Impact of Village Governance Quality on the Satisfaction of Farmers’ Life Experiences

Abstract

This study presents a discussion concerning the impact of village governance quality on farmers’ life experience satisfaction using a multiple linear regression model. Accordingly, there is an analysis regarding the heterogeneity of the impact of village governance quality on farmers’ life experience satisfaction from the perspective of income differentiation and career differentiation. The results show the following: (1) The improvement of village governance quality is conducive to improving the satisfaction of farmers’ life experiences. Among them, the living and social conditions have the greatest impact, followed by village cohesion, and then village inclusiveness. (2) From the perspective of income differentiation, the quality of village governance plays the largest role in promoting the life experience satisfaction of middle-income farmers, followed by low-income farmers, and then high-income farmers. (3) From the perspective of occupational differentiation, the quality of village governance has the largest role in promoting the satisfaction of part-time farmers’ life experiences, followed by full-time farmers, and then non-agricultural farmers. Based on the research conclusion, it is suggested that strengthening the quality of village governance and paying attention to the differentiation of the farmers’ economy and occupation will improve the satisfaction of farmers’ life experiences.

1. Introduction

The quality of village governance is related to the modernization of rural social governance capacity and the governance system; in particular, it is more related to the well-being of farmers [1]. Improving the quality of village governance has a positive effect on stimulating the vitality of rural society, promoting the harmony and order of villages, and enhancing farmers’ life satisfaction [2]. In essence, farmers’ life satisfaction is a subjective psychological feeling of farmers when their living needs in villages are met, which can reflect the overall evaluation of village governance quality to a certain extent. From an academic point of view, relevant research mainly focuses on analyzing the life satisfaction of urban residents or migrant workers and pays less attention to the life satisfaction of rural residents [3]. In terms of index measurement, most of the existing studies directly measure life satisfaction by using the single-item Likert scale [4]. These articles only give a vague assessment of the individual’s overall life and lack a comprehensive judgment of life satisfaction from multiple perspectives, such as consumption level, work status, living environment, family relationships, health status, and social life. In fact, for farmers, villages are the main spatial fields of their lives, and the quality of village governance has an important impact on their life satisfaction. Despite this, few studies have explored the relationship between the two.

Farmers, as participants in village governance and sharers of governance results, can test the effectiveness of village governance practice by their experience satisfaction with the changes in village life brought about by the quality of village governance. Simultaneously, because of the different resource endowments of farmers with different occupational types and income levels, their psychological responses to changes in village life caused by the quality of village governance will also be different. Hence, this study used questionnaire survey data from Sichuan, Gansu, Shaanxi, and the Ningxia Autonomous Region to measure the quality of village governance, empirically examine the direction and degree of influence of village governance quality on farmers’ satisfaction with living experiences, and explore the heterogeneity of influence from different dimensions of village governance quality. Moreover, this was done from the perspectives of occupational and income differentiation of farmers.

2. Theoretical Analysis and Research Hypotheses

2.1. The Influence Mechanism of Village Governance Quality on Farmers’ Satisfaction with Living Experiences

As a social field space for farmers’ lives, the direct reflection of the quality of governance of villages is farmers’ satisfaction with their experiences of village life. According to the social quality theory, the quality of village governance mainly includes four aspects: village development level, village cohesion, village inclusiveness, and grassroots government empowerment level [5]. The logic of good governance in village society is to build a rural governance field with a high degree of satisfaction with farmers’ life experiences by improving the level of village development, enhancing village cohesion, promoting village inclusiveness, and empowering grassroots governments. The improvement of the quality of village governance is conducive to improving the satisfaction of farmers’ living experiences.

The living and social conditions of villages involve the protection of people’s livelihoods in the areas of education, medical care, drinking water, transportation, ecology, etc., which are the basic material conditions for the orderly improvement of the quality of village governance. They improve the convenience and comfort of farmers’ lives by ensuring the material resources of farmers’ village life, improving village infrastructure conditions, and the village’s ecological environment [6]. Village cohesion is the general consensus formed by farmers in terms of unity and sharing and value norms. However, the imbalance of economic structure, the loss of social order, and the lack of social trust caused by the rapid transformation of rural society will also adversely affect the quality of life of peasant villages [7]. The weakening of village cohesion will reduce the satisfaction of farmers’ living experiences. The core of village inclusiveness advocates more equality of opportunity and shared results, emphasizing that in the right institutional environment, farmers support each other and have the confidence to move upward, reflecting the pluralistic relationship and rule system of the village [8]. A more inclusive village can provide farmers with the right to participate in public activities, such as village construction and village cadre election; furthermore, it will enable farmers to share village resources and achievements in the process of participating in village governance, reduce farmers’ relative deprivation through freedom of choice and movement, and then, improve their satisfaction with village life experiences. The empowerment of grassroots governments is an institutional guarantee to improve the quality of village governance and farmers’ satisfaction with their living experiences [9]. Notably, in the vast rural areas, the development history and personality characteristics of each village are different, sinking the power of autonomy to the village, thereby giving play to the main position of farmers to participate in village governance, which is conducive to the development of grassroots democratic consultative politics and can also enhance the senses of belonging, acquisition, and happiness of farmers. Thus, based on the above discussion, this study proposes the following research hypotheses.

Hypothesis 1 (H1):

The quality of village governance has a positive impact on farmers’ satisfaction with their living experiences.

Hypothesis 1a (H1a):

The level of village development has a positive impact on farmers’ satisfaction with their living experiences.

Hypothesis 1b (H1b):

Village cohesion has a positive impact on farmers’ satisfaction with their living experiences.

Hypothesis 1c (H1c):

Village inclusiveness has a positive impact on farmers’ satisfaction with their living experiences.

Hypothesis 1d (H1d):

Empowerment by grassroots governments has a positive impact on farmers’ satisfaction with their living experiences.

2.2. Heterogeneous Effects from the Perspective of Farmer Differentiation

Based on the above analysis, the satisfaction of farmers’ living experiences is closely related to the quality of village governance. However, farmers of different income classes and different occupational types have different expectations and experiences of village life. Specifically, in terms of village development levels and compared with high-income farmers, middle- and low-income farmers are limited by their own resource endowments and are more in urgent need of improving social security conditions, such as education and medical care. Village development can improve their own feasible ability and family development, reduce the prudent savings of farmers to prevent uncertain risks, increase farmers’ enjoyment consumption tendencies, and have a positive effect on the improvement of farmers’ satisfaction with life experiences [10]. In terms of village cohesion and compared with high-income farmers, farmers at the middle-income and low-income levels need more help and trust from the village society; given this, factors such as altruistic tendencies, social trust, and fairness in resource distribution can improve their satisfaction with their life experiences. In terms of village inclusiveness, when the village resource distribution system is not perfect, there is a phenomenon of low-income and middle-income farmers who are excluded from resource acquisition and distribution [11]. However, in more inclusive villages, low-income, and middle-income farmers’ access to and distribution rights can be effectively guaranteed, and they can receive more social support in a neighborly and friendly village environment. In terms of grassroots government empowerment and compared with high-income farmers, middle- and low-income farmers are in weak positions in village social governance and participation in public affairs. By giving these farmers more rights to participate in village governance and development, they can effectively improve their senses of belonging to the village and recognize their memberships, which then improves their satisfaction with living experiences. Therefore, the following research hypothesis is put forward.

Hypothesis 2 (H2):

Compared with high-income farmers, the quality of village governance has a greater effect on the improvement of the satisfaction of low- and middle-income farmers’ living experiences.

The influence of village governance quality on farmers’ satisfaction with their living experiences is not only regulated by the differentiation of farmers’ incomes but also by the difference in occupation types caused by the allocation of household labor resources. In terms of the level of village development and since full-time farmers basically maintain the traditional self-sufficient production mode, production factors, such as household labor, land, and capital, are mainly used for agricultural production activities and the source of livelihood is mainly dependent on agricultural production [12]. At the same time, villages are the main areas of full-time farmers’ lives, and improvements in village education, medical care, sanitation, and other living conditions have a more obvious role in promoting the satisfaction of full-time farmers’ living experiences. In terms of village cohesion and since the source of full-time farmers is mainly agriculture, they face the dual limitations of natural and market risks, which are more likely to affect their quality of life because of natural disasters or market price fluctuations. Accordingly, these events have negative impacts on their life moods. In terms of village inclusiveness and compared with full-time farmers, the complete detachment of amphibious and non-agricultural farmers (farmers who rent out their land and then do non-agricultural work) in part-time farmers’ residences makes the effect of village inclusiveness relatively weak on the satisfaction of the living experiences of these two types of farmers. In terms of grassroots government empowerment, part-time farmers and non-agricultural farmers are more eager to obtain higher social or economic status through non-farm employment opportunities, have a lower degree of participation in grassroots democracy and public affairs in villages, and spend relatively less time living in villages. Given this, the quality of village governance has less impact on the satisfaction of the life experiences of these two types of farmers. Thus, based on the above discussion, this study proposes the following research hypothesis.

Hypothesis 3 (H3):

Compared with part-time farmers and non-agricultural farmers, the quality of village governance has a greater effect on the improvement of the satisfaction of full-time farmers’ living experiences.

3. Data, Variables, and Model Construction

3.1. Data Sources

The data in this study are derived from three rural social sampling surveys carried out by the research group in the western region of China from 2020 to 2022, respectively. The information was from February to June 2020 in Gansu Province, Ningxia Hui Autonomous Region; from July to September 2021 in Shaanxi Province; and from December 2021 to March 2022 in Sichuan Province. The stratified sampling method was adopted, and the sampling was conducted at the three levels of province, county, and village, and the village was taken as the sampling unit to conduct the household interview sampling survey. For the specific household interview, farmer respondents over 16 years old were selected for interview according to the method of Kish table. The self-filling questionnaires were used for highly educated respondents; otherwise, the trained investigators collected data through face-to-face interviews. A total of 2003 sample questionnaires were collected from these three rural social sample surveys. Subsequently, after removing invalid questionnaires (abnormal key indicators, incomplete information, and completely similar answers), 1442 valid questionnaires were finally obtained. Specifically, the efficiency of the questionnaires reached 72%, and the overall sample survey situation met the expected goals.

3.2. Variable Selection

The explanatory variable in this study is the farmer’s life experience satisfaction (LES). Farmers’ life satisfaction is a subjective evaluation of their living conditions by individuals based on their own standards. The evaluations of the life experiences of the village are a subjective cognition, and overall judgment involved the life experiences of the village’s consumption levels, working environments, living environments, family relationships, health statuses, and social lives. From a psychological angle, there is a belief the overall evaluation of the life experiences of the villages in which farmers are located is an intuitive psychological expression of the well-being of the life of the field in which they live [13]. Therefore, this paper constructs an index system of satisfaction with farmers’ life experiences from six aspects: consumption level, working environment, living environment, family relationship, health status, and social life. It then measures the satisfaction of farmers’ life experiences using the method of fuzzy comprehensive evaluation; notably, the measurement result was 0.6132, and the variance was 0.0022.

Combined with the previous explanation of the connotation of village governance quality, this study constructs a village governance quality evaluation index system from four dimensions: village development level, village cohesion, village inclusiveness, and grassroots government empowerment level. Among them, the living and social conditions of villages includes five aspects: educational equity, the convenience of medical treatment, drinking-water safety, travel convenience, and environmental comfort; village cohesion includes three aspects: shared values, altruistic tendencies, and social trust; village inclusion includes three aspects: social exclusion, equity, and support; grassroots government empowerment includes three aspects: self-success, grassroots democracy, and social participation. In the empirical analysis, this study not only examines the influence of the comprehensive index of village governance quality on farmers’ satisfaction with living experiences but also analyzes the sub-dimensional impact.

Referring to and drawing on the existing research results and combined with the actual situation of the survey farmers, this study classifies the sample farmers from the two dimensions of income and occupational differentiation [14]. Among them, the differentiation of farmers’ incomes is based on the distribution of farmers’ annual income (I) levels. Hence, the farmers are divided into low-income farmers (I ≤ 12,000 RMB, 25 quantiles); middle-income farmers (12,000 RMB < I < 40,000 RMB, 50 quantiles); and high-income farmers (I ≤ 40,000 RMB, 75 quantiles). The occupational differentiation of farmers is divided into three categories according to their degree of farming: full-time, part-time, and non-agricultural farmers.

Referring to the existing research, the individual characteristics of farmers, household characteristics, and village environments were selected as the control variables [15]. The definitions of each variable and the results of the descriptive statistical analysis are shown in

Table 1. Variable definitions and descriptive statistical analysis.

The Variable Name	The Meaning of the Variable	Average Value	Standard Deviation
The farmer’s life experience satisfaction	Comprehensive evaluation score	0.6132	0.0022
Quality of village governance	Standardized by factor analysis	0	1
The living and social conditions	Standardized by factor analysis	0	1
Village cohesion	Standardized by factor analysis	0	1
Village inclusion	Standardized by factor analysis	0	1
Empowerment and empowerment of grassroots government	Standardized by factor analysis	0	1
Gender	0 = Male; 1 = Female	0.3397	0.474
Age	Actual surveyed age of household head (years)	42.8324	13.127
Marital Status	1 = unmarried; 2 = married; 3 = widowed; 4 = divorced or separated; 5 = other	2.075	1.617
Education level	1 = Elementary school and below; 2 = Junior high school; 3 = High school or junior college; 4 = College; 5 = Bachelor’s degree and above	2.028	1.043
Health status	1= very healthy; 2 = healthier; 3 = average; 4 = worse; 5 = very poor	3.8895	1.054
Political appearance	1 = Chinese Party member; 2 = Democratic Party; 3 = the masses	2.7275	0.755
Number of family members	Actual surveyed total household size (persons)	5.0674	3.228
Number of labor force	Number of actual surveyed household labor force (persons)	2.6043	2.163
Housing type	1 = Straw house; 2 = Earth house; 3 = Brick house; 4 = Brick and tile house; 5 = Steel and concrete	3.8217	1.027
Whether it is a low-income household	0 = No; 1 = Yes	0.1281	0.352
Distance to the county seat	Distance from the village to the county seat (km)	24.9847	18.881
Number of households living in the village	Number of households in the actual surveyed villages (households)	147.175	348.008
Degree of residential dispersion	1 = very dispersed; 2 = more dispersed; 3 = average; 4 = more concentrated; 5 = very concentrated	3.0522	1.164
Whether there are pollution sources	0 = No; 1 = Yes	0.1195	0.432
Whether there is a bus	0 = No; 1 = Yes	0.3335	0.539

. From the perspective of individual characteristics, 33.97% of the sample were women, and their average age was close to 43 years old. Moreover, most were married, their average education level was junior high school, their health status was poor, and most of them were masses. From the perspective of household characteristics, the average number of households in the sample farmers was five, the average labor force was close to three, most of the houses were brick and wood houses, and 12.81% of the sample were low-income households. From the characteristics of villages, the average distance from the village where the sample farmers were located to the county seat was 24.98 kilometers, the average number of households in the villages was 147, and the degree of residential dispersion was average. Furthermore, 11.95% of the villages had pollution sources, and 33.35% of the villages had buses. The specific meaning of the variables and their statistical characteristics are shown in Table 1.

3.3. Model Construction

The explanatory variable in this study is a continuous variable obtained by entropy weight treatment in six dimensions: consumption level, working status, living environment, family relationship, health status, and social life. Therefore, the multiple linear regression model was used to estimate the influence of village governance quality and its four dimensions on farmers’ satisfaction with living experiences. Subsequently, the sample farmers were classified and discussed from the perspectives of income and occupational differentiation, and the heterogeneity of the influence of village governance quality on farmers’ satisfaction with living experiences was investigated. The model is as follows:

$$LES{I}_i={\alpha }_i+{\beta }_i{Q}_i+{\sum }_{j=1}^{15}{\gamma }_{ij}{x}_{ij}+{\epsilon }_i$$

(1)

In Formula (1), $LES{I}_i$ indicates the satisfaction of the farmer’s life experience; $Q_i$ indicates the quality of governance in the village where the ith farmer is located, including village development level, village cohesion, village inclusiveness, and grassroots empowerment; $X_{ij}$ indicates other variables that may affect the satisfaction of the farmer’s life experience (including variables such as individual peasant characteristics, household characteristics, village environment, etc.). Thus, ${\alpha }_i, {\beta }_i,$ and ${\gamma }_{ij}$ are the parameters to be estimated, while ${\epsilon }_i$ represents a random error term.

To ensure the reliability of the estimation results of the multiple linear regression model, this paper reconstructs the satisfaction of the farmers in the interpreted variables by referring to the existing research practice of replacing the explanatory variables for robustness testing using the phrase “Are you satisfied with the living experience in your village?” For this question, the answer options include 1 = “very dissatisfied”; 2 = “dissatisfied”; 3 = “general”; 4 = “satisfied”; 5 = “very satisfied.” The answer to this question is re-estimated as a new explanatory variable, replacing the original explanatory variable. Since the new explanatory variable is a multivariate-ordered variable, which is measured by the five-point Likert scale, the multivariate-ordered probit model is used to test the robustness and analyze the reliability of the influence of village governance quality on farmers’ satisfaction with living experiences. The model expression is as follows:

$$LES{I}_i^{*}={\beta }_i{Q}_i+{\displaystyle \sum }_{j=1}^{15}{\gamma }_{ij}{x}_{ij}+{\epsilon }_i$$

(2)

In Equation (2), $LES{I}_i^{*}$ indicates the satisfaction of the farmer’s life experience; $Q_I$ indicates the quality of governance in the village where the $i$th farmer is located; $X_{ij}$ represents other variables that may affect the satisfaction of the farmer’s life experience; ${\beta }_I$ and ${\gamma }_{ij}$ are the parameters to be estimated, and ${\epsilon }_I$ represents the random error term. Since the satisfaction level of $LES{I}_I$ of the farmer’s life experience here is the five ordered categorical variables, the relationship between the unobservable variables, $LES{I}_i^{*}$ and $LES{I}_I$, is as follows:

$$LES{I}_i=\{\begin{array}{c}1\mathrm{if}LES{I}_i^{*}\le r_1\\ 2\mathrm{if} r_1<LES{I}_i^{*}\le r_2 \\ 3\mathrm{if} r_2<LES{I}_i^{*}\le r_3 \\ \begin{array}{c} 4\mathrm{if} r_3<LES{I}_i^{*}\le r_4 \\ 5\mathrm{if}{r}_4<LES{I}_i^{*} \end{array}\end{array}$$

(3)

In Equation (3), $r_1<r_2<r_3<r_4$ represent tangent points, which are the parameters to be estimated. The ordered conditional probability distribution for constructing farmers’ satisfaction level, $LES{I}_I$, is as follows:

$$p=\left(LES{I}_i=1|Q_i,x_{ij}\right)=\Phi \left(r_1-{\beta }_i{Q}_i-{\displaystyle \sum }_{j=1}^{15}{\gamma }_{ij}{x}_{ij}\right)$$

(4)

$$p=\left(LES{I}_i=2|Q_i,x_{ij}\right)=\Phi \left(r_2-{\beta }_i{Q}_i-{\displaystyle \sum }_{j=1}^{15}{\gamma }_{ij}{x}_{ij}\right)-\Phi \left(r_1-{\beta }_i{Q}_i-{\displaystyle \sum }_{j=1}^{15}{\gamma }_{ij}{x}_{ij}\right)$$

(5)

$$p=\left(LES{I}_i=3|Q_i,x_{ij}\right)=\Phi \left(r_3-{\beta }_i{Q}_i-{\displaystyle \sum }_{j=1}^{15}{\gamma }_{ij}{x}_{ij}\right)-\Phi \left(r_2-{\beta }_i{Q}_i-{\displaystyle \sum }_{j=1}^{15}{\gamma }_{ij}{x}_{ij}\right)$$

(6)

$$p=\left(LES{I}_i=4|Q_i,x_{ij}\right)=\Phi \left(r_4-{\beta }_i{Q}_i-{\displaystyle \sum }_{j=1}^{15}{\gamma }_{ij}{x}_{ij}\right)-\Phi \left(r_3-{\beta }_i{Q}_i-{\displaystyle \sum }_{j=1}^{15}{\gamma }_{ij}{x}_{ij}\right)$$

(7)

$$p=\left(LES{I}_i=5|Q_i,x_{ij}\right)=1-\Phi \left(r_4-{\beta }_i{Q}_i-{\displaystyle \sum }_{j=1}^{15}{\gamma }_{ij}{x}_{ij}\right)$$

(8)

The variables and parameters in Equations (4)–(8) have the same meanings as the variables and parameters in Equations (2) and (3).

4. Analysis of Model Estimation Results

The quality of village governance has an impact on farmers’ satisfaction with their life experiences, which is an important premise for empirically testing the heterogeneity of the relationship between the two from the perspective of farm household differentiation. First, this study uses a multiple linear regression model to estimate the effect of village governance quality on farmers’ satisfaction with their life experiences and to confirm whether there is a relationship between the two. Then, the changes in the relationship between village governance quality and farmers’ living experience satisfaction are analyzed from the perspective of farmers’ income differentiation and occupation. Additionally, the heterogeneous influence of village governance quality on farmers’ satisfaction with life experiences was investigated.

4.1. The Influence of Village Governance Quality on Farmers’ Satisfaction with Living Experiences

Stata 16.0 software was used to estimate the relevant parameters of village governance quality and its four sub-dimensional variables on farmers’ satisfaction with their living experiences, and the results are shown in

Table 2. Estimation of the effect of village governance quality on farmers’ satisfaction with their life experiences.

	Model (1)	Model (2)	Model (3)	Model (4)	Model (5)
Quality of village governance	0.2133 *** (0.0223)
The living and social conditions		0.1846 *** (0.0219)
Cohesion of village			0.1526 *** (0.0220)
Inclusiveness of villages				0.1228 *** (0.0208)
Grassroots governments are empowered and empowered					0.1393 *** (0.0214)
Gender	−0.0123 (0.0447)	−0.0355 (0.0447)	−0.0244 (0.0448)	−0.0269 (0.0451)	−0.0212 (0.0448)
Age	−0.0035 * (0.0018)	−0.0028 (0.0018)	−0.0029 (0.0018)	−0.0027 (0.0018)	−0.0027 (0.0018)
Marital status	0.0343 (0.0393)	0.0388 (0.0396)	0.0355 (0.0399)	0.0474 (0.0399)	0.0367 (0.0399)
Education level	−0.0184 (0.0215)	−0.0037 (0.0211)	−0.0058 (0.0218)	0.0077 (0.0216)	−0.0076 (0.0216)
Health status	−0.0481 ** (0.0203)	−0.0446 ** (0.0203)	−0.0437 ** (0.0204)	−0.0434 ** (0.0205)	−0.0464 ** (0.0204)
Political status	0.0208 (0.0304)	0.0003 (0.0330)	0.0098 (0.0307)	−0.0019 (0.0305)	0.0073 (0.0305)
Number of family members	−0.0352 *** (0.0121)	−0.0413 *** (0.0120)	−0.0418 *** (0.0122)	−0.0445 *** (0.0121)	−0.0458 *** (0.0120)
Number of labor force	0.0569 ** (0.0227)	0.0772 *** (0.0224)	0.0683 *** (0.0229)	0.0723 *** (0.0228)	0.0784 *** (0.0226)
Type of housing	0.0288 (0.0213)	0.0103 (0.0217)	0.0464 ** (0.0214)	0.0461 ** (0.0215)	0.0433 ** (0.0214)
Whether it is a low-income household	−0.0445 (0.0608)	−0.0474 (0.0612)	−0.0250 (0.0617)	−0.0639 (0.0618)	−0.0653 (0.0616)
Distance to the county seat	0.0027 *** (0.0010)	0.0024 ** (0.0010)	0.0021 ** (0.0010)	0.0021 ** (0.0010)	0.0022 ** (0.0011)
Number of village residents	0.0000 (0.0000)	0.0001 (0.0001)	0.0001 (0.0001)	0.0000 (0.0000)	0.0000 (0.0000)
Degree of residential dispersion	0.0138 (0.0180)	0.0111 (0.0183)	0.0278 (0.0182)	0.0335 * (0.0182)	0.0423 ** (0.0180)
Whether there are sources of pollution	−0.2128 *** (0.0667)	−0.2429 *** (0.0668)	−0.2534 *** (0.0672)	−0.2576 *** (0.0674)	−0.2401 *** (0.0675)
Whether there is bus access	−0.0071 (0.0400)	−0.0251 (0.0405)	0.0351 (0.0399)	0.0197 (0.0401)	0.0261 (0.0400)
Constant terms	0.1201 (0.2110)	0.1824 (0.2125)	−0.0170 (0.2117)	−0.0429 (0.2130)	−0.0323 (0.2115)
Sample size	1442	1442	1442	1442	1442
Adjusted R2	0.088	0.076	0.062	0.055	0.059

Note: ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively; inside the parentheses is the robust standard error.

. According to Model (1), the influence coefficient of village governance quality on farmers’ satisfaction with living experiences is 0.2133 and significant at the 1% statistical level. This indicates that village governance quality can significantly improve farmers’ satisfaction with living experiences; accordingly, H1 is thereby tested here. Regarding the four sub-dimensions of village governance quality, Model (2) shows the influence coefficient of village living and social conditions on farmers’ satisfaction with living experience is 0.1846 and significant at the 1% statistical level. Moreover, the influence coefficient is the largest in the four sub-dimensions of village governance quality, indicating village living and social conditions can significantly improve farmers’ satisfaction with living experiences. Therefore, H1a is tested, and the village living and social conditions will play the biggest roles in the process of village governance quality to improve farmers’ LES. Concerning village cohesion, Model (3) presents the influence coefficient of village cohesion on farmers’ satisfaction with living experiences is 0.1526 and significant at the 1% statistical level, indicating village cohesion is conducive to improving farmers’ satisfaction with living experiences. Given this, H1b is tested. From Model (4), the influence coefficient of village inclusiveness on farmers’ satisfaction with life experiences is 0.1526, which is significant at the statistical level of 1%. This indicates village inclusiveness has a significant positive impact on farmers’ satisfaction with living experiences. Thus, H1c is then tested here; however, among the four dimensions of village governance quality, its impact is relatively small. According to Model (5), the influence coefficient of grassroots government empowerment on farmers’ satisfaction with life experiences is 0.1393, which is significant at the 1% statistical level. This indicates grassroots government empowerment can significantly improve farmers’ satisfaction with life experiences Therefore, H1d is tested.

Among the control variables, from the level of individual characteristics, the health status variables had negative impacts on the satisfaction of farmers’ life experiences at the significance level of 5% in models (1)~(5), indicating the worse the health status, the lower the satisfaction of life experience. From the perspective of household characteristics, the variable of the household population had a significant negative impact on the satisfaction of farmers’ life experiences in models (1)~(5), and all were significant at the statistical level of 1%, indicating farmers with a larger family size had lower satisfaction with their life experience. The coefficient of the household labor force size variable is significantly positive in all five models and significant at least at the 5% statistical level. This indicates the higher the number of farmers’ household workforces, the higher their satisfaction with their life experiences. From the level of village characteristics, the coefficient of influence of the distance variable from farmers’ villages to the county seat on their satisfaction with their life experiences were all positive and significant at least at the 5% statistical level. This indicates the farther the farmer’s village is from the county, the higher the satisfaction level of his life experience. Whether there were pollution source variables or not at the statistical level of 1%, there was a significant negative impact on farmers’ satisfaction with their living experiences. This indicates farmers who are in villages with pollution sources have a lower level of satisfaction with their life experiences.

4.2. Analysis of the Impact Effect from the Perspective of Income Differentiation

In this study, the sampled farmers were divided into the three following groups: low-income, middle-income, and high-income. This was done according to the distribution of farmers’ annual income levels, and there was a separate estimate of the effect of village governance quality on farmers’ satisfaction with their life experiences for each group. Accordingly, the results are shown in

Table 3. Estimates of the effect of village governance quality on farmers’ satisfaction with their life experiences at different income levels.

	Low-Income Group	Middle-Income Group	High-Income Group
Quality of village governance	0.2171 *** (0.0461)	0.3054 *** (0.0356)	0.1741 *** (0.0378)
Gender	−0.0396 (0.0921)	−0.0477 (0.0689)	0.0813 (0.0751)
Age	−0.0110 *** (0.0036)	−0.0031 (0.0027)	0.0096 *** (0.0035)
Marital status	0.0276 (0.0863)	0.0948 * (0.0555)	0.0232 (0.0728)
Education level	−0.0649 (0.0464)	−0.0085 (0.0297)	0.0226 (0.0430)
Health status	−0.0710 ** (0.0330)	−0.0415 (0.0341)	−0.0073 (0.0415)
Political status	0.0847 (0.0895)	0.0343 (0.0481)	−0.0320 (0.0430)
Number of family members	−0.1136 *** (0.0251)	−0.0028 (0.0182)	0.0103 (0.0204)
Number of labor force	0.1320 *** (0.0442)	0.0242 (0.0345)	0.0570 (0.0414)
Type of housing	−0.1607 *** (0.0509)	0.0516 (0.0324)	0.0845 ** (0.0336)
Whether it is a low-income household	−0.1993 * (0.1123)	−0.0546 (0.0913)	−0.0840 (0.1251)
Distance to the county seat	0.0030 * (0.0017)	0.0073 *** (0.0020)	0.0025 (0.0017)
Number of village residents	0.0002 (0.0002)	−0.0000 (0.0000)	0.0002 (0.0002)
Degree of residential dispersion	−0.0054 (0.0399)	0.0046 (0.0258)	0.0182 (0.0343)
Whether there are sources of pollution	−0.4515 *** (0.1275)	−0.1088 (0.1006)	0.0203 (0.1402)
Whether there is bus access	−0.2163 *** (0.0752)	0.1196 * (0.0630)	0.2786 *** (0.0780)
Constant terms	1.6970 *** (0.4580)	−0.4325 (0.3303)	−1.1601 *** (0.3877)
Sample size	385	636	421
Adjusted R2	0.158	0.143	0.097

Note: ***, **, and * indicate significance levels of 1%, 5%, and 10%, respectively; inside the parentheses is the robust standard error.

. The quality of village governance has a significant positive effect on the satisfaction level of life experiences of farmers in all three groups at the 1% statistical level; notably, this effect size shows a trend of “middle-income group (0.3054) > low-income group (0.2171) > high-income group (0.1741).” This result indicates that relative to farmers in the higher income group, the quality of village governance has a greater effect on the satisfaction level of life experiences of farmers in the middle-income and low-income groups, especially farmers in the middle-income group. Therefore, H2 is tested.

4.3. Analysis of the Impact Effect from the Perspective of Occupational Differentiation

According to the definition and classification standards of farmers’ occupational differentiation, farmers are divided into three categories: full-time, part-time, and non-agricultural farmers. Moreover, the influence effect of village governance quality on the satisfaction of the life experience of farmers of the three occupational types is estimated respectively, and the results are shown in

Table 4. The impact of village governance quality on the satisfaction of farmers’ living experiences in different occupational types was estimated.

	Non-Agricultural Type	Part-Time Type	Full-Time Type
Quality of village governance	0.2011 *** (0.0514)	0.2145 *** (0.0340)	0.2134 *** (0.0373)
Gender	0.2472 ** (0.0993)	−0.1178 * (0.0690)	−0.0456 (0.0750)
Age	−0.0038 (0.0036)	−0.0008 (0.0029)	−0.0036 (0.0033)
Marital status	−0.0718 (0.0722)	0.0314 (0.0620)	0.1007 (0.0793)
Education level	−0.0314 (0.0458)	−0.0553 * (0.0304)	0.0824 * (0.0499)
Health status	−0.0110 (0.0352)	−0.0831 ** (0.0396)	−0.0626 * (0.0336)
Political status	−0.0265 (0.0619)	−0.0111 (0.0456)	0.0151 (0.0614)
Family size	−0.0631 ** (0.0274)	−0.0050 (0.0181)	−0.0480 ** (0.0211)
Workforce size	0.0719 (0.0521)	0.0258 (0.0333)	0.0957 ** (0.0398)
Housing type	−0.1065 ** (0.0522)	0.0850 ** (0.0359)	0.0631 * (0.0343)
Is a low-income household	0.0733 (0.1324)	−0.0450 (0.1035)	−0.0792 (0.1001)
Distance to county seat	−0.0022 (0.0027)	0.0061 *** (0.0018)	0.0021 (0.0014)
Number of village households	−0.0007 ** (0.0003)	0.0000 (0.0000)	0.0002 (0.0002)
Residential dispersion	−0.0978 ** (0.0416)	0.0287 (0.0287)	0.0377 (0.0294)
Are there sources of pollution	−0.5401 *** (0.1502)	−0.1757 (0.1149)	−0.0739 (0.1045)
Availability of bus	0.0469 (0.0919)	−0.1181 * (0.0629)	0.0737 (0.0653)
Constant term	1.4882 *** (0.4451)	−0.0813 (0.3409)	−0.3607 (0.3947)
Sample size	295	637	510
Adjusted R2	0.153	0.130	0.084

Note: *, **, and *** indicate significance at the statistical levels of 10%, 5%, and 1%, respectively; Robust standard errors are in parentheses.

. In particular, the quality of village governance has the greatest impact on the satisfaction of part-time farmers’ living experiences, with a regression coefficient of 0.2145, which is significant at the statistical level of 1%. Followed by full-time farmers, the influence coefficient of village governance quality on the satisfaction of full-time farmers’ living experiences was 0.2134, which was significant at the statistical level of 1%.

However, the influence of village governance quality on the satisfaction of non-agricultural farmers’ living experiences was relatively small, and the regression coefficient was 0.2011, which was significant at the statistical level of 1%. The influence coefficient of village governance quality on the satisfaction of the life experience of the three occupational types of farmers is “part-time farmer > full-time farmer > non-agricultural farmer,” and thus, H3 is partially verified. The possible reason may be part-time farmers are engaged in both agricultural production and non-agricultural industries, and strong social mobility enhances their development abilities; given this, part-time farmers have higher village governance capabilities, and the sense of achievement and personal value realization brought by participating in village governance improves their satisfaction with their life experiences. Compared with part-time farmers, full-time farmers rely more on cultivated land resources, homesteads, and productive tools to maintain livelihood stability, and their economic income and feasible ability are weaker; yet, their long-term living in village communities can improve their satisfaction with their life experiences. Although the incomes of non-agricultural farmers engaged in non-agricultural activities are much higher than that of the other two types of farmers, because they live outside the village for a long time or engage in non-agricultural industry, they rarely participate in village life and village governance. As such, the quality of village governance has the least impact on the satisfaction of non-agricultural farmers’ village life experiences.

5. Endogeneity and Robustness Test

5.1. Endogenous Testing

When analyzing the influence of village governance quality on farmers’ satisfaction with living experiences, there may be endogenous problems caused by mutual causation, measurement bias, missing variables, and other factors. In this study, the instrumental variable method is used to control potential endogenous problems, and the “average village governance quality of other samples in the same village” is selected as the instrumental variable of village governance quality in this sample with reference to the research ideas of Luo Mingzhong et al. (2022) [16]. The reason for choosing this instrumental variable is that, on the one hand, the relationships between villagers in the village area are very close, and the behavior and psychological feelings of farmers often have a “peer effect”; that is, the individual behavior and psychological feelings of farmers are often inevitably affected by other farmers around them. On the other hand, the evaluation of the quality of village governance by other surrounding villagers often does not directly affect the satisfaction of the farmer’s life experiences, and the farmer cannot control the evaluation of the quality of village governance by other villagers. Therefore, the instrumental variable theoretically meets the correlation and exogenous requirements.

In this study, the two-stage least squares method (2SLS) was used for model estimation; accordingly,

Table 5. The impact of the quality of village governance on the satisfaction of farmers’ life experiences.

	Stage 1	Stage 2
Explanatory Variables	Quality of Village Governance	Satisfaction of Farmers’ Life Experience
Instrumental variable: Average quality of governance in the same village	0.6222 *** (0.0957)
Quality of village governance		0.2128 *** (0.0502)
control variable	Controlled	Controlled
F-Measure of Stage 1	20.6171
Weak instrumental variable: Wald F-Measure	40.9037
R2	0.1875	0.0742
Sample size	1442	1442

Note: *** indicate significance at the statistical levels of 1%; Robust standard errors are in parentheses. To save space, the regression results for the control variables are not shown here.

reports the estimation results using the instrumental variable method. The regression coefficient of the instrumental variable in the first stage is 0.6222 and is significant at the statistical level of 1%, indicating the instrumental variable meets the correlation requirement.

In addition, the weak instrumental variable test statistic is well above the cut-off level of 10%, indicating there is no weak instrumental variable problem with the selected instrumental variable. The results of the second stage of regression show that after considering the potential endogenous problems, the quality of village governance can significantly improve the satisfaction of farmers’ living experiences at the statistical level of 1%, which is consistent with the previous conclusion. It shows the conclusion regarding the quality of village governance has a significant positive impact on farmers’ satisfaction with living experiences is still valid under the condition of overcoming possible endogenous problems.

5.2. Robustness Test

As mentioned above, to test the robustness of the influence of village governance quality on farmers’ satisfaction with their living experiences from the perspective of farmers’ differentiation, this study re-estimates the influence of village governance quality on farmers’ satisfaction with life experiences of different income levels and occupations by substituting the explanatory variables. The results are shown here in

Table 6. Estimation of the effect of village governance quality on the satisfaction of farmers’ life experiences in different occupational types.

	Explanatory Variables: Satisfaction of Farmers’ Life Experience
	Income Differentiation			Occupational Differentiation
	Low-Income Group	Middle-Income Group	High-Income Group	Non-Agricultural Type	Part-Time Type	Full-Time Type
Quality of village governance	0.2784 ***	0.4202 ***	0.2601 ***	0.2823 ***	0.2880 ***	0.2840 ***
	(0.0568)	(0.0499)	(0.0541)	(0.0681)	(0.0471)	(0.0493)
Control variable	Controlled	Controlled	Controlled	Controlled	Controlled	Controlled
Sample size	385	636	421	295	637	510
Pseudo R2	0.026	0.018	0.014	0.021	0.017	0.012

Note: *** indicate significance at the statistical levels of 1%, Robust standard errors are in parentheses. To save space, the regression results for the control variables are not shown here.

.

It can be seen from Table 6 that although the numerical sizes and significances of the regression coefficients are slightly different when using the new explanatory variables, the coefficient directions and relative sizes are still basically consistent with the regression results from the perspective of farmer differentiation presented above. However, the importance and significances of the regression coefficient values differ slightly. Specifically, from the perspective of income differentiation and compared with high-income farmers, the quality of village governance still has a greater effect on the satisfaction of low-income and middle-income farmers’ living experiences, especially middle-income farmers. From the perspective of occupational differentiation and compared with non-agricultural farmers, the improvement of village governance quality is more conducive to promoting the satisfaction of the life experiences of part-time farmers and full-time farmers. The above results further indicate the estimation results from the perspective of farmers’ income differentiation and occupational differentiation have certain robustness and reliability.

6. Conclusions

Using microscopic research data from 180 villages and 1442 farmers in four provinces and regions: Sichuan Province, Shaanxi Province, Gansu Province, and Ningxia Hui Autonomous Region, this study uses a multivariate linear regression model to explore the impact of village governance quality on farmers’ satisfaction with life experiences from the perspective of income differentiation and occupational differentiation. It was found the quality of village governance has a significant positive impact on farmers’ satisfaction with their living experiences; that is, the improvement of village governance quality is conducive to improving farmers’ satisfaction with their living experiences. Moreover, the influence effect of village governance quality on farmers’ satisfaction with their living experiences has the phenomena of “middle-income farmers > low-income farmers > high-income farmers” and “part-time farmers > pure agricultural farmers > non-agricultural farmers.”

Based on the above conclusions, this study proposes the following policy implications: the village governance quality factor, which consists of four dimensions: village development level, village cohesion, village inclusiveness, and empowerment of grassroots government, should be emphasized in the aspect of enhancing farmers’ satisfaction with their life experiences. First, it is necessary to strengthen the cultivation of common values, altruism, and social trust within villages, reduce social exclusion within villages, promote social equity and social support, expand farmers’ development channels, and strengthen democracy and social participation within villages. Second, the income and occupational differentiation of farmers have brought new challenges to rural economic and social governance; thus, in the process of improving farmers’ satisfaction with their life experiences, it is necessary to adhere to the value orientation of farmers’ main body status so village governance can highly overlap with farmers’ differentiation.

There are two limitations to this study. First, the data used in this paper are the rural social survey data of China, which cannot well represent the actual situation of rural areas in other countries; future studies could expand the sample size to other countries. Second, the village governance quality in this paper is measured by the scale and factor analysis method. Although we try to achieve unified standards and effective data in the measurement process, subjective judgment bias is inevitable. Therefore, future research will try to use the big data method to obtain corresponding variables.