The effect of national higher education initiatives on university rankings

The study addresses how national higher education initiatives—government-led programs intended to elevate university quality and global competitiveness—affect world university rankings. Motivated by the increasing emphasis on human capital and innovation, many countries have launched excellence initiatives with explicit ranking-related goals. World university rankings provide a relatively objective and quantifiable benchmark to assess such policies. The paper poses three key questions: (1) What is the impact of national higher education initiatives on university rankings? (2) To what extent do universities from different countries and regions see rank improvements after participating? (3) What explains cross-country and regional heterogeneity in effects? The introduction situates these questions within the broader policy landscape, noting multiple national programs (e.g., China’s 211/985/Double First-Class, South Korea’s BK21/WCU, Japan’s COE/Global COE/Top Global University, Germany’s Exzellenzinitiative, France’s IdEx, Russia’s Project 5-100, etc.) and argues that rankings are a suitable tool to evaluate their effectiveness.

University quality and ranking performance are shaped by national- and institution-level factors, including faculty strength, infrastructure, funding, governance, economic capacity, R&D expenditure, political stability, institutions, and language. A central determinant is the higher education management model: government-controlled versus government-supervised. Government-controlled systems (common in continental Europe, Japan, South Korea) involve stronger state intervention, facilitating concentrated investments via initiatives; government-supervised systems (e.g., US, UK, Canada) confer greater autonomy. Scholars debate their merits: supervised models mitigate excessive control and foster elite institutions; controlled models enable rapid resource concentration and ranking gains. International rankings (THE, QS, US News, ARWU) enable comparative assessments and often align with initiative performance metrics. Prior evaluations of initiatives have focused on publications, productivity, efficiency, student sorting, and perceived quality, but these measure partial aspects. Using global rankings offers a more comprehensive lens. The literature lacks broad, cross-country comparisons of initiatives’ ranking impacts; this study fills that gap by employing QS and ARWU rankings to evaluate effects and heterogeneity.

Design: Countries were classified as treated if a formal, government-supported initiative aimed at improving international competitiveness of higher education existed; otherwise, they were controls. Given staggered adoption across countries, the study used a Staggered Difference-in-Differences (DID) model to estimate the effect of initiatives on rankings. Model: y_it = β0 + β1 T + β2 X_i + γ_t + η_i + ε_it, where y_it denotes a university’s world ranking position and its rank improvement; T is a treatment indicator equal to 1 for years in which a university’s country has an initiative; X_i includes national-level controls; γ_t are time fixed effects; η_i are country fixed effects; ε_it is the error term. β1 captures the average treatment effect of initiatives. Outcomes and transformations: Because movement near the top of rankings is harder than at lower tiers, the study used logarithms of world ranking positions and focused on percent changes. It analyzed both the rank level (note: smaller rank numbers are better, so negative coefficients indicate improvements) and rank improvement (previous year’s rank minus current year’s rank; positive values indicate improvement). Controls: Urbanization rate, total population, GDP, education investment, and gross enrollment rate in higher education. Time and country fixed effects were included, with robust standard errors. Parallel trends: An event study complemented DID to examine dynamic effects and assess the parallel trends assumption, using a window from −5 to +16 years around policy implementation. Data: Two long-standing rankings were used to ensure continuity and robustness: QS (top 300 universities, 2004–2020) and ARWU (top 500 universities, 2003–2020). QS incorporates both objective indicators and reputation (50% weight), while ARWU emphasizes objective research excellence measures (e.g., Nobel/Fields, highly cited researchers, Nature/Science publications). Descriptive statistics contrasted treatment and control groups and indicated that treated universities started with worse average ranks but exhibited positive average rank improvements, and that treated countries generally had lower socioeconomic development levels.

- National initiatives significantly improved rankings: - QS: Treated universities had 53.04-place better ranks and 17.65-place higher annual rank improvements than controls. - ARWU: Treated universities had 23.52-place better ranks and 12.09-place higher annual rank improvements than controls. - Descriptive patterns: Treated universities started lower in rankings but showed positive average improvements; control universities tended to worsen. Treated countries had lower urbanization, GDP, and higher populations on average. - Regional heterogeneity (rank improvement effects): - QS: Europe +12.04 places; Asia-Pacific +61.72 places. - ARWU: Europe +11.78 places; Asia-Pacific +94.04 places. Effects are substantially larger in Asia-Pacific than in Europe. - Differences between rankings: Changes were larger in QS than ARWU, consistent with QS incorporating indicators (e.g., reputation, internationalization, faculty-student ratio) that can respond more quickly to investment and policy, whereas ARWU focuses on stringent research excellence metrics (e.g., Nobel/Fields, Nature/Science) that are harder to shift in the short term. - Event study: Dynamic plots were used to test parallel trends before treatment; results were presented for both ARWU and QS.

The findings show that national higher education initiatives causally improve university rankings, addressing the core question of whether such policies are effective. Larger effects in the Asia-Pacific region likely reflect greater initial disparities and earlier, more mature implementation of initiatives (e.g., China, South Korea), enabling faster catch-up relative to Europe’s more stable, mature systems. The greater responsiveness of QS versus ARWU indicators suggests that initiatives rapidly enhance dimensions like internationalization and reputation but have more limited short-term impact on top-tier research excellence. Governance context matters: more government-controlled systems have used initiatives to concentrate resources and steer rapid development, whereas government-supervised systems rely more on autonomy and competition. The results imply that initiatives can accelerate convergence for late-developing systems but also risk incentivizing short-term, ranking-oriented behavior if not carefully designed.

Using panel data from QS (2004–2020, top 300) and ARWU (2003–2020, top 500) and a staggered DID with event-study validation, the study shows that national higher education initiatives significantly improve participating universities’ rankings, with particularly strong effects in the Asia-Pacific region and larger short-term gains in QS than ARWU. These programs have enabled late-developing countries to concentrate resources and accelerate progress toward world-class status. Policy recommendations include: avoid overemphasis on short-term ranking gains; encourage sustained investments in high-cost, slow-return activities that build genuine excellence; grant universities greater autonomy in personnel and finance; modernize governance to balance oversight with independence; and maintain dynamic selection and competition for efficient resource allocation. The study underscores that while initiatives are effective mechanisms for rapid improvement, long-term strategies beyond rankings are essential for durable, comprehensive quality.

- Reliance on QS and ARWU rankings may not fully capture the breadth of teaching and research quality; rankings tend to emphasize quantitative indicators and can incentivize short-termism. - Short-term effects are more visible in QS than in ARWU’s stringent research excellence metrics, indicating limited immediate impact on top-tier outcomes. - Treated countries differ socioeconomically from controls; although controls were included (urbanization, GDP, population, education investment, higher education enrollment) and fixed effects applied, residual confounding cannot be entirely ruled out. - The sample is limited to the top 300 QS and top 500 ARWU universities over the study periods, which may affect generalizability beyond these tiers.