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author:

Ou, Y. (Ou, Y..) [1] | Li, H. (Li, H..) [2] | Long, H. (Long, H..) [3]

Indexed by:

Scopus

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. © 2025 by the authors.

Keyword:

carbon emissions county-level China difference-in-differences green development talent attraction

Community:

  • [ 1 ] [Ou Y.]School of Economics and Management, Ningde Normal University, Ningde, 352100, China
  • [ 2 ] [Ou Y.]College of Commerce, National Chengchi University, Taipei, 11605, China
  • [ 3 ] [Li H.]School of Economics and Management, Fuzhou University, Fuzhou, 350108, China
  • [ 4 ] [Long H.]School of Economics and Management, Fuzhou University, Fuzhou, 350108, China

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Source :

Sustainability (Switzerland)

ISSN: 2071-1050

Year: 2025

Issue: 11

Volume: 17

2 . 5 9 2

JCR@2018

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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