Relationship between higher education expansion and economic growth: empirical evidence from China

Purpose This study empirically analyses the relationship between China’s economic growth and higher education, specifically examining the background of China’s higher education expansion that commenced in 1999. Design/methodology/approach The research employs the Autoregressive Distributed Lag (ARDL) model with annual data, choosing the number of entrants and graduates as measures of higher education. Findings As results emerge, economic progress exerts a positive influence on entrants at the short-cycle tertiary level, whereas it negatively affects Master’s entrants in both the long run and short run. Furthermore, an increase in graduates from Bachelor’s or Master’s programmes hampers economic growth. Practical implications The findings imply that the talents cultivated by higher education do not match the demands of economic development since the expansion. It is recommended that there should be strategic planning for quantity adjustment and quality improvement across different tertiary levels to better fit market needs. Originality/value Extensive research efforts have looked at education as a whole without differentiating between various tertiary levels when assessing its impact on the economy. This article categorises higher education into four levels and explores their connections to economic growth. In addition, earlier research has predominantly relied on enrollment series as a measure of higher education. This article utilises the indicators of entrants and graduates so as to assess their relationships with economic growth from the perspective of supply and demand.

Authors

Publication Details

Journal
Asian Education and Development Studies
Published
2025-04-14
DOI
https://doi.org/10.1108/aeds-09-2024-0212
Citations
1
Primary Topic
Economic Growth and Productivity
Type
article
Field-Weighted Citation Impact
3.13
Controls
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article

Relationship between higher education expansion and economic growth: empirical evidence from China

Husaina Banu Kenayathulla, Tian Chen
1 citations
Asian Education and Development Studies
Economic Growth and Productivity
3.13
article

Relationship between higher education expansion and economic growth: empirical evidence from China

Husaina Banu Kenayathulla, Tian Chen
article en
1 citations

Abstract

Purpose This study empirically analyses the relationship between China’s economic growth and higher education, specifically examining the background of China’s higher education expansion that commenced in 1999. Design/methodology/approach The research employs the Autoregressive Distributed Lag (ARDL) model with annual data, choosing the number of entrants and graduates as measures of higher education. Findings As results emerge, economic progress exerts a positive influence on entrants at the short-cycle tertiary level, whereas it negatively affects Master’s entrants in both the long run and short run. Furthermore, an increase in graduates from Bachelor’s or Master’s programmes hampers economic growth. Practical implications The findings imply that the talents cultivated by higher education do not match the demands of economic development since the expansion. It is recommended that there should be strategic planning for quantity adjustment and quality improvement across different tertiary levels to better fit market needs. Originality/value Extensive research efforts have looked at education as a whole without differentiating between various tertiary levels when assessing its impact on the economy. This article categorises higher education into four levels and explores their connections to economic growth. In addition, earlier research has predominantly relied on enrollment series as a measure of higher education. This article utilises the indicators of entrants and graduates so as to assess their relationships with economic growth from the perspective of supply and demand.

Asian Education and Development StudiesVol. 14(3)
Openalex Percentile: Top 9%
Economic Growth and Productivity
3.13
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