Working Papers

Working Papers

Networked Inequality: The Role of Changes in Network Heterogeneity and Network Size in Attitudes Towards Inequality
– with Guillermo Beck, Julio Iturra-Sanhueza, Gabriel Otero, and Benjamín Muñoz –

Abstract: Existing research on attitudes towards inequality has predominantly focused on individual class or socioeconomic position, with little attention paid to the role of personal networks. The limited existing research has primarily focused on the influence of specific class ties, while overlooking a crucial dimension: network size. Moreover, the lack of quantitative data containing information about socioeconomic standing, network configuration and attitudes over time for a group of the same individuals has hindered the accurate testing of the influence of personal networks on attitudes towards inequality. To address these gaps, the main goal of this paper is to examine the extent to which changes in the size and heterogeneity of acquaintanceship networks affect attitudes towards inequality in Chile – a country with high levels of income and wealth inequality. We utilise quantitative data from two waves (2016-2018) of a representative panel survey for the urban Chilean population, provided by the Chilean Longitudinal Social Survey (ELSOC). Our cross-sectional analyses indicate that network heterogeneity and network size both enhance perceptions of income inequality and preferences for equality, while decreasing perceptions of meritocracy. In the fixed effects regression models, however, network size is more closely linked to an increased perception of inequality, while network heterogeneity is more strongly associated with greater preferences for equality. Moreover, increases in network size tend to reduce meritocratic beliefs. These findings suggest that network size and network heterogeneity are complementary network characteristics in explaining attitudes towards inequality..

Stability and Evolution of Acquaintance Networks Across the Life Course
– with Benjamín Muñoz and Vicente Espinoza –

This study examines the reliability and evolution of acquaintance network size over time using the Network Scale-Up Method (NSUM) and data from three waves (2016, 2018, 2021) of the Chilean Longitudinal Social Survey (ELSOC), a nationally representative urban panel. We assess the longitudinal stability of NSUM-based metrics and explore the sociodemographic and life-event factors associated with changes in network size. Reliability tests—including Heise scores and intraclass correlation coefficients—confirm the consistency of the method, revealing stable yet gradually expanding network measures. Panel regression models show that subjective social status and head-of-household roles are consistently associated with network growth, while gender, income, and religious affiliation have no significant effects. Difference-in-differences models further indicate that participation in social organizations contributes to network expansion, whereas most life events (e.g., marriage or employment transitions) have limited impact. These findings underscore NSUM’s validity for longitudinal research and offer novel insights into how social engagement fosters network resilience and shapes the distribution of social capital over time.

From Cohesion to Division: Macrostructural Factors Driving Class Homogeneity

Class-based homophily in social networks plays a critical role in shaping economic opportunities, mobility, and social cohesion. However, the extent to which economic inequality and welfare state generosity structure network composition remains insufficiently understood. Existing studies on crowding-in and crowding-out effects have primarily focused on social capital and trust, neglecting their implications for homophily, one of the core characteristics of social networks. This study addresses this gap by examining how macrostructural factors influence class-based network homogeneity across 32 countries. Using data from the 2017 International Social Survey Programme (ISSP) on social networks, this study applies multilevel regression models to analyze how social class, economic inequality, and welfare state generosity interact to shape network composition. The findings challenge conventional expectations. Intermediate-class individuals, rather than acting as bridges between the working and service classes, exhibit more homogeneous networks than anticipated, suggesting that network structure operates more as a stratified resource than as an intermediary mechanism. Additionally, while economic inequality was expected to reinforce class segmentation, its effects appear more pronounced among the working class, while upper-class individuals maintain exclusive networks regardless of inequality levels. Furthermore, welfare state generosity exhibits weaker effects than theorized, suggesting that network homogeneity is primarily driven by class-based social dynamics rather than national-level redistributive policies. These findings contribute to three major debates. First, they advance research on stratification and social networks by demonstrating that class remains the dominant determinant of network composition, even in contexts of high redistribution. Second, they integrate welfare state and inequality research, illustrating how macrostructural conditions shape network segmentation differently across class positions. Third, they challenge existing assumptions about interclass interactions, showing that social participation structures, rather than economic redistribution, play a more crucial role in fostering network diversity. These insights highlight how economic structures, welfare policies, and class-based social capital interact to shape inequality, mobility, and social cohesion in contemporary societies.

Work in Progress

Gaining Social Capital? The Impact of Entering Politics on Social Trajectories
– with Joaquín Rozas-Bugueño –

This project examines how institutional participation shapes the political networks of former members of Chile’s Constitutional Convention (2021–2022). Using network analysis and a natural experiment approach, we assess how electoral experience affects brokerage, cohesion, and embeddedness—highlighting differences between independent activists and party-affiliated delegates.

Rethinking Class Through Wealth: A Comparative Approach to Asset-Based Stratification

This project develops and validates an asset-based class schema that captures new forms of social stratification emerging under financialized capitalism. Moving beyond occupational models, it argues that wealth structure—defined by the interaction of asset ownership, income sources, and liabilities—constitutes a distinct axis of inequality. Drawing on harmonized panel data from the U.S. (PSID), Germany (SOEP), and the Luxembourg Wealth Study (LWS), the project uses Latent Class Analysis and supervised machine learning to inductively identify empirical asset classes. These are complemented by a deductive model grounded in recent theories of asset-based stratification. The study examines how asset-based class positions predict life chances, financial vulnerability, and redistributive attitudes, with a focus on the central role of housing. The project aims to revitalize class analysis by offering a multidimensional, institutionally grounded framework that captures the political and material consequences of asset inequality in contemporary capitalist societies.