We examine changes in inequality in socio-emotional skills very early in life in two British cohorts born 30 years apart. We construct socio-emotional scales comparable across cohorts for both boys and girls, using two validated instruments for the measurement of child behaviour. We identify two dimensions of socio-emotional skills for each cohort: ‘internalising’ and ‘externalising’, related to the ability of children to focus their concentration and to engage in interpersonal activities, respectively. Using recent methodological advances in factor analysis, we establish comparability in the inequality of these early skills across cohorts, but not in their average level. We document for the first time that inequality in these early skills has increased across cohorts, especially for boys and at the bottom of the distribution. We also document changes in conditional skills gaps across cohorts. We find an increase in the socio- emotional skills gap in the younger cohort for children born to mothers with higher socio-economic status (education and employment), and to mothers who smoked during pregnancy. The increase in inequality in early socio-emotional skills is particularly pronounced for boys. On the other hand, we find a decline in the skills gradient for children without a father figure in the household. Lastly, we document that socio-emotional skills measured at a much earlier age than in most of the existing literature are significant predictors of outcomes both in adolescence and adulthood, in particular health and health behaviours. Our results show the importance of formally testing comparability of measurements to study skills differences across groups, and in general point to the role of inequalities in the early years for the accumulation of health and human capital across the life course.
J13: Fertility; Family Planning; Child Care; Children; Youth
J24: Human Capital; Skills; Occupational Choice; Labor Productivity
I14: Health and Inequality
I24: Education and Inequality
C38: Classification Methods; Cluster Analysis; Principal Components; Factor Models