Most universities performed better than expected

INSIGHTS & RESOURCES

Most universities performed better than expected in the year of crisis

The Australian 
by Keith Houghton
30 March 2022

Key Takeaways:

  1. Initial fears of the pandemic severely impacting universities were disproven, as many institutions successfully adapted to the situation.
  2. Universities engaged in various strategies, such as staff retrenchments, wage freezes, and campus closures, to mitigate the impact of
    COVID-19.
  3. The Research and Education Efficiency Frontier (REEF) approach measured university productivity, and overall productivity at the end of 2020 was stronger than the previous year.
  4. Only eight out of the universities analyzed experienced declining productivity in 2020, with 29 showing improvement.
  5. Productivity growth across the sector averaged 4.5%, which was impressive compared to previous years.
  6. The highest productivity growth occurred in the early 2000s and the period from 2008 to 2013.
  7. Some universities, such as Monash, University of Technology Sydney, University of NSW, University of Melbourne, and University of Queensland, performed above average, while only one Group of Eight university showed a decline.

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Full article:

Last month, university data for 2020 was released by Acting Education Minister Stuart Robert. This first official data reveals the effects of the pandemic on Australia’s universities.

Many had proselytised that Covid-19 would be the ruin of universities, and certain commentators courageously listed selected universities as being “high risk”. While the list proved inaccurate, many were apprehensive over the damage that Covid would do to the long-term health of Australia’s universities.

While the commentary at the time was predominantly negative, many in the sector simply set about doing what they could to survive and craft a positive future. Results from empirical analysis based on the Research and Education Efficiency Frontier productivity modelling technique show that, to a large extent, they succeeded.

There has been widespread engagement by university executives, senior academic and non-academic staff and others on approaches to dealing with the pandemic. During 2020, a variety of solutions were implemented.

These ranged from large-scale staff retrenchments to wage freezes and more. Whole campuses were closed and outsourcing arrangements were terminated or greatly scaled back. The scale and urgency of the response were apparent.

The 2020 data shows a range of different strategies proved successful. Not only did the “high risk” universities all survive but several prospered.

Indeed, the REEF approach, which measures in an integrated way university productivity in research and education, shows the sector reinvented itself where overall productivity at the end of 2020 was stronger than 12 months earlier.

However, the effort needed was considerable, and the sacri­fices were many – perhaps most noticeably for sessional academic staff and, of course, the pain felt by domestic and international students was considerable.

Of the universities analysed, only eight suffered declining productivity between 2019 and 2020, with 29 showing improvement.

Productivity growth across the sector averaged 4.5 per cent across the year. Compared with previous years, this is impressive. In 2019, university productivity improved by a meagre 1.2 per cent. Between 2016 and 2018, average productivity improved by about 1 per cent a year. The long-term average from 2001 to 2020 was about 3.5 per cent. The sector’s highest level of productivity growth occurred in the early 2000s and the period from 2008 to 2013.

Of the eight institutions that suffered a productivity decline, five showed decreasing research publication rates (and across the sector only seven declined). The average increase in university publication rates for 2020 is 5.39 per cent.

Above-average universities include Monash, the University of Technology Sydney, the University of NSW, the University of Melbourne and the University of Queensland, among others. Indeed, only one Group of Eight university showed a decline.

 

Using expenditure as the key input variable in the REEF methodology, the universities that comprised the “efficiency frontier” – that is, the universities that produced the largest quantum of teaching and research outcomes, in their own preferred mix of these two activities, per million dollars of expenditure – are the University of Western Australia, with a stronger research intensity; Victoria University, with a teaching emphasis; and the University of Wollongong, with a balance between the two. All three also occupied the frontier in 2019.

If one looks not at expenditure as the input variable but academic staffing, UWA and VU are again on the frontier as exemplar institutions. But, possibly via some combination of innovation and tenacity or simple good management, Charles Darwin University, Western Sydney University and Curtin University are also on the frontier. The differing membership between these two productivity measures provides some guidance on where productivity strengths exist.

For CDU, WSU and Curtin being on the frontier for academic staffing and not for expenditure points to possible productivity enhancement opportunities in areas other than academic staffing. These might be structural, policy, and/or infrastructure, among others.

Returning to expenditure, the sector, in general, has done an impressive job in trimming expenses to reflect declining revenue. Of the eight universities showing declining productivity, only one reported cutting expenses in 2020 compared with 2019. Across the entire sector, the equivalent full-time student load declined, on average, only 1 per cent; however, the spread is uneven. The largest reported decline was Federation University, with a 12 per cent decrease. The strongest positive growth was CDU at 18 per cent.

There were five universities where productivity growth exceeded 10 per cent. Two are Go8 members, two are in the Innovative Research Universities group, and one is a Regional Universities Network member.

The outcome for UNSW is particularly striking. It had achieved little or even negative productivity growth in the years preceding, but in 2020 it experienced a productivity bounce of more than 11 per cent, fuelled in part by a substantial lift in the research publication rate. There was no measurable decline in research quality. The chart below shows the 2001-20 productivity history of UNSW.

 

Of the eight institutions that declined in productivity, only one is Go8 affiliated, two each are aligned with RUN and the Australian Technology Network, and three institutions are unaligned.

Thanks largely to the heroic effort of university executives (including several who cut their own salaries), academic and non-academic staff, students and other key stakeholders, Australian universities survived the first wave of the effects of Covid.

While there was considerable pain, tension and, by several measures, an adverse impact on teaching quality and the working lives of many, results for productivity growth are consistent with a university sector that has withstood these challenges.

More especially, the sector appears to have prepared itself well for a future that may, in time, return to some form of normality.

Keith Houghton is chief academic strategist at Higher Education and Research Group

There is growing anticipation that the federal government’s response to the Universities Accord review’s final report will come soon. Given this and the fact that the budget is less than a month away, it is timely to review one of the final report’s key insights.

Recently released analysis finds that one large Group of Eight university outperformed other public universities in its research and education productivity outcomes during the pandemic.

The joint and common cost problem arises where there are two or more outputs that arise from costs that are shared in the production of these outputs. In many situations, the ability to assign costs to these two or more outputs is not complex. But there are instances where it is highly complex. In these situations, there is a need to use advanced analytics to provide a valid and reliable estimate of costs.

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