Home is where the heart is?The Impact of perceived social status on Residents' Subjective Well-Being——The moderating role of income and its urban-rural heterogeneity

Home is where the heart is?The Impact of perceived social status on Residents' Subjective Well-Being——The moderating role of income and its urban-rural heterogeneity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Home is where the heart is?The Impact of perceived social status on Residents' Subjective Well-Being——The moderating role of income and its urban-rural heterogeneity Yu Ding, Wenqing Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9559814/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background Relocation is a significant life event that affects an individual’s mental health and well-being. Whilst previous research has examined the influence of subjective social status and income on subjective well-being, little attention has been paid to the relationship between these three factors in the context of residential mobility, and there has been a lack of systematic investigation into the moderating role of income in the relationship between subjective social status and well-being. This study aims to explore the relationship between the subjective social status and subjective well-being of migrants, as well as the moderating role played by income in this relationship. Methods Drawing on five waves of data from the China Family Panel Studies (CFPS) covering the period 2014–2022, this study employs a fixed-effects panel model to systematically examine the impact of migrants’ perceived social status on their subjective well-being, as well as the moderating role of income. The dependent variable, subjective well-being, was constructed by standardising self-reported happiness and life satisfaction indices using Z-scores. The independent variable, subjective social status, was measured using a 5-point scale, whilst the income variable was truncated at the top and bottom 1 per cent and transformed using the natural logarithm to test its moderating effect. Results After controlling for complex interactions, subjective social status (β = 0.161, p < 0.01) and annual income (β = 0.045, p < 0.05) exhibited highly significant positive main effects on well-being, whilst the moderating effect of income differed significantly between urban and rural areas. Conclusions Subjective social status is a key psychological mechanism underpinning the sense of well-being among migrant residents, whilst income serves, to a certain extent, as a substitute for the psychological rewards associated with social status; however, its effectiveness is markedly context-dependent. Consequently, against a backdrop of ever-increasing population mobility, enhancing residents’ well-being cannot rely solely on income growth; equal importance must be attached to their perception of social status and the process of social integration. In particular, differentiated strategies for social governance and public services should be formulated to address the distinct urban and rural contexts. Subjective social status Income Subjective well-being Residential Mobility CFPS Figures Figure 1 Background With the increasing mobility of the population, relocation has become one of the defining features of contemporary society; it is not merely a physical change of living space, but is also accompanied by the breakdown and reconstruction of social networks, the realignment of identity, and the unfolding of psychological adaptation processes. [ ] Migration disrupts an individual’s social networks and reference groups in their society of origin, altering their existing social frame of reference and basis for social comparison; as a result, the individual must reassess their circumstances and social standing whilst adapting to their new environment. [ ][ ] According to social comparison theory, when objective, non-social means of assessment are difficult to apply, individuals often assess their own abilities and circumstances by comparing themselves with others [ ] .In this process, subjective social status becomes a key factor in individuals’ assessment of their own circumstances and has a significant impact on their subjective well-being.Unlike socio-economic status, which is based on objective indicators such as income and education, subjective social status emphasises an individual’s perception of their position within the social hierarchy and reflects the social status as perceived by the individual. [ ] An individual’s perception of their social position can enhance their sense of well-being through mechanisms such as self-identity, social comparison and the acquisition of psychological resources. [ ] Furthermore, compared with residents living in a stable social environment, migrants face greater uncertainty as they adapt to their new surroundings, and their psychological adjustment process is more complex. [ ] Their sense of well-being is more susceptible to the influence of their subjective social status; that is, an individual’s subjective perception of their own social position plays a more critical role in the psychological adjustment process. [ ][ ] The economic resources available to individuals, particularly their income levels, play a fundamental role in shaping their subjective sense of well-being.People’s basic material desires are quite similar; consequently, at any given point in time, individuals with higher incomes tend to be happier. [ ] However, this effect is not linear; once income reaches a certain level, the marginal benefit diminishes significantly. Low income is significantly associated with lower life satisfaction and poorer emotional well-being, whereas high income, whilst improving life satisfaction, has a limited impact on emotional well-being. [ ] Consequently, an individual’s subjective sense of well-being is not simply influenced by income levels, but depends significantly on the process of social comparison. Income levels influence well-being indirectly by affecting an individual’s perception of their subjective social status.Previous research has shown that subjective social status—defined as an individual’s overall assessment of their socio-economic position—is often a more effective predictor of health and well-being outcomes than objective status, whilst income level is one of the key factors determining an individual’s perception of their socio-economic status. [ ] Individuals derive utility from comparing their income with that of others (social comparison), which profoundly influences the sense of status and happiness they derive from their income. [ ] When individuals of different income levels engage in social comparison, the reference groups they choose and the criteria they apply may vary, resulting in differences in the impact of subjective social status on well-being across different income groups. Consequently, income level, as a key economic resource variable, acts as a moderator in the relationship between subjective social status and subjective well-being. Furthermore, this moderating effect may also be influenced by differences in social contexts. Research has found that families who have migrated from rural to urban areas in China report lower levels of well-being than rural families. [ ] In other words, given the same income or resources, social reference frameworks and life circumstances may have a significant impact on the experience of well-being. On this basis, this paper proposes the following research hypotheses: H1: Subjective social status has a significant positive effect on the subjective well-being of migrants. In other words, the higher an individual’s perceived social status, the higher their reported level of subjective well-being. H2: Annual income acts as a moderator in the relationship between subjective social status and subjective well-being, and this moderating effect varies depending on whether the respondent lives in an urban or rural area. H2a: In urban areas, annual income acts as a negative moderator of the relationship between social status and well-being; that is, as income rises, the return on well-being from social status diminishes. H2b: In rural areas, the aforementioned moderating effect of annual income is not significant, and the positive impact of social status on well-being remains relatively stable across different income groups. This study presents a new examination of the relationship between residents’ perceived social status, income levels and subjective well-being. Against the backdrop of rapid urbanisation, China is experiencing large-scale and frequent population movements and changes in residence; this mobility has a profound impact on the social structure of cities and the daily lives of residents. By 2020, the size of China’s migrant population had reached nearly 376 million, accounting for approximately 26.04% of the total population [ ] .At the same time, in China—particularly within a social structure based on kinship and geographical ties—an individual’s perception of their social status is heavily dependent on their social network [ ] .A change of residence has a more direct impact on the restructuring of this framework, as well as on one’s perceived social status and sense of well-being.Consequently, compared with long-term residents, migrants rely more heavily on their subjective assessment of their circumstances to establish their social position within a new social environment, and their subjective perceptions may have a more pronounced impact on their sense of well-being.Existing research has largely been conducted on the general population, overlooking the specific mechanisms underlying the role of subjective social status among migrant groups in the context of residential mobility, and lacking a systematic examination of the moderating role of income in the relationship between subjective social status and well-being. Our analysis of sample data from relevant regions will help address the new public health challenges posed by rapid urbanisation. This study is not only of empirical significance but also makes a valuable contribution to public policy design.By identifying the mechanisms through which the subjective social status of migrant residents influences their sense of well-being, and by revealing the moderating role of income levels in this process, this paper argues that relying solely on income growth is unlikely to sustainably improve the subjective well-being of the migrant population; perceptions of social status and psychological adaptation are equally crucial factors.Consequently, in policy implementation, whilst ensuring basic economic conditions are met, greater emphasis should be placed on the social integration of migrant residents. By promoting community participation and strengthening psychological identification, their sense of belonging and identification with their new environment can be enhanced, thereby bringing about a sustained improvement in their subjective well-being. Methods Data source The data used in this paper is drawn from the China Family Panel Studies (CFPS). In 2010, the CFPS conducted a baseline survey across 25 provinces nationwide, ultimately completing interviews with 14,960 households and 42,590 individuals; since then, surveys have been conducted every two years.The data was collected and published through a collaboration between the China Family Panel Studies (CFPS) at Peking University and the Survey Research Centre at the University of Michigan, amongst other institutions. In terms of the levels of data collection, the CFPS has gathered data at three levels—individual, household and community—covering a wide range of topics including family relationships, migration, health and perceptions of social class.In accordance with the data and variable requirements specified in this paper, the main variables were drawn from five rounds of data covering the period 2014–2022. The data were sourced from 25 provinces, municipalities and autonomous regions, and more than 400 administrative villages. After excluding invalid samples, only those with observations from two or more periods were retained, resulting in a final sample of 1,762 valid cases.The variables used in this study are all derived from the China Family Panel Studies (CFPS) questionnaire, which includes several standardised psychological scales covering three main areas: personal traits, parent-child relationships and subjective attitudes. [ ] Most of these scales are based on established international instruments, which have been adapted or developed specifically for the Chinese context. Measures Dependent variable:Subjective well-being Subjective well-being refers to an individual’s overall assessment of their life, experiences and psychological state. In addition to objective factors such as education, marital status, employment and household registration, the CFPS (2022) adult questionnaire includes specific questions designed to measure respondents’ life satisfaction and subjective well-being.Previous research has shown that subjective well-being (SWB) comprises three core components: life satisfaction, positive emotions and negative emotions. [ ] In large-scale social surveys, using such items to assess well-being as a whole is a common and effective approach. [ ] In order to measure respondents’ subjective well-being more accurately and ensure that the results are more robust and reliable, this paper has selected two questions from the questionnaire to serve as indicators of subjective well-being.Question 1 was measured using a 0–10-point self-report scale: ‘How happy do you feel?’; Question 2 was measured using a 1–5-point Likert scale: ‘On a scale of 1 to 5, how satisfied are you with your life?’.Values falling outside the range of the two variables were treated as missing values. To eliminate differences in units, we standardised both variables using Z-scores, generating standardised variables with a mean of 0 and a standard deviation of 1. On this basis, we calculated the arithmetic mean of the two standardised variables to construct a ‘composite well-being index’, thereby laying a solid measurement foundation for rigorous subsequent testing of the relationship between subjective social status and subjective well-being. Key independent variable: subjective social status The study adopted the definition of class identity proposed by Jackman and his wife (1973), namely, ‘an individual’s perception of their position within the social class structure’. [ ] Existing research typically measures this variable through individuals’ subjective assessments of their own social status; a common method involves the use of a ‘social ladder’ or self-rated ranking. [ ] The dependent variable in this study is subjective social class identity, which was measured using a 5-point scale in all five rounds of the CFPS Adult Survey conducted between 2014 and 2022. The specific question asked was: ‘On a scale of 1 to 5, how would you rate your social status in this community?’ A higher score indicates that the respondent perceives their social class status to be higher. Adjustment variable: annual income In this study, annual income refers to the total income received by respondents during a specific year, including earned income, net business income, property income and transfer income; it serves as a key indicator for measuring an individual’s economic resources.The variable is derived from the CFPS adult questionnaire, specifically the question: ‘What was your total after-tax wage income from all jobs (main job + other jobs) over the past 12 months?’ In order to accurately assess its moderating effect within the model, to bring its distribution closer to a normal distribution to satisfy the model’s assumptions, and to minimise the potential impact of outliers on the estimates, this study truncated the income data at the top and bottom 1%. The truncated income values were then added by 1 and transformed using the natural logarithm; the resulting continuous variable is such that higher values indicate greater absolute economic resources among respondents. Covariates This study utilised common demographic variables as control variables, including gender, age, marital status, neighbourhood trust and experience of full-time employment.Neighbourly trust, as a key indicator of social capital, has been extensively examined by researchers for its impact on subjective well-being and is considered an essential control variable; numerous studies have indicated that gender and marital status exert a certain influence on residents’ subjective well-being[ ].Married people report higher levels of subjective well-being than those who are single, separated, divorced or widowed[ ].Furthermore, numerous studies have shown that job stability has a significant impact on an individual’s subjective well-being.[ ]All of the above variables have been included as control variables in this paper. Statistical analysis This study utilises Stata 14 for data analysis and employs a stratified, stepwise statistical analysis strategy. It aims to systematically examine the impact of subjective social status on residents’ subjective well-being and to investigate the moderating role of annual income in this relationship. Given that the dependent variable in this study, the ‘Comprehensive Well-being Index’, is a continuous variable, a multiple linear regression model was employed.Given the panel structure of the data, we have opted for a fixed-effects panel regression model in order to account for individual heterogeneity that does not vary over time.The Hausman test formally confirmed that the fixed-effects model is superior to the random-effects model.To address potential issues of heteroscedasticity and within-subject autocorrelation, all models report robust standard errors adjusted for clustering at the individual level.In particular, Model 1 is a main effects model, which regresses subjective well-being against subjective social status, annual income and a series of theoretically relevant control variables to establish a baseline relationship. Wellbeing_it = β 0 + β 1 Status_it + β 2 Income_it + β 3 Controls_it + λ_t + α_i + ϵ_it Model 2 is an interaction model for continuous variables. To test the continuous moderating effect of annual income, an interaction term between subjective social status and annual income was added to Model 1.Use the testparm command to test the statistical significance of this interaction term, in order to determine whether the effect of social status on well-being varies linearly with income level, where α_i denotes the individual fixed effect. Wellbeing_it = β 0 + β 1 Status_it + β 2 Income_it + β 3 (Status_it × Income_it) + β 4 Controls_it + λ_t + α_i + ϵ_it To test for the continuous moderating effect of age, an interaction term between age and residential mobility was introduced. By calculating the marginal effect of residential mobility, we analysed how the magnitude of the effect varies linearly with age. Wellbeing i = β 0 + β 1 Age i + β 2 Residential i + β 3 (Age i ×Residential i )+β 4 Gender i + β 5 Marriage i + β 6 Job i + β7Trust i +ϵ i To gain a deeper understanding of the significant interaction effects between continuous variables, we followed the analytical procedure recommended by Aiken and West.The average marginal effect of subjective social status on well-being was calculated at several key levels of annual income.The results are presented using marginal effects plots generated via Stata’s margins and marginsplot commands, clearly illustrating how the relationship between migrants’ subjective social status and subjective well-being varies with changes in their level of economic resources. This paper describes continuous variables using the mean, standard deviation, maximum and minimum values, and categorical variables using categories and proportions. Results were presented as odds ratios (ORs), 95% Confidence Interval (95% CI), and corresponding P values. A p-value < 0.05 was considered significant. Results Most of the variables used in this study are continuous, whilst some control variables are categorical. Among the 1,762 valid responses, some variables exhibited varying degrees of missing data due to non-response, non-applicable items and data cleaning.As shown in Tables 1 and 2 , the average age of respondents was 33.1 years, with 70.66% being male and 29.34% female. Table 1 Descriptive statistics of quantitative variables Quantitative variable Observed value Mean value Standard deviation Min Max Well-being 1762 −0.074 0.86 −3.2 1.32 edu_years 1607 9.23 3.9 0 22 trust 1762 6.56 2.01 0 10 age 1762 33.1 10.69 16 71 ln_income_w 1762 10.22 1.98 0 12.3 social_status 1762 2.71 0.91 1 5 Table 2 Descriptive statistics of qualitative variables qualitative variables Observed value Sort Percent sort Percent Gender 1762 0/female 29.34% 1/male 70.66% marriage 1762 1/married 53.75% 2/others 46.25% job 1756 1/self employed 11.96% 2/employed 88.04% urban_rural 1642 0/rural 48.36% 1/urban 51.64% Table 3 presents the results of a regression analysis based on a fixed-effects panel model, which primarily examines the effects of subjective social status and annual income on residents’ subjective well-being, and further analyses the urban-rural heterogeneity of the moderating effect of annual income. Model 1 is a model of the main effect of migrants’ perceived social status on subjective well-being. After controlling for other factors, perceived social status has a highly statistically significant positive effect on well-being.Specifically, for every one-unit increase in subjective social status, residents’ overall well-being index rises significantly by an average of approximately 0.132 units(β = 0.132, SE = 0.035, t = 3.80, p < 0.001, 95% CI [0.064, 0.200]).This finding supports the study’s main hypothesis, namely that the higher migrants rate their own social status, the greater their subjective well-being. Building on Model 1, Model 2 introduces an interaction term between subjective social status and the logarithm of annual income to test whether annual income moderates the relationship between the two.After controlling for the interaction term, the positive main effects of subjective social status (β = 0.129, 95% CI:0.060–0.198, p < 0.001) and annual income (β = 0.038, 95% CI:0.009–0.067, p = 0.011) on overall well-being remained significant. The interaction coefficient was negative and reached marginal significance (β=−0.026, 95% CI:−0.053–0.001, p = 0.056).These findings suggest that annual income may act as a negative moderator in the relationship between social status and well-being; in other words, as income rises, the positive impact of social status on well-being tends to diminish.In other words, among lower-income groups, the increase in well-being resulting from a rise in social status is more pronounced, whereas among higher-income groups, the same degree of social advancement has a relatively limited effect on enhancing well-being. Table 3 result Variables (1) (2) (3) (4) Full sample (Main) Full sample (Interaction) Rural subsample Urban subsample Main Variables​ Subjective social status 0.132 *** 0.129 *** 0.162 *** 0.152 *** (0.035) (0.035) (0.056) (0.052) Log annual income 0.040 *** 0.038 ** 0.041 * 0.004 (0.015) (0.015) (0.024) (0.022) Subjective social status × Log annual income -0.026 * 0.019 -0.057 *** (0.014) (0.025) (0.017) Control Variables​ Age -0.147 -0.133 0.003 -0.049 (0.158) (0.158) (0.023) (0.159) Gender (male = 1) -0.358 -0.354 0.020 -0.900 (0.576) (0.575) (0.861) (0.765) Years of education -0.001 0.001 -0.014 0.041 * (0.015) (0.015) (0.026) (0.022) Neighborhood trust 0.064 *** 0.063 *** 0.044 0.073 *** (0.016) (0.016) (0.029) (0.022) Job type (Ref: Self-employed/Informal) Employee -0.057 -0.046 -0.029 0.047 (0.083) (0.083) (0.120) (0.132) Urban residence (Ref: Rural) -0.031 -0.032 (0.075) (0.074) Year Fixed Effects yes yes yes yes Constant 3.987 3.565 -0.254 1.126 (4.386) (4.383) (0.950) (4.282) Observations 1489 1489 711 778 Number of individuals 806.000 806.000 445.000 476.000 Within R-squared 0.059 0.064 0.057 0.130 Note: Cluster-robust standard errors are in parentheses. Significance levels: *p < 0.10,p < 0.05, *p < 0.01.​ All models are individual fixed-effects models. The reference category for job type is Self-employed/Informal. The variable Urban residenceis omitted in the rural and urban subsample models. Year dummy variables are included but coefficients are not shown for brevity.** To investigate the potential heterogeneity in the moderating effect of income, we conducted separate regression analyses for rural and urban residents. Model 3 examines the moderating effect of income in the rural subsample.The coefficient for subjective social status was 0.162 (p < 0.01). The interaction term between social status and income had a positive coefficient, but was not statistically significant (β = 0.019, p = 0.450).This suggests that, in rural areas, the positive impact of subjective social status on well-being is robust and is not significantly moderated by individual income levels. Model 4 examines the moderating effect of income in the urban subsample. In contrast, the results for the urban sample reveal a different pattern.Although the main effect of social status remained significantly positive (β = 0.152, p < 0.01), the interaction coefficient was negative, larger in magnitude, and highly significant (β= −0.057, p < 0.01).This suggests that, in urban areas, annual income exerts a significant negative moderating effect. Specifically, compared with low-income urban residents, high-income urban residents derive significantly less of a boost to their sense of well-being from an improvement in their perceived social status. To rigorously test whether the urban-rural differences in the aforementioned moderating effects are statistically significant within a single model framework, we estimated a fixed-effects model incorporating a triple interaction term of ‘subjective social status × annual income × urban-rural’ (see Table 4 ). Table 4 Triple Interaction Model Results Variables (1)Composite well-being index Main Effects​ Subjective social status (centered) 0.161***(0.045) Log annual income (centered) 0.045**(0.019) Urban residence (Ref: Rural) -0.031 (0.074) Two-way Interactions​ Subjective social status × Urban residence -0.070 (0.059) Log annual income × Urban residence -0.016 (0.026) Subjective social status × Log annual income 0.014 (0.022) Three-way Interaction​ Subjective social status × Log annual income × Urban residence -0.067 (0.029) Control Variables​ Age -0.109(0.158) Gender (male = 1) -0.319 (0.573) Years of education 0.001 (0.015) Neighborhood trust 0.063*** (0.016) Job type (Ref: Self-employed/Informal) Job type (Employee) -0.048 (0.083) Year Fixed Effects Yes Model Statistics​ Observations 1,489 Number of individuals (N_g) 806 Within R-squared (r2_w) 0.065 Note: Coefficients are reported with cluster-robust standard errors in parentheses. Significance levels: *p < 0.10,p < 0.05, *p < 0.01.​ Reference groups: The variable Urban residenceis a dummy (1 = Urban, 0 = Rural). The rural category is the reference group for all interaction terms involving residence. Dummy variables for survey years (2014–2022) are included; 2012 is the reference year. Coefficients for year dummies are omitted for brevity. The results show that, after controlling for complex interactions, the positive main effects of subjective social status (β = 0.161, p < 0.01) and annual income (β = 0.045, p < 0.05) on well-being remain highly significant.None of the coefficients for the interaction terms were significant; there was no difference between urban and rural areas in terms of the ‘direct effect of social status on well-being’ and the ‘direct effect of income on well-being’.It is worth noting that the coefficient for the three-way interaction term ‘subjective social status × annual income × urban/rural’ is − 0.067 and is statistically significant at the 5% level (p < 0.05), indicating that the moderating effect of income differs significantly between urban and rural areas.The fact that the moderating effect was not significant in the rural sample but was significantly negative in the urban sample further supports Hypothesis H2, namely that the attenuating moderating effect of income is primarily observed in urban areas. To illustrate the direction and magnitude of this moderating effect, we have calculated the marginal effects of social status across different income levels for both rural and urban settings, as shown in Table 5 : Table 5 Average Marginal Effects of Subjective Social Status on Well-Being Condition (Income × Residence) Marginal Effect Std. Err. z-value p-value 95% CI Income = -1, Rural 0.146 0.051 2.89 0.004 [0.047, 0.246] Income = -1, Urban 0.143 0.047 3.02 0.003 [0.050, 0.236] Income = 0, Rural 0.161 0.045 3.55 0.000 [0.072, 0.249] Income = 0, Urban 0.091 0.046 1.99 0.046 [0.001, 0.180] Income = 1, Rural 0.175 0.050 3.47 0.001 [0.076, 0.274] Income = 1, Urban 0.038 0.050 0.76 0.446 [-0.060, 0.136] In the rural sample, social status had a significant positive effect on well-being regardless of income level (all p < 0.05). In the urban sample, however, when income levels were high (Income = 1), the effect of social status became non-significant (p = 0.446).This further corroborates the findings of the triple interaction model, namely that the moderating effect of income is primarily observed in urban areas. Note Error bars represent 95% confidence intervals. The left panel (Rural Sample) shows stable positive effects across income levels, while the right panel (Urban Sample) shows a clear decreasing trend, illustrating the significant negative moderating role of income in urban areas only. Figure 1 Conditional marginal effects of subjective social status on well-being at different levels of income, stratified by urban-rural residence. As shown in Fig. 1, there are significant differences in the pattern of marginal effects between urban and rural samples, as evidenced by variations in the nature and strength of the moderating effect depending on the type of residence; this provides direct evidence for the core hypothesis that ‘the moderating effect of income exhibits urban-rural heterogeneity’.In the rural sample (left-hand figure), the line representing the marginal effect remains largely flat across different income levels, with point estimates stabilising between 0.15 and 0.18. Within the rural social structure, the increase in well-being resulting from an improvement in subjective social status is robust and is not significantly moderated by the level of an individual’s economic resources. In the urban sample (see figure on the right), the marginal effect shows a clear downward trend. As income levels rise, the effect size falls from 0.143 (income = -1 SD) to 0.091 (income = 0), and eventually drops to an insignificant 0.038 (p = 0.446) at higher income levels (+ 1 SD).The data in Table 5 confirm that the effect is significantly positive only at low and average income levels; at high income levels, the 95% confidence interval straddles zero, revealing that, for urban residents, an increase in economic income significantly weakens the positive impact of social status on well-being. Discussion Drawing on panel data from the five waves of the China Family Panel Study (2014–2022), this study employs a fixed-effects model to systematically examine the impact of migrants’ perceived social status on their well-being, with a particular focus on the moderating role of personal income and urban-rural differences. Perceived social status and subjective well-being among migrants After effectively controlling for individual heterogeneity that does not vary over time, this study found that subjective social status has a significant and robust positive effect on the subjective well-being of migrants.Fixed-effects models reveal that, even for the same individual, a sense of well-being increases as their self-perceived social status rises over time.This finding is consistent with classical social comparison theory, which posits that individuals assess their own circumstances by comparing themselves with others, thereby influencing their subjective experience [ ] .For those who have moved to a new place of residence, the relocation process is often accompanied by a breakdown of existing social networks and challenges in establishing a new sense of identity; the way individuals perceive their relative standing in their new environment is a key source of social respect, psychological security and a sense of belonging. The socio-cultural context of the Chinese society in which the study’s sample is situated reinforces this mechanism.Influenced by traditional Confucian thought and a collectivist culture, Chinese society has always placed great emphasis on social order, social courtesy and face, and networks of personal connections. An individual’s social status is not only determined by economic resources, but is also closely linked to the prestige, respect and trust they command within their family, neighbourhood and community.This cultural context may have amplified the symbolic significance and practical impact of perceived social status on the psychological well-being of migrants.When a person feels they have a high ‘status’ within a new community, this is not merely a sense of psychological superiority; it is more likely to signify a more robust local support network, less feelings of exclusion, and stronger expectations of social integration. [ ] An Analysis of the Regulatory Role of Economic Income Income not only has a direct impact on well-being, but, more importantly, it moderates the relationship between social status and well-being.The full-sample analysis indicates that, as income rises, the positive impact of social status on well-being tends to diminish; the interaction coefficient is negative and approaches the level of significance (interaction β= −0.026, p = 0.056).For migrants, once their financial resources have reached a certain level, the additional happiness derived from an improvement in social status begins to diminish. We believe that an improvement in social status often leads to greater social acceptance, less discrimination based on identity, and a stronger sense of self-worth, all of which can significantly enhance well-being.However, once an individual’s income is sufficient to meet their material security and basic developmental needs, the psychological benefits associated with social status—such as a sense of respect and social recognition—tend to diminish.Income plays a functional ‘substitute’ role here, partially compensating for the psychological security provided by social status. Urban-rural heterogeneity in the income-adjusting effect Further research has revealed that the moderating effect of income on the relationship between social status and well-being exhibits significant urban-rural heterogeneity.This conclusion has been corroborated by the data in two ways. Sub-sample regression analysis shows that the moderating effect of income is significantly negative only in the urban sub-sample, whereas it is not significant in the rural sub-sample. Research suggests that the fundamental differences in urban and rural social structures have shaped this heterogeneity.In urban areas, high mobility has created a diverse and competitive environment. Individuals have a wide range of avenues for self-fulfilment, and the frameworks for social comparison have become more complex.High incomes provide urban residents with a wide range of material choices, abundant leisure activities and diverse social opportunities; to some extent, this may alleviate their psychological craving for and reliance on traditional status symbols such as professional prestige and community identity, thereby causing the psychological rewards derived from social status to diminish as income rises.This demonstrates that, in urban areas, an individual’s economic income has the potential to influence and even replace their social capital. In rural areas, social networks in China’s countryside are even more tightly knit, based on kinship and geographical ties, and traditional notions of reputation and face continue to exert a profound influence.A higher social status is not merely a subjective psychological perception; it is also closely linked to tangible local authority, family prestige and access to mutual support networks. These implicit resources, deeply embedded in local social relationships, cannot be fully replaced by monetary income alone.Consequently, regardless of an individual’s economic circumstances, higher social status implies access to more reliable social support and a more respected local identity, thereby exerting a stable and widespread positive influence on well-being. The differences in the moderating effect of economic income in rural areas suggest that the ‘face’ value inherent in rural social status is of irreplaceable importance to individual well-being. Strengths and limitations The study utilises panel data from five waves of the China Family Panel Study (2014–2022) and employs a fixed-effects model for analysis. This approach effectively controls for individual heterogeneity that does not vary over time, thereby identifying the relationship between subjective social status and well-being, as well as its moderating mechanisms.The study focuses in particular on ‘migrant residents’, a group whose numbers are growing rapidly amid the process of rapid urbanisation. Through the use of a triple interaction model and marginal effect analysis across subsamples, the analysis provides an in-depth examination of the urban-rural heterogeneity in the moderating role of economic income, thereby offering empirical evidence from China’s transitioning society to support relevant theories. However, this paper also has certain limitations that need to be addressed in future research.Firstly, the definition of ‘migrant residents’ is based primarily on whether they have relocated across district or county boundaries; it does not distinguish more precisely between the reasons for migration, the distance travelled, or the duration of the move. These factors may influence their social integration and psychological experience, and more in-depth heterogeneity analyses could be conducted in the future.Secondly, although significant heterogeneity has been identified between urban and rural areas, there remain substantial differences within these categories; for example, the social structures and cultural norms may vary between cities of different tiers and between rural areas in different regions.Thirdly, given the limited sample size, the study was unable to conduct a more in-depth analysis or discussion of different types of migrant populations. In future, natural experiments or more refined longitudinal data designs could be employed to further validate the causal relationships involved. Conclusions Drawing on five years of panel data from the China Family Panel Study, this study employs a fixed-effects model to systematically examine the mechanisms through which migrants’ subjective social class identity influences their well-being, whilst also exploring the moderating role of economic income and its urban-rural heterogeneity.The main findings are as follows:(1) Subjective social status has a robust positive effect on the well-being of migrants. Even when controlling for individual-level characteristics that remain constant, individuals report significantly higher levels of well-being when they perceive an improvement in their social status within their new environment. This suggests that, for those who have relocated, a positive subjective social status serves as a crucial foundation for re-establishing a sense of social belonging and achieving psychological security.(2) Economic income plays a significant moderating role in the relationship between social status and well-being. As personal income rises, the increase in well-being resulting from higher social status tends to diminish; that is, once economic resources are sufficient to meet basic needs, the additional psychological rewards derived from social status diminish relatively, as economic resources assume, to a certain extent, the psychological security function traditionally associated with social status.(3) The moderating effect of economic income exhibits marked urban-rural heterogeneity. The moderating effect of economic income is significant only in the urban sample, whereas it is not evident in the rural sample. The findings of the aforementioned study indicate that, in the face of a large-scale mobile and migrant population, public policy must go beyond the narrow focus on economic support and physical resettlement, and should instead prioritise their social and psychological integration.In urban areas, attention should be paid to ensuring that high-income migrants can realise their potential in diverse ways; through community-building and the fostering of cultural identity, we can help bridge the psychological gap that may arise from the diminishing effects of their social status.In rural areas, policy efforts should place greater emphasis on enhancing migrants’ sense of identification with and belonging to their new environment through rural revitalisation and cultural development; this is likely to be more effective in boosting the subjective well-being of rural migrants than mere financial subsidies. Abbreviations CFPS China Family Panel Studies Declarations Acknowledgements We extend our sincere gratitude to the institutions responsible for the collection and dissemination of data from the China Family Panel Studies (CFPS), namely the China Social Survey Centre at Peking University and the Survey Research Centre at the University of Michigan, USA. We also acknowledge the invaluable contributions made to this research by all respondents, local authorities, and community organisations. Authors' contributions DY proposed the research concept. All authors participated in the study design. DY was responsible for data analysis and drafted the initial manuscript. ZWQ provided literature review support. All authors jointly interpreted the results and rigorously revised the manuscript. All authors read and approved the final version, agreeing to take full responsibility for the integrity and accuracy of the research. Funding This study was supported by the Humanities and Social Sciences Youth Foundation, Ministry of Education of the People's Republic of China (Project No. 22YJC810001),and National Social Sciences Found Youth Project (Project No. 23CZZ013). Availability of data and materials The data supporting the findings of this study are available from [ China Household Panel Survey]. However, as these data are licensed for use in this research, their availability is restricted and therefore not publicly accessible.However, the data may be accessed by authors upon reasonable request and with the permission of the [Centre for Social Science Surveys, Peking University]. Ethics approval and consent to participate This study utilised publicly available secondary data from the China Family Panel Studies (CFPS). Ethical approval for the collection of the original CFPS data was granted by the Institute of Social Science Survey (ISSS) at Peking University. Written informed consent was obtained from all participants by the CFPS research team prior to data collection. This study constitutes a secondary analysis of de-identified data and therefore does not require additional ethical approval. All research procedures adhere to the relevant principles of the Declaration of Helsinki. Consent for publication Not applicable Competing interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. References Oishi S. The psychology of residential mobility: implications for the self, social relationships, and well-being. Perspect Psychol Sci . 2010;5(1):5–21. Berry JW. Immigration, acculturation, and adaptation. Appl Psychol . 1997;46:5–34. doi:10.1111/j.1464-0597.1997.tb01087.x. Clark AE, Frijters P, Shields MA. Relative income, happiness, and utility: an explanation for the Easterlin paradox and other puzzles. J Econ Lit . 2008;46(1):95–144. doi:10.1257/jel.46.1.95. Festinger L. A theory of social comparison processes. Hum Relat . 1954;7(2):117–40. Euteneuer F. Subjective social status and health. Curr Opin Psychiatry . 2014;27(5):337–43. doi:10.1097/YCO.0000000000000083. Haught HM, Rose J, Geers A, Brown JA. Subjective social status and well-being: the role of referent abstraction. J Soc Psychol . 2015;155(4):356–69. doi:10.1080/00224545.2015.1015476. Adler NE, Epel ES, Castellazzo G, Ickovics JR. Relationship of subjective and objective social status with psychological and physiological functioning: preliminary data in healthy white women. Health Psychol . 2000;19(6):586–92. doi:10.1037/0278-6133.19.6.586. Berry JW. Immigration, acculturation, and adaptation. Appl Psychol . 1997;46:5–34. doi:10.1111/j.1464-0597.1997.tb01087.x. Graham C, Felton A. Inequality and happiness: insights from Latin America. J Econ Inequal . 2006;4:107–22. doi:10.1007/s10888-005-9009-1. Easterlin RA. Income and happiness: towards a unified theory. Econ J . 2001;111(473):465–84. http://www.jstor.org/stable/2667943. Accessed 15 Jan 2026. Kahneman D, Deaton A. High income improves evaluation of life but not emotional well-being. Proc Natl Acad Sci U S A . 2010;107(38):16489–93. doi:10.1073/pnas.1011492107. Kahneman D, Deaton A. High income improves evaluation of life but not emotional well-being. Proc Natl Acad Sci U S A . 2010;107(38):16489–93. doi:10.1073/pnas.1011492107. Clark AE, Frijters P, Shields MA. Relative income, happiness, and utility: an explanation for the Easterlin paradox and other puzzles. J Econ Lit . 2008;46(1):95–144. doi:10.1257/jel.46.1.95. Knight J, Gunatilaka R. Great expectations? The subjective well-being of rural-urban migrants in China. World Dev. 2010;38(1):113–24. National Bureau of Statistics of China. Tabulation on the 2020 Population Census of the People’s Republic of China . Beijing: National Bureau of Statistics of China; 2021. http://www.stats.gov.cn/sj/pcsj/rkpc/d7c/202111/P020211126523667366751.pdf. Accessed 15 Jan 2026. Fei X. From the Soil: The Foundations of Chinese Society . Shanghai: Shanghai People’s Publishing House; 2006. Xie Y, Hu JW, Zhang CN. China Family Panel Studies: Concept and Practice. Society . 2014;34(02):1-32. https://doi.org/10.15992/j.cnki.31-1123/c.2014.02.003. Diener, E. (1984). Subjective well-being. Psychological Bulletin , 95(3), 542–575. https://doi.org/10.1037/0033-2909.95.3.542 Cheung F, Lucas RE. Assessing the validity of single-item life satisfaction measures: results from three large samples. Qual Life Res . 2014 Dec;23(10):2809-18. doi: 10.1007/s11136-014-0726-4. Epub 2014 Jun 3. PMID: 24890827; PMCID: PMC4221492. Jackman MR, Jackman RW. An interpretation of the relation between objective and subjective social status. Am Sociol Rev . 1973;38:569–82. Adler NE, Epel ES, Castellazzo G, Ickovics JR. Relationship of subjective and objective social status with psychological and physiological functioning: preliminary data in healthy white women. Health Psychol . 2000;19(6):586–92. doi:10.1037/0278-6133.19.6.586. Batz C, Tay L. Gender differences in subjective wellbeing. In: Diener E, Oishi S, Tay L, editors. Handbook of wellbeing . Salt Lake City (UT): DEF Publishers; 2018. Wadsworth T. Marriage and subjective wellbeing: how and why context matters. Soc Indic Res . 2016;126:1025–1048. doi:10.1007/s11205-015-0930-9. Bonanomi A, Rosina A. Employment status and wellbeing: a longitudinal study on young Italian people. Soc Indic Res . 2020;161:1–18. doi:10.1007/s11205-020-02376-x. Festinger L. A theory of social comparison processes. Hum Relat . 1954;7(2):117–40. Lever JP. Poverty, stressful life events, and coping strategies. Span J Psychol . 2008;11:228–249. Additional Declarations No competing interests reported. Supplementary Files Tableurbanruralheterogeneity.rtf tripleinteractionfull.rtf Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 05 May, 2026 Editor assigned by journal 05 May, 2026 Editor invited by journal 03 May, 2026 Submission checks completed at journal 03 May, 2026 First submitted to journal 03 May, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9559814","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":636947913,"identity":"ef556020-ee5d-45e4-bc3c-82f424ea67c0","order_by":0,"name":"Yu Ding","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYDCCw2DSBspjI15LGilaDiBpJE4L33Hew695287L88/uMWD4UHaYgX92A34tkof50qx5224bzrhzxoBxxrnDDBJ3DuDXYnCYx8wYqCXBQCLHgJm37TCDgUQCUVrOQbT8JVKL8WPetgMQLYzEaJEE2sI451yy4YwbaQUHe86l80jcIKCF7/wZ4w9vyuzk+Wckb3zwo8xajn8GAS1AwCbFA2UdAGIePCrhgPnjD2KUjYJRMApGwcgFAKIMP9OgNhVUAAAAAElFTkSuQmCC","orcid":"","institution":"Central China Normal University","correspondingAuthor":true,"prefix":"","firstName":"Yu","middleName":"","lastName":"Ding","suffix":""},{"id":636947914,"identity":"c6993190-96dd-4b58-a8c6-a8f2aa056c1d","order_by":1,"name":"Wenqing Zhang","email":"","orcid":"","institution":"Central China Normal University","correspondingAuthor":false,"prefix":"","firstName":"Wenqing","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2026-04-29 03:25:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9559814/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9559814/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109296350,"identity":"a2277eb3-4bae-4e0c-b759-aa425b489cdb","added_by":"auto","created_at":"2026-05-15 08:46:35","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":248240,"visible":true,"origin":"","legend":"\u003cp\u003eNote: Error bars represent 95% confidence intervals. The left panel (Rural Sample) shows stable positive effects across income levels, while the right panel (Urban Sample) shows a clear decreasing trend, illustrating the significant negative moderating role of income in urban areas only.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 1:\u003c/strong\u003e Conditional marginal effects of subjective social status on well-being at different levels of income, stratified by urban-rural residence.\u003c/p\u003e","description":"","filename":"Figure1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9559814/v1/f7e792b5e8b1054c5488ad7c.jpeg"},{"id":109297337,"identity":"40b435b6-d751-49a7-bd8a-bc52048cbeb5","added_by":"auto","created_at":"2026-05-15 08:56:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":450435,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9559814/v1/aad737f1-f17d-4d0e-9be4-6395f1a02824.pdf"},{"id":109281881,"identity":"a38265b6-4254-4af4-8dfb-cf2c9bbecbb9","added_by":"auto","created_at":"2026-05-14 18:22:37","extension":"rtf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":13079,"visible":true,"origin":"","legend":"","description":"","filename":"Tableurbanruralheterogeneity.rtf","url":"https://assets-eu.researchsquare.com/files/rs-9559814/v1/81d08986e1c1e0da8f03631f.rtf"},{"id":109296608,"identity":"9d3a00cf-8067-45c1-b2b2-d5fd733ae78b","added_by":"auto","created_at":"2026-05-15 08:48:31","extension":"rtf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":8822,"visible":true,"origin":"","legend":"","description":"","filename":"tripleinteractionfull.rtf","url":"https://assets-eu.researchsquare.com/files/rs-9559814/v1/550902f78774336d9527a56b.rtf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Home is where the heart is?The Impact of perceived social status on Residents' Subjective Well-Being——The moderating role of income and its urban-rural heterogeneity","fulltext":[{"header":"Background","content":"\u003cp\u003eWith the increasing mobility of the population, relocation has become one of the defining features of contemporary society; it is not merely a physical change of living space, but is also accompanied by the breakdown and reconstruction of social networks, the realignment of identity, and the unfolding of psychological adaptation processes.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn1\" id=\"#FNLinkFn1\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003eMigration disrupts an individual\u0026rsquo;s social networks and reference groups in their society of origin, altering their existing social frame of reference and basis for social comparison; as a result, the individual must reassess their circumstances and social standing whilst adapting to their new environment.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn2\" id=\"#FNLinkFn2\"\u003e\u003c/a\u003e\u003csup\u003e][\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn3\" id=\"#FNLinkFn3\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAccording to social comparison theory, when objective, non-social means of assessment are difficult to apply, individuals often assess their own abilities and circumstances by comparing themselves with others\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn4\" id=\"#FNLinkFn4\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003e.In this process, subjective social status becomes a key factor in individuals\u0026rsquo; assessment of their own circumstances and has a significant impact on their subjective well-being.Unlike socio-economic status, which is based on objective indicators such as income and education, subjective social status emphasises an individual\u0026rsquo;s perception of their position within the social hierarchy and reflects the social status as perceived by the individual.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn5\" id=\"#FNLinkFn5\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003eAn individual\u0026rsquo;s perception of their social position can enhance their sense of well-being through mechanisms such as self-identity, social comparison and the acquisition of psychological resources.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn6\" id=\"#FNLinkFn6\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003eFurthermore, compared with residents living in a stable social environment, migrants face greater uncertainty as they adapt to their new surroundings, and their psychological adjustment process is more complex.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn7\" id=\"#FNLinkFn7\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003eTheir sense of well-being is more susceptible to the influence of their subjective social status; that is, an individual\u0026rsquo;s subjective perception of their own social position plays a more critical role in the psychological adjustment process.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn8\" id=\"#FNLinkFn8\"\u003e\u003c/a\u003e\u003csup\u003e][\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn9\" id=\"#FNLinkFn9\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe economic resources available to individuals, particularly their income levels, play a fundamental role in shaping their subjective sense of well-being.People\u0026rsquo;s basic material desires are quite similar; consequently, at any given point in time, individuals with higher incomes tend to be happier.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn10\" id=\"#FNLinkFn10\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003eHowever, this effect is not linear; once income reaches a certain level, the marginal benefit diminishes significantly. Low income is significantly associated with lower life satisfaction and poorer emotional well-being, whereas high income, whilst improving life satisfaction, has a limited impact on emotional well-being.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn11\" id=\"#FNLinkFn11\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003eConsequently, an individual\u0026rsquo;s subjective sense of well-being is not simply influenced by income levels, but depends significantly on the process of social comparison. Income levels influence well-being indirectly by affecting an individual\u0026rsquo;s perception of their subjective social status.Previous research has shown that subjective social status\u0026mdash;defined as an individual\u0026rsquo;s overall assessment of their socio-economic position\u0026mdash;is often a more effective predictor of health and well-being outcomes than objective status, whilst income level is one of the key factors determining an individual\u0026rsquo;s perception of their socio-economic status.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn12\" id=\"#FNLinkFn12\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003eIndividuals derive utility from comparing their income with that of others (social comparison), which profoundly influences the sense of status and happiness they derive from their income.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn13\" id=\"#FNLinkFn13\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003eWhen individuals of different income levels engage in social comparison, the reference groups they choose and the criteria they apply may vary, resulting in differences in the impact of subjective social status on well-being across different income groups. Consequently, income level, as a key economic resource variable, acts as a moderator in the relationship between subjective social status and subjective well-being.\u003c/p\u003e \u003cp\u003eFurthermore, this moderating effect may also be influenced by differences in social contexts. Research has found that families who have migrated from rural to urban areas in China report lower levels of well-being than rural families.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn14\" id=\"#FNLinkFn14\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003eIn other words, given the same income or resources, social reference frameworks and life circumstances may have a significant impact on the experience of well-being.\u003c/p\u003e \u003cp\u003eOn this basis, this paper proposes the following research hypotheses:\u003c/p\u003e \u003cp\u003eH1: Subjective social status has a significant positive effect on the subjective well-being of migrants. In other words, the higher an individual\u0026rsquo;s perceived social status, the higher their reported level of subjective well-being.\u003c/p\u003e \u003cp\u003eH2: Annual income acts as a moderator in the relationship between subjective social status and subjective well-being, and this moderating effect varies depending on whether the respondent lives in an urban or rural area.\u003c/p\u003e \u003cp\u003eH2a: In urban areas, annual income acts as a negative moderator of the relationship between social status and well-being; that is, as income rises, the return on well-being from social status diminishes.\u003c/p\u003e \u003cp\u003eH2b: In rural areas, the aforementioned moderating effect of annual income is not significant, and the positive impact of social status on well-being remains relatively stable across different income groups.\u003c/p\u003e \u003cp\u003eThis study presents a new examination of the relationship between residents\u0026rsquo; perceived social status, income levels and subjective well-being. Against the backdrop of rapid urbanisation, China is experiencing large-scale and frequent population movements and changes in residence; this mobility has a profound impact on the social structure of cities and the daily lives of residents. By 2020, the size of China\u0026rsquo;s migrant population had reached nearly 376\u0026nbsp;million, accounting for approximately 26.04% of the total population\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn15\" id=\"#FNLinkFn15\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003e.At the same time, in China\u0026mdash;particularly within a social structure based on kinship and geographical ties\u0026mdash;an individual\u0026rsquo;s perception of their social status is heavily dependent on their social network\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn16\" id=\"#FNLinkFn16\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003e.A change of residence has a more direct impact on the restructuring of this framework, as well as on one\u0026rsquo;s perceived social status and sense of well-being.Consequently, compared with long-term residents, migrants rely more heavily on their subjective assessment of their circumstances to establish their social position within a new social environment, and their subjective perceptions may have a more pronounced impact on their sense of well-being.Existing research has largely been conducted on the general population, overlooking the specific mechanisms underlying the role of subjective social status among migrant groups in the context of residential mobility, and lacking a systematic examination of the moderating role of income in the relationship between subjective social status and well-being. Our analysis of sample data from relevant regions will help address the new public health challenges posed by rapid urbanisation.\u003c/p\u003e \u003cp\u003eThis study is not only of empirical significance but also makes a valuable contribution to public policy design.By identifying the mechanisms through which the subjective social status of migrant residents influences their sense of well-being, and by revealing the moderating role of income levels in this process, this paper argues that relying solely on income growth is unlikely to sustainably improve the subjective well-being of the migrant population; perceptions of social status and psychological adaptation are equally crucial factors.Consequently, in policy implementation, whilst ensuring basic economic conditions are met, greater emphasis should be placed on the social integration of migrant residents. By promoting community participation and strengthening psychological identification, their sense of belonging and identification with their new environment can be enhanced, thereby bringing about a sustained improvement in their subjective well-being.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source\u003c/h2\u003e \u003cp\u003eThe data used in this paper is drawn from the China Family Panel Studies (CFPS). In 2010, the CFPS conducted a baseline survey across 25 provinces nationwide, ultimately completing interviews with 14,960 households and 42,590 individuals; since then, surveys have been conducted every two years.The data was collected and published through a collaboration between the China Family Panel Studies (CFPS) at Peking University and the Survey Research Centre at the University of Michigan, amongst other institutions. In terms of the levels of data collection, the CFPS has gathered data at three levels\u0026mdash;individual, household and community\u0026mdash;covering a wide range of topics including family relationships, migration, health and perceptions of social class.In accordance with the data and variable requirements specified in this paper, the main variables were drawn from five rounds of data covering the period 2014\u0026ndash;2022. The data were sourced from 25 provinces, municipalities and autonomous regions, and more than 400 administrative villages. After excluding invalid samples, only those with observations from two or more periods were retained, resulting in a final sample of 1,762 valid cases.The variables used in this study are all derived from the China Family Panel Studies (CFPS) questionnaire, which includes several standardised psychological scales covering three main areas: personal traits, parent-child relationships and subjective attitudes.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn17\" id=\"#FNLinkFn17\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003e Most of these scales are based on established international instruments, which have been adapted or developed specifically for the Chinese context.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDependent variable:Subjective well-being\u003c/h2\u003e \u003cp\u003eSubjective well-being refers to an individual\u0026rsquo;s overall assessment of their life, experiences and psychological state. In addition to objective factors such as education, marital status, employment and household registration, the CFPS (2022) adult questionnaire includes specific questions designed to measure respondents\u0026rsquo; life satisfaction and subjective well-being.Previous research has shown that subjective well-being (SWB) comprises three core components: life satisfaction, positive emotions and negative emotions.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn18\" id=\"#FNLinkFn18\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003e In large-scale social surveys, using such items to assess well-being as a whole is a common and effective approach.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn19\" id=\"#FNLinkFn19\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003eIn order to measure respondents\u0026rsquo; subjective well-being more accurately and ensure that the results are more robust and reliable, this paper has selected two questions from the questionnaire to serve as indicators of subjective well-being.Question 1 was measured using a 0\u0026ndash;10-point self-report scale: \u0026lsquo;How happy do you feel?\u0026rsquo;; Question 2 was measured using a 1\u0026ndash;5-point Likert scale: \u0026lsquo;On a scale of 1 to 5, how satisfied are you with your life?\u0026rsquo;.Values falling outside the range of the two variables were treated as missing values. To eliminate differences in units, we standardised both variables using Z-scores, generating standardised variables with a mean of 0 and a standard deviation of 1. On this basis, we calculated the arithmetic mean of the two standardised variables to construct a \u0026lsquo;composite well-being index\u0026rsquo;, thereby laying a solid measurement foundation for rigorous subsequent testing of the relationship between subjective social status and subjective well-being.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eKey independent variable: subjective social status\u003c/h3\u003e\n\u003cp\u003eThe study adopted the definition of class identity proposed by Jackman and his wife (1973), namely, \u0026lsquo;an individual\u0026rsquo;s perception of their position within the social class structure\u0026rsquo;.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn20\" id=\"#FNLinkFn20\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003eExisting research typically measures this variable through individuals\u0026rsquo; subjective assessments of their own social status; a common method involves the use of a \u0026lsquo;social ladder\u0026rsquo; or self-rated ranking.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn21\" id=\"#FNLinkFn21\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003eThe dependent variable in this study is subjective social class identity, which was measured using a 5-point scale in all five rounds of the CFPS Adult Survey conducted between 2014 and 2022. The specific question asked was: \u0026lsquo;On a scale of 1 to 5, how would you rate your social status in this community?\u0026rsquo; A higher score indicates that the respondent perceives their social class status to be higher.\u003c/p\u003e\n\u003ch3\u003eAdjustment variable: annual income\u003c/h3\u003e\n\u003cp\u003eIn this study, annual income refers to the total income received by respondents during a specific year, including earned income, net business income, property income and transfer income; it serves as a key indicator for measuring an individual\u0026rsquo;s economic resources.The variable is derived from the CFPS adult questionnaire, specifically the question: \u0026lsquo;What was your total after-tax wage income from all jobs (main job\u0026thinsp;+\u0026thinsp;other jobs) over the past 12 months?\u0026rsquo; In order to accurately assess its moderating effect within the model, to bring its distribution closer to a normal distribution to satisfy the model\u0026rsquo;s assumptions, and to minimise the potential impact of outliers on the estimates, this study truncated the income data at the top and bottom 1%. The truncated income values were then added by 1 and transformed using the natural logarithm; the resulting continuous variable is such that higher values indicate greater absolute economic resources among respondents.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCovariates\u003c/h2\u003e \u003cp\u003eThis study utilised common demographic variables as control variables, including gender, age, marital status, neighbourhood trust and experience of full-time employment.Neighbourly trust, as a key indicator of social capital, has been extensively examined by researchers for its impact on subjective well-being and is considered an essential control variable; numerous studies have indicated that gender and marital status exert a certain influence on residents\u0026rsquo; subjective well-being[\u003ca class=\"FNLink\" href=\"#Fn22\" id=\"#FNLinkFn22\"\u003e\u003c/a\u003e].Married people report higher levels of subjective well-being than those who are single, separated, divorced or widowed[\u003ca class=\"FNLink\" href=\"#Fn23\" id=\"#FNLinkFn23\"\u003e\u003c/a\u003e].Furthermore, numerous studies have shown that job stability has a significant impact on an individual\u0026rsquo;s subjective well-being.[\u003ca class=\"FNLink\" href=\"#Fn24\" id=\"#FNLinkFn24\"\u003e\u003c/a\u003e]All of the above variables have been included as control variables in this paper.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThis study utilises Stata 14 for data analysis and employs a stratified, stepwise statistical analysis strategy. It aims to systematically examine the impact of subjective social status on residents\u0026rsquo; subjective well-being and to investigate the moderating role of annual income in this relationship.\u003c/p\u003e \u003cp\u003eGiven that the dependent variable in this study, the \u0026lsquo;Comprehensive Well-being Index\u0026rsquo;, is a continuous variable, a multiple linear regression model was employed.Given the panel structure of the data, we have opted for a fixed-effects panel regression model in order to account for individual heterogeneity that does not vary over time.The Hausman test formally confirmed that the fixed-effects model is superior to the random-effects model.To address potential issues of heteroscedasticity and within-subject autocorrelation, all models report robust standard errors adjusted for clustering at the individual level.In particular, Model 1 is a main effects model, which regresses subjective well-being against subjective social status, annual income and a series of theoretically relevant control variables to establish a baseline relationship.\u003c/p\u003e \u003cp\u003eWellbeing_it\u0026thinsp;=\u0026thinsp;β\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;β\u003csub\u003e1\u003c/sub\u003eStatus_it\u0026thinsp;+\u0026thinsp;β\u003csub\u003e2\u003c/sub\u003eIncome_it\u0026thinsp;+\u0026thinsp;β\u003csub\u003e3\u003c/sub\u003eControls_it\u0026thinsp;+\u0026thinsp;λ_t\u0026thinsp;+\u0026thinsp;α_i + ϵ_it\u003c/p\u003e \u003cp\u003eModel 2 is an interaction model for continuous variables. To test the continuous moderating effect of annual income, an interaction term between subjective social status and annual income was added to Model 1.Use the testparm command to test the statistical significance of this interaction term, in order to determine whether the effect of social status on well-being varies linearly with income level, where α_i denotes the individual fixed effect.\u003c/p\u003e \u003cp\u003eWellbeing_it\u0026thinsp;=\u0026thinsp;β\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;β\u003csub\u003e1\u003c/sub\u003eStatus_it\u0026thinsp;+\u0026thinsp;β\u003csub\u003e2\u003c/sub\u003eIncome_it\u0026thinsp;+\u0026thinsp;β\u003csub\u003e3\u003c/sub\u003e(Status_it \u0026times; Income_it) + β\u003csub\u003e4\u003c/sub\u003eControls_it\u0026thinsp;+\u0026thinsp;λ_t\u0026thinsp;+\u0026thinsp;α_i + ϵ_it\u003c/p\u003e \u003cp\u003eTo test for the continuous moderating effect of age, an interaction term between age and residential mobility was introduced. By calculating the marginal effect of residential mobility, we analysed how the magnitude of the effect varies linearly with age.\u003c/p\u003e \u003cp\u003eWellbeing\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;β\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;β\u003csub\u003e1\u003c/sub\u003eAge\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;β\u003csub\u003e2\u003c/sub\u003eResidential\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;β\u003csub\u003e3\u003c/sub\u003e(Age\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u0026times;Residential\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e)+β\u003csub\u003e4\u003c/sub\u003eGender\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;β\u003csub\u003e5\u003c/sub\u003eMarriage\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;β\u003csub\u003e6\u003c/sub\u003eJob\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;β7Trust\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e+ϵ\u003csub\u003ei\u003c/sub\u003e\u003c/p\u003e \u003cp\u003eTo gain a deeper understanding of the significant interaction effects between continuous variables, we followed the analytical procedure recommended by Aiken and West.The average marginal effect of subjective social status on well-being was calculated at several key levels of annual income.The results are presented using marginal effects plots generated via Stata\u0026rsquo;s margins and marginsplot commands, clearly illustrating how the relationship between migrants\u0026rsquo; subjective social status and subjective well-being varies with changes in their level of economic resources.\u003c/p\u003e \u003cp\u003eThis paper describes continuous variables using the mean, standard deviation, maximum and minimum values, and categorical variables using categories and proportions.\u003c/p\u003e \u003cp\u003eResults were presented as odds ratios (ORs), 95% Confidence Interval (95% CI), and corresponding P values. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eMost of the variables used in this study are continuous, whilst some control variables are categorical. Among the 1,762 valid responses, some variables exhibited varying degrees of missing data due to non-response, non-applicable items and data cleaning.As shown in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the average age of respondents was 33.1 years, with 70.66% being male and 29.34% female.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics of quantitative variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuantitative variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObserved value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWell-being\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eedu_years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003etrust\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eln_income_w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esocial_status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics of qualitative variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003equalitative variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObserved value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSort\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003esort\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0/female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e29.34%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1/male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e70.66%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emarriage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1/married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.75%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2/others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e46.25%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ejob\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1/self employed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2/employed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e88.04%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eurban_rural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0/rural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48.36%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1/urban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e51.64%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the results of a regression analysis based on a fixed-effects panel model, which primarily examines the effects of subjective social status and annual income on residents\u0026rsquo; subjective well-being, and further analyses the urban-rural heterogeneity of the moderating effect of annual income.\u003c/p\u003e \u003cp\u003eModel 1 is a model of the main effect of migrants\u0026rsquo; perceived social status on subjective well-being. After controlling for other factors, perceived social status has a highly statistically significant positive effect on well-being.Specifically, for every one-unit increase in subjective social status, residents\u0026rsquo; overall well-being index rises significantly by an average of approximately 0.132 units(β\u0026thinsp;=\u0026thinsp;0.132, SE\u0026thinsp;=\u0026thinsp;0.035, t\u0026thinsp;=\u0026thinsp;3.80, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 95% CI [0.064, 0.200]).This finding supports the study\u0026rsquo;s main hypothesis, namely that the higher migrants rate their own social status, the greater their subjective well-being.\u003c/p\u003e \u003cp\u003eBuilding on Model 1, Model 2 introduces an interaction term between subjective social status and the logarithm of annual income to test whether annual income moderates the relationship between the two.After controlling for the interaction term, the positive main effects of subjective social status (β\u0026thinsp;=\u0026thinsp;0.129, 95% CI:0.060\u0026ndash;0.198, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and annual income (β\u0026thinsp;=\u0026thinsp;0.038, 95% CI:0.009\u0026ndash;0.067, p\u0026thinsp;=\u0026thinsp;0.011) on overall well-being remained significant. The interaction coefficient was negative and reached marginal significance (β=\u0026minus;0.026, 95% CI:\u0026minus;0.053\u0026ndash;0.001, p\u0026thinsp;=\u0026thinsp;0.056).These findings suggest that annual income may act as a negative moderator in the relationship between social status and well-being; in other words, as income rises, the positive impact of social status on well-being tends to diminish.In other words, among lower-income groups, the increase in well-being resulting from a rise in social status is more pronounced, whereas among higher-income groups, the same degree of social advancement has a relatively limited effect on enhancing well-being.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eresult\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFull sample\u003c/p\u003e \u003cp\u003e(Main)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFull sample\u003c/p\u003e \u003cp\u003e(Interaction)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRural subsample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUrban subsample\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMain Variables​\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSubjective social status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.132\u003c/b\u003e\u003csup\u003e\u003cb\u003e***\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.129\u003c/b\u003e\u003csup\u003e\u003cb\u003e***\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.162\u003c/b\u003e\u003csup\u003e\u003cb\u003e***\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.152\u003c/b\u003e\u003csup\u003e\u003cb\u003e***\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.056)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.052)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLog annual income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.040\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.038\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.041\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.024)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.022)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubjective social status \u0026times; Log annual income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.026\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.057\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.017)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl Variables​\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.158)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.158)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.159)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (male\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.900\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.576)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.575)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.861)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.765)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYears of education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.026)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.022)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeighborhood trust\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.064\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.063\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.073\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.029)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.022)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJob type (Ref: Self-employed/Informal)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.083)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.083)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.120)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.132)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban residence (Ref: Rural)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.075)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.074)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear Fixed Effects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.987\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.126\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(4.386)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(4.383)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.950)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4.282)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e711\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e778\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of individuals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e806.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e806.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e445.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e476.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWithin R-squared\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: Cluster-robust standard errors are in parentheses. Significance levels: *p\u0026thinsp;\u0026lt;\u0026thinsp;0.10,p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, *p\u0026thinsp;\u0026lt;\u0026thinsp;0.01.​\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAll models are individual fixed-effects models. The reference category for job type is Self-employed/Informal. The variable Urban residenceis omitted in the rural and urban subsample models. Year dummy variables are included but coefficients are not shown for brevity.**\u003c/p\u003e \u003cp\u003eTo investigate the potential heterogeneity in the moderating effect of income, we conducted separate regression analyses for rural and urban residents. Model 3 examines the moderating effect of income in the rural subsample.The coefficient for subjective social status was 0.162 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The interaction term between social status and income had a positive coefficient, but was not statistically significant (β\u0026thinsp;=\u0026thinsp;0.019, p\u0026thinsp;=\u0026thinsp;0.450).This suggests that, in rural areas, the positive impact of subjective social status on well-being is robust and is not significantly moderated by individual income levels.\u003c/p\u003e \u003cp\u003eModel 4 examines the moderating effect of income in the urban subsample. In contrast, the results for the urban sample reveal a different pattern.Although the main effect of social status remained significantly positive (β\u0026thinsp;=\u0026thinsp;0.152, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), the interaction coefficient was negative, larger in magnitude, and highly significant (β= \u0026minus;0.057, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).This suggests that, in urban areas, annual income exerts a significant negative moderating effect. Specifically, compared with low-income urban residents, high-income urban residents derive significantly less of a boost to their sense of well-being from an improvement in their perceived social status.\u003c/p\u003e \u003cp\u003eTo rigorously test whether the urban-rural differences in the aforementioned moderating effects are statistically significant within a single model framework, we estimated a fixed-effects model incorporating a triple interaction term of \u0026lsquo;subjective social status \u0026times; annual income \u0026times; urban-rural\u0026rsquo; (see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTriple Interaction Model Results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)Composite well-being index\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMain Effects​\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubjective social status (centered)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.161***(0.045)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLog annual income (centered)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.045**(0.019)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban residence (Ref: Rural)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.031 (0.074)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTwo-way Interactions​\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubjective social status \u0026times; Urban residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.070 (0.059)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLog annual income \u0026times; Urban residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.016 (0.026)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubjective social status \u0026times; Log annual income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.014 (0.022)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eThree-way Interaction​\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubjective social status \u0026times; Log annual income \u0026times; Urban residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.067 (0.029)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eControl Variables​\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.109(0.158)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender (male\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabc\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.319 (0.573)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYears of education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabd\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001 (0.015)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeighborhood trust\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabe\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.063*** (0.016)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eJob type (Ref: Self-employed/Informal)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJob type (Employee)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabf\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.048 (0.083)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear Fixed Effects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel Statistics​\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabg\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,489\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of individuals (N_g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabh\" border=\"1\"\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e806\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWithin R-squared (r2_w)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eNote: Coefficients are reported with cluster-robust standard errors in parentheses. Significance levels: *p\u0026thinsp;\u0026lt;\u0026thinsp;0.10,p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, *p\u0026thinsp;\u0026lt;\u0026thinsp;0.01.​\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eReference groups: The variable Urban residenceis a dummy (1\u0026thinsp;=\u0026thinsp;Urban, 0\u0026thinsp;=\u0026thinsp;Rural). The rural category is the reference group for all interaction terms involving residence. Dummy variables for survey years (2014\u0026ndash;2022) are included; 2012 is the reference year. Coefficients for year dummies are omitted for brevity.\u003c/p\u003e \u003cp\u003eThe results show that, after controlling for complex interactions, the positive main effects of subjective social status (β\u0026thinsp;=\u0026thinsp;0.161, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and annual income (β\u0026thinsp;=\u0026thinsp;0.045, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) on well-being remain highly significant.None of the coefficients for the interaction terms were significant; there was no difference between urban and rural areas in terms of the \u0026lsquo;direct effect of social status on well-being\u0026rsquo; and the \u0026lsquo;direct effect of income on well-being\u0026rsquo;.It is worth noting that the coefficient for the three-way interaction term \u0026lsquo;subjective social status \u0026times; annual income \u0026times; urban/rural\u0026rsquo; is \u0026minus;\u0026thinsp;0.067 and is statistically significant at the 5% level (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating that the moderating effect of income differs significantly between urban and rural areas.The fact that the moderating effect was not significant in the rural sample but was significantly negative in the urban sample further supports Hypothesis H2, namely that the attenuating moderating effect of income is primarily observed in urban areas.\u003c/p\u003e \u003cp\u003eTo illustrate the direction and magnitude of this moderating effect, we have calculated the marginal effects of social status across different income levels for both rural and urban settings, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e:\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAverage Marginal Effects of Subjective Social Status on Well-Being\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCondition\u003c/p\u003e \u003cp\u003e(Income \u0026times; Residence)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarginal Effect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStd. Err.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ez-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome = -1, Rural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[0.047, 0.246]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome = -1, Urban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[0.050, 0.236]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome\u0026thinsp;=\u0026thinsp;0, Rural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[0.072, 0.249]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome\u0026thinsp;=\u0026thinsp;0, Urban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[0.001, 0.180]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome\u0026thinsp;=\u0026thinsp;1, Rural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[0.076, 0.274]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome\u0026thinsp;=\u0026thinsp;1, Urban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e[-0.060, 0.136]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the rural sample, social status had a significant positive effect on well-being regardless of income level (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In the urban sample, however, when income levels were high (Income\u0026thinsp;=\u0026thinsp;1), the effect of social status became non-significant (p\u0026thinsp;=\u0026thinsp;0.446).This further corroborates the findings of the triple interaction model, namely that the moderating effect of income is primarily observed in urban areas.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eNote\u003c/strong\u003e \u003cp\u003eError bars represent 95% confidence intervals. The left panel (Rural Sample) shows stable positive effects across income levels, while the right panel (Urban Sample) shows a clear decreasing trend, illustrating the significant negative moderating role of income in urban areas only.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eFigure 1\u003c/strong\u003e \u003cp\u003eConditional marginal effects of subjective social status on well-being at different levels of income, stratified by urban-rural residence.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;1, there are significant differences in the pattern of marginal effects between urban and rural samples, as evidenced by variations in the nature and strength of the moderating effect depending on the type of residence; this provides direct evidence for the core hypothesis that \u0026lsquo;the moderating effect of income exhibits urban-rural heterogeneity\u0026rsquo;.In the rural sample (left-hand figure), the line representing the marginal effect remains largely flat across different income levels, with point estimates stabilising between 0.15 and 0.18. Within the rural social structure, the increase in well-being resulting from an improvement in subjective social status is robust and is not significantly moderated by the level of an individual\u0026rsquo;s economic resources.\u003c/p\u003e \u003cp\u003eIn the urban sample (see figure on the right), the marginal effect shows a clear downward trend. As income levels rise, the effect size falls from 0.143 (income = -1 SD) to 0.091 (income\u0026thinsp;=\u0026thinsp;0), and eventually drops to an insignificant 0.038 (p\u0026thinsp;=\u0026thinsp;0.446) at higher income levels (+\u0026thinsp;1 SD).The data in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e confirm that the effect is significantly positive only at low and average income levels; at high income levels, the 95% confidence interval straddles zero, revealing that, for urban residents, an increase in economic income significantly weakens the positive impact of social status on well-being.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDrawing on panel data from the five waves of the China Family Panel Study (2014\u0026ndash;2022), this study employs a fixed-effects model to systematically examine the impact of migrants\u0026rsquo; perceived social status on their well-being, with a particular focus on the moderating role of personal income and urban-rural differences.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePerceived social status and subjective well-being among migrants\u003c/h2\u003e \u003cp\u003eAfter effectively controlling for individual heterogeneity that does not vary over time, this study found that subjective social status has a significant and robust positive effect on the subjective well-being of migrants.Fixed-effects models reveal that, even for the same individual, a sense of well-being increases as their self-perceived social status rises over time.This finding is consistent with classical social comparison theory, which posits that individuals assess their own circumstances by comparing themselves with others, thereby influencing their subjective experience\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn25\" id=\"#FNLinkFn25\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003e.For those who have moved to a new place of residence, the relocation process is often accompanied by a breakdown of existing social networks and challenges in establishing a new sense of identity; the way individuals perceive their relative standing in their new environment is a key source of social respect, psychological security and a sense of belonging.\u003c/p\u003e \u003cp\u003eThe socio-cultural context of the Chinese society in which the study\u0026rsquo;s sample is situated reinforces this mechanism.Influenced by traditional Confucian thought and a collectivist culture, Chinese society has always placed great emphasis on social order, social courtesy and face, and networks of personal connections. An individual\u0026rsquo;s social status is not only determined by economic resources, but is also closely linked to the prestige, respect and trust they command within their family, neighbourhood and community.This cultural context may have amplified the symbolic significance and practical impact of perceived social status on the psychological well-being of migrants.When a person feels they have a high \u0026lsquo;status\u0026rsquo; within a new community, this is not merely a sense of psychological superiority; it is more likely to signify a more robust local support network, less feelings of exclusion, and stronger expectations of social integration.\u003csup\u003e[\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn26\" id=\"#FNLinkFn26\"\u003e\u003c/a\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eAn Analysis of the Regulatory Role of Economic Income\u003c/h2\u003e \u003cp\u003eIncome not only has a direct impact on well-being, but, more importantly, it moderates the relationship between social status and well-being.The full-sample analysis indicates that, as income rises, the positive impact of social status on well-being tends to diminish; the interaction coefficient is negative and approaches the level of significance (interaction β= \u0026minus;0.026, p\u0026thinsp;=\u0026thinsp;0.056).For migrants, once their financial resources have reached a certain level, the additional happiness derived from an improvement in social status begins to diminish.\u003c/p\u003e \u003cp\u003eWe believe that an improvement in social status often leads to greater social acceptance, less discrimination based on identity, and a stronger sense of self-worth, all of which can significantly enhance well-being.However, once an individual\u0026rsquo;s income is sufficient to meet their material security and basic developmental needs, the psychological benefits associated with social status\u0026mdash;such as a sense of respect and social recognition\u0026mdash;tend to diminish.Income plays a functional \u0026lsquo;substitute\u0026rsquo; role here, partially compensating for the psychological security provided by social status.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eUrban-rural heterogeneity in the income-adjusting effect\u003c/h2\u003e \u003cp\u003eFurther research has revealed that the moderating effect of income on the relationship between social status and well-being exhibits significant urban-rural heterogeneity.This conclusion has been corroborated by the data in two ways. Sub-sample regression analysis shows that the moderating effect of income is significantly negative only in the urban sub-sample, whereas it is not significant in the rural sub-sample.\u003c/p\u003e \u003cp\u003eResearch suggests that the fundamental differences in urban and rural social structures have shaped this heterogeneity.In urban areas, high mobility has created a diverse and competitive environment. Individuals have a wide range of avenues for self-fulfilment, and the frameworks for social comparison have become more complex.High incomes provide urban residents with a wide range of material choices, abundant leisure activities and diverse social opportunities; to some extent, this may alleviate their psychological craving for and reliance on traditional status symbols such as professional prestige and community identity, thereby causing the psychological rewards derived from social status to diminish as income rises.This demonstrates that, in urban areas, an individual\u0026rsquo;s economic income has the potential to influence and even replace their social capital.\u003c/p\u003e \u003cp\u003eIn rural areas, social networks in China\u0026rsquo;s countryside are even more tightly knit, based on kinship and geographical ties, and traditional notions of reputation and face continue to exert a profound influence.A higher social status is not merely a subjective psychological perception; it is also closely linked to tangible local authority, family prestige and access to mutual support networks. These implicit resources, deeply embedded in local social relationships, cannot be fully replaced by monetary income alone.Consequently, regardless of an individual\u0026rsquo;s economic circumstances, higher social status implies access to more reliable social support and a more respected local identity, thereby exerting a stable and widespread positive influence on well-being. The differences in the moderating effect of economic income in rural areas suggest that the \u0026lsquo;face\u0026rsquo; value inherent in rural social status is of irreplaceable importance to individual well-being.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eThe study utilises panel data from five waves of the China Family Panel Study (2014\u0026ndash;2022) and employs a fixed-effects model for analysis. This approach effectively controls for individual heterogeneity that does not vary over time, thereby identifying the relationship between subjective social status and well-being, as well as its moderating mechanisms.The study focuses in particular on \u0026lsquo;migrant residents\u0026rsquo;, a group whose numbers are growing rapidly amid the process of rapid urbanisation. Through the use of a triple interaction model and marginal effect analysis across subsamples, the analysis provides an in-depth examination of the urban-rural heterogeneity in the moderating role of economic income, thereby offering empirical evidence from China\u0026rsquo;s transitioning society to support relevant theories.\u003c/p\u003e \u003cp\u003eHowever, this paper also has certain limitations that need to be addressed in future research.Firstly, the definition of \u0026lsquo;migrant residents\u0026rsquo; is based primarily on whether they have relocated across district or county boundaries; it does not distinguish more precisely between the reasons for migration, the distance travelled, or the duration of the move. These factors may influence their social integration and psychological experience, and more in-depth heterogeneity analyses could be conducted in the future.Secondly, although significant heterogeneity has been identified between urban and rural areas, there remain substantial differences within these categories; for example, the social structures and cultural norms may vary between cities of different tiers and between rural areas in different regions.Thirdly, given the limited sample size, the study was unable to conduct a more in-depth analysis or discussion of different types of migrant populations. In future, natural experiments or more refined longitudinal data designs could be employed to further validate the causal relationships involved.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eDrawing on five years of panel data from the China Family Panel Study, this study employs a fixed-effects model to systematically examine the mechanisms through which migrants\u0026rsquo; subjective social class identity influences their well-being, whilst also exploring the moderating role of economic income and its urban-rural heterogeneity.The main findings are as follows:(1) Subjective social status has a robust positive effect on the well-being of migrants. Even when controlling for individual-level characteristics that remain constant, individuals report significantly higher levels of well-being when they perceive an improvement in their social status within their new environment. This suggests that, for those who have relocated, a positive subjective social status serves as a crucial foundation for re-establishing a sense of social belonging and achieving psychological security.(2) Economic income plays a significant moderating role in the relationship between social status and well-being. As personal income rises, the increase in well-being resulting from higher social status tends to diminish; that is, once economic resources are sufficient to meet basic needs, the additional psychological rewards derived from social status diminish relatively, as economic resources assume, to a certain extent, the psychological security function traditionally associated with social status.(3) The moderating effect of economic income exhibits marked urban-rural heterogeneity. The moderating effect of economic income is significant only in the urban sample, whereas it is not evident in the rural sample.\u003c/p\u003e \u003cp\u003eThe findings of the aforementioned study indicate that, in the face of a large-scale mobile and migrant population, public policy must go beyond the narrow focus on economic support and physical resettlement, and should instead prioritise their social and psychological integration.In urban areas, attention should be paid to ensuring that high-income migrants can realise their potential in diverse ways; through community-building and the fostering of cultural identity, we can help bridge the psychological gap that may arise from the diminishing effects of their social status.In rural areas, policy efforts should place greater emphasis on enhancing migrants\u0026rsquo; sense of identification with and belonging to their new environment through rural revitalisation and cultural development; this is likely to be more effective in boosting the subjective well-being of rural migrants than mere financial subsidies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCFPS \u0026nbsp; \u0026nbsp;China Family Panel Studies\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch3\u003eAcknowledgements\u003c/h3\u003e\n\u003cp\u003eWe extend our sincere gratitude to the institutions responsible for the collection and dissemination of data from the China Family Panel Studies (CFPS), namely the China Social Survey Centre at Peking University and the Survey Research Centre at the University of Michigan, USA. We also acknowledge the invaluable contributions made to this research by all respondents, local authorities, and community organisations.\u003c/p\u003e\n\u003ch3\u003eAuthors\u0026apos; contributions\u003c/h3\u003e\n\u003cp\u003eDY proposed the research concept. All authors participated in the study design. DY was responsible for data analysis and drafted the initial manuscript. ZWQ provided literature review support. All authors jointly interpreted the results and rigorously revised the manuscript. All authors read and approved the final version, agreeing to take full responsibility for the integrity and accuracy of the research.\u003c/p\u003e\n\u003ch3\u003eFunding\u003c/h3\u003e\n\u003cp\u003eThis study was supported by the Humanities and Social Sciences Youth Foundation, Ministry of Education of the People\u0026apos;s Republic of China (Project No. 22YJC810001),and National Social Sciences Found Youth Project (Project No. 23CZZ013).\u003c/p\u003e\n\u003ch3\u003eAvailability of data and materials\u003c/h3\u003e\n\u003cp\u003eThe data supporting the findings of this study are available from [ China Household Panel Survey]. However, as these data are licensed for use in this research, their availability is restricted and therefore not publicly accessible.However, the data may be accessed by authors upon reasonable request and with the permission of the [Centre for Social Science Surveys, Peking University].\u003c/p\u003e\n\u003ch3\u003eEthics approval and consent to participate\u003c/h3\u003e\n\u003cp\u003eThis study utilised publicly available secondary data from the China Family Panel Studies (CFPS). Ethical approval for the collection of the original CFPS data was granted by the Institute of Social Science Survey (ISSS) at Peking University. Written informed consent was obtained from all participants by the CFPS research team prior to data collection.\u003c/p\u003e\n\u003cp\u003eThis study constitutes a secondary analysis of de-identified data and therefore does not require additional ethical approval. All research procedures adhere to the relevant principles of the Declaration of Helsinki.\u003c/p\u003e\n\u003ch3\u003eConsent for publication\u003c/h3\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003ch3\u003eCompeting interests\u003c/h3\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":" \u003col\u003e\n\u003cli\u003eOishi S. The psychology of residential mobility: implications for the self, social relationships, and well-being. \u003cem\u003ePerspect Psychol Sci\u003c/em\u003e. 2010;5(1):5\u0026ndash;21.\u003c/li\u003e\n\u003cli\u003eBerry JW. Immigration, acculturation, and adaptation. \u003cem\u003eAppl Psychol\u003c/em\u003e. 1997;46:5\u0026ndash;34. doi:10.1111/j.1464-0597.1997.tb01087.x.\u003c/li\u003e\n\u003cli\u003eClark AE, Frijters P, Shields MA. Relative income, happiness, and utility: an explanation for the Easterlin paradox and other puzzles. \u003cem\u003eJ Econ Lit\u003c/em\u003e. 2008;46(1):95\u0026ndash;144. doi:10.1257/jel.46.1.95.\u003c/li\u003e\n\u003cli\u003eFestinger L. A theory of social comparison processes. \u003cem\u003eHum Relat\u003c/em\u003e. 1954;7(2):117\u0026ndash;40.\u003c/li\u003e\n\u003cli\u003eEuteneuer F. Subjective social status and health. \u003cem\u003eCurr Opin Psychiatry\u003c/em\u003e. 2014;27(5):337\u0026ndash;43. doi:10.1097/YCO.0000000000000083.\u003c/li\u003e\n\u003cli\u003eHaught HM, Rose J, Geers A, Brown JA. Subjective social status and well-being: the role of referent abstraction. \u003cem\u003eJ Soc Psychol\u003c/em\u003e. 2015;155(4):356\u0026ndash;69. doi:10.1080/00224545.2015.1015476.\u003c/li\u003e\n\u003cli\u003eAdler NE, Epel ES, Castellazzo G, Ickovics JR. Relationship of subjective and objective social status with psychological and physiological functioning: preliminary data in healthy white women. \u003cem\u003eHealth Psychol\u003c/em\u003e. 2000;19(6):586\u0026ndash;92. doi:10.1037/0278-6133.19.6.586.\u003c/li\u003e\n\u003cli\u003eBerry JW. Immigration, acculturation, and adaptation. \u003cem\u003eAppl Psychol\u003c/em\u003e. 1997;46:5\u0026ndash;34. doi:10.1111/j.1464-0597.1997.tb01087.x.\u003c/li\u003e\n\u003cli\u003eGraham C, Felton A. Inequality and happiness: insights from Latin America. \u003cem\u003eJ Econ Inequal\u003c/em\u003e. 2006;4:107\u0026ndash;22. doi:10.1007/s10888-005-9009-1.\u003c/li\u003e\n\u003cli\u003eEasterlin RA. Income and happiness: towards a unified theory. \u003cem\u003eEcon J\u003c/em\u003e. 2001;111(473):465\u0026ndash;84. http://www.jstor.org/stable/2667943. Accessed 15 Jan 2026.\u003c/li\u003e\n\u003cli\u003eKahneman D, Deaton A. High income improves evaluation of life but not emotional well-being. \u003cem\u003eProc Natl Acad Sci U S A\u003c/em\u003e. 2010;107(38):16489\u0026ndash;93. doi:10.1073/pnas.1011492107.\u003c/li\u003e\n\u003cli\u003eKahneman D, Deaton A. High income improves evaluation of life but not emotional well-being. \u003cem\u003eProc Natl Acad Sci U S A\u003c/em\u003e. 2010;107(38):16489\u0026ndash;93. doi:10.1073/pnas.1011492107.\u003c/li\u003e\n\u003cli\u003eClark AE, Frijters P, Shields MA. Relative income, happiness, and utility: an explanation for the Easterlin paradox and other puzzles. \u003cem\u003eJ Econ Lit\u003c/em\u003e. 2008;46(1):95\u0026ndash;144. doi:10.1257/jel.46.1.95.\u003c/li\u003e\n\u003cli\u003eKnight J, Gunatilaka R. Great expectations? The subjective well-being of rural-urban migrants in China. \u003cem\u003eWorld Dev.\u003c/em\u003e 2010;38(1):113\u0026ndash;24.\u003c/li\u003e\n\u003cli\u003eNational Bureau of Statistics of China. \u003cem\u003eTabulation on the 2020 Population Census of the People\u0026rsquo;s Republic of China\u003c/em\u003e. Beijing: National Bureau of Statistics of China; 2021. http://www.stats.gov.cn/sj/pcsj/rkpc/d7c/202111/P020211126523667366751.pdf. Accessed 15 Jan 2026.\u003c/li\u003e\n\u003cli\u003eFei X. \u003cem\u003eFrom the Soil: The Foundations of Chinese Society\u003c/em\u003e. Shanghai: Shanghai People\u0026rsquo;s Publishing House; 2006.\u003c/li\u003e\n\u003cli\u003eXie Y, Hu JW, Zhang CN. China Family Panel Studies: Concept and Practice. \u003cem\u003eSociety\u003c/em\u003e. 2014;34(02):1-32. https://doi.org/10.15992/j.cnki.31-1123/c.2014.02.003.\u003c/li\u003e\n\u003cli\u003eDiener, E. (1984). Subjective well-being. \u003cem\u003ePsychological Bulletin\u003c/em\u003e, 95(3), 542\u0026ndash;575. https://doi.org/10.1037/0033-2909.95.3.542\u003c/li\u003e\n\u003cli\u003eCheung F, Lucas RE. Assessing the validity of single-item life satisfaction measures: results from three large samples. \u003cem\u003eQual Life Res\u003c/em\u003e. 2014 Dec;23(10):2809-18. doi: 10.1007/s11136-014-0726-4. Epub 2014 Jun 3. PMID: 24890827; PMCID: PMC4221492.\u003c/li\u003e\n\u003cli\u003eJackman MR, Jackman RW. An interpretation of the relation between objective and subjective social status. \u003cem\u003eAm Sociol Rev\u003c/em\u003e. 1973;38:569\u0026ndash;82.\u003c/li\u003e\n\u003cli\u003eAdler NE, Epel ES, Castellazzo G, Ickovics JR. Relationship of subjective and objective social status with psychological and physiological functioning: preliminary data in healthy white women. \u003cem\u003eHealth Psychol\u003c/em\u003e. 2000;19(6):586\u0026ndash;92. doi:10.1037/0278-6133.19.6.586.\u003c/li\u003e\n\u003cli\u003eBatz C, Tay L. Gender differences in subjective wellbeing. In: Diener E, Oishi S, Tay L, editors. \u003cem\u003eHandbook of wellbeing\u003c/em\u003e. Salt Lake City (UT): DEF Publishers; 2018. \u003c/li\u003e\n\u003cli\u003eWadsworth T. Marriage and subjective wellbeing: how and why context matters. \u003cem\u003eSoc Indic Res\u003c/em\u003e. 2016;126:1025\u0026ndash;1048. doi:10.1007/s11205-015-0930-9.\u003c/li\u003e\n\u003cli\u003eBonanomi A, Rosina A. Employment status and wellbeing: a longitudinal study on young Italian people. \u003cem\u003eSoc Indic Res\u003c/em\u003e. 2020;161:1\u0026ndash;18. doi:10.1007/s11205-020-02376-x.\u003c/li\u003e\n\u003cli\u003eFestinger L. A theory of social comparison processes. \u003cem\u003eHum Relat\u003c/em\u003e. 1954;7(2):117\u0026ndash;40.\u003c/li\u003e\n\u003cli\u003eLever JP. Poverty, stressful life events, and coping strategies. \u003cem\u003eSpan J Psychol\u003c/em\u003e. 2008;11:228\u0026ndash;249.\u003c/li\u003e\n\u003cli\u003e\u003c/li\u003e\n \u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Subjective social status, Income, Subjective well-being, Residential Mobility, CFPS","lastPublishedDoi":"10.21203/rs.3.rs-9559814/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9559814/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eRelocation is a significant life event that affects an individual\u0026rsquo;s mental health and well-being. Whilst previous research has examined the influence of subjective social status and income on subjective well-being, little attention has been paid to the relationship between these three factors in the context of residential mobility, and there has been a lack of systematic investigation into the moderating role of income in the relationship between subjective social status and well-being. This study aims to explore the relationship between the subjective social status and subjective well-being of migrants, as well as the moderating role played by income in this relationship.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eDrawing on five waves of data from the China Family Panel Studies (CFPS) covering the period 2014\u0026ndash;2022, this study employs a fixed-effects panel model to systematically examine the impact of migrants\u0026rsquo; perceived social status on their subjective well-being, as well as the moderating role of income. The dependent variable, subjective well-being, was constructed by standardising self-reported happiness and life satisfaction indices using Z-scores. The independent variable, subjective social status, was measured using a 5-point scale, whilst the income variable was truncated at the top and bottom 1 per cent and transformed using the natural logarithm to test its moderating effect.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAfter controlling for complex interactions, subjective social status (β\u0026thinsp;=\u0026thinsp;0.161, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and annual income (β\u0026thinsp;=\u0026thinsp;0.045, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) exhibited highly significant positive main effects on well-being, whilst the moderating effect of income differed significantly between urban and rural areas.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eSubjective social status is a key psychological mechanism underpinning the sense of well-being among migrant residents, whilst income serves, to a certain extent, as a substitute for the psychological rewards associated with social status; however, its effectiveness is markedly context-dependent. Consequently, against a backdrop of ever-increasing population mobility, enhancing residents\u0026rsquo; well-being cannot rely solely on income growth; equal importance must be attached to their perception of social status and the process of social integration. In particular, differentiated strategies for social governance and public services should be formulated to address the distinct urban and rural contexts.\u003c/p\u003e","manuscriptTitle":"Home is where the heart is?The Impact of perceived social status on Residents' Subjective Well-Being——The moderating role of income and its urban-rural heterogeneity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-14 18:22:34","doi":"10.21203/rs.3.rs-9559814/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-05-05T23:21:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-05T23:19:28+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-05-04T02:50:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-05-03T08:27:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2026-05-03T08:22:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cc9b131e-9945-475e-bcf4-30076f0bd2d8","owner":[],"postedDate":"May 14th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewersInvited","content":"21","date":"2026-05-05T23:21:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-05T23:19:28+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-05-04T02:50:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-05-03T08:27:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2026-05-03T08:22:33+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T18:22:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-14 18:22:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9559814","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9559814","identity":"rs-9559814","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}