Analysis of industrial transformation and upgrading in resource-exhausted cities: evidence from city-level and enterprise-level panel data.

Yiwen Peng

European Journal of Government and Economics2025https://doi.org/10.17979/ejge.2025.14.1.10797article
ABDC C
Weight
0.50

What the paper says

Massive and irrational exploitation of natural resources promoted the industrialization process, which formed different categories of resource-based cities. Although these cities have made dramatic contributions to socio-economic development in the last two decades, they are now facing grave problems due to resource depletion. Industrial transformation and upgrading are the only ways to cope with this situation. Therefore, this study utilizes the city-level and enterprise-level data to analyze the industrial transformation and upgrading of resource-exhausted cities in China. Both the macro- and micro-empirical results demonstrate that the central policy of the State Council has a positive feedback on industrial transformation. Then the findings of baseline regression are validated by robustness and heterogeneity tests. What’s more, the policy facilitates industrial upgrading by promoting transition to technology-intensive and high-value chain industries. Finally, we propose relevant implications for industrial transformation on the basis of the main findings.

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https://doi.org/https://doi.org/10.17979/ejge.2025.14.1.10797

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@article{yiwen2025,
  title        = {{Analysis of industrial transformation and upgrading in resource-exhausted cities: evidence from city-level and enterprise-level panel data.}},
  author       = {Yiwen Peng},
  journal      = {European Journal of Government and Economics},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.17979/ejge.2025.14.1.10797},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.