China has made significant strides in poverty reduction, yet relative and subjective poverty remain challenges. While objective poverty is often measured by income and consumption, subjective poverty focuses on individuals' perceptions of their well-being. This study addresses the gap in understanding subjective poverty by examining the role of social networks. Existing research on subjective poverty often focuses on relative income or social inequality, but the direct influence of social networks, especially their dual roles of providing social support and serving as reference groups, has not been thoroughly explored. This paper aims to fill this gap by analyzing how social networks, through both social support and reference group mechanisms, affect subjective poverty. The study also investigates the mediating and moderating roles of objective poverty in this relationship. Understanding these mechanisms is crucial for developing effective poverty reduction policies that address both objective and subjective dimensions of poverty.

The literature on poverty has evolved from a focus on absolute, unidimensional measures to encompass relative and multidimensional perspectives, incorporating subjective well-being. While objective poverty measures are useful, they fail to capture individuals' subjective experiences and perceptions of their own well-being. Several theories attempt to explain subjective poverty: the relative income hypothesis emphasizes comparisons with others; the social inequality hypothesis highlights the impact of broader societal disparities; and multifactorial synthesis integrates multiple factors. However, the literature lacks a comprehensive investigation of the influence of social networks, especially their distinct functions in providing social support and forming reference groups. Previous studies have mainly examined the impact of social networks on objective poverty, overlooking their role in shaping subjective perceptions of poverty. This paper contributes to the literature by explicitly integrating both the social support and reference group mechanisms within a single analytical framework.

This study utilizes data from the China Labor Dynamics Survey (CLDS) for the years 2014, 2016, and 2018. The sample, after cleaning, includes 32,257 households. Subjective poverty is measured using subjective socioeconomic status, assessed using Cantril's ladder method. Social support is operationalized as emotional (ENSC) and instrumental (INSC) support, measured by the number of individuals in the respondent's social network who provide each type of support. The social network's function as a reference group is measured through homogeneous network comparison (HONC) and heterogeneous network comparison (HENC) questions, assessing respondents' perceived relative living standards compared to similar and dissimilar individuals within their network, respectively. Objective poverty is defined using a relative poverty line based on 40% of the median per capita disposable income, differentiated by urban and rural areas. Control variables include demographics, income, education, employment, social insurance, and sense of fairness. The analysis employs OLS regression for continuous dependent variables and logit regression for binary ones. Instrumental variable techniques are used to address potential endogeneity issues in the social network variables. Mediation and moderation analyses are performed to test the hypothesized relationships.

The results confirm that social networks significantly affect subjective poverty through both social support and reference group mechanisms. Both emotional and instrumental social support are negatively associated with subjective poverty, suggesting that greater social support leads to lower subjective poverty. However, after controlling for endogeneity, emotional support exhibits a stronger negative effect on subjective poverty than instrumental support. Individuals with higher status in their homogeneous social networks report lower subjective poverty, while the effect from heterogeneous networks is smaller. Objective poverty acts as a mediator for the social support mechanisms. However, its effect on subjective poverty is smaller when individuals are already objectively poor. Objective poverty moderates the relationship between social network comparisons and subjective poverty, reducing the influence of reference group effects when respondents experience objective poverty.

The findings support the hypothesis that social networks play a crucial role in alleviating subjective poverty. Both social support and relative standing within the social network significantly influence subjective poverty perceptions. The mediating role of objective poverty underscores the importance of tackling both objective and subjective dimensions of poverty. The moderating effect highlights that the impact of social comparisons on subjective poverty is contingent on the objective circumstances. When individuals are objectively poor, material concerns likely outweigh social comparisons, decreasing the influence of social reference points on subjective poverty levels.

This study contributes to the literature by simultaneously examining the social support and reference group mechanisms through which social networks impact subjective poverty. It highlights the importance of considering subjective aspects alongside objective measures of poverty and emphasizes the conditional nature of relative income effects. Future research could focus on refining the measurement of social networks, particularly distinguishing between different types of network relationships, and exploring the interaction between social networks and other poverty alleviation interventions.

The study relies on self-reported data, which may be subject to biases. The cross-sectional nature of the data limits the ability to establish causal relationships definitively. The measurement of social networks could be further refined using more detailed network data, including the types and strengths of relationships among network members and the influence of specific network characteristics on subjective poverty. The study's reliance on a specific relative poverty line could also influence the results.