RDP 2021-06: What Is Driving Participation and Diversity Trends in Economics? A Survey of High School Students 3. Empirical Approach and Results

3.1 Which school and individual characteristics are most strongly associated with choosing Economics?

To ascertain the school and individual characteristics that are most strongly associated with choosing Economics, we consider a number of model specifications (Table 3).

Table 3: Model Specifications
Dependent variable Data Method Interpretation of coefficients
EconSchoolj = 1 if school j has at least 1 Economics student; 0 otherwise Year 12 enrolments for all NSW high schools; administrative data Probit The effect of school characteristics on the likelihood of a school teaching Economics, all else equal. May reflect factors from the supply side (school's inclination to offer Economics as a subject choice) and demand side (student's inclination to choose Economics).
EconShar e j = Econenrolment s j HSCenrolment s j where Econ enrolmentsj is the number of Economics enrolments and HSC enrolmentsj is the total number of Year 12 students (awarded a HSC)
EconSharej > 0if EconSchoolj = 1;
EconSharej = 0if EconSchoolj = 0
Year 12 enrolments for all NSW high schools; administrative data Heckman The effect of school characteristics on the proportion of students taking Economics, all else equal. Reflects demand-side factors (student's inclination to choose Economics).
EconStudentij = 1 if student i from school j is an Economics student; 0 otherwise
EconStudentij = 0 if EconSchoolj = 0
Year 11 and 12 students in all sampled schools; survey data (supplemented with administrative school-level details matched to the student record) Heckprobit The effect of individual and school characteristics on the likelihood of a student choosing Economics), all else equal. Reflects demand-side factors (student's inclination to choose Economics).

Utilising administrative data on all schools in NSW, we first examine the importance of school characteristics for whether or not a school teaches Economics (Table 4, column (1)). For a school to be teaching Economics, both supply and demand conditions must be met: (i) they offered Economics as a subject choice (i.e. they were not constrained by a teacher/resource shortage); and (ii) students selected Economics (i.e. enough students chose Economics to meet a minimum class size). As such, the coefficients in our first specification (column (1)) may reflect factors from both the school supply side and student demand side. We find that schools are significantly more likely to teach Economics if they have a higher socio-economic status, a larger Year 12 cohort, teach a larger variety of subjects, or are all boys. For example, a 100 point (i.e. 1 standard deviation) increase in ICSEA is associated with a 16 percentage point increase in the likelihood of studying Economics, holding all other variables at their means. All else equal, school sector (government versus non-government) and location (regional versus metro) are not significant factors in the likelihood of a school teaching Economics.

Table 4: Likelihood of Studying Economics
  (1)
EconSchoolj
(2)
EconSharej
(3)
EconStudentij
(4)
EconStudentij
(5)
EconStudentij
(6)
EconStudentij
Male     0.10** 0.09*** 0.07** 0.07***
Bilingual     0.03 0.03 0.02 0.02
Interest         0.06*** 0.05***
Understanding         0.09*** 0.08***
ATAR         0.04 0.04
Non-government 0.02 −3.42*** −0.16** −0.15* −0.11 −0.11
Regional −0.02 −1.62 0.13 0.10 0.08 0.06
ICSEA (/100) 0.16*** 8.01*** 0.14* 0.16** 0.09 0.13*
All boys school 0.25*** 6.51*** −0.11 −0.05 −0.20 −0.10*
All girls school 0.05 −2.53*** −0.08 −0.06 −0.22* −0.17***
Subjects taught 0.01*** 0.04        
Subjects taught (ordinal)     −0.06 −0.04 −0.07 −0.04*
Year 12 cohort size
(/100)
0.15***          
Constant   −76.69***        
Observations 768 768 1,995 1,238 1,141 719
of which selected   316 1,238   719  
Year(s) 12 12 11 & 12 11 & 12 11 & 12 11 & 12
Method Probit Heckman Heckprobit Probit Heckprobit Probit
Wald χ2   31.32*** 0.46   1.57  
School-clustered standard errors     Yes Yes Yes Yes
Pseudo R2 0.50***     0.13***   0.31***
Log likelihood   1,255.49*** −863.48   −481.11  

Notes: Column (2) displays coefficients, all other columns display marginal effects; Wald χ2 is the chi-squared from a Wald test of independence of the outcome and selection equations (H0 : ρ = 0); *,** and *** denotes statistical significance at the 10, 5 and 1 per cent levels, respectively

Sources: Australian Curriculum, Assessment and Reporting Authority; NSW Education Standards Authority; RBA

To isolate the student demand side we examine variation in the proportion of students who take Economics (Economics enrolments as a share of the Year 12 cohort) within schools that offer Economics.[10] We estimate a Heckman model to account for the selection effect of excluding schools where Economics is not offered. The size of the Year 12 cohort is used as an exclusion restriction. All else equal, larger schools are more likely to offer Economics, and we argue that the cohort size is unlikely to affect student demand for Economics. However, larger schools may offer a greater variety of subjects, which could affect student demand for Economics, so we include the number of subjects offered as an additional control in the selection and outcome equations. The Wald test of independence of the selection and outcome equations confirms the significance of a selection effect (Table B1).

Isolating the student demand side, we find that higher socio-economic status is associated with increased demand for Economics amongst students (Table 4, column (2)); this suggests that the higher likelihood of Economics being taught at schools with higher socio-economic status (Table 4, column (1)) is not just attributable to school supply-side factors. Non-government schools experience lower demand for Economics relative to government schools, holding socio-economic status and other characteristics constant. Relative to co-ed schools, all boys schools are associated with greater student demand for Economics, and all girls schools are associated with less.

A key contribution of the student survey data is the ability to isolate the individual student characteristics from the schools' characteristics that relate to students' demand for Economics. We do this using the sample of students at schools that teach Economics, accounting for sample selection. We estimate a probit model with sample selection (heckprobit), using the size of the Year 12 cohort as an exclusion restriction (Table 4, columns (3) and (5)). The Year 12 cohort size in this model is a series of dummy variables representing size categories (rather than a continuous variable as used in the school-level estimation).[11] Standard errors are clustered by school accounting for the stratified approach to sampling.

The heckprobit estimation fails to reject the null hypothesis of independence of the selection and outcome equations; this is surprising given the significant selection effect identified using the administrative data on the population of schools (Table B1). This may reflect the lack of variation from using dummy variables rather than continuous variables when identifying the selection effect, or the smaller sample of schools included in the survey sample (particularly for Year 11 and 12 students; Table 2), rather than an absence of selection.[12] As a comparison, the model is estimated as a probit (without sample selection) using the sample of schools where Economics is taught (Table 4, columns (4) and (6)).

These estimates imply that males are more likely to choose Economics than females, even when controlling for school characteristics. This clarifies that the greater prominence of males in Economics (Figure 1) reflects differences by sex, and is not just a product of confounding school factors. We also control for bilingual status, as a proxy for ethnicity, though this is not significant. We find there is a greater likelihood of males and students from a higher socio-economic background studying Economics, even when controlling for other student characteristics (Table 4, columns (5) and (6)). For example, these results are robust to the inclusion of variables for perceived interest in Economics, perceived understanding of Economics, and whether they take into account how well a subject scales for the Australian Tertiary Admission Rank (ATAR).[13]

We find that when controlling for perceived understanding and interest in Economics, the marginal effects of being male are reduced slightly but remain significant. This provides some indication that only part of the reason that males are more likely to study Economics than females is because they tend to be more interested or have a better perceived understanding of Economics. Including these variables also renders the marginal effect of school sector insignificant. A further analysis of differences in student perceptions is explored in the following section.

Overall, we conclude that students' demand for Economics is strongly associated with socio-economic background and sex, confirming that the aggregate picture of diversity in enrolments is not driven by any confounding factors that might have been at play.

3.2 What are students' perceptions of Economics?

A novel feature of the survey data is students' perceptions of Economics, regardless of whether or not they chose it, shedding light on the reasons for lower participation and diversity in Economics enrolments. We asked students to consider a range of statements about Economics, and to indicate the extent to which they agree or disagree with each on a five-point Likert scale (from ‘strongly disagree’ to ‘strongly agree’).

What positive perceptions do students have about Economics? Students typically believe that economics can be used for social good, isn't all about money and that an economics degree leads to a wide range of career options (Table 5). They also do not tend to believe economics is more of a career for men. Students typically believe they could do well at Economics in Year 11 and 12 and that it scales well for the ATAR. They perceive that Economics provides skills for everyday life. Interestingly, these positive perceptions are in contrast to findings from surveys of Australian university students (Lewis and Norris 1997; Ward et al 2000; Azzalini and Hopkins 2002).

What negative perceptions do students have about Economics? Students generally do not perceive Economics as interesting and have little desire to know more about it. Economics is perceived as having a heavier workload than most other Year 11 and 12 subjects. And while Economics is seen as providing skills and tools for everyday life, students generally indicated they prefer to study Business Studies because they think it will be more useful for their future and more interesting. These results are in line with insights from liaison and the revealed preference for Business Studies over Economics in enrolment data. While students perceive an economics degree to lead to a wide range of career opportunities, students are less likely to have a clear understanding of Economics (the subject) or the careers available if they were to choose Economics (as a subject).

Table 5: Perceptions of Economics – Descriptive Statistics
Short label Full survey statement(a) Net balance(b) (%) Strong net balance(c) (%)
Understanding I have a good understanding of what Economics is 6*** −3***
Interesting I find Economics interesting as a subject 0 −4***
Could do well I think I could do well in Economics if I put my mind to it 42*** 16***
Clear idea of how good I have a clear idea of whether I would be good at Economics 16*** 2**
Want to know more I want to know more about Economics 11*** 1
Risk because I don't know It's a risk to study Economics because I don't know what it's about 9*** 3***
Teachers promote There are teachers at my school who promote the study of Economics 15*** 2***
Business easier I would prefer to study Business Studies over Economics because I think it's easier 11*** 3***
Business more useful I would prefer to study Business Studies over Economics because I think it will be more useful for my future 26*** 10***
Business more interesting I would prefer to study Business Studies over Economics because I think it's more interesting 22*** 9***
Clear idea of careers I have a clear idea of the careers available to me if I were to study Economics 5*** −2***
Wide range of careers An economics degree leads to a wide range of career options(d) 44*** 11***
More a career for men Economics is a career option for men more than women(d) −21*** −16***
Need intelligence You need to be intelligent to study Economics 20*** 3***
Need maths You need to be good at Maths to study Economics 34*** 8***
Heavier workload Economics is a subject that has a heavier workload in comparison to most other Year 11 and 12 subjects 30*** 9***
Scales well for ATAR Economics is a subject that scales well for the ATAR 40*** 11***
Important It's important to know about Economics in today's society 55*** 17***
Skills for everyday life Studying Economics will teach me skills and tools I can use in my everyday life 45*** 11***
Used for social good Economics can be used for social good(d) 50*** 13***
Not all about money Economics is not all about money(d) 30*** 7***

Notes: *,** and *** denotes statistical significance at the 10, 5 and 1 per cent levels, respectively
(a) Statements relate to the study of Economics in Year 11 and 12, unless indicated otherwise
(b) Share of respondents selecting ‘Tend to agree’ or ‘Strongly agree’ minus the share of respondents selecting ‘Tend to disagree’ or ‘Strongly disagree’
(c) Share of respondents selecting ‘Strongly agree’ minus the share of respondents selecting ‘Strongly disagree’
(d) Statement related to economics in general

Source: RBA

3.3 What differences in perceptions of Economics exist by sex and socio-economic background?

To investigate what attitudes and beliefs may underpin the difference in likelihood of studying Economics by sex and socio-economic background, we consider a model with the dependent variable Perceptionij, which takes the values ‘1 – Strongly disagree’, ‘2 – Tend to disagree’, ‘3 – Neither agree nor disagree’, ‘4 – Tend to agree’ or ‘5 – Strongly agree’ for each perception statement. We estimate an ordered probit model with school-level and student-level variables. These questions are asked to Year 10, 11 and 12 students.

We find that females were less likely than males to ‘have a good understanding of what Economics is’, ‘find Economics interesting as a subject’ or ‘want to know more about Economics’ (Table 6). For example, males are 4 percentage points more likely than females to strongly agree with the statement ‘I have a good understanding of what Economics is’, holding all other variables at their means. Females are also less likely than males to feel ‘I could do well in Economics if I put my mind to it’ or ‘have a clear idea of whether I would be good at Economics’, and more likely to believe that Economics is ‘a risk to study because I don’t know what it is about'. Furthermore, female students perceived that teachers were less likely to promote Economics as a subject. Females were also more likely than males to perceive Business Studies as easier, more useful and more interesting than Economics. In terms of career development, females were less likely to have clear or positive perceptions of career opportunities from studying economics. However, females were less likely to perceive ‘economics is a career option for men more than women’. Importantly, these findings remained even when accounting for whether schools did or did not offer Economics in their schools.

Many of these trends were also present for students in schools with a lower socio-economic background (compared with higher socio-economic). In particular, students from a lower socio-economic background are less likely to feel ‘I could do well in Economics if I put my mind to it’ or ‘I have a clear idea of whether I would be good at Economics’. Students from a lower socio-economic background were also less likely to ‘have a good understanding of what Economics is’, or have a clear perception of career opportunities from studying economics. These students are more likely to believe that ‘it is a risk to study Economics because I don't know what it's about’.

The finding that students who are female (compared with male) and from a lower socio-economic background (compared with higher socio-economic) are less likely to ‘have a good understanding of what Economics is’ is one possible reason for differences in other perceptions about Economics. If this were the case, it would imply that interventions that increased understanding would be an efficient way to eliminate gaps in perceptions more broadly. To further investigate the relationship between understanding and perceptions, we re-estimate the regressions controlling for students' perceived understanding of Economics.

Table 6: Perceptions of Economics – Regression Results
Average marginal effects of ordered probit
  Understanding Interesting Could do well Clear idea of how good Want to know more Risk because I don't know Teachers promote
Male 0.04*** 0.05*** 0.05***(a) 0.04*** 0.04***(a) −0.03*** 0.03***(a)
ICSEA (/100) 0.01*** −0.00 0.03*** 0.01**(a) −0.01 −0.03*** 0.05***
Bilingual 0.02*** 0.05*** 0.06*** 0.02** 0.05*** 0.01 0.02
Non-govt −0.02*** −0.00 0.02 0.00 −0.00 0.02*** −0.05**
All boys school 0.02*** 0.04*** 0.09*** 0.02 0.06*** −0.02 0.03
All girls school −0.01 −0.01 −0.01 −0.00 −0.01 0.00 −0.01
Observations 3,897 3,708 3,812 3,463 3,998 3,839 3,547
Pseudo R2 0.014 0.017 0.020 0.011 0.012 0.007 0.018
  Business easier Business more useful Business more interesting Clear idea of careers Wide range of careers More a career for men
Male −0.03*** −0.05*** −0.05*** 0.04*** 0.02**(a) 0.02***
ICSEA (/100) −0.01 −0.03*** −0.02 0.01**(a) 0.01 −0.01***
Bilingual 0.02** 0.01 −0.00 0.03*** 0.03** 0.01*
Non-govt 0.00 0.02 0.01 −0.02* 0.02 −0.01
All boys school −0.01 −0.00 −0.00 0.04*** 0.05*** 0.01
All girls school 0.03*** 0.01 0.02 0.01 0.01 0.00
Observations 3,605 3,691 3,705 3,561 3,290 3,624
Pseudo R2 0.005 0.005 0.004 0.015 0.008 0.005
  Need intelligence Need maths Heavier workload Scales well for ATAR Important Skills for everyday life Used for social good Not all about money
Male 0.01 −0.00 −0.00 0.01 0.02 0.01 0.01 −0.01
ICSEA (/100) 0.00 −0.01 0.01 0.01 0.02*(a) 0.01 0.01 0.01
Bilingual 0.01** 0.03*** 0.03*** 0.04*** 0.05*** 0.02* 0.04*** 0.04***
Non-govt −0.01 −0.00 −0.00 0.00 0.01 0.03** 0.02 0.00
All boys school 0.00 −0.02 0.06*** 0.06*** 0.03* 0.04** 0.05*** 0.02
All girls school 0.00 0.01 0.01 0.01 −0.01 0.00 −0.02 −0.01
Observations 3,749 3,649 3,028 2,796 3,812 3,698 3,525 3,479
Pseudo R2 0.001 0.004 0.008 0.009 0.007 0.005 0.010 0.004

Notes: Calculated at ‘5 – Strongly agree’; results are robust to calculating at ‘1 – Strongly disagree’; *,** and *** denotes statistical significance at the 10, 5 and 1 per cent levels, respectively; robust standard errors clustered at the school level
(a) ‘Male’ or ‘ICSEA’ effect is no longer statistically significant when controlling for perceived understanding of Economics

Sources: Australian Curriculum, Assessment and Reporting Authority; NSW Education Standards Authority; RBA

Some of the differences between sex and socio-economic background are no longer statistically significant once accounting for perceived understanding (see results with (a) superscript in Table 6). In particular, accounting for a lower perceived understanding of Economics eliminates the sex difference in the desire to ‘want to know more about Economics’, students' perceptions of teachers promoting Economics as a subject, and perceptions that ‘an economics degree leads to a wide range of career options’. Similarly, controlling for a lower perceived understanding of Economics eliminates differences between students from different socio-economic backgrounds in clarity of career opportunities from studying economics.

There still remains, however, a gap to be closed. Females are less likely than males to ‘have a clear idea of whether I would be good at Economics’ or ‘have a clear idea of the careers available to me if I were to study Economics’, and students from a lower socio-economic background are less likely to feel ‘I could do well in Economics if I put my mind to it’. It remains that females and students from a lower socio-economic background are more likely to believe that it is ‘a risk to study Economics because I don't know what it's about’ and have favourable perceptions of Business Studies. Furthermore, students from a lower socio-economic background are less likely to report that teachers at their school promote the study of Economics. And it also remains that males are more likely to find Economics interesting, controlling for a lower perceived understanding of Economics.

To shed light on whether the nature of the topics included in the Year 11 and 12 Economics syllabus appeal more to males than females, the survey gave students a list of Economics topics (based on the Economics syllabus) and asked them to select the 2 that were most interesting. The data reveal that females and males do differ in the topics they find most interesting (Figure 4). In particular, female students were more likely to cite ‘identifying problems’, whereas male students were more likely to cite the ‘share market’.

Figure 4: Topics of Interest
Share of Year 10–12 students
Figure 4: Topics of Interest

Note: * denotes statistically significant difference at the 5 per cent level after controlling for school type, socio-economic status and language

Source: RBA

Footnotes

The administrative data available do not allow us to identify schools where Economics was offered but not taught due to a lack of student demand. We instead take Economics being taught (at least one Economics student enrolled) as a proxy for Economics beings offered. [10]

In matching the school-level information to the survey dataset, it was necessary for the HSC cohort size and number of subjects taught variables to be collapsed into 5 categories to prevent identification of individual schools in the dataset (a requirement of the ethics approval). [11]

When we exclude the variable that controls for number of subjects, the results are qualitatively similar. [12]

The importance placed on ATAR scaling relates to students' responses to what they consider when selecting subjects in general; see Livermore and Major (2020) for more details on factors students consider when selecting subjects. The results are also robust to the inclusion of controls for the other subjects studied. [13]