas with relatively low education quality, individuals with higher learning talent are more capable of acquiring knowledge and skills, even under limited conditions, and thus have a greater probability of becoming a high-skilled laborer. In contrast, individuals with lower learning talent typically require more intensive educational support—both public and familial—to reach a comparable skill level [23]. Consequently, for less talented students, remaining in rural areas where educational resources are scarce reduces their chances of becoming a high-skilled laborer. As a result, rural households with less talented children are more inclined to pursue urban education through migration, viewing it as a necessary strategy to compensate for limited local educational opportunities. Thus, the lower the student’s learning talent, the higher the migration willingness of rural households. Secondly, the student’s gender, age, birth order, and other personal characteristics can affect β —namely, the parent’s altruistic tendency. For instance, in multi-child households, altruism is not necessarily equal across offspring. Parents may exhibit greater altruism toward children who are male or firstborn [24,25]. Therefore, a child’s personal attributes can systematically shape how willing parents are to support costly education-related migration decisions.

2.2.2. Migration Capacity

According to proposition 1, when the benefits of rural–urban student migration exceed the costs, i.e., when U i | M i = 1 > U i | ( M i = 0 ) , a rural household i   is expected to choose urban schooling for their offspring. Conversely, when U i | ( M i = 1 ) < | ( M i = 0 ) , a rural household i is expected to choose rural schooling for their offspring. The probability of a rural household i engaging in rural–urban student migration can be expressed as
Pr M i = 1 = P r { U i M i = 1 > U i ( M i = 0 ) }
From Formula (16), it can be seen that the predetermined family income I i   does not affect   Δ U i , and therefore does not influence migration willingness. However, since rural–urban student migration increases the education investment expenditure for the offspring and incurs additional migration costs ( x i + σ i U E ) , actual migration behavior is subject to income constraints. Therefore, Proposition 1 is a necessary, but not sufficient, condition. The actual probability of a rural household i   engaging in rural–urban student migration is given by
Pr M i = 1 = Pr U i M i = 1 > U i ( M i = 0 ,   I i c i + x i + σ i U E + i }
Formula (19) implies that even if rural–urban student migration is the optimal choice, some rural households cannot actually engage in it due to income constraints ( I i < c i + x i + σ i U E + i ). Therefore, Proposition 3 is proposed:
Proposition 3.
A positive net utility of rural–urban student migration, along with additional education expenditure and migration costs that are not constrained by income limitations, are sufficient and necessary conditions for rural households to engage in rural–urban student migration.
In Proposition 3, stating that the additional education expenditure and migration costs of rural–urban student migration are not subject to income constraints means that rural households engaging in rural–urban student migration must have a certain level of migration capacity. This capacity depends on the relative sizes of family income I i , as well as additional education expenditure and migration costs ( x i + σ i U E ) . Continuing with the static analysis of Formula (19), the following conclusions can be drawn:
d Pr M i = 1 d I i > 0 ,     d Pr M i = 1 d σ i U E < 0
Based on this, Proposition 4 is proposed:
Proposition 4.
Rural households are more likely to have migration capacity under the following conditions:
(1)
When family income is higher  ( I i ) ;
(2)
When the cost of rural–urban student migration is lower  ( σ i U E ) .
The key parameters ( I i ,     σ i U E ) in Proposition 4 are directly or indirectly related to the micro-level factors of rural households, and, thus, rural households with different characteristics have different migration capacities. Therefore, Proposition 4 can further identify the key factors affecting the migration capacity of rural households:
(1)
The impact of family resource endowment on migration capacity: Family resource endowment can influence I i , consequently affecting migration capacity. Firstly, total family income directly represents I i . The higher the family income, the stronger the migration capacity. Secondly, the family income of rural households includes wage income, property income, business income, and transfer income. The number of laborers in the family affects wage income, while the cultivated land area affects business income or property income. Therefore, the greater the number of family laborers and the larger the cultivated land area, the stronger the migration capacity.
(2)
The impact of parental individual endowment on migration capacity: Parental individual endowment can influence I i and σ i U E , consequently affecting migration capacity. Firstly, the parental level of education, occupation type, workplace, and personal annual income can influence I i . Personal annual income directly contributes to total family income, and the individual’s level of education, occupation type, and workplace indirectly contribute to total family income by influencing personal annual income. Generally, individuals with higher education, those employed in white-collar occupations, or those working in urban areas tend to have higher personal incomes. Secondly, the parents’ workplaces can also influence migration capacity by affecting σ i U E . When the parents’ workplaces are in the city, their offspring are more likely to meet the enrollment conditions for urban migrant workers, which reduces the cost of rural–urban student migration.

3. Empirical Research Design

Having established a set of theoretical propositions using mathematical modeling, we conducted an empirical analysis to test whether these hypotheses hold in real-world settings. Specifically, the following sections adopt a mixed-methods approach that combines quantitative econometric analysis with qualitative insights from field interviews. This empirical strategy enables us to examine both the driving factors and the formation mechanism of rural households’ decisions regarding rural–urban student migration in China.

3.1. Study Area

The empirical materials used in this study come from County D in Province X, China, obtained during on-site investigations conducted by the author from 13 July to 1 August 2022. In accordance with academic ethical norms and specific contractual agreements, the identity of the sample county remains undisclosed. This confidentiality, mandated by an agreement signed with the county-level government before the commencement of the fieldwork, was critical for accessing detailed county data and securing the trust of the participants involved in the study. Located in the mid-western part of Province X, County D is a typical agricultural county. It was selected as the sample county due to its typical and representative nature for researching rural–urban student migration issues in China. Geographically, County D is neither adjacent to the administrative center of its affiliated prefecture-level city, H City, nor is it the most remote among the counties under H City’s jurisdiction. Regarding urban–rural disparity, in 2021, the ratio of per capita disposable income between urban and rural residents in County D was 2.6:1, close to the national average of 2.5:1. In terms of educational development, County D passed the national assessment of balanced development of compulsory education in 2020 and ranked in the middle among provincial-level areas for compulsory education development. Regarding rural–urban student migration, the migration rate within County D and the rate calculated at the national level through CFPS data show relatively small differences (County D’s rural–urban student migration rates in 2012, 2014, 2018, and 2020 were 14.79%, 19.98%, 19.55%, and 21.55%, respectively, while national-level migration rates calculated using CFPS data in 2012, 2014, 2018, and 2020 were 11.57%, 16.99%, 19.77%, and 22.61%, respectively).

3.2. Data Sources

The data obtained from on-site investigations include two types: rural household questionnaire survey data and in-depth interview materials for individual cases. The questionnaire survey employed a two-stage stratified random sampling method. In the first stage, two primary schools and two junior high schools were randomly selected in the urban areas, and four primary schools and four junior high schools were randomly selected in rural areas. In the second stage, an equidistant sampling method was used to randomly select twenty rural registered students from each grade of each urban school and ten rural registered students from each grade of each rural school, with the questionnaires answered by the students’ parents. To ensure the smooth progress of the questionnaire survey and the quality of the samples, an oversampling method was adopted during the actual questionnaire distribution, ensuring that the number of questionnaires distributed in each grade of each school was not less than the specified target quantity. A total of 960 questionnaires were distributed, and 916 valid questionnaires were collected, yielding an effective rate of 95.42%. For the individual case interviews, 40 rural household samples were randomly selected, and each interview with the respondents lasted no less than 30 min. The coding method for interview records is XXYY-P (or N), where XX represents the respondent’s place of residence (township), YY represents the respondent’s code in the township, and P and N represent the respondent’s identity as the parent of the student and other family members (mostly grandparents), respectively.

3.3. Econometric Model Setting

To empirically examine rural households’ decisions regarding student migration, this study focuses on two key outcomes: migration willingness and migration capacity. Both are treated as binary outcomes, indicating whether a household is willing to send a child to study in an urban area and whether it has the actual means to do so. These two dimensions jointly reflect the full migration decision, resulting in four possible combinations: unwilling and unable, unwilling but able, willing but unable, and both willing and able. Since willingness and capacity are likely influenced by overlapping factors and may be interdependent, estimating them separately could lead to biased results. Therefore, this study uses a bivariate Probit model, which allows us to jointly estimate the likelihood of both outcomes while accounting for their potential correlation [26].

3.4. Variable Selection

3.4.1. Dependent Variables: Migration Willingness and Migration Capacity

Rural households’ decisions regarding rural–urban student migration in China are influenced by both migration willingness and migration capacity. Before conducting the empirical research in this study, it is necessary to identify which rural households have migration willingness and which have migration capacity. According to the push–pull theory, the relative strength of urban pull, rural push, urban push, and rural pull factors determines whether rural households have migration willingness [27]. Rural households with migration willingness also need to have a certain level of migration capacity to overcome intermediate resistance and ultimately achieve the migration behavior. Based on this theoretical framework, this study uses information obtained from a survey questionnaire about the reasons for the occurrence and non-occurrence of rural–urban student migration to assess and identify the migration willingness and migration capacity of rural households. The specific identification mechanism is illustrated in Figure 1.
Specifically, regarding rural–urban student migration behavior, the questionnaire first asked for the name of the school where the child was currently enrolled. The options were divided into two groups: the first four items were urban schools, and the next eight items were rural schools. If the child was currently enrolled in an urban school, rural–urban student migration behavior had occurred; if the child was currently enrolled in a rural school, rural–urban student migration behavior had not occurred. For those samples where rural–urban student migration behavior had not occurred, further inquiries were made about the reasons for not sending the child to an urban school, with the options shown in Figure 2. If the responses included urban push factors or rural pull factors, it was considered that the rural household had no migration willingness. If the responses included intermediate resistance factors, it was considered that the rural household had no migration capacity.
Among all rural household samples, 63.10% have migration willingness and 84.06% have migration capacity. Specifically, 8.08% have neither migration willingness nor migration capacity, 28.82% have no migration willingness but have migration capacity, 7.86% have migration willingness but no migration capacity, and 55.24% have both migration willingness and migration capacity. In the samples where rural–urban student migration behavior had not occurred, 17.56% have migration willingness but no migration capacity. For these rural households, engaging in rural–urban student migration is the optimal choice, but, due to the constraint of migration capacity, rural–urban student migration cannot actually occur.

3.4.2. Explanatory Variables

Micro-level factors influencing the migration willingness and migration capacity of rural households can be broadly categorized into four areas: family resource endowment, parents’ personal endowment, students’ individual characteristics, and cognitive factors. This study selects key explanatory variables from each of these categories. Specifically, family resource endowment includes family annual income, labor quantity, and land area, representing capital, labor, and land resources, respectively. For the parents’ personal endowment, based on the family joint decision-making model, family decisions are influenced by the characteristics of multiple decision-makers. Therefore, this study includes variables representing the personal endowment characteristics of both the father and the mother as control variables in the equation. Students’ individual characteristics include the student’s gender, age, birth order in the family, and learning talent. Cognitive factors include educational values [28].
To address the identification problem of the simultaneous equations system, this study selects the variable “same-group migration rate” to identify the willingness equation. The same-group migration rate refers to the percentage of parents among relatives and friends who send their children to urban schools. Typically, the same-group migration rate can influence the migration willingness of rural households through the same-group effect, but it is evidently independent of factors influencing migration capacity [29]. Additionally, the regression controls for regional fixed effects by accounting for the student’s household registration location (precise to the township level), thereby excluding the influence of external environmental factors on the decision of rural–urban student migration.

4. Empirical Results and Analysis

4.1. Driving Factors Influencing Rural–Urban Student Migration Decisions

Table 1 presents the regression results of the bivariate Probit model. Model (1) displays the regression results for factors influencing rural households’ migration willingness, while Model (2) shows the results for factors influencing rural households’ migration capacities. The results indicate that the Wald statistic for the model is 15.2156 with a p-value of 0.0001, passing the significance test at the 1% level. The null hypothesis for the Wald test in the context of the bivariate Probit model is that the error terms of the two equations—migration willingness and migration capacity—are uncorrelated. Significance at the 1% level indicates that the null hypothesis is not valid. Therefore, it is necessary to use the bivariate Probit model for estimation.

4.1.1. Influence of Family Resource Endowment

Family resource endowment has no significant impact on the migration willingness of rural households, but significantly influences their migration capacity. Specifically, family annual income and arable land area have a significant positive effect on migration capacity, while the number of laborers has no significant impact. The resource endowment of rural households has a limited impact on the cost–benefit analysis of rural–urban student migration, thus not significantly affecting a family’s net income from student migration. Since rural–urban student migration involves high migration costs, these resource endowments will influence the migration capacity of rural households. On the one hand, rural households undergoing student migration need to bear additional costs for their children’s education and living expenses, which are explicit costs. On the other hand, parents also need to make sacrifices in terms of their careers and income to take care of their children’s daily lives, representing the opportunity cost of student migration, i.e., implicit costs. Therefore, higher family annual income means more financial support for children’s education and greater capacity to make adjustments in terms of income and career choices, resulting in stronger migration capacity [30]. Similarly, a larger arable land area implies higher potential agricultural production and operational income, as well as higher potential land transfer rents, contributing to an increased migration capacity through income diversification.

4.1.2. Influence of Parent’s Personal Endowment

Parental personal endowment significantly affect both the migration willingness and migration capacity of rural households. Specifically, the mother’s education level, workplace, occupation type, and annual income, as well as the father’s occupation type, have significant impacts on migration willingness. The mother’s workplace and occupation type, along with the father’s annual income and occupation type, significantly impact migration capacity. Overall, the personal endowments of both parents influence migration willingness and capacity, but the effects of the father and mother differ, reflecting their different roles in the decision-making process for rural–urban student migration [31]. Households with higher maternal education levels are associated with stronger migration willingness. Mothers working in urban areas within the county or in white-collar jobs exhibit higher migration willingness than those working in rural areas or unemployed mothers. Conversely, households with fathers engaged in agricultural occupations have lower migration willingness than those with unemployed fathers. Regarding migration capacity, households with mothers working in urban areas, either inside or outside the county, have stronger migration capacities than those with mothers working in rural areas. Similarly, households with fathers in blue-collar, white-collar, or individual business occupations have stronger migration capacities than those with unemployed fathers. Households with mothers in individual business occupations also have stronger migration capacities than those with unemployed mothers. Higher paternal annual income is also associated with a stronger migration capacity.

4.1.3. Influence of Student Individual Characteristics

Students’ individual characteristics significantly affect the migration willingness of rural households, but do not significantly impact their migration capacity. Previous studies have shown a preference for boys in rural–urban student migration decisions, influenced by traditional gender preference in Chinese rural households [32,33]. However, this study’s regression analysis indicates that gender does not significantly impact migration willingness. This result suggests that the traditional gender preference may be diminishing in rural China, reflecting a shift towards more gender-neutral attitudes in educational decisions. Student age has a significant negative impact on migration willingness, with parents more inclined to send younger children to urban schools. Birth order also has a significant negative impact on migration willingness, indicating a preference for the eldest child. Additionally, lower learning talent significantly increases migration willingness, indicating that rural households prefer to send children with lower attention levels to urban areas for study.

4.1.4. Influence of Other Factors

Cognitive factors do not significant impact the migration willingness and capacity of rural households. The mean value of the variable representing rural households’ educational values is 4.2598, indicating that most rural households agree that educational attainment is crucial for their children’s future achievements. This reflects the high importance placed on education in rural China, with no significant differences in cognitive aspects regarding rural–urban student migration. The same-group migration rate has a significant impact on the migration willingness of rural households. The same-group migration rate significantly impacts migration willingness. A higher proportion of parents among relatives and friends sending their children to urban schools increases the migration willingness of rural households due to the group effect.

4.2. Mechanisms of Rural–Urban Student Migration Decision-Making

Based on theoretical analysis and empirical research on the driving factors of migration willingness and capacity, this paper delineates the logical relationships among rural households’ migration willingness, migration capacity, and migration behaviors regarding children’s schooling. Building upon this, the paper constructs a decision-making mechanism for rural–urban student migration (Figure 3). In this section, with the data displayed in Figure 3 and deep interview data obtained in County D, this paper further elucidates the mechanisms behind the formation of rural households’ migration willingness and capacity.

4.2.1. Formation Mechanism of Rural Households’ Migration Willingness

The migration willingness of rural households is based on a cost–benefit analysis of rural–urban student migration, influenced by urban pulling factors, rural pushing factors, urban pushing factors, and rural pulling factors. Interviews whose children transferred from rural schools to urban schools reflect these changes in cost–benefit before and after migration. For example, improved convenience and facilities in urban schools increase parental satisfaction. One parent noted, “Previously, the children attended a village school with limited facilities. After third grade, they had to go to a neighboring village for school. Most villagers started finding ways to send their children to urban schools from fourth grade. The children experienced significant changes after moving to urban schools. Before, they had to walk an hour to school, waking up at 6 a.m. Now, the school is just 10 min away, making it much more convenient. The urban school has modern facilities and equipment, unlike the village school that used chalkboards. The teaching staff is also better equipped, with teachers not having to handle multiple subjects at once” (LL01-P). Another parent observed, “The village school offered average education, and my child’s grades were around 40–50 points, which did not meet our expectations. We hoped she could score above 90 points. Since transferring to the urban school, she is indeed scoring above 90 points. We are very satisfied” (DX01-P). A third parent remarked, “The management and educational quality of the urban school are high, and it is relatively convenient to attend. The teachers are excellent, and the management here is effective, unlike the relatively loose management in the township school” (BL01-P).
As decision recipients, students’ individual characteristics influence the cost–benefit of rural–urban student migration. For instance, younger children with lower self-reliance require more parental care, making parents more inclined to keep them close. In contrast, older children with better self-reliance are more likely to stay in rural schools. As one parent explained, “I used to farm, but I started working in the county town last year. I have two children—the younger one just started first grade this year and is with me. Since he is still young, bringing him out earlier helps him get used to the urban environment and learn more effectively. The older one is already in sixth grade and can take care of himself, so it’s more convenient for him to stay home and attend school there” (XA03-P). The preference for the eldest child may stem from rural households balancing “quantity–quality” considerations. Older students entering compulsory education with fewer siblings yield a higher return on investment through migration. As birth order decreases and the number of siblings increases, the time and resources available to each child are reduced, lowering migration willingness. This finding validates the classic theory of the “quantity–quality trade-off” [34]. Attention concentration is a crucial learning talent influencing academic performance and lifelong educational achievement [35]. Parents who send their children to urban schools often note differences: “The urban school is strictly managed, the teachers are responsible, and the children have a big playful heart, so it is better to be strict” (BL04-P); “The management of the urban school is effective, but the rural school is relatively loose” (DS03-P); “The teachers in the urban school often hold parent-teacher meetings and communicate one-on-one with parents” (DX02-P). Interviews reveal that parents generally perceive stricter management and better educational quality in urban schools, contributing to increased migration willingness, especially for students with lower attention concentration.
The formation of rural households’ migration willingness involves joint decision-making among family members, with the final decision closely related to the personal wishes and economic capacity of the core decision-maker. In this process, the role of mother’s characteristics outweighs that of the father’s, influenced by traditional gender roles. Within the family, mothers typically assume more responsibilities related to the care and education of children [36]. Therefore, the mother’s personal characteristics play a more significant role in increasing migration benefits and reducing migration costs. Mothers’ migration willingness is influenced by their education level, workplace, occupation type, and annual income, while fathers’ migration willingness is influenced by their occupation type. These factors shape the personal life course of both parents, leading to different parental characteristics and varying degrees of migration willingness.
Firstly, the education level of the mother and the occupational types of both parents significantly influence family educational values, shaping how they perceive the potential benefits of rural–urban student migration, which in turn affects their willingness to migrate. Mothers with incomplete compulsory education often have outdated educational expectations, expressing attitudes like “study if possible; if not, find work,” perceiving limited returns from migration and thus lacking willingness. Fathers in farming occupations often lack the desire for social mobility, while mothers in white-collar jobs have a stronger desire for their children to achieve social advancement through education. Fathers engaged in farming often expressed sentiments like “Why go to the urban area? Schooling in the village is fine” (DS09-P) and “Reading anywhere is the same. I make a good income from raising cattle, and I hope my child works here in the future, no need to go to the urban school” (LL02-P). In contrast, a mother working in the financial industry in the urban area stated that, “Although I only have a high school education, my job allows me to interact with politicians and wealthy people. I understand that education is the best way out. So, I plan to support my child as much as I can so that he can at least go to graduate school” (DS03-P). These examples demonstrate how parental education and occupational background influence the perceived educational returns (benefits) of migration, thereby shaping their willingness to pursue it.
Secondly, the mother’s workplace influences the perceived and actual costs associated with rural–urban student migration. Since mothers are often primarily responsible for childcare and education, their working location greatly impacts the logistical and emotional cost of supporting a child in an urban school, thus shaping migration willingness. Mothers working in urban areas tend to express greater willingness to migrate, as proximity makes child-rearing more manageable. As one mother explained, “It’s convenient for me to work in urban areas to take care of my children. I can cook three meals a day for them and drive them to and from school on my motorized scooter in five minutes” (DS01-P). Conversely, mothers working in rural areas prefer to keep their children in rural areas, minimizing the practical burden of commuting or managing separate households: “I can spend more time with the kids when they’re studying in the village” (DS09-P). Additionally, working in urban areas exposes mothers to different parenting norms and educational perspectives, reinforcing the perceived long-term benefits of urban schooling. One mother stated, “When I was engaged in agriculture in the village, I couldn’t be exposed to new things. In urban areas, I found that people were very different, and I realized that letting children go to school in the urban area would help them a lot” (DX01-P). Another added, “I often talk to my colleagues in the urban area about how to educate my children better and which school is better. These conversations influence my own ideas and help me” (DS05-P). Thus, the mother’s workplace shapes the cost–benefit evaluation of migration and directly influences her willingness to pursue it.
Lastly, the mother’s personal income not only strengthens her financial contribution to the household, but also enhances her influence in decision-making, which together shape the household’s migration capacity. Decisions regarding rural–urban student migration involve multiple participants, primarily both parents, requiring negotiation and consensus. A higher maternal income increases her bargaining power and the household’s ability to absorb migration-related costs [37]. One high-earning mother explained, “I earn 8000–9000 yuan a month, and my child’s father, who is self-employed, also earns well. We often discuss our ideas, and deciding whether to send our child to an urban school is a joint decision” (GL01-P). Our interviews suggest that, compared to mothers, fathers are less likely to engage in discussions about their children’s education with colleagues or peers. While this pattern does not necessarily imply a lack of concern, it may reflect lower levels of active involvement or differences in communication norms. This observation aligns with prior findings that mothers tend to play a more active role in educational decision-making and information gathering in rural households [38]. When mothers lack decision-making power, the migration decision often reflects the father’s preference. In such cases, limited information and support may constrain the family’s capacity to execute migration decisions. Therefore, maternal income not only reflects economic ability, but also affects intra-household power dynamics, both of which are critical to determining a rural household’s willingness for migration.

4.2.2. Mechanism of Formation of Rural Households’ Migration Capacity

The resistance factors accompanying rural–urban student migration require a certain level of migration capacity to overcome. On the one hand, a significant challenge is the additional cost of housing, either through purchasing or renting. Rural households often face substantial financial burdens to facilitate their children’s education in urban areas. One parent shared that, “In 2007, my family bought our first house in the county for over 150,000 yuan, allowing our eldest daughter to attend an urban school from the first grade in 2009” (YA01-P). Another mentioned, “Before buying our house, both children attended rural primary school. In 2014, to have them attend urban school, we paid 200,000 yuan for a house. Now, relatives and friends are also buying houses for the sake of education” (BL02-P). Renting is also common, as one parent noted: “We used to rent a house in the urban area for 350 yuan per month. In 2015, we bought a house with a down payment of 100,000 yuan, totaling 320,000 yuan” (LR01-P). Another said, “In 2018, we bought a house to make it convenient for our children to go to school in the urban area, with a down payment of 100,000 yuan and a total cost of 200,000 yuan, plus a monthly mortgage of 2000 yuan” (BL01-P). For those who continue renting, one parent explained, “To attend an urban school, one needs to provide a rental certificate, with a monthly rent of 500 yuan” (DS02-P). Another added, “Previously, two people working in the city could rent a single room for 400–500 yuan per month. Now, with the child going to school, we need a larger place, costing over 900 yuan per month” (XA01-P).
On the other hand, living expenses in urban areas significantly increase with rural–urban student migration. Rural households in County G reported that post-migration living expenses were at least double their pre-migration expenses in rural areas. One parent noted, “The monthly living expenses for one child amount to 1000 yuan (we have two children), and our total family expenses reach 3000 yuan per month” (GL01-P). Another parent explained, “In the village, we could grow vegetables and manage with 800–900 yuan per month. Now, we face significant financial pressure, spending over 2000 yuan per month in the urban area” (XA01-P).
Differentiated resource endowments among rural households result in varying migration capacities. In County D, 55 households expressed a desire for their children to attend urban schools, but lacked the means. Of these, 22 households had annual incomes below CNY 10,000, 23 had incomes between CNY 10,000 and 40,000, and 10 had incomes between CNY 40,000 and 60,000. The average annual income of these households was CNY 30,700, all less than CNY 60,000. Some households explained that limited family resources constrained their migration capacity: “Renting a house requires money for everything, and we can’t afford to bring the children for urban school” (LL05-P). Both parents are the main labor resources in rural households, with the father typically being the primary income source. Therefore, the father’s personal income level and occupation type greatly impact the family’s income stability and migration capacity. The mother’s income significantly contributes to the family only if she is self-employed. Additionally, the mother’s workplace affects childcare, enabling children to migrate as “children of migrant workers”, which helps reduce migration costs. Thus, the personal endowments of both parents significantly affect the migration capacity of rural households.

5. Conclusions and Discussion

Institutional changes during the transformation of China’s urban–rural dual structure have created opportunities and possibilities for rural households to engage in rural–urban student migration. In response to these opportunities, some rural households have chosen to migrate, while others have not. This divergence reflects the adaptive rational decisions made by rural households aiming to maximize household utility, demonstrating their agency and strategic decision-making. Based on a theoretical analysis and empirical data from rural households in County D, Province X, China, this paper explores the driving factors and formation mechanisms of rural households’ decisions regarding rural–urban student migration in China. The conclusions and discussion are presented below.
Firstly, this paper innovatively combines the classic economic analysis framework of rural household behavior within the unique context of China. By developing the model and providing theoretical explanations, this study addresses the non-monetary disutility caused by parent–child separation—a common issue in rural households practicing the “urban–rural amphibious” model. By incorporating this factor, this paper offers a more accurate and context-specific theoretical explanation for the decision-making mechanisms and driving factors behind rural–urban student migration in China.
Secondly, rural households’ decisions regarding rural–urban student migration are influenced both by migration willingness and migration capacity. Only households that possess both migration willingness and migration capacity can actualize rural–urban student migration. Migration willingness is based on a cost–benefit analysis, while migration capacity involves overcoming intermediate barriers. Among the samples where rural–urban student migration did not occur, 17.56% had migration willingness, but lacked migration capacity, preventing them from making optimal decisions to maximize household utility. This lack of migration capacity hinders some rural children, who would benefit from urban education, from migrating to urban areas. This poses a challenge to the smooth advancement of China’s new urbanization, which focuses on human-centric development within the context of rural–urban integration. To optimize rural households’ decisions regarding rural–urban student migration and to promote the family-oriented migration of the agricultural transfer population, it is essential to improve the cost-sharing mechanisms of education. Facilitating collaboration among the government, enterprises, social organizations, and other stakeholders will provide better educational support and guarantees for the rural–urban migration of students, promoting sustainable development and balanced urbanization.
Finally, this paper analyzes the factors influencing rural households’ migration willingness and capacity, as well as the formation mechanisms of these factors. Migration willingness is shaped by joint decision-making by both parents, and is primarily influenced by parental personal characteristics and the student’s individual characteristics. Key parental characteristics include the mother’s education level, workplace, occupation, and annual income, as well as the father’s occupation, all of which significantly impact migration willingness. The student’s individual features, such as age, birth order, and learning aptitude, are also significant factors. Migration capacity is determined by family resource endowment, with parental personal characteristics serving as core labor resources that influence this capacity. Within the family resource endowment, household annual income and cultivated land area significantly affect migration capacity. Additionally, the mother’s workplace and occupation, as well as the father’s occupation and annual income, have significant impacts on migration capacity. The findings highlight the importance of a holistic approach that considers both this willingness and capacity in order to promote sustainable development and balanced urbanization, ultimately ensuring that rural students have equitable access to educational opportunities in urban areas.
Although County D exhibits characteristics that are broadly representative of many county-level regions in China, its specific geographic and socioeconomic context imposes certain limitations on the generalizability of our findings. As such, the conclusions drawn from this study are likely to be more applicable to other mid-level counties with similar features—particularly those located in central and western China that display moderate levels of urban–rural inequality, relatively balanced development in compulsory education, and limited geographic proximity to major urban centers. To enhance the robustness and applicability of future research, comparative case studies involving multiple regions with diverse administrative affiliations, geographic conditions, urbanization levels, and distributions of educational resources are recommended. Additionally, longitudinal research designs would provide a deeper understanding of how rural–urban student mobility evolves over time in response to changing policies and broader patterns of regional development.

Author Contributions

Conceptualization, R.W., H.Q. and F.Z.; methodology, R.W.; investigation, R.W.; writing—original draft preparation, R.W., H.Q. and J.W.; writing—review and editing, R.W., H.Q., J.W. and F.Z.; funding acquisition, F.Z.; supervision, F.Z.; project administration, F.Z. All authors have read and agreed to the published version of this manuscript.

Funding

This research was funded by the Major Program of the National Social Science Foundation of China (grant number 21ZDA059) and the National Natural Science Foundation of China (grant number 72073134). The APC was covered by the Major Program of the National Social Science Foundation of China (grant number 21ZDA059).

Institutional Review Board Statement

This study does not require further approval from an Ethics Committee or Institutional Review Board (IRB), as it does not involve clinical trials on humans or animals, nor does it include any unethical practices. Our research focuses on understanding the decision-making logic of Chinese rural households in selecting the location of their children’s education, using a combination of questionnaire surveys and in-depth interviews. All participants were adults—specifically, parents or other relatives of the students. Therefore, the study does not directly involve human or animal subjects in a way that would necessitate formal ethical review under existing guidelines. We strictly adhered to the ethical principles outlined in the Declaration of Helsinki (1975, revised 2013). Prior to data collection, informed consent was obtained from all participants, who were fully informed of the purpose and voluntary nature of the study. Furthermore, we anonymized all collected data to ensure the privacy and confidentiality of respondents. The study does not involve any harm to individuals or infringement of personal or commercial interests. In addition, our research meets the ethical exemption criteria outlined in the Ethical Review Measures for Life Sciences and Medical Research Involving Humans, jointly issued in February 2023 by China’s National Health Commission, Ministry of Education, Ministry of Science and Technology, and State Administration of Traditional Chinese Medicine. Specifically, Article 32 of these Measures states that: “Human life science and medical research involving the use of human information data or biospecimens may be exempt from ethical review if it does not cause harm to human participants, does not involve sensitive personal information or commercial interests, and meets one of the following conditions. The aim of this exemption is to reduce unnecessary burdens on researchers and to promote the development of research involving human subjects in life sciences and medicine: 1. The research uses publicly available data obtained legally, or data derived from the observation of public behavior without interference; 2. The research uses anonymized information data; 3. The research uses existing human biospecimens, where the sources comply with relevant laws and ethical principles, and the research content and purpose fall within the scope of standard informed consent, and do not involve human reproductive cells, embryos, reproductive cloning, chimerism, or heritable gene editing; 4. The research uses human-derived cell lines or cell strains from biobanks, where the research content and purpose fall within the scope authorized by the provider, and do not involve human embryos, reproductive cloning, chimerism, or heritable gene editing”. Based on this regulatory framework and the nature of our study, we respectfully submit that our research qualifies for ethical review exemption.

Informed Consent Statement

Informed consent was obtained from all subjects involved in this study.

Data Availability Statement

The authors do not have permission to share data.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. The identification mechanisms of rural households’ migration willingness and migration capacity.
Figure 1. The identification mechanisms of rural households’ migration willingness and migration capacity.
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Figure 2. Reasons for the occurrence and non-occurrence of rural–urban student migration behavior.
Figure 2. Reasons for the occurrence and non-occurrence of rural–urban student migration behavior.
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Figure 3. Mechanisms of rural–urban student migration decision-making.
Figure 3. Mechanisms of rural–urban student migration decision-making.
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Table 1. Estimation results of the bivariate Probit model.
Table 1. Estimation results of the bivariate Probit model.
(1)(2)
Migration WillingnessMigration Capacity
Family annual income−0.00050.0236 **
(0.0085)(0.0102)
Number of laborers0.01490.0264
(0.0526)(0.0554)
Arable land area0.00670.1125 **
(0.0380)(0.0463)
Father’s education level0.00700.0061
(0.0275)(0.0301)
Mother’s education level0.0471 *0.0039
(0.0268)(0.0281)
Father’s workplace (with rural areas as a reference)
Urban areas inside the county0.10320.2277
(0.1807)(0.1965)
Urban areas outside the county−0.20990.0054
(0.1649)(0.1575)
Mother’s workplace (with rural areas as a reference)
Urban areas inside the county1.3566 ***0.5936 ***
(0.1766)(0.1852)
Urban areas outside the county0.15900.4299 **
(0.1920)(0.1993)
Father’s occupation type (with unemployment as a reference)
Farmer−0.6196 **0.3743
(0.2560)(0.2539)
Blue-collar worker−0.35880.6857 ***
(0.2680)(0.2482)
White-collar worker0.20590.9972 **
(0.4076)(0.4309)
Individual business owner0.31830.7449 **
(0.3540)(0.3551)
Mother’s occupation type (with unemployment as a reference)
Farmer−0.29930.0109
(0.1891)(0.1953)
Blue-collar worker0.10360.1986
(0.2046)(0.2174)
White-collar worker0.7989 **0.5639
(0.3458)(0.3790)
Individual business owner−0.17630.6627 *
(0.3626)(0.3712)
Father’s annual income0.01770.0475 *
(0.0249)(0.0266)
Mother’s annual income0.0624 **0.0190
(0.0282)(0.0266)
Student’s gender0.0042−0.1479
(0.1161)(0.1195)
Student’s age−0.0815 ***0.0083
(0.0238)(0.0233)
Student’s birth order−0.1489 **0.0299
(0.0712)(0.0748)
Student’s learning talent−0.1318 **−0.0938
(0.0565)(0.0603)
Educational values0.0807−0.0428
(0.0915)(0.0909)
Same-group migration rate1.4150 ***
(0.2260)
Regional fixed effectsControlledControlled
Constant−0.32876.8300
(0.4625)(11.0000)
Observations916916
Wald chi215.2156 ***
athrho−0.3182 ***
(0.0816)
* p < 0.10; ** p < 0.05; *** p < 0.01. Standard error of robust standard errors in parentheses.
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Wang, R.; Qiao, H.; Wei, J.; Zheng, F. To Stay or to Migrate: Driving Factors and Formation Mechanisms of Rural Households’ Decisions Regarding Rural–Urban Student Migration in China. Societies 2025, 15, 226. https://doi.org/10.3390/soc15080226

AMA Style

Wang R, Qiao H, Wei J, Zheng F. To Stay or to Migrate: Driving Factors and Formation Mechanisms of Rural Households’ Decisions Regarding Rural–Urban Student Migration in China. Societies. 2025; 15(8):226. https://doi.org/10.3390/soc15080226

Chicago/Turabian Style

Wang, Ruonan, Hui Qiao, Jinyang Wei, and Fengtian Zheng. 2025. "To Stay or to Migrate: Driving Factors and Formation Mechanisms of Rural Households’ Decisions Regarding Rural–Urban Student Migration in China" Societies 15, no. 8: 226. https://doi.org/10.3390/soc15080226

APA Style

Wang, R., Qiao, H., Wei, J., & Zheng, F. (2025). To Stay or to Migrate: Driving Factors and Formation Mechanisms of Rural Households’ Decisions Regarding Rural–Urban Student Migration in China. Societies, 15(8), 226. https://doi.org/10.3390/soc15080226

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