Challenging stereotypes in economics

The treatment (outreach sessions) will provide information on what economics is about, and what types of jobs you can do with an economics degree. The information is designed to challenge stereotypes about economics. The subject information will include both a description of what economics is about, emphasizing its breadth and real-world relevance, and an example of how economics can be used to think about a topical issue. Similarly, the jobs information will illustrate the breadth of different careers that you can do with an economics degree, emphasizing opportunities outside banking, including health and digital sectors.

The treatment also involves a role model in the form of a current economics student (an economics “champion”) who will deliver the information. Unlike previous role model interventions where the role models are deliberately chosen to be inspiring (Porter and Serra, 2020; Breda et al., 2021), the champions are chosen to be relatable in order to convey the impression to young people that economists are like them. The role models have two intended effects – first, a direct effect of challenging the stereotype of economists as pale, male and stale and second, an effect of making the information treatment more powerful by making the session more engaging and increasing the credibility of the information (= a reinforcement effect).

Challenging stereotypes in economics is arguably different from doing so in STEM because most young people have very limited or no experience of the subject before they have to make a choice about whether to study it (at age 16 or 18). Breda et al. (2021) test the effect of an inspirational role model intervention on students who are already studying STEM. These students have direct experience of STEM as a subject, but there are stereotypes about STEM careers. The intervention is also an attempt to change girls’ self-concept so that they see themselves as people who can do STEM. Similarly, Porter and Serra (2020) test the effect of inspirational role models on people who are already studying/ have direct experience of economics. Our intervention is primarily aimed at changing people’s perceptions of – and increasing their interest in – the subject.

2022-11-01

2023-07-15

The evaluation will have two stages - with different outcomes

• Stage 1 will evaluate the impact of the sessions on intentions and perceptions. The first stage of evaluation will be done at the end of 2022-23 on wave 1 schools (and will be updated at the end of 2023-24 on wave 2 schools). The data will come from a bespoke survey. Exploiting the random timing of the survey (at the start/ end of the session), the evaluation will capture the effect of attending a session on student intentions and perceptions.

• Stage 2 will evaluate the impact of the sessions on subject choices. This will be done using the administrative data for 2024-25. This is the first point at which we will observe the actual subject choices of wave 1 students (for A levels or degree choices). Here we will exploit the staggered roll-out design to implement a DiD approach that compares equivalent cohorts of students over time between schools that received the intervention in wave 1 and those who received it in wave 2 (so had the intervention provided to a different birth cohort). The evaluation will exploit administrative data (from the National Pupil Database).

Outcome variables capturing intentions/ perceptions are summarized in the table below:

Name Scale Statement
Intentions 0 – 10 How likely are you to study economics
Hard_n 0 – 10 Subject would be hard
Interesting_n 0 – 10 Subject would be interesting
Friends_n 0 – 10 I would make friends among people studying this subject
DoWell_n 0 – 10 I would do well in this subject
Enjoy_n 0 – 10 I would enjoy studying this subject
GoodJob_n 0 – 10 This subject would help me to get a well-paid job
EnjoyJob_n 0 – 10 This subject would help me to get a job I would enjoy

n = 1, 2, 3, 4, where 1 = Economics, 2 = Business, 3 = Psychology and 4 = Maths or Medicine (depending on whether asked to year 10 or year 12 students)

In total, we expect to have information across ~1,200 sessions in ~300 schools (covering approx. 36,000 students), split between wave 1 (2022-23) and wave 2 (2023-24) schools (and split between years 10 and 12).

Randomisation will be done in two stages. First, schools will be allocated into two waves: approx half the schools will be treated in year 1 (2022-23) and half in year 2 (2023-24). This allocation should be as good as random. We will use a DiD approach to evaluate the effect of the sessions on student choices in which the wave 2 schools act as a control for wave 1 schools. This evaluation will use admin (National Pupil Database) data which means that the wave 2 schools do not need to be contacted until 2023-24.

Second, randomisation across sessions (within schools). The champion delivering the session will administer a short survey to collect information on intentions and perceptions. This will be done (on a randomized basis) either at the start of a session (control) or at the end of a session (treatment). This will happen in both year 1 and year 2. Randomisation will be done in advance, but within-school rather than unconditionally across all classrooms: this reduces the risk of some schools ending up with all classrooms being surveyed before or after the session, which would prevent the use of school fixed effects. This second dimension of randomisation allows us to perform an evaluation of whether perceptions and intentions are shifted by the programme without having to separately survey “control” schools; the latter would be difficult to achieve in practice, since such schools have no incentive to allow us to run the survey. To analyse these data we will use a simple difference approach that compares responses from students receiving the survey after the intervention (T) to those receiving it before (C).

Randomization done in office by a computer

Stage 1
randomization at the session level
Stage 2
randomization at the school level

Yes

In total, we expect to have information for up to ~1,200 sessions in ~300 schools.
This is based on 30 universities taking part

approx. 36,000 students (based on 30 universities taking part)

stage 1
up to 600 sessions treatment (likely to be split by age)
up to 600 sessions control (likely to be split by age)


stage 2
150 schools treatment 1
150 schools control