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Carbon Emission Reduction Effects of Government Talent Attraction Policies: Evidence from Fujian Province, China

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  • Yangting Ou

    (School of Economics and Management, Ningde Normal University, Ningde 352100, China
    College of Commerce, National Chengchi University, Taipei 11605, China)

  • Haixian Li

    (School of Economics and Management, Fuzhou University, Fuzhou 350108, China)

  • Houyin Long

    (School of Economics and Management, Fuzhou University, Fuzhou 350108, China)

Abstract

Fujian Province launched a talent recruitment policy in 2012 to integrate top university graduates into grassroots government roles, aiming to support green development. This study investigates the impact of recruiting “three-high” talents—those who are highly educated, skilled, and specialized—on reducing county-level carbon emissions. Using panel data from 134 counties between 2007 and 2021, we apply a time-varying difference-in-differences model. Robustness checks, including propensity score matching estimation, placebo tests, and fixed-effect controls, confirm the reliability of our results. We find that the policy significantly reduces carbon emission intensity, primarily by enhancing green technological innovation. The effect is more pronounced in urban, economically developed, and non-resource-based regions, especially where public awareness of green practices is higher. These findings suggest that localized talent policies can play a critical role in advancing low-carbon development. Our results offer new evidence for integrating human capital strategies into environmental policy design and highlight the importance of aligning recruitment efforts with regional development needs to support China’s carbon neutrality goals.

Suggested Citation

  • Yangting Ou & Haixian Li & Houyin Long, 2025. "Carbon Emission Reduction Effects of Government Talent Attraction Policies: Evidence from Fujian Province, China," Sustainability, MDPI, vol. 17(11), pages 1-20, June.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:11:p:5159-:d:1671636
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