Abstract
This paper presents and applies a methodology of socioeconomic classification that integrates asset- and social class approaches. We employ data from the 2013 Brazilian National Household Survey and use latent class analysis to identify clusters and classify the working population. With regard to social class the Brazilian occupations are classified based on the European Socioeconomic Classification (ESeC) schema and an indicator of employment status. As for household wealth, we use the items related to household condition, ownership of durable goods and access to public services with the highest discriminatory power. We also make use of variables that account for the Brazilian spatial and socio-demographic heterogeneity. We found four clusters which we term latent socioeconomic stratum (LSeS). When compared we found an ordered pattern from the best-off LSeS (1) to the worst-off (4) with respect to household wealth and ESeC classes. Nevertheless, although the class composition of each LSeS reveals a distinct concentration of specific ESeC classes, all classes are present in each LSeS. Controlling for social class, differences in household wealth are more marked between LSeS than between social classes within the same LSeS. Hence, the methodology unveils the latent socioeconomic strata, reveals a class schema for each stratum and points out potential stratum fractions within them. The results were validated using variables external to the model, namely household food security status and years of schooling. The external validation revealed the same ordered pattern and the presence of stratum fractions.
Highlights
The social stratification of a given population into groups with distinct levels of income, wealth, prestige, and power characterizes human societies across time
To identify the number of latent classes, i.e., the latent socioeconomic strata (LSeS) that best describe the unobserved heterogeneity in the sample, we estimated the model with asset indicators, household characteristics, and access to basic services, i.e., the manifestation of the latent class variable (Collins and Lanza, 2010)
We developed and applied a methodology of classification integrating the asset approach, social class schema and socio-demographic indicators that influence the value of goods as well as the households’ access to basic services
Summary
The social stratification of a given population into groups with distinct levels of income, wealth, prestige, and power characterizes human societies across time. Social stratification refers to the multidimensional, latent and dynamic arrangement of society that stems from the uneven distribution and appropriation of such types of capital between strata These differences tend to influence chances, performances and outcomes in domains such as demography (Bollen et al 2001; Schneider and Hastings 2015), health research (House et al 1994; Braveman et al 2005), education (Bukodi and Goldthorpe 2013), labor market (Lucchini and Schizzerotto 2010) and social mobility (Erikson and Goldthorpe 2010; Breen and Jonsson 2005). The criteria for item selection are pivotal to the consistency of the index
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