Evaluating the Role of Next-Generation Productive Forces in Mitigating Carbon Lock-In: Evidence from Regional Disparities in China

Chenchen Song, Zhiling Guo, Xiaoyue Ma, Jijiang He () and Zhengguang Liu
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Chenchen Song: Business School, Beijing Information Science and Technology University, Beijing 100192, China
Zhiling Guo: Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hong Kong, China
Xiaoyue Ma: School of Economics, Northwest University of Political Science and Law, Xi’an 710122, China
Jijiang He: Faculty of Social Sciences, Tsinghua University, Beijing 100084, China
Zhengguang Liu: Department of Chemical Engineering, School of Engineering, The University of Manchester, Manchester M13 9PL, UK

Sustainability, 2025, vol. 17, issue 9, 1-30

Abstract: Carbon lock-in (CLI), defined as the structural persistence of fossil-fuel-based systems, poses a significant barrier to decarbonization. As CLI continues to impede China’s progress toward carbon neutrality, understanding the role of next-generation productive forces (NGPFs) in breaking this path dependence has become increasingly urgent; however, it remains underexplored in empirical research. This study examines the impact of NGPFs on CLI using provincial panel data from 2012 to 2022. Composite indices for NGPFs and CLI are constructed using the entropy weight method. The analysis applies instrumental variable estimation (IV-GMM) to address potential endogeneity, feasible generalized least squares (FGLS) to account for heteroskedasticity, and spatial Durbin models (SDMs) to capture spatial dependence. In addition, quantile regression is used to explore distributional effects, and subsample regressions are conducted to assess regional heterogeneity. The results show that (1) a 1% increase in NGPFs leads to approximately a 0.9643% reduction in CLI, effectively mitigating CLI. (2) NGPF levels are high in Beijing, Shanghai, and Guangdong, while being constrained in Heilongjiang, Gansu, and Qinghai. Provinces like Jiangsu, Zhejiang, and Shandong are rapidly catching up. (3) Shanxi, Inner Mongolia, and Shandong struggle with high comprehensive CLI from carbon-heavy industries; in contrast, Beijing, Shanghai, and Hainan show low CLI. (4) As CLI levels increase (90th percentile), the effectiveness of NGPFs in reducing CLI gradually diminishes (−0.2724). (5) The impact of NGPFs on CLI is not significant in the Eastern region, while in the Central and Western regions, the effects are −1.1365 and −1.0137, respectively. This study offers vital insights for shaping policies that promote sustainable growth and mitigate CLI in China.

Keywords: green development; industrial transformation; low-carbon transition; spatial heterogeneity; environmental policy; technological upgrading (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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