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Article

Land Attachment, Intergenerational Differences and Land Transfer: Evidence from Sichuan Province, China

by
Guihua Liu
1,
Liping Yang
1,
Shili Guo
2,
Xin Deng
3,
Jiahao Song
1 and
Dingde Xu
1,4,*
1
College of Management, Sichuan Agricultural University, Chengdu 611130, China
2
School of Economics, Southwestern University of Finance and Economics, Chengdu 610074, China
3
College of Economics, Sichuan Agricultural University, Chengdu 611130, China
4
Sichuan Center for Rural Development Research, College of Management, Sichuan Agricultural University, Chengdu 611130, China
*
Author to whom correspondence should be addressed.
Land 2022, 11(5), 695; https://doi.org/10.3390/land11050695
Submission received: 14 April 2022 / Revised: 3 May 2022 / Accepted: 3 May 2022 / Published: 6 May 2022
(This article belongs to the Special Issue Agricultural Land Use and Food Security)
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Abstract

:
It is of great significance to explore the influencing factors of land flow to promote moderate-scale agricultural operation. However, few studies have explored the quantitative influences of land attachment and intergenerational difference on land transfer. Based on the survey data of 540 rural households in Sichuan Province, this study uses factor analysis method to divide land attachment into land satisfaction, land rootedness, and land dependence, and further empirically tests the impact mechanism of land attachment and intergenerational difference on land flow by using Probit model and Tobit model. The results are as follow: (1) land attachment is significantly correlated with land flow-out, but not with land flow-in. (2) Different dimensions of land attachment have different impacts on land flow-out. Among them, land rootedness and land dependence have significant negative impacts on farmers’ land flow-out behavior and land flow-out area, while land satisfaction has a significant positive impact on farmers’ land flow-out behavior and has no significant impact on the land flow-out area. (3) Different generations of land attachment have different impacts on land flow-out. Among them, the land attachment of the new-generation farmers has no significant impact on land flow-out. Among middle-aged farmers, land dependence had a significant negative impact on land flow-out behavior and area, and land rootedness had a significant negative impact on land flow-out behavior; however, land satisfaction had a significant positive impact on land flow-out behavior and area. Among the older generation of farmers, land dependence has a significant negative impact on land flow-out behavior and area, while land satisfaction and land rootedness have no significant impact on land flow-out behavior and area. Therefore, in promoting the practice of land flow, we should pay attention to the differences of farmers’ emotional demands, improve the supporting policies of land flow by classification, reduce farmers’ dependence on “land security”, solve farmers’ concerns on land flow, and promote the rational flow of land factors.

1. Introduction

The development of modern agriculture has attracted much attention. Activating land management rights and promoting land circulation are important means to achieve moderate-scale agricultural operation and are an inevitable trend of China’s agricultural modernization [1,2,3]. In recent years, several Central Documents NO.1 (as the first policy statement released by Chinese central authorities each year, the document is seen as an indicator of policy priorities.) have placed a special emphasis on promoting land flow and supporting moderate-scale operation [4]. At the same time, China has successively issued documents such as the Opinions on Improving the Measures for The Separation of Contracted Management Rights of Rural Land (an opinion document issued by the general office of the CPC Central Committee and the general office of the State Council) and The Operating Standards for the Flow and Exchange Market of Rural Land Management Rights (Trial) (a management standard formulated in accordance with relevant laws, regulations, and policies) to promote the orderly flow of land-management rights and realize large-scale agricultural operations [5,6,7]. Despite the continuous attention and active promotion of such policies by the government, the development of large-scale agricultural operation based on land transfer has not been as smooth as expected [8]. According to the statistics of the Ministry of Agriculture and Rural Affairs, the land circulation area in China reached 555 million mu (1 mu ≈ 0.067 ha) in 2020, accounting for about 40.1% of the contracted farmland area in China [9]. However, a large amount of cultivated land is still managed by small farmers in a decentralized manner, and the land transfer has not completely reversed the agricultural economic pattern dominated by small-scale farmers in China [10]. For a long time, small farmers, as the main body of agricultural production and management in China, and small-scale production of farmers have produced a series of problems, such as land fragmentation and decentralization [11], low agricultural production efficiency [12], and inability to use economies of scale [13], which may pose challenges to economic and environmental sustainability and restrict the further development of modern agriculture in China. Researches show that land transfer can promote the improvement of economies of scale and efficiency [14] and improve agricultural benefits and farmers’ income through the improvement of economies of scale [15]. Therefore, it is of great practical significance to explore how to promote farmers’ land circulation to realize large-scale management.
In the studies of land transfer factors, existing literature mainly focuses on individual characteristics [16], family characteristics [17], and policy characteristics [18,19], and provides guidance and reference for this paper. However, most of these studies are based on the hypothesis of “rational man” and pay more attention to farmers’ interests and land policies, ignoring the attachment of “man” to land in the man–land relationship. Almost every aspect of human activities is driven by emotion [20], and farmers’ land transfer behaviors are no exception. Land attachment is the product of farmers’ psychological response to land [21,22], which plays a guiding and regulating role in farmers’ land transfer behaviors. In addition, with the change of times and economic development, the trend of intergenerational differentiation of farmers in China has become increasingly obvious [23]. Intergenerational differences will lead to gradually differentiated cognition, emotion, and behaviors of farmers of different generations [24], which will inevitably affect their decision-making regarding land transfer behaviors. Thus, it is necessary to analyze the influence mechanism of land attachment and intergenerational difference on land transfer. Currently, few studies [21,25] focus on the impact of land attachment and intergenerational differences on land transfer. Although they provide some ideas and basis for this paper, they still have some problems. First, they lack a systematic analysis combining qualitative and quantitative analysis. Second, the attachment to land is complex and diversified, but they are limited to a certain emotion, which may not fully reflect the impact of land attachment on land transfer decision-making.
Therefore, the study uses the factor analysis method to divide land attachment into land satisfaction, land rootedness, and land dependence; analyzes the influencing mechanism of farmers’ land attachment on land transfer; and further explores intergenerational differences from the perspective of land attached to the impact on the land circulation differences, utilizing the survey data of 540 rural households in Sichuan Province.

2. Materials and Methods

2.1. Overview of the Study Area and Data Source

2.1.1. Overview of the Study Area

Sichuan Province is located in Southwest China. The terrain is high in the West and low in the East, with rich and diverse geomorphic types, mainly including plains, hills, and mountains. With a total area of 486,000 km2, the province governs 21 prefecture level administrative regions and 183 county-level divisions. By the end of 2020, registered residence had a registered population of 90.816 million in Sichuan Province, including 56.061 million rural residents. The regional GDP reached 4859.876 billion yuan (1 yuan ≈ 0.14 euro or 0.15 dollar) and the agricultural output value was 470.188 billion yuan [26]. Sichuan had 100.842 million mu of cultivated land, and the per-capita cultivated land in the province was about 1.11 mu [27]. Among the sample counties, Yuechi County had the largest permanent population of more than 700,000, while Gaoxian county and Jiajiang County only had a permanent population of more than 300,000. In terms of the total regional output value, Jiajiang County and Yuechi County were more than 20 billion, but Gaoxian county was less than 17 billion.
Jiajiang County, Yuechi County, and Gao County are representative counties in plain, hilly, and mountainous areas of Sichuan Province, respectively. Their common characteristics are the small area of cultivated land per capita, the serious aging of agricultural labor force, and the widespread phenomenon of land transfer. Based on these common characteristics, the above counties were selected as the location of this study.

2.1.2. Data Source

The data used in this study mainly come from the questionnaire survey conducted by the research group in Sichuan Province in July 2021. The survey methods are as follows [28]: Firstly, in order to compare the impact of land attachment on land transfer under different agricultural production conditions. Jiajiang County (plain area), Yuechi County (hilly area), and Gao County (mountainous area) were selected as the research sites according to the level of economic development and landform. Secondly, according to the high, medium and low levels of township economic development, three sample townships were selected from each sample county. Thirdly, three sample villages were selected from each sample township in the same way. Finally, we randomly selected 20 farmers from each sample village and interviewed them or their families. The content of the questionnaire mainly includes the basic information of farmers, capital and land use, and so on. The survey involved 3 counties, 9 townships, and 27 villages. The response rate of farmers was 100%, and 540 valid questionnaires were obtained. Among the 540 respondents, 310 farmers transferred land, accounting for 57.4%. There were 230 farmers who had not transferred land, accounting for 42.6% of the total. The average contracted cultivated land scale of 540 respondents is 3.67 mu. Specially, there are 17 farmers under 1 mu, 51 farmers under 1–2 mu, 121 farmers under 2–3 mu, 132 farmers under 3–4 mu, 86 farmers under 4–5 mu, 93 farmers under 5–6 mu, and 68 farmers above 6 mu. The distribution map of the sample area is shown in Figure 1.

2.2. Theoretical Analysis and Research Hypothesis

2.2.1. Land Attachment

Land attachment originates from the theory of place attachment. Place attachment refers to the positive emotional connection or relationship between people and their living environment [29]. Researchers have deeply explored place attachment from the perspectives of anthropology, geography, sociology, and environmental psychology, and emphasized the connection between material and culture in terms of identity [30,31]; place; community and social linkages [32]; the symbolic meaning of place attachment [33]; and the cognitive, emotional, and behavioral components of place attachment [34]. Place was defined as a unique geographical space, including the biophysical properties of farm property and surrounding landscape, as well as the social connections and relationships cultivated in this space [35]. Farmers can form a separate attachment to each of these elements (farms) in a special way. At the same time, some people believed that for farmers, land is not only a space to provide them with life, work, entertainment, and social communication, but also a place with symbolic significance and repositories of emotion [22,36,37]. Therefore, land attachment can be said to be place attachment in a narrow sense, which refers to the positive emotional relationship between people and land [38]. Researchers held that farmers are rooted in the land and have a deep attachment to the land. For instance, Gray [39] proposed that farmers’ attachment to land can be attributed to the innate “genetic metaphor”. Carr [40] found that Chaga women on Mount Kilimanjaro in Tanzania have a deep attachment to their land and home. Quinn and Halfacre [22] also found that both farmers living on their own land and farmers renting land have a strong attachment to land.
Although researchers have conducted rich discussions on the phenomenon of land attachment and deeply conveyed land attachment in the study of the emotional relationship between farmers and land, the academic definition of land attachment is still vague [41]. This paper studies the attachment of Chinese farmers to cultivated land. Therefore, in the definition of land attachment, the article not only refers to the definition of local attachment, but also draws lessons from the views of Chinese scholars. Chinese academic circles often express farmers’ emotional attachment to land as land complex or land dependence. For example, Chen [42] defined the land complex as a deep mysterious emotion of possession, love, and attachment to the land deeply hidden in the hearts of farmers. Zhang et al. [43] believed that land complex refers to the unique attitude of farmers to give land an emotional and mysterious value. Combined with the reality and the author’s perception, this paper considers that land attachment is a kind of affection, possession (or nostalgia), and dependence of farmers on the land they own (or used to own). In terms of the dimension division of land attachment, the study also draws lessons from the dimensions of place attachment: sense of place, place identity, place dependence, rootedness, and place satisfaction [44,45]. Then the paper also refers to the division of land complex or land dependence in Chinese Studies: traditional beliefs, land dependence, and off-farmland business [43]; farmers’ economic and emotional dependence on land [43]; and satisfaction, rootedness, and land dependence [46]. Therefore, under comprehensive consideration, this study divides land attachment into three dimensions: land satisfaction, land rootedness, and land dependence. Among them, land satisfaction refers to farmers’ satisfaction with land production and utilization; land rootedness refers to farmers’ sense of identity, attention, and sense of return to land; and land dependence refers to the economic and emotional dependence of farmers on land.

2.2.2. The Impact of Land Attachment on Land Transfer

Why do farmers get attached to their land? Because land brings not only a living environment and material output [22,40], but also social relations and social identity [47]. What impact does land attachment have on farmers’ behavior? Ingram and Kirwan [48] mentioned in their research that due to farmers’ emotional attachment to the land, elderly farmers are still unwilling to give up their shares in the farm even if they intend to leave the farm, and they also worry that the people who take over their farm would not seriously manage it. Ma [49] investigated the depth of farmers’ attachment to land and found that it affected the transformation of farmers’ land use: from multiple crop planting to single crop planting, cash crop planting, or abandonment.
The influence of farmers’ cultivated land attachment on cultivated land transfer behavior is the focus of this section. We can explain the influence mechanism between land attachment and land transfer from the perspective of emotional sociology. Most emotional sociologists believed that emotion is the key mechanism to guide and stimulate micro actions [50]. Emotion is the power of action, affecting people’s attitude and cognition, and guiding people’s decisions and behaviors. Studies have shown that if a person has a strong emotional attachment to an item, they are more likely to keep the item instead of selling it [51], and the emotional attachment to the item will affect the individual’s mentality of “all his geese are swans”, which in turn can affect the way people deal with things [52]. In the context of rural China, farmers develop emotional attachment to the land in the long-term cultivation process, and the intensity of this attachment depends on individual needs. The individual needs of farmers are complex, and the influence of land attachment on land circulation is also complicated. In general, the stronger farmers’ land attachment is, the more inclined they are to grow their own land or flow into land rather than flow out of land. Specifically, the higher the satisfaction of farmers on land use, the stronger the rootedness, the heavier the economic dependence and emotional dependence, and the more inclined they are to grow the land themselves or flow into land rather than flow out of land. However, at present, the main force of rural farming in China is middle-aged farmers, who are the sandwich generation that have to look after their elderly and their little children [53,54]. Their economic rationality is stronger than their survival rationality, and they are more willing to adopt a part-time livelihood strategy, so they are more cautious in the aspect of land flow-in. Thus, the following hypotheses are proposed:
H1a: Land attachment has a significant negative impact on land flow-out, but no significant impact on land flow-in.
Under the interaction of the urbanization process and land transfer policy, the relationship between man and land is constantly changing and gradually becoming more unstable. Therefore, the dimension of land attachment is unstable, and different dimensions of land attachment may have different impacts on land transfer. Thus, the following hypotheses are proposed:
H1b: There may be differences in the effects of land satisfaction, land rootedness, and land dependence on land transfer-out.

2.2.3. The Impact of Land Attachment on Land Transfer from the Perspective of Intergenerational Differences

Intergenerational difference was proposed by Karl Mannheim, which represents the group characteristics with differences in values, preferences, attitudes, and behaviors among generations due to different birth years and growth backgrounds [55]. Subsequently, Lyons and Kuron [56] defined “generation” as a group with the same birth age and experiencing the same major social events in the key growth stage. There are differences in values and preferences among individuals of different generations [57], which can lead to different value judgments and behavior patterns [58]. Some scholars have concluded that the essence of intergenerational differences is the result of the combined effect of time effect, generation effect, and age effect [59], while the sample farmers in this study are less affected by time effect. Therefore, the intergenerational differences in this paper are mainly reflected in the generation effect and age effect. Generation effect refers to the differentiation of behavior and cognition between generations [58,60]. For example, the older generation of farmers in the sample experienced the establishment of the household contract responsibility system in their middle-age and youth, and regaining the land made them have a deeper emotion for the land [21]. While the new generation of farmers experienced the wave of market economic development and the continuous improvement of market consciousness, they formed a behavior attitude completely different from that of the middle-age and older generations of farmers. The age effect refers to the difference in psychological characteristics caused by age differences [59]. For instance, the older generations of farmers are relatively older, have a long time to deal with land, and their sense of land “real right” and land attachment are stronger than those of middle-age and new-generation farmers. Therefore, with the changes of rural society, the depth of land attachment of several generations has produced intergenerational differences [21,25]. This difference is largely affected by multiple factors, including gender, age, educational level, income, ideology, and social economy.
Specifically, the older generations of farmers have a very deep attachment to land [61]. Many older generation farmers rely on land for their livelihood all their life [62,63]. Land is the foundation of their survival, which gives them a sense of security [22], joy, and belonging, and forms strong land attachment. Under the dual effects of land attachment and distrust of the land-transfer market, the older generation of farmers are unwilling to transfer out of the land. Meanwhile, the restrictive effect of aging on labor capacity is stronger than the promoting influence of aging on land attachment [43], which can lead to the inability of elderly farmers to transfer in land. For the middle-aged generation of farmers, the intensity of their land attachment is between the new generation and the old generation. Some middle-aged generation farmers are in the prime of their life and are vigorous, and the deep emotion accumulated from long-term contact with the land made them more enthusiastic about agricultural production, so they were not willing to flow out of the land. Meanwhile, other middle-aged farmers consider life more rationally. No matter how much land they cultivate, they pay more attention to the economic value and living security brought by land [21]. Such middle-aged farmers may flow out the land due to the low comparative benefits of agriculture. However, like the old generation of farmers, their attachment to the land makes it difficult to give up the land, and they tend to transfer out of the land for a short time or often pay attention to the utilization of the transfer-out land. The younger generation of farmers gradually abandoned their land attachment with the development of their rational and economic awareness [61]. So, compared with the middle-aged and the old-generation farmers, the land attachment of the new generation of farmers is obviously lighter. Johnsen [64] showed that when household income depends more on non-agricultural income, participation in agricultural activities and land income decreases, resulting in the separation of people and land, and reducing individual identification with the land. The new generation of farmers have higher education and employment ability [65], and the non-agricultural income is higher than the agricultural income. They are not only no longer limited to land production but also have gotten rid of the shackles of “land is the lifeblood”. Besides, the new generation of farmers have relatively short contact with the land and do not pay attention to land production. In addition, under the influence of the thought of “despising peasant” [41], they have a fading land attachment and are more willing to transfer out of the land than in. In a word, farmers’ land attachments are various among the different generations, which leads to different land transfer decisions. Thus, the following hypothesis is proposed:
H2a: The land attachment of the new generation of farmers has a significant positive effect on land flow-out, but no significant impact on land flow-in.
The land attachment of middle-aged and older generation farmers has a significant inhibitory effect on land flow-out, but has no significant influence on land flow-in.
H2b: There may be intergenerational differences in the impact of land satisfaction, land rootedness, and land dependence on land transfer-out.
Based on the above analysis, this study brings land attachment, intergenerational differences, and land transfer decisions into the same analysis framework (Figure 2) and discusses the impact of land attachment and intergenerational differences on land transfer, in order to provide a new perspective for the study of land transfer.

2.3. Variable Definitions

2.3.1. Dependent Variables

The two dependent variables of this study are land transfer behaviors and area. The transfer behaviors specifically include “transfer-out behavior” and “transfer-in behavior”, which mainly take “does your family transfer out land?” and “does your family transfer in land?” as the basis of the farmers’ transfer behaviors. If the answer is yes, we record it as 1, otherwise as 0. The transfer area divided “transfer-out area” and “transfer-in area”, which was measured by “how many mu of land does your family transfer out?” and “how many mu land does your family transfer in?”. Then we wrote down the farmers’ answers directly.

2.3.2. Core Explanatory Variables

The one core independent variable of this study is land attachment. This study divides the measurement items of land attachment into three dimensions: land satisfaction, land rootedness, and land dependence. The first dimension is land satisfaction, which mainly measures whether farmers are satisfied with the status of land use by asking whether they agree with the statements of “I feel very satisfied with the current land use purpose” and “I feel very satisfied with the current land use condition”. The second is the land rootedness dimension, corresponding to the questionnaire questions “I always pay attention to my own land” and “I hope my future generations can understand the rural land”, which mainly measures whether farmers still have deep embeddedness to the land. The third is the dimension of land dependence. Corresponding to the questionnaire questions “land is not only the source of living of a family, but also the spiritual pillar of an individual” and “land is the basic living security even when I work in cities or cannot engage in agricultural production”, it mainly measures whether farmers still have economic and emotional dependence on land. There are 6 questions in total in the three dimensions, and the variables are assigned 1–5 according to the answers of farmers. In the reliability test, Cronbach ‘α coefficient of the 6 questions is 0.71, greater than 0.7, indicating good reliability. In the validity test, the calculated KMO value is 0.68; manifesting the 6 questions is suitable for factor analysis on account of their KMO value, which is greater than 0.6 and the significance level is high. In principal component analysis, three common factors are extracted according to the preset and rotated by the maximum variance method. The cumulative variance contribution rate reaches 76.07%, which can effectively explain the problem information. The results of factor analysis are shown in Table 1.
Another core independent variable of the study is intergenerational differences. In the measurement of intergenerational differences, considering the serious aging of agricultural labor force in the study area, and drawing on the research of Xie and Huang [65], this research divides generations by 1955 and 1970. Then the study generates dummy variables to signify intergenerational differences. If the head of a household was born after 1970, that person is named “new generation of farmer”, and the value is 1. If he or she was born between 1955 and 1970, he or she is called “middle-aged generation of farmer”, with a value of 2. If born before 1955, he or she is recorded “older generation of farmer”, and we assign a value of 3.

2.3.3. Control Variables

On the basis of the relevant studies [3,65,66,67,68], the study summarizes the control variables into four categories: the first is the characteristics of the head of household (gender and years of education), the second is the characteristics of the family (the proportion of non-agricultural income, the value of agricultural fixed assets, etc.), the third is the characteristics of social security, and the fourth is the characteristics of the village. Variable definitions and descriptive statistical analysis are shown in Table 2.

2.4. Research Models

2.4.1. Probit Model

When the explained variables are “transfer-out behavior” and “transfer-in behavior”, they belong to two categories of variables [8,9], so the Probit model is constructed for parameter estimation. The basic regression formula is set as follows:
Y1i = β0 + β1sati + β2rooi + β3depi + β4 Σ coni + εi
In Formula (1), Y1i represents whether farmer i transfers out or in land; sati represents the i’s satisfaction with land use; rooi represents the land rootedness of farmer i; depi represents the land dependence of farmer i; Σ coni is a set of control variables; β0 is a constant term; β1, β2, β3, and β4 respectively represent the corresponding regression coefficients, and εi is the random error term.

2.4.2. Tobit Model

When the explained variables are “transfer-out area” and “transfer-in area”, their values are similar to continuous variables and have more zero values [65,69]. Therefore, the Tobit model is used to test the impact of land attachment on land transfer scale. The basic regression equation is set as follows:
Y2i = α0 + α1sati + α2rooi + α3depi + α4∑coni + ei
In Formula (2), Y2i represents the land transfer-out or transfer-in area of farmer i, and the setting of other variables is consistent with Formula (1).

3. Results

3.1. Basic Regression Results of the Impact of Land Attachment on Land Transfer

The basic regression estimation results are shown in Table 3. Table 3 shows that although the impact coefficient of land attachment on land transfer-in is mostly positive, it is not significant, because land transfer-in is more affected by agricultural production conditions, non-agricultural income, and other factors. From the perspective of land transfer out, land rootedness and land dependence in land attachment have a negative impact on farmers’ land transfer-out behavior and area at a significant level of 5%, indicating that land rootedness and land dependence can inhibit land transfer-out. With other conditions unchanged, if the land rootedness is improved by one unit, the land transfer out probability will be reduced by 3.2% and the land transfer-out area will be reduced by 39.9%. Similarly, if the land dependence increases by one level, the land transfer-out probability will be reduced by 3.8% and the land transfer-out area will be reduced by 45.2%. Different from land rootedness and land dependence, land satisfaction significantly and positively promoted farmers’ land transfer-out behavior at the level of 10%, but had no significant impact on the area of land transfer out. From the above results, we can see that the impact of land attachment on land transfer out is complex. Although the overall effect is inhibition, it has both inhibition and promotion in detail, which verifies H1a and H1b.

3.2. Model Robustness Test of the Impact of Land Attachment on Land Transfer

Because the explained variables “transfer-out behavior” and “transfer-in behavior” are assigned with “0 or 1”, they belong to binary variables. The Probit model is used for estimation in basic regression. In order to test the robustness of the regression results, this study uses the model replacement method to replace the Probit model with the Logit model for estimation. In addition to the model substitution method, the common robustness check methods also include variable substitution method. This study replaces the explanatory variables, replaces the measurement items of “transfer-out area” and “transfer-in area” with “transfer-out rent” and “transfer-in rent”, and carries out regression analysis again. The robustness test results (Table 4) show that although the impact of land satisfaction on land transfer-out behavior fails to pass the 10% significance test, the regression coefficient is still positive, and the land rootedness and land dependence in land attachment significantly inhibit land transfer out at the level of 5%, respectively. This is basically consistent with the basic regression estimation results, indicating that the results are relatively robust and reliable.

3.3. Intergenerational Differences in the Impact of Land Attachment on Land Transfer

According to the previous analysis, the land attachment of farmers in different generations is different, so how can the intergenerational differences of land attachment be reflected in land transfer? From this aspect, we answer this question by grouping regression according to the three generations of new, middle-aged, and older generation. Considering the length of the paper, only the regression results with the explanatory variables of “transfer-out behavior” and “transfer-out area” are reported. The results (Table 5) show that the land attachment of the new generation of farmers has no significant impact on land transfer out, which may be because the new generation of farmers have higher market awareness and pay more attention to interests in land transfer out. Among the middle-aged generation of farmers and the older generation of farmers, land dependence has an inhibitory effect on land transfer-out behavior and land transfer-out area, but land satisfaction and land rootedness only have a significant impact on the middle-aged farmers, and the effect is completely opposite. Thus, H2a and H2b are partially verified.

4. Conclusions and Discussions

Based on the above analysis, this study mainly draws the following conclusions: (1) There is a significant correlation between land attachment and land transfer out, but not with land transfer in. On the whole, farmers’ land attachment can negatively affect their transfer-out behavior and area. (2) Different dimensions of land attachment have different effects on land transfer out. Among them, land rootedness and land dependence have a significant negative impact on farmers’ land transfer-out behavior and land transfer-out area, while land satisfaction has a significant positive impact on farmers’ land transfer-out behavior, but has no significant impact on land transfer-out area. Why does land satisfaction promote land transfer out? The main reason may be that with the acceleration of urbanization and the continuous promotion of land policies, farmers’ awareness of land use has gradually deepened. Even if they are unable to participate or invest in farming, they will transfer out of land rather than abandon land because of their inner satisfaction and love for the land. At the same time, it is precisely because of this satisfaction and love that many farmers are more cautious in considering the area of land transfer out. (3) Different generations of land attachment have different effects on land transfer out. Among them, the land attachment of the new generation of farmers has no significant impact on land transfer out. In middle-aged farmers, land satisfaction and land dependence have a significant impact on land transfer-out behavior and land transfer-out area, but the effect is opposite. Land satisfaction is a positive impact, and land dependence is a negative impact. Besides, land rootedness only has a significant negative impact on land transfer-out behavior. Among the older generation of farmers, land dependence has a significant negative impact on land transfer-out behavior and land transfer-out area, while land satisfaction and land rootedness have no significant impact on land transfer out. Compared with the results of basic regression, the inhibitory effect of land rootedness on the transfer out of land of the older generation of farmers is no longer significant in group regression. It may be due to the decline of their labor ability and the popularization of old-age insurance, which reduce their concern and expectation for land.

5. Policy Recommendations

According to the above conclusions, the following suggestions are put forward: (1) The government should respect the subject status of farmers and pay attention to the differences of farmers’ emotional demands. The Chinese government has repeatedly stressed that promoting land transfer and developing modern agriculture should be closely linked with China’s national conditions. Since ancient times, Chinese farmers have had deep attachment to land, which should be paid attention to. On the one hand, the formulation and implementation of land policy should fully consider the “emotional” factors of farmers, follow the “people-oriented” principle, respect the wishes of farmers, and care about the emotional demands of different groups of farmers. On the other hand, in the practice of promoting land transfer, the executor should safeguard the legitimate rights and interests of farmers, absorb the opinions of different groups of farmers, and adopt the strategy of gradual guidance and promotion. (2) The urban and rural social security system should be improved to solve farmers’ “security concerns” by classification. Most farmers believe that land transfer means the loss of “land security”, which can easily result in resistance to it. Therefore, the government and society should actively promote the construction of a social security system and give full play to the alternative role of social security. On the one hand, they should strengthen and improve the rural social old-age security system and do a good job in the coordination and connection between the new rural old-age insurance and other security systems, which has a positive impact on the transfer of land by elderly farmers; on the other hand, they should speed up the establishment of a national mobile social security system and improve the level of social security, which can effectively solve the social security problem of non-agricultural employment of young and middle-aged farmers and reduce the resistance of land transfer. (3) Local governments should carry out employment skills training to improve farmers’ employability. For farmers engaged in agriculture, the government should regularly conduct agricultural skill training, vigorously introduce advanced agricultural production technology, and raise their agricultural production and management skills. For non-agricultural employment farmers, the government should perfect the non-agricultural employment market, improve the employment security mechanism, and launch non-agricultural employment skills training in order to improve their non-agricultural employment ability and non-agricultural income. These may stimulate the transfer-in willingness of farmers who engaged in agriculture and the transfer-out willingness of farmers who engaged in non-agricultural employment. (4) The government should establish a sound agricultural land transfer trading market and improve the transfer supervision mechanism. The incompleteness of the property rights trading market and the loopholes in the supervision mechanism hinder the circulation of agricultural land to a certain extent. Therefore, on the one hand, they should establish a comprehensive and professional agricultural land transfer trading market, ensuring it has an open, fair, and standardized operation; improve farmers’ sense of trust in the transfer market; and stimulate farmers’ willingness to transfer. On the other hand, they should improve the land transfer supervision mechanism, strengthening supervision measures, standardizing land transfer behaviors, strengthening services, properly solving contradictions and disputes, and improving farmers’ satisfaction.

Author Contributions

Conceptualization, G.L. and D.X.; methodology, G.L., J.S. and D.X.; formal analysis, G.L., S.G., L.Y. and D.X.; investigation, G.L., L.Y., J.S. and D.X.; writing—original draft preparation, G.L. and D.X.; writing—review and editing, G.L. and D.X.; supervision, D.X.; funding acquisition, D.X. Methodology, L.Y., S.G., X.D. and J.S. All authors have read and agreed to the published version of the manuscript.

Funding

This project was funded by Major project of Sichuan Social Science Planning Base (SC19EZD038),“dynamic research on multidimensional poverty of rural families” (20FYB018), a later-funded project of the National Social Science Foundation of China; the youth project of humanities and social sciences of the ministry of education “research on family life cycle, sustainable livelihood and precision poverty alleviation” (19YJC790126); the investigation and research project of rural fixed observation point villages and farmers of the ministry of agriculture and rural areas “research on the general situation and trend of rural changes in China” (NYK202109081); and Sichuan Agricultural University “double branch plan” excellent young talent training program.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Liu, Y. Introduction to land use and rural sustainability in China. Land Use Policy 2018, 74, 1–4. [Google Scholar] [CrossRef]
  2. Li, Y.; Wu, W.; Liu, Y. Land consolidation for rural sustainability in China: Practical reflections and policy implications. Land Use Policy 2018, 74, 137–141. [Google Scholar] [CrossRef]
  3. Deng, X.; Xu, D.; Zeng, M.; Qi, Y. Does early-life famine experience impact rural land transfer? Evidence from China. Land Use Policy 2019, 81, 58–67. [Google Scholar] [CrossRef]
  4. Chen, J. The breakthrough of land dependence and land transfer dilemma: A new theoretical framework. Yunnan Soc. Sci. 2020, 6, 29–34. [Google Scholar]
  5. Xu, D.; Guo, S.; Xie, F.; Liu, S.; Cao, S. The impact of rural laborer migration and household structure on household land use arrangements in mountainous areas of Sichuan Province, China. Habitat Int. 2017, 70, 72–80. [Google Scholar] [CrossRef]
  6. Xu, D.; Yong, Z.; Deng, X.; Zhuang, L.; Qing, C. Rural-urban migration and its effect on land transfer in rural China. Land 2020, 9, 81. [Google Scholar] [CrossRef] [Green Version]
  7. Zhou, Y.; Li, X.; Liu, Y. Land use change and driving factors in rural China during the period 1995–2015. Land Use Policy 2020, 99, 105048. [Google Scholar] [CrossRef]
  8. Xu, J.; Zhang, Z. Effects of agricultural machinery socialization service on farmland transfer. J. Jiangsu Agric. Sci. 2021, 37, 1310–1319. [Google Scholar] [CrossRef]
  9. Xu, C.; Dang, H.; Yu, J. The influence of intergenerational division of non-agricultural employment on farmland transfer behavior: Analysis of mediating effect based on agricultural production service outsourcing. J. Northwest AF Univ. (Soc. Sci. Ed.) 2022, 22, 141–150. [Google Scholar] [CrossRef]
  10. Zhong, Z.; Hu, J.; Cao, S. Land transfer and socialized service: “Route Competition” or “Complement each other”?—Case study of 12 villages in Linyi, Shandong Province. Chin. Rural Econ. 2020, 10, 52–70. [Google Scholar]
  11. Peng, W.; Gu, J. Small farmers’ management, difficult representation of connection and identification of deep roots—Also on the choice of organic connection between small farmers and modern agricultural development. World Agric. 2020, 12, 108–117. [Google Scholar] [CrossRef]
  12. Otsuka, K. Food insecurity, income inequality, and the changing comparative advantage in world agriculture. Agric. Econ. 2013, 44, 7–18. [Google Scholar] [CrossRef]
  13. Hanandeh, A.E.; Gharaibeh, M.A. Environmental efficiency of olive oil production by small and micro-scale farmers in northern Jordan: Life cycle assessment. Agric. Syst. 2016, 148, 169–177. [Google Scholar] [CrossRef]
  14. Teklu, T.; Lemi, A. Factors affecting entry and intensity in informal rental land markets in Southern Ethiopian highlands. Agric. Econ. 2004, 30, 117–128. [Google Scholar] [CrossRef]
  15. Li, C. The formation mechanism of appropriate scale management performance on the background of farmland transfer: An analysis based on CVP model. Econ. Geogr. 2017, 37, 191–197. [Google Scholar] [CrossRef]
  16. Li, J.; Gao, Y.; Zang, J. The impact of farmers’ risk awareness on decision-making behavior of land transfer. J. Agrotech. Econ. 2014, 11, 21–30. [Google Scholar] [CrossRef]
  17. Ye, Z.; Cai, J.; Chen, Y.; Xia, X. Research on the impact of household life cycle on household land transfer behavior: An empirical analysis based on household survey data in Qinling-Dabashan Mountains. Resour. Environ. Yangtze Basin 2019, 28, 1929–1937. [Google Scholar]
  18. Wang, S. Research on the influencing factors of farmers’ land transfer: Based on the perspective of land transfer subsidy policy effectiveness. Chin. J. Agric. Resour. Reg. Plan. 2018, 39, 224–230. [Google Scholar] [CrossRef]
  19. Xu, Z.; Ning, K.; Zhong, F.; Ji, Y. New Rural Insurance and Transfer of farmland: Can institutional Endowment Replace Land Endowment?—Based on the perspective of household demographic structure and mobility constraints. Manag. World 2018, 34, 86–97. [Google Scholar] [CrossRef]
  20. Turner, J.H.; Stets, J.E. The Sociology of Emotions; Cambridge University Press: New York, NY, USA, 2005. [Google Scholar]
  21. Wang, Y. The Intergenerational Differences and Changes of Farmer Land Attachment in the New Period—T Village of Heilongjiang Province as an Example; Harbin Engineering University: Harbin, China, 2018. [Google Scholar]
  22. Quinn, C.E.; Halfacre, A.C. Place matters: An investigation of farmers’ attachment to their land. Hum. Ecol. Rev. 2014, 20, 117–132. [Google Scholar] [CrossRef]
  23. Yang, Z.; Wang, Y. Research on farmers’ cultivated land quality protection behavior in different generations: Based on the survey of 829 households in Hubei and Henan Provinces. J. Agrotech. Econ. 2015, 10, 48–56. [Google Scholar] [CrossRef]
  24. Cheng, J.; Liu, Y. Farmers’ land emotions and their intergenerational differences—Based on the analysis of land transfer. J. Shanxi Agric. Univ. (Soc. Sci. Ed.) 2021, 20, 41–48. [Google Scholar] [CrossRef]
  25. Zhang, Z.; Song, J.; Yan, C.; Xu, D.; Wang, W. Rural Household Differentiation and Poverty Vulnerability: An Empirical Analysis Based on the Field Survey in Hubei, China. Int. J. Environ. Res. Public Health 2022, 19, 4878. [Google Scholar] [CrossRef]
  26. The Data Is from Sichuan Bureau of Statistics. Available online: http://tjj.sc.gov.cn/scstjj/c105855/nj.shtml (accessed on 28 April 2022).
  27. The Data Comes from Sichuan Provincial People’s Government. Available online: https://www.sc.gov.cn/10462/c107043/2021/6/7/1bc2b429a21b48f396c5ce08f20a7cd7.shtml (accessed on 28 April 2022).
  28. Qing, C.; He, J.; Guo, S.; Zhou, W.; Deng, X.; Xu, D. Peer effects on the adoption of biogas in rural households of Sichuan Province, China. Environ. Sci. Pollut. Res. 2022. [Google Scholar] [CrossRef]
  29. Shumaker, S.A.; Taylor, R.B. Toward a clarification of people-place relationships: A model of attachment to place. Environ. Psychol. Dir. Perspect. 1983, 2, 19–25. [Google Scholar]
  30. Trudeau, D. Politics of belonging in the construction of landscapes: Place-making, boundary-drawing and exclusion. Cult. Geogr. 2006, 13, 421–443. [Google Scholar] [CrossRef] [Green Version]
  31. Walsh, K. Migrant masculinities and domestic space: British home-making practices in Dubai. Trans. Inst. Br. Geogr. 2011, 36, 516–529. [Google Scholar] [CrossRef]
  32. Mah, A. Devastation but also home: Place attachment in areas of industrial decline. Home Cult. 2009, 6, 287–310. [Google Scholar] [CrossRef] [Green Version]
  33. Low, S.M. Symbolic ties that bind. In Place Attachment; Springer: Boston, MA, USA, 1992; pp. 165–185. [Google Scholar]
  34. Scannell, L.; Gifford, R. Defining Place Attachment: A Tripartite Organizing Framework. J. Environ. Psychol. 2010, 30, 1–10. [Google Scholar] [CrossRef]
  35. Cheshire, L.; Meurk, C.; Woods, M. Decoupling farm, farming and place: Recombinant attachments of globally engaged family farmers. J. Rural Stud. 2013, 30, 64–74. [Google Scholar] [CrossRef]
  36. Tveit, M.; Ode, Å.; Fry, G. Key concepts in a framework for analysing visual landscape character. Landsc. Res. 2006, 31, 229–255. [Google Scholar] [CrossRef]
  37. Nassauer, J.I. Care and stewardship: From home to planet. Landsc. Urban Plan. 2011, 100, 321–323. [Google Scholar] [CrossRef]
  38. Xu, G.; Huang, X.; Zhou, Y.; Xu, Y.; Li, J. Literature review on land attachment. Mod. Urban Res. 2017, 10, 2–6. [Google Scholar]
  39. Gray, J. Family farms in the Scottish borders: A practical definition by hill sheep farmers. J. Rural Stud. 1998, 14, 341–356. [Google Scholar] [CrossRef]
  40. Carr, E.P. Community and Land Attachment of Chagga Women on Mount Kilimanjaro, Tanzania; Brigham Young University: Provo, UT, USA, 2004. [Google Scholar]
  41. Deng, M. The Research of Farmers’ Land Attachment in Transformation Period: Take Q Village of Yichang in Hubei Province as an Example; Southwest University: Chongqing, China, 2016. [Google Scholar]
  42. Chen, S. Change of farmers’ emotion on land in the economic transition: A perspective of farmers’ disparity. China Land Sci. 2013, 27, 35–41. [Google Scholar] [CrossRef]
  43. Zhang, J.; Zheng, X. The Impact of Aging labor Force on rural Land Transfer: Should land complex and labor capacity limitation be dominant? Resour. Environ. Yangtze Basin 2020, 29, 997–1004. [Google Scholar] [CrossRef]
  44. Williams, D.R.; Vaske, J.J. The measurement of place attachment: Validity and generalizability of a psychometric approach. For. Sci. 2003, 49, 830–840. [Google Scholar] [CrossRef]
  45. Hernandez, B.; Martin, A.M.; Ruiz, C.; del Carmen, H.M. The role of place identity and place attachment in breaking environmental protection laws. J. Environ. Psychol. 2010, 30, 281–288. [Google Scholar] [CrossRef]
  46. Xue, D.; Chen, Q.; Lyu, Y. Land dependence and local attachment of rural residents in Weibei Upland under the background of land circulation: A comparative study of land-lost and normal farmers in Huangling County. J. Shanxi Norm. Univ. (Nat. Sci. Ed.) 2019, 47, 31–39. [Google Scholar] [CrossRef]
  47. Rozin, P.; Wolf, S. Attachment to land: The case of the land of Israel for American and Israeli Jews and the role of contagion. Judgm. Decis. Mak. 2008, 3, 325. [Google Scholar]
  48. Ingram, J.; Kirwan, J. Matching new entrants and retiring farmers through farm joint ventures: Insights from the Fresh Start Initiative in Cornwall, UK. Land Use Policy 2011, 28, 917–927. [Google Scholar] [CrossRef]
  49. Ma, A.; Cai, Y.; Zhang, A. Game analysis and solution path of interest groups related to cultivated land ecological compensation. China Popul. Resour. Environ. 2012, 22, 114–119. [Google Scholar] [CrossRef]
  50. Wang, P.; Hou, J. The Current Situation and Trend of Emotion Sociology. Soc. Sci. 2005, 4, 70–87. [Google Scholar] [CrossRef]
  51. Yang, X.; Deng, J. The influence of emotional attachment on consumer participation in collaborative consumption: A perspective of product disposition. Consum. Econ. 2014, 30, 56–60. [Google Scholar]
  52. Xu, D.; Peng, L.; Liu, S.; Wang, X. Influences of risk perception and sense of place on landslide disaster preparedness in southwestern China. Int. J. Disaster Risk Sci. 2018, 9, 167–180. [Google Scholar] [CrossRef] [Green Version]
  53. Xu, D.D.; Zhang, J.F.; Xie, F.T.; Liu, S.Q.; Cao, M.T.; Liu, E.L. Influential factors in employment location selection based on “push-pull” migration theory—a case study in Three Gorges Reservoir area in China. J. Mt. Sci. 2015, 12, 1562–1581. [Google Scholar] [CrossRef]
  54. Xu, D.; Zhang, J.; Rasul, G.; Liu, S.; Xie, F.; Cao, M.; Liu, E. Household livelihood strategies and dependence on agriculture in the mountainous settlements in the Three Gorges Reservoir Area, China. Sustainability 2015, 7, 4850–4869. [Google Scholar] [CrossRef] [Green Version]
  55. Zhang, Y.; Chen, M.; Kuang, F.; Lai, Z. Study on the influencing factors of farmers’ ecological cultivation behavior under intergenerational differences—Based on 2068 questionnaires in Jiangxi Province. J. Southwest Univ. (Nat. Sci. Ed.) 2021, 43, 108–115. [Google Scholar] [CrossRef]
  56. Kupperschmidt, B.R. Multigeneration employees: Strategies for effective management. Health Care Manag. 2000, 19, 65–76. [Google Scholar] [CrossRef]
  57. Lyons, S.; Kuron, L. Generational differences in the workplace: A review of the evidence and directions for future research. J. Organ. Behav. 2014, 35, S139–S157. [Google Scholar] [CrossRef]
  58. Dencker, J.C.; Joshi, A.; Martocchio, J.J. Towards a theoretical framework linking generational memories to workplace attitudes and behaviors. Hum. Resour. Manag. Rev. 2008, 18, 180–187. [Google Scholar] [CrossRef]
  59. Chen, M.; Yuan, D.; Kuang, F.; Wu, Q.; Xie, X. Effects of household differentiation and intergenerational differences on adoption of ecological farming. China Popul. Resour. Environ. 2019, 29, 79–86. [Google Scholar] [CrossRef]
  60. Yang, H.; Yuan, K.; Chen, Y.; Mei, Y.; Wang, Z. Effect of farmer differentiation and generational differences on their willingness to exit rural residential land: Analysis of intermediary effect based on the cognition of the homestead value. Resour. Sci. 2020, 42, 1680–1691. [Google Scholar] [CrossRef]
  61. Mendras, H.; Li, P.L. The End of Farmers; Social Sciences Academic Press (China): Beijing, China, 2005. [Google Scholar]
  62. Cao, M.; Xu, D.; Xie, F.; Liu, E.; Liu, S. The influence factors analysis of households’ poverty vulnerability in southwest ethnic areas of China based on the hierarchical linear model: A case study of Liangshan Yi autonomous prefecture. Appl. Geogr. 2016, 66, 144–152. [Google Scholar] [CrossRef]
  63. Xu, D.; Peng, L.; Liu, S.; Su, C.; Wang, X.; Chen, T. Influences of migrant work income on the poverty vulnerability disaster threatened area: A case study of the Three Gorges Reservoir area, China. Int. J. Disaster Risk Reduct. 2017, 22, 62–70. [Google Scholar] [CrossRef]
  64. Johnsen, S. The redefinition of family farming: Agricultural restructuring and farm adjustment in Waihemo, New Zealand. J. Rural Stud. 2004, 20, 419–432. [Google Scholar] [CrossRef]
  65. Xie, H.; Huang, Y. Research on farmland abandonment behavior of farmers from different generational perspectives: Based on questionnaire survey of 293 farmers in Xingguo County, Jiangxi Province. China Land Sci. 2021, 35, 20–30. [Google Scholar] [CrossRef]
  66. Xu, J.; Zhang, Z. The impact of non-agricultural entrepreneurship on farmland transfer-out. Res. Agric. Mod. 2021, 42, 1083–1092. [Google Scholar] [CrossRef]
  67. Guo, S.; Lin, L.; Liu, S.; Wei, Y.; Xu, D.; Li, Q.; Su, S. Interactions between sustainable livelihood of rural household and agricultural land transfer in the mountainous and hilly regions of Sichuan, China. Sustain. Dev. 2019, 27, 725–742. [Google Scholar] [CrossRef]
  68. Xu, D.D.; Cao, S.; Wang, X.X.; Liu, S.Q. Influences of labor migration on rural household land transfer: A case study of Sichuan Province, China. J. Mt. Sci. 2018, 15, 2055–2067. [Google Scholar] [CrossRef]
  69. Gong, Y.; Lyu, M. The impact of rural intergenerational mobility on land transfer. J. South China Agric. Univ. (Soc. Sci. Ed.) 2018, 17, 75–83. [Google Scholar] [CrossRef]
Land 11 00695 g001 550
Figure 1. Distribution map of sample area.
Figure 1. Distribution map of sample area.
Land 11 00695 g001
Land 11 00695 g002 550
Figure 2. Theoretical analysis framework of this study.
Figure 2. Theoretical analysis framework of this study.
Land 11 00695 g002
Table
Table 1. Factor analysis results of land attachment.
Table 1. Factor analysis results of land attachment.
DimensionIndexAssignmentMeanFactor Analysis Results
Factor 1Factor 2Factor 3
Land satisfactionI feel very satisfied with the current land use purpose.Likert 5-point scale a4.1190.9200.1590.086
I feel very satisfied with the current land use condition.Likert 5-point scale a4.0930.9130.1540.136
Land rootednessI always pay attention to my own land.Likert 5-point scale a4.4150.1480.6740.316
I hope my future generations can understand the rural land.Likert 5-point scale a3.5650.1600.836−0.031
Land dependenceLand is not only the source of living of a family, but also the spiritual pillar of an individual.
Land is the basic living security even when I work in cities or cannot engage in agricultural production.		Likert 5-point scale a
Likert 5-point scale a		4.006
4.267		0.072
0.139		0.476
−0.004		0.679
0.891
Note: a 1 = Totally disagree; 2 = Relatively disagree; 3 = Neither agree nor oppose; 4 = Relatively agree; 5 = Totally agree.
Table
Table 2. Description of variable and descriptive statistics.
Table 2. Description of variable and descriptive statistics.
VariablesCodeDefinition and AssignmentMeanSD
Transfer-out behaviorY1Whether farmers transfer out of land (yes = 1; no = 0)0.2190.414
Transfer-out areaY2How much land area does the family transfer out (mu a)0.5571.378
Transfer-out rentY2-robustHow much rent does the family get from the transferred land (×104 yuan b)0.0250.087
Transfer-in behaviorY3Whether farmers transfer into land (yes = 1; no = 0)0.3870.488
Transfer-in areaY4How much land area does the family transfer out (mu a)2.75320.280
Transfer-in rentY4-robustHow much rent does the family get from the transferred land (×104 yuan b)0.1121.953
Land satisfactionX1Result from factor analysis01
Land rootednessX2Result from factor analysis01
Land dependenceX3Result from factor analysis01
Intergenerational differencesZBorn after 1970 = 1; Born between 1955 and 1970 = 2; Born before 1955 = 32.1370.713
New generationZ1Yes=1; no = 00.1940.396
Middle-aged generationZ2Yes=1; no = 00.4740.500
Older generationZ3Yes=1; no = 00.3310.471
Head genderC1Gender of head of a household (female=1; male = 0)0.1110.315
Head educationC2Education years of head of a household (years)6.7553.167
Non-agricultural incomeC3The ratio of non-agricultural income in total household income (%)0.7520.298
Agricultural fixed assetsC4Logarithm of agricultural fixed assets value (×104 yuan b)0.1330.340
Land areaC5Contracted cultivated land area owned by households (mu a)3.6752.197
InsuranceC6Whether the family pays endowment insurance (yes = 1; no = 0)0.7370.441
Village terrainC7The terrain of the rural households’ village (plain = 1; hill = 2; mountain = 3)1.8520.804
County 1C8County 1 = Jiajiang0.3330.472
County 2C9County 2 = Gaoxian0.3330.472
County 3C10County 3 = Yuechi0.3330.472
Note: a 1 mu ≈ 667 m2 or 0.067 ha. b 1 yuan ≈ 0.15 dollar or 0.14 euro.
Table
Table 3. The regression results of the impact of land attachment on land transfer.
Table 3. The regression results of the impact of land attachment on land transfer.
Variable CodeY1Y2Y3Y4
CoefficientDy/dxCoefficientDy/dxCoefficientDy/dxCoefficientDy/dx
X10.119 *0.030 *0.3200.3200.0650.021−0.671−0.671
(0.068)(1.738)(0.223)(1.436)(0.060)(1.091)(1.706)(−0.393)
X2−0.125 **−0.032 **−0.399 **−0.399 **0.0340.0112.7692.769
(0.061)(−2.072)(0.192)(−2.077)(0.060)(0.572)(1.950)(1.420)
X3−0.146 **−0.038 **−0.452 **−0.452 **0.0670.0221.4271.427
(0.061)(−2.432)(0.183)(−2.470)(0.059)(1.123)(1.652)(0.864)
C10.480 **0.123 **1.106 **1.106 **−0.374 **−0.121 **−8.247 **−8.247 **
(0.191)(2.544)(0.538)(2.055)(0.190)(−1.970)(4.194)(−1.966)
C20.0190.0050.0340.0340.0140.005−0.093−0.093
(0.024)(0.794)(0.082)(0.410)(0.021)(0.692)(0.472)(−0.197)
Z2−0.100−0.026−0.391−0.3910.1690.0554.6164.616
(0.177)(−0.564)(0.570)(−0.686)(0.168)(1.008)(4.859)(0.950)
Z30.1600.0410.2660.2660.1150.0372.6662.666
(0.205)(0.784)(0.655)(0.406)(0.197)(0.586)(5.028)(0.530)
C31.089 ***0.279 ***4.267 ***4.267 ***−0.763 ***−0.247 ***−21.250 **−21.250 **
(0.295)(3.918)(1.001)(4.263)(0.198)(−4.006)(8.931)(−2.379)
C4−0.172−0.044−0.497−0.4970.810 ***0.262 ***45.112 *45.112 *
(0.244)(−0.705)(0.864)(−0.576)(0.310)(2.678)(24.486)(1.842)
C50.089 ***0.023 ***0.585 ***0.585 ***−0.114 ***−0.037 ***−2.184 **−2.184 **
(0.033)(2.735)(0.131)(4.447)(0.031)(−3.797)(0.991)(−2.205)
C60.305 *0.078 *1.048 **1.048 **0.0140.0054.0754.075
(0.161)(1.940)(0.524)(2.002)(0.134)(0.107)(3.247)(1.255)
C70.0430.011−0.115−0.1150.245 *0.080*6.336 *6.336 *
(0.132)(0.322)(0.478)(−0.240)(0.128)(1.939)(3.536)(1.792)
C8 a0.741 ***0.190 ***2.147 ***2.147 ***−0.871 ***−0.282 ***−11.959 **−11.959 **
(0.216)(3.550)(0.717)(2.995)(0.203)(−4.510)(5.501)(−2.174)
C9 a0.1260.0320.2190.219−0.764 ***−0.247 ***−15.371 **−15.371 **
(0.182)(0.691)(0.644)(0.341)(0.167)(−4.841)(6.059)(−2.537)
Constant−2.792 *** −9.952 *** 0.458 −7.056
(0.509) (1.797) (0.420) (10.243)
Observations540 540 540 540
Chi260.078 *** 94.222 ***
Pseudo R20.133 0.092 0.145 0.071
Note: ***, **, and * respectively represent significance at the statistical level of 1%, 5%, and 10%. The numbers in parentheses below the coefficient are robust standard errors. The “Dy/dx” is the average marginal effect, and the number in parentheses are Z statistics. a the reference group is 3 = Yuechi County.
Table
Table 4. The robust tests of the impact of land attachment on land transfer.
Table 4. The robust tests of the impact of land attachment on land transfer.
Variable CodeModel Replace: Logit Replace ProbitVariable Replace: Rent Replace Area
Y1Y3Y2-RobustY4-Robust
X10.1950.1180.019−0.036
(0.123)(0.102)(0.017)(0.086)
X2−0.226 **0.055−0.032 **0.121
(0.105)(0.101)(0.015)(0.090)
X3−0.257 **0.107−0.041 ***−0.124
(0.105)(0.100)(0.014)(0.110)
Control variablesyesyesyesyes
Constant−4.999 ***0.698−1.725 ***−5.306 ***
(0.938)(0.724)(0.198)(0.934)
Observations540540540540
Chi261.712 ***82.988 ***
Pseudo R20.1370.1460.5640.314
Note: *** and ** respectively indicate significance at the statistical levels of 1% and 5%. Figures in brackets are robust standard errors.
Table
Table 5. The intergenerational difference of the impact of land attachment on land transfer.
Table 5. The intergenerational difference of the impact of land attachment on land transfer.
Variable CodeNew GenerationMiddle-Aged GenerationOlder Generation
Y1Y2Y1Y2Y1Y2
X10.0580.1320.285 **0.751 *0.0550.195
(0.104)(0.261)(0.124)(0.391)(0.128)(0.395)
X2−0.074−0.321−0.181 **−0.395−0.023−0.185
(0.138)(0.349)(0.090)(0.269)(0.125)(0.385)
X30.042−0.050−0.211 **−0.519 *−0.239 **−0.594 **
(0.139)(0.385)(0.095)(0.267)(0.104)(0.264)
Control variablesyesyesyesyesyesyes
Constant−7.963 ***−22.310 ***−3.447 ***−11.710 ***−1.806 **−6.797 ***
(1.061)(3.540)(0.957)(3.086)(0.803)(2.533)
Observations105105256256179179
Chi2701.158 *** 26.846 *** 32.310 ***
Pseudo R20.2180.1430.1660.1010.200.148
Note: ***, **, and * respectively indicate significance at the statistical levels of 1%, 5%, and 10%. Figures in brackets are robust standard errors.
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Liu, G.; Yang, L.; Guo, S.; Deng, X.; Song, J.; Xu, D. Land Attachment, Intergenerational Differences and Land Transfer: Evidence from Sichuan Province, China. Land 2022, 11, 695. https://doi.org/10.3390/land11050695

AMA Style

Liu G, Yang L, Guo S, Deng X, Song J, Xu D. Land Attachment, Intergenerational Differences and Land Transfer: Evidence from Sichuan Province, China. Land. 2022; 11(5):695. https://doi.org/10.3390/land11050695

Chicago/Turabian Style

Liu, Guihua, Liping Yang, Shili Guo, Xin Deng, Jiahao Song, and Dingde Xu. 2022. "Land Attachment, Intergenerational Differences and Land Transfer: Evidence from Sichuan Province, China" Land 11, no. 5: 695. https://doi.org/10.3390/land11050695

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