The Impact of University Basic Research on Regional Economic Growth

Authors

DOI:

https://doi.org/10.31181/jidmgc21202645

Keywords:

University basic research, Regional economic growth, Knowledge transfer, Human capital, Government intervention

Abstract

Universities are major contributors to basic research, and their roles in knowledge creation and human capital development are widely recognized as fundamental drivers of regional economic growth. Whether these functions are effectively transformed into economic performance across Chinese provinces, however, remains an open empirical question. Using panel data from 30 Chinese provinces, this study systematically investigates the impact of university basic research on regional economic growth. Baseline estimates are obtained using a two-way fixed-effects model and are validated through a series of robustness checks, including alternative variable specifications, lagged models, and system GMM estimation. The findings show no statistically significant relationship between university basic research and regional economic growth during the sample period. Mechanism analysis further indicates that university basic research does not significantly enhance human capital accumulation, technological innovation, or entrepreneurship, despite the fact that all three factors contribute positively to regional economic growth. These results suggest the existence of an upstream bottleneck that limits the transformation of academic knowledge into economic value. In addition, government intervention significantly weakens the relationship between university basic research and human capital accumulation. Overall, the findings highlight institutional barriers to the economic commercialization of university research in China and provide policy implications for strengthening public governance, research training, and knowledge transfer mechanisms.

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Published

2026-08-02

How to Cite

Chen, X. (2026). The Impact of University Basic Research on Regional Economic Growth. Journal of Intelligent Decision Making and Granular Computing, 2(1), 225-241. https://doi.org/10.31181/jidmgc21202645