Variable construction

Years of schooling and cognitive outcomes

The measure of schooling employed is the report of years of secondary schooling com- pleted. This is derived from the schooling question asking “How old were you when you left school?”. Then years of schooling is constructed as the age the respondent reports leaving school minus five.

Episodic memory—retrieving memories associated with specific events—was mea- sured by performance on an immediate and delayed word recall test. Memory is an im- portant early indicator of potential cognitive impairment, and word recall tests are used in cognitive impairment screening tests (Kimet al.,2014). A list of 10 words are read aloud by the computer, the respondent is to repeat these words in any order and the number cor- rectly recalled is recorded by the interviewer. This procedure is repeated (about 5 minutes) later in the module to measure delayed recall. Immediate and delayed word recall scores are highly correlated with clinical dementia diagnoses (Wu et al. , 2013). The number of words correctly recalled in each test were summed, to create a variable (Word Recall) ranging from 0 to 20.

The Serial 7 Subtraction test is a component of clinical screening instruments for cog- nitive impairment (i.e,., the Mini Mental State Examination (Crumet al., 1993) and the Cambridge Mental Disorders of the Elderly Examination (Rothet al.,1986)). In the Serial 7 test, respondents are asked to begin at 100 and subtract 7, five times. After each subtrac- tion, the respondent is again prompted by the interview to “take 7 away from that?”. The number of correct answers was summed to create a variable ranging from 0 to 5.

The Verbal Fluency test asked respondents to name as many animals as possible in one minute. In addition to testing semantic memory, this tests also executive function as, to perform well, it requires some level of abstract thinking and mental flexibility within a time limit. The test is from the cognitive assessment component of the Cambridge Mental

Human capital formation 1.3. DATA AND SETTING

Disorders of the Elderly Examination, an interview procedure for the diagnosis and mea- surement of dementia in the elderly (Roth et al. ,1986), and has been successfully been employed in extensions of the MMSE (Kimet al. ,2014). The number of animals listed ranges from 0 to 71.

The Numeric Ability test assessed ability to solve “every day” numerical problems. The Numeric Ability test asks the respondent five questions of increasing complexity, for example, the first question is as follows: “In a sale, a shop is selling all items at half price. Before the sale, a sofa costs £300. How much will it cost in the sale?". The number of questions correctly answered was summed to have a range of 0 to 5.

The distributions of the raw scores are presented in Appendix2.A. The continuous measures, Word Recall and Verbal Fluency, were standardised by subtracting the sample mean and dividing by the sample standard deviation, to faciliate interpretation and compa- rability with previous studies. The Serial 7 Subtraction and the Numeric Ability tests were dichotomised to create a binary variables. Subtractiontakes the value 1 for respondents

with 5 correct answers to the Serial 7 Subtraction, and zero otherwise. Numeracy takes

the value 1 for respondents with 4 or 5 correct answers to the Numeric Ability test, and zero otherwise.

Occupation variables

The mechanisms underlying the education gradient in cognitive function are inevitably complex and interacting. This paper aims to test one specific hypothesis suggested by theory, namely the role of occupation type and labour market participation patterns. in explaining the effect of schooling on cognitive performance, rather than aiming to exhaus- tively model all the channels which may be involved.

The first measure employed is the five-class National Statistics Socio-economic Classi- fication (NS-SEC) occupational classification. The five-class NS-SEC groups occupations defined by the Standard Occupation Classification into five categories: 1) Semi-routine; routine; never-worked and long-term unemployed; 2) Lower supervisory and technical oc- cupations; 3) Small employers and own account workers; 4) Intermediate occupations; 5) Higher professional; large employers, higher managerial and administrative occupations.

1.3. DATA AND SETTING CHAPTER 1. SCHOOLING AND COGNITION

The NS-SEC is available for both the first job chosen after leaving secondary school, and the current job (or previous job, if the respondent is currently out of the work). The chief focus is on the current, or most recent, occupation, which will capture effects associ- ated with the so-called “use-it-or-lose-it" hypothesis: continuing to engage in a stimulating occupation maintains cognitive reserve and stave off cognitive decline. As an additional measure, the first job is of interest as mechanism because the activity chosen immediately after secondary school is especially amenable to policy intervention. For instance, in the UK context, a current policy development has increased the minimum “participation age”, for which young people must remain in education or training, from 16 years to 18 years. This initial start may have longer run implications for labour market trajectories.

Previous occupation was disproportionately missing among those reporting they were long-term sick or disabled, or unemployed. For this group, information from the US em- ployment history module was used to ascertain their activity. Respondents to the US report an employment history of their economic activity status (e.g., full-time work, part-time, unemployed, receiving government benefits, etc.) from when they first left full-time edu- cation until their current spell. For those who did not report a current or previous labour market status, individuals who also reported being out of the paid work for at least 50% of their potential working life were coded as NS-SEC category 1 (Semi-routine; routine; never-worked and long-term unemployed).

In addition to the occupation type of first and current job, a final measure of occupation type relates directly to the usage of specific skill types, employing occupational skills pro- files developed byDickersonet al. (2012). Dickersonet al. (2012) have matched the UK SOC 2010 codes with the US Occupational Information Network (O*NET), a database characterising the skills, abilities, work characteristics of occupations. The O*NET ques- tionnaire is completed by workers and external job analysts. Over 250 questions are asked about job characteristics, ordescriptors, arranged into the following domains: education

and training, knowledge, skills, abilities, work activities, work context and work style. For each descriptor, both the level and importance of that item are elicited. The individual responses are averaged within occupations. Therefore, for each individual, they do not

Human capital formation 1.3. DATA AND SETTING

necessarily reflect the skills actually used in a job.

The literature on occupation, education and cognitive outcomes has raised the hypoth- esis that especially demanding or complex mental tasks may play an important role in maintaining cognitive performance (Fisheret al. , 2014). One specific example of these types of complex skills (chosen partly due to data availability) are those used in what are commonly characterised as STEM occupations. These roles require substantively com- plex, technical expertise—involving logic, reasoning and numeracy. Examining the role of these specific types of skills contributes to the literature assessing the role of skills type in determining cognitive ageing, and provides a useful complement to the occupation type measures described above.

The measure of STEM-skill usage, henceforth termed technical skill, uses variables

from the Abilities and Skills from the matched O*NET data (the questions in the Ability and Skill domains were filled out by external job analysts, rather than the job incumbents themselves). This measure was matched to the occupation of first job after leaving school.2

The Abilities items used are: deductive reasoning; information ordering; mathematical reasoning; number facility. The Skills items are: mathematics; science; technology de- sign; programming. For each item, there is a variable rating the level of each decriptor used in the job, and its importance. The average of the level and importance variables across the Skills and Abilities items identified above are used as a simple continuous measure, where a higher value indicates greater usage of these skills—on average—in an occupation.

Analytical sample

All three subsamples of the US were employed: the General Population Sample, con- tinuing BHPS participants, and the Ethnic Minority Boost sample. Survey weights were employed throughout the analyses, which weights adjust for unit non-response—the com- bined probabilities of being selected into the BHPS, GPS and EMB and continuing to Wave 3 of the survey—and the complex survey design.

Since the location of school was not available among the cohorts considered, it was not

2_{At the time of writing, the current occupation variable in the US was coded as SOC2000. Only when}

respondents switched to a new job, the new job was coded as SOC2010. Therefore it was not possible to match the O*NET measure to complete data on current occupation.