ABSTRACT
We study how early-life cognitive skills, non-cognitive abilities, and family characteristics influence educational choices and affect later employment outcomes and wages. The analysis was carried out on a cohort of UK females observed at different life stages by adopting the British National Child Development Study database. Our findings provide evidence of how early-life abilities and family characteristics affect both the educational attainment and later labour market outcomes of female workers. However, we found that educational levels interact with early-life abilities, productive characteristics in general, and other characteristics, giving rise to different employment outcomes and income prospects conditioned on educational attainment. Occupational outcomes and wages of low-educated women are more sensitive to factors that are not strictly linked to productivity.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1 If we observe the proportion of adults with tertiary education, the male to female gap is equal to nine percentage points in favour of females.
2 The selection and the attrition bias problems in the NCDS data have been investigated in some papers. Hawkes and Plewis (Citation2006) have found that the attrition and non-response issues can be associated with only a few significant predictors.
3 This information was gathered from the 1991 NCDS sweep and is recovered when individuals are 33 years old.
4 Despite the share of females that only completed compulsory education has decreased overtime, the interest for factors determining educational achievements and their consequences for performance in the labour market remains crucial, in the light of the increasing level of job and wage polarization and raising inequality and poverty in many developed countries.
5 The NCDS 1974–2000 work histories file has been used to determine the cumulated working experiences of cohort-members when they were aged 16–42.
6 A higher BSAG test score corresponds to higher social maladjustment, hence poorer non-cognitive skills (Stott Citation1969).
7 The distribution of respective (original) test scores are plotted in and presented in the Appendix.
8 Descriptive statistics related to 1991 can be provided upon request.
9 We implicitly assumed that, conditional on covariates, being married does not directly affect the wage. This means there should not be any correlations between confounding factors affecting wages (e.g. ability) and the probability of being married. This seems to be reasonable, although one could consider that the productivity of female workers (and then the wage) may decrease once married because of, for example, increased domestic duties.
10 We ran regressions also for part-timers, according to the model specification discussed above. Results can be provided upon request.