COVID-19 means that universities should not be held to performance funding targets

6/4/20: Since this post was written, the minister has indicated that performance funding is being reconsidered due to COVID-19.

The government’s university performance funding scheme was always based on  questionable assumptions. Among them is the belief that we can reliably distinguish a university’s contribution to various outcome indicators from the other influences on those same numbers.

I’m sceptical enough of this in normal times. But COVID-19 means that, despite the extraordinary efforts of academics and other university staff to provide continuity of education and student support, three of the four performance indicators – graduate employment, student satisfaction, and equity group enrolment share – will or are likely to worsen compared to recent years. The fourth – attrition – will probably show a positive trend that also has little to do with university performance.

Due to the total amount of performance funding being linked to population growth, COVID-19 driven changes to migration levels will also reduce how much performance money is on offer.

Graduate employment

Let’s start with graduate employment, which has a 40 per cent weighting in the performance funding formula. As I argued in a blog post on Monday, previous record-bad employment results in 2014 will be significantly exceeded. Read More »

How should we measure SES for research students?

Last week the Department of Education issued a report on equity students enrolled in research higher degree programs. As those who have read my work over the years know, I think we have significant conceptual and empirical problems in measuring socioeconomic status in higher education. And these are even more significant for higher degree students than they are for undergraduates.

What this means is that even though the report’s overall conclusion, that high SES students are ‘over-represented’ in research degrees, must be true based on other empirical evidence and theory, its statement that ‘this data should … be used with caution’ is a warning that should be heeded.

Problem One: We are only using a geographic proxy indicator for SES, the ABS Index of Education and Occupation. A person is classified as low SES if they live in an area in which the population has relatively low levels of education and relatively high levels of people who are unemployed or work in lower-skill occupations.  But people with high levels of education and with high skill jobs live in otherwise low SES areas, and vice-versa.

Problem Two: We define as low SES people living in the lowest 25 per cent of areas by the Index of Education and Occupation. That is too small a share – the next quartile up is sociologically similar.

Problem Three: For research students, are we interested in their current socioeconomic status or their background? Regardless of their background, if they already have a degree (which they almost certainly do if they are in a research degree) and work in a professional job, as is quite likely to to be the case, then they are not going to be classed as low SES by the standard bureaucratic measures. And if they have moved to study and/or to be closer to professional job markets, then they will probably live in high SES areas.Read More »

The case for redefining low socioeconomic status in higher education

(This post also appears on the Grattan Institute blog.)

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.*

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Young people were less likely to enter higher education in the years after Whitlam than before. Demography and deficits were against them.

The three politicians with the greatest impact on higher education participation were Robert Menzies, John Dawkins and Julia Gillard. Yet I never hear anyone say, depending on their age, that “I only went to university because of Menzies/Dawkins/Gillard”.

Yet for Gough Whitlam the story is different. Last week USQ VC Geraldine Mackenzie was reported in the Australian saying “I was very fortunate to go to university after the Whitlam years when it was all free. Otherwise I may not have had that same opportunity.” And in February shadow education minister Tanya Plibersek told the Universities Australia conference that “it feels like every week, I meet someone in their 60s or 70s who reminds me about how Gough Whitlam was responsible for them going to university.”

I have argued before that Whitlam, Prime Minister 1972-1975, was very significant in the history of Australian higher education and has some lasting legacies. But I think the lesson from Whitlam’s time for now is that the biggest drivers of participation are supply-side policies on student places, and in particular how they interact with demography and fiscal policy. Because both these factors were significant in the free education era, the long-term trend towards increased higher education participation was interrupted.

Free education lasted from 1974 to 1986 (there were small charges in 1987 and 1988, before HECS started in 1989). The chart below shows that 19-year-old participation rates went up in 1976 but then fell and did not return to the previous peak until 1986. At the low point in 1982, the 19-year old higher education participation rate was 2 percentage points lower than it had been in 1975 (unfortunately, my data source starts in 1975).

19 year old participation

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Is government spending on tertiary education getting more progressive?

One long-made argument against tertiary education subsidies is that they are regressive. University students tend to come from more privileged backgrounds, and therefore high-income households receive a disproportionate share of government spending on higher education.

Based on gross household income, ABS data on the distribution of government benefits released today confirms that this is still true, as the chart below shows, although the ratio between the highest and lowest income quintiles is lower now than in the past.

Slide2

On an equivalised income basis, which takes into account household size, the distribution of spending is more even. This reflects the fact that although students tend to come from relatively affluent households, these also tend to be relatively large households containing a couple and their children. Making it disposable income makes it more even still, given progressive taxation. Read More »

Does ATAR measure more than SES?

One reason ATAR is criticised is that it tends to reproduce socioeconomic status.

One of ATAR’s critics complains that it is

“…more likely to measure the relative wealth of schools, more than a student’s abilities. In fact, using a students’ postcode might work just as well.”

Similarly, another critic says that “ATAR scores align more closely to postcode than they do to human potential…”.

While ATAR is not this deterministic – there are a range of abilities in every part of the SES spectrum – it’s true that ATAR correlates with family background, student home location and school attended (the scale of school effects after controlling for SES  is contested).

But that the ATAR achieved is influenced by a student’s social background does not mean it isn’t measuring something real about likely academic performance.

As the chart below shows, fail rates increase as ATARs go down across the socioeconomic spectrum. For a given ATAR, there is very little difference by SES.Grattan ATAR_chartdeck

Similarly, attrition after first year is more closely associated with ATAR than SES, as seen in the chart below. attrit_atar_ses

Although differing slightly in some of the detail, this is consistent with my posts earlier this year arguing that SES has most of its effects prior to post-school education, with  university access, performance and outcomes being similar for low SES students as other students: the same results, or small positive or negatives. It is also consistent with our recent Grattan report on dropping out, which found more narrowly, but also with more statistical rigour, that low SES in itself only had a small negative effect on completion rate.

 

 

 

 

Higher education inequality: do graduate outcomes differ by socioeconomic status?

In earlier posts in this series on inequality and higher education, I have suggested that the SES participation differences are largely driven by prior academic performance and that different SES groups seem to experience higher education in much the same way, but low SES students are less likely to complete their degrees. In this post, I will look at outcomes for the students who do complete their degrees.

First, are there differences in rates of getting a job? The 2017 Graduate Outcomes Survey finds that there are small differences. About four months after completing their bachelor degree, 73.6 per cent of high SES graduates who were looking for full-time work had found it, compared to 70.3 per cent of low SES graduates. However, of those who were working full time low SES students were slightly less likely to report not fully using their skills at work than high SES graduates (27.1 per cent compared to 28.9 per cent). It is difficult to say whether there is any direct SES effect in these results, as employment outcomes differ substantially by field of education, and SES differences in discipline choices could explain the results.

The Graduate Outcomes Survey also looks at starting salaries in the first full-time job after completing an undergraduate degree. Again, we find a small SES difference: the median starting salary for high-SES graduates in 2017 was $61,000, and for low SES graduates it was $60,000. This does not tell us whether there is any direct SES effect (such as not being able to access social networks to find professional jobs) or whether other factors such as discipline explain the result. A study using an earlier first year out survey had a limited control for discipline, as well as controls for weighted average marks, gender, and various other factors. It found no negative salary effect for low SES students, using a geographic measure of SES.

One possible cause of SES differences is that low SES students tend to attend the less prestigious universities, reflecting the school results issues reported in an earlier post. For example, 7.5 per cent of the University of Sydney’s students are low SES on a geographic measure, compared to 26.2 per cent of Western Sydney University students.

In theory, university attended should affect starting salaries. There are well-known differences in entry requirements between universities, which employers may take as a more reliable measure of ability than university marks, and employers may assume that the more prestigious universities have better teaching (can attract better staff, have more to spend – although student satisfaction surveys don’t support this conclusion). The first full-time job is when employers have to make greatest use of proxy indicators of potential, since most new graduates lack a track record in full-time skilled employment. Consistent with this, nearly 40 per cent of graduate employers say they have preferred institutions, mostly Group of Eight universities.

In practice, however, many studies have found no or small starting salary differences by university or university grouping (eg here, here, here, here and here). What course you take matters much more to your income than what university you attend. Read More »