In an op-ed for The Australian, League of Scholars CEO Paul McCarthy explores the data behind the dramatic growth in global positioning for Australian higher education institutions. The piece breaks down the multifactor data driving this success, highlighting the interconnected roles of revenue generation, research performance, and international talent acquisition

Key Insights Explored

• A Virtuous Cycle of Growth
  The analysis reveals a clear relationship between university revenue and global rankings. Rises in rankings lead to short-term revenue increases (typically with a one-year lag), largely stemming from student tuition. This revenue is then reinvested into high-quality research, creating a virtuous cycle where growing revenues fuel growing rankings, and vice versa.

• Long-Term Returns on Investment
  Increases in revenue are associated with longer-term increases in global rankings, though this process generally features a lag of eight to nine years. This near-decade gap between investment and reflected returns underscores the necessity for long-term thinking and planning within the higher education sector

• The Vital Overseas Talent Pipeline
  While capital investment is critical, universities rely heavily on talented people engaged in quality research and teaching. Attracting research talent from overseas is a vital component of Australia's higher education system. Over the past five years, academics moving from overseas accounted for approximately 40 per cent of all new research talent movements into Australian universities.

• Global Capital Efficiency
  Australia is currently the most capital-efficient country in the world in terms of its total R&D investment relative to the global positioning of its universities. For instance, Australia invests $20bn annually and places 12 universities in the Top 200, compared to countries like Canada which invests $29bn but only places 10.
  

Our Data Science Methodology
Behind the analysis is League of Scholars data. By tracking global research talent movements and correlating them with institutional revenue and historical ranking data, the team is developing a new multifactor AI model. This model predicts future likely university rankings given a variety of inputs, including revenue, talent, and reputation. This helps to better understand and predict how and where universities can best direct their current investments to yield maximum future returns.

Citation: McCarthy, Paul. "Our universities are growing in revenue and reputation." The Australian, February 15, 2023.