ScholarOne - Social Rigidity Across and Within Generations: A Predictive
Approach
Abstract
How well can individuals’ parental background and previous life
experiences predict their mid-life Socio-Economic Status (SES)
attainment? This question is central to stratification research, as a
strong power of earlier experiences in predicting later-life outcomes
signals substantial intra- or intergenerational status persistence, or
put simply, social rigidity. Running machine learning models on panel
data to predict outcomes that include hourly wage, total income, family
income, and occupational status, we find that a large number (around
4,000) of predictors commonly used in the stratification literature
improves the prediction of one’s life chances in middle to late
adulthood by about 10 to 50 percent, compared with a null model that
uses a simple mean of the outcome variable. The level of predictability
depends on the specific outcome being analyzed, with labor market
indicators like wages and occupational prestige being more predictable
than broader socioeconomic measures such as overall personal and family
income. Grouping a comprehensive list of predictors into four unique
sets that cover family background, childhood and adolescence
development, early labor market experiences, and early adulthood family
formation, we find that including income, employment status, and
occupational characteristics at early career significantly improves
models’ prediction accuracy for mid-life SES attainment. Further, we
illustrate the application of predictive models to examine sources of
between-group disparity by life stages. Using the Black-white difference
as the example, we find that racial differences in early labor market
experiences are the most critical in explaining racial inequality in
mid-life SES attainment, especially for low-income individuals.