7.4.1 BCS70 data
The British Cohort Study (BCS70) is a longitudinal birth cohort study that started in 1970 following just over 17,000 people born across Great Britain. Data were collected when individuals were 5, 10, 16, 26 and every 4 years thereafter. In the most recent wave of data available for analysis, collected in 2012, individuals were 42 years old. Data on a wide variety of characteristics and outcomes were collected including social circumstances, cognitive ability, educational achievement and choices, and occupational outcomes. Of a total sample of 9,448 individuals, 1,968 obtained a degree by 42 and recorded gender and subject choice.
The majority of individuals who attended university in this cohort would have started their courses in the late 1980’s – early 1990’s. This was after the great expansion of the higher education system that followed the Second World War, just before (or during) the conversion of polytechnics1 (which traditionally offered
more vocationally oriented degrees) to full university status, and before the introduction of tuition fees (initially in 1998) and erosion of financial assistance for students. There were also large differences in the number of students attending
1 Graduates from polytechnics are included in the study because they were likely to have converted to universities
136 university in this time, compared to the current day, with around one in five 18 year-olds attending university in 1990. In the BCS70 sample 23.5% of the total 2012 cohort had attained a degree by 42.
Multiple imputation using chained equations was employed to account for missing data on other variables, with 20 datasets created (White, Royston, & Wood, 2011). For full specification of variables used in imputations, see appendix A. Because this accounts for missing data, but not attrition over time, longitudinal weights were also constructed using logistic regression modelling predicting probability of being in the most recent wave based on baseline characteristics. Characteristics chosen were informed by Mostafa & Wiggins (2014), and included sex, birthweight, parity, mother’s age, whether mother lived in the southeast of England in the first survey, social class at birth, and mother’s and father’s age at completion of education.
7.4.2 NLSY79 data
The National Longitudinal Survey of Youth 1979 (NLSY79) is also a longitudinal panel study, in which participants were interviewed annually up to 1994 and biannually thereafter. The survey began with a nationally representative sample of 12,686 young people, and covers a broad range of topics and outcomes, with detailed information on education, cognitive ability and occupational outcomes. Unlike BCS70 the study is not a birth cohort. Individuals were between 14-22 at the time of the first survey, and were born between 1957-1964. Thus, although the cohorts are close in age, there is some time lag, and additional age controls for the NLSY79 cohort were included in analysis. If they attended university between 18 and 21 years old, they would have attended between the years 1975-1985. I restricted the sample to those who were dependent on their parents at the start of the study, as only for these participants did parents complete questions about income, and to those who were 21 or under. The final sample included 7,856 individuals, of which 1,571 were graduates who had completed a four-year degree by 2004 (26% of the sample), with a mean age1 of 16.8 at the start of the survey,
and 42.5 by 2004.
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7.4.3 Key variables Field of study
Subjects were grouped into three categories including: Science, Technology, Engineering and Maths (STEM) subjects; Law1, Economics and Management (LEM)
subjects, and Other Social Sciences, Arts and Humanities subjects (OSSAH). Whilst historically many studies have classified field of study as a binary one between STEM and non-STEM subjects, a number of studies suggest that including a further group of subjects with positive occupational outcomes (LEM subjects) gives a better overall picture of differences in outcomes (e.g. Walker and Zhu, 2013). Students who studied a joint-honours degree (unless they had a primary subject) were classed as OSSAH. The majority of people had studied an OSSAH subject, followed by STEM subjects, then LEM subjects. Overall, more people in the UK sample had studied an OSSAH subject compared with the US sample, and in the US more people had studied a LEM subject.
Table 7.1: Proportion of graduates holding a degree in each subject group in BCS70 and NLSY79
Field of study UK (BCS70) US (NLSY79)
N % N % STEM 633 32.1 503 31.6 LEM 373 18.9 395 25.5 OSSAH 962 49.0 673 42.9 Total 1,968 100 1,571 100 Family background
Parents’ education was the primary measure of family background used in this study. In BCS70, highest qualification levels were recorded, and in NLSY79 years of study within educational levels were recorded. I have attempted to match relative levels of education with qualifications (shown in table 7.2). In the final measure, parents who studied in post-compulsory education are classified as ‘highly educated.’ In both cases the highest qualification of both parents, or the
1 Whilst ‘law’ itself was not included in the US sample, pre-law and related subjects were (including 19
individuals). These were considered equivalent to law in the UK, as in both cases further study would be required to becoming a practicing lawyer, and would not automatically lead to a career in law.
138 qualification of the only parent, was used for analysis1. Overall parents of degree
holders in the US sample are more educated than the UK sample.
A number of other family background characteristics were included, such as eligibility for Free School Meals (in the UK), family income (in the US), whether participants had attended a private (fee paying) school, and whether they grew up without a biological or step father in the household (in the US this is measured at the first survey, in the UK at any point between 5, 10, and 16 years old). Ethnicity is also included in models, in the UK people are classified as white or Black and Minority Ethnicity (BME), due to low ethnic variation, and in the US people are classified as black, Hispanic, or non-black, non-Hispanic.
Table 7.2: Family background measures in the BCS70 and NLSY79
Classification Whole sample (%) Graduates (%) UK US UK US UK US High parental education A levels or above Some college or above 19.2 33.1 52.7 63.2 Low parental
education O-levels or below High school or below 80.8 66.9 47.3 36.8 Low income/ poverty Free school meals Bottom 10% income 13.3 11.1 4.1 4.3 Privately educated 1.5 5.8 8.4 11.6
Father (bio or step)
not in household At 5, 10 or 16 (any) interview At first 18.4 21.5 11.2 15.2
Earnings
Earnings for the BCS70 sample were computed from two variables: Gross earnings from work, and period earnings cover (for example weekly, monthly, yearly). Individuals whose period of earnings was not disclosed had to be coded as ‘missing.’ Yearly earnings for the NLSY79 sample used the truncated gross income from salary and wages. In both countries measures were taken when participants were 42 (on average for the NLSY79 sample). Yearly earnings were then converted to 2017 prices using CPI figures.
1 In the majority of cases, the father’s education was higher than the mother’s education. Robustness checks
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Gender
Models are run separately for men and women, because students’ gender strongly predicts the subjects they will choose to study throughout education. Girls and women are most likely to choose subjects that are people-focused and require greater language and communication skills (typically arts, humanities and health spheres), whilst male students are more likely to choose subjects with strong mathematical or technical components (Cech et al., 2011; England et al., 2007). Whilst this gendered pattern of subject choice is a persistent phenomenon across countries and time-points, there are differences in the extent of disparities across countries (Charles & Bradley, 2002).
Cognitive tests
For the UK measure a composite score was created using Principle Components Analysis (PCA), combining scores in age 5 and 10 tests including; the copying designs test, the human figure drawing test, the English Picture Vocabulary Test (EPVT), the complete a profile test, and the Schonell reading test, Edinburgh Reading Test and the Friendly Maths Test. Cronbach alpha for these items was 0.75. For more information on cognitive ability measures provided in BCS70 see Parsons (2014). Cognitive ability in NLSY79 was measured using scores from the Armed Forces Qualification Test (AFQT) taken around the beginning of the survey, calculated using 2006 standards. Both measures were standardized to mean zero, standard deviation one. Because the US measure of cognitive ability was taken in adolescence/ early adulthood, it is likely this measure will be more strongly associated with differences in upbringing (therefore more reflective of social background). It is also likely the case that both measures are highly reflective of circumstance, and should be interpreted as measures of achievement in a low stakes test rather than ‘innate’ ability.
University prestige
University type is strongly associated with outcomes after university, but is also associated with the subjects people choose to study (Bostwick, 2016); students may choose an easier (or less subscribed) subject to gain acceptance to a higher- ranking university. Because the returns to degrees by university are extremely varied, the decision was made to include a continuous rather than categorical
140 variable. Average UCAS points1 (pre university exam scores) of admitted students
were linked with the university. This acts as a measure of the competition for places at the university (for example, the competition for places at Oxbridge is much higher than other prestigious universities, and whilst universities may have similar entrance requirements their admitted students may have very different final UCAS scores), a proxy for individuals’ academic achievement, and a further signal to employers of higher ability.