Since the early 1990s, higher education statistics have defined someone as of low socio-economic status if they are from a region classified in the lowest 25 per cent in Australia according to the ABS Index of Education and Occupation.
Universities are rewarded for enrolling students from these areas. A participation fund of about $135 million is distributed between universities according to their share of low SES students. A university’s success in the new performance-funding scheme will depend in part on it enrolling low-SES students.
The low-SES definition has been criticised over the years, usually because it often misclassifies individuals. High-SES people live in low-SES areas, and vice versa. But we need a balance between precision and practicalities. To recruit additional low-SES students, universities need to first identify them. Geographic areas are easier to find than individuals with particular family characteristics.
Although geographic SES measures should be retained, the lowest 25 per cent definition needs reconsidering. As the chart below shows, in 2016 higher education participation rates in the lowest quartile were not clearly distinct from the second quartile. Generally, the weighted average participation/attainment rates at the ABS SA2 geographic level cluster at around 25 per cent for people aged 18-23 across the lowest 50 per cent of areas by the Index of Education and Occupation. An SA2 is roughly the size of a postcode. The smaller SA1 is used for defining low SES, but it is not available using the 5-year prior residence question.
The chart uses the addresses of young people five years previously to assess their socio-economic rating. This avoids wrongly classifying students who move to study. Addresses near universities usually rate very highly on the Index of Education and Occupation.
The overall similar weighed averages are because the second quartile is sociologically similar to the first quartile.
Across the entire lowest 50 per cent of regions by the Index of Education and Occupation, the vast majority of people age 40-59 don’t have a degree. This is the age category most likely to be the parents of people seeking their initial post-school education.
Unsurprisingly given these educational patterns, across the lowest deciles at least two-thirds of working people in these ages work in occupations that typically require an upper-vocational qualification or less.
Most young people in the lower half of areas by the Index of Education and Occupation will grow up in homes where nobody has direct experience of university. Their most visible occupational role models will usually hold jobs that do not require a higher education qualification.
What of the exceptions? Some of the outliers can be explained by regional/metro differences. Students from regional areas are less likely to go to university than their city peers after accounting for socio-economic status.
But the main reason for the exceptions is cultural differences in attitudes to education, observed in participation rates by language background.
The high-participation outliers are suburbs with large Asian populations. For example Springvale in Melbourne’s south-east is in the lowest 10 per cent of areas according to the Index of Education and Occupation. But it has a large Asian or southern Asian population, with 27 per cent of 18-23 year-olds in 2016 reporting their ancestry as Vietnamese, 20 per cent as Chinese, and 10 per cent as Indian. In 2016, 51 per cent of this age group from Springvale were at university or already had a degree, putting them at the same level as Ainslie in the ACT, which is in the top 10 per cent of areas by the Index of Education and Occupation.
The low-participation outliers are, unfortunately but not unexpectedly, remote areas with large Indigenous populations. More than 500 18-23 year olds in the 2016 Census reported living in East Arnhem in the Northern Territory five years previously, but none of them were at university. As the chart shows, there are other zero or very-low percentage point participation/attainment areas.
These differences suggest the Index of Education and Occupation is an inefficient way of defining low SES for educational purposes. If the policy goal is to increase enrolments from low-SES populations (financial and reputational rewards go to universities that achieve this), does it make sense to encourage universities to focus on areas that already have very high participation rates?
Wouldn’t it be better to pay more attention to areas that for whatever reason have low participation rates, even if quirks of the Index of Education and Occupation formula give them SES ratings that disqualify them from low-SES rewards? Why use proxy data when we have direct measures of whether an area has low participation in higher education or not?
In many cases, as the second chart shows, the same areas would be classified as disadvantaged under either system. But if we defined low-participation area as places where 25 per cent or less of the youth cohort attend university, we would include many second-quartile Index of Education and Occupation areas, as well as some higher-quartile areas. We would still get mismatch at an individual level, but university resources would be better directed to areas of need than they are now.