This paper examines whether industrial structure upgrading alters the effect of financial development on urban energy efficiency. The estimations use a balanced panel of 282 Chinese prefecture-level cities from 2008 to 2023, estimated separately for 112 resource-based and 170 non-resource-based cities, using dynamic panel threshold models that allow for persistence and endogenous regressors. The coefficient on financial development is positive and statistically significant on both sides of the estimated industrial-structure-upgrading threshold in both city types. Its marginal effect, however, differs between the two city types once the threshold is crossed. In resource-based cities, the coefficient rises from 0.127 to 0.135 after the threshold of 0.397. In non-resource-based cities, it falls from 0.149 to 0.035 after the threshold of 0.358. The pattern remains when financial development is replaced by its one-period lag. Our results suggest that industrial structure upgrading raises the energy-efficiency payoff to finance in resource-based cities, whereas the smaller post-threshold effect in non-resource-based cities points to diminishing returns to financial expansion and a greater role for credit allocation. Our study helps explain conflicting evidence on finance and energy efficiency and shows why financial policy should vary with city type and industrial structure.
Aller, C., Herrerias, M. J., & Ordóñez, J. (2018). The effect of financial development on energy intensity in China. The Energy Journal, 39(1_suppl), 25–38. https://doi.org/10.5547/01956574.39.SI1.call
Caner, M., & Hansen, B. E. (2004). Instrumental variable estimation of a threshold model. Econometric Theory, 20(5), Article 5. https://doi.org/10.1017/S0266466604205011
Canh, N. P., Thanh, S. D., & Nasir, M. A. (2020). Nexus between financial development & energy intensity: Two sides of a coin? Journal of Environmental Management, 270, 110902. https://doi.org/10.1016/j.jenvman.2020.110902
Cao, J., Law, S. H., Samad, A. R. A., & Mohamad, W. N. W. (2023). Internal mechanism analysis of the financial vanishing effect on green growth: Evidence from China. Energy Economics, 120, 106579. https://doi.org/10.1016/j.eneco.2023.106579
Chen, S., Liao, G., Drakeford, B. M., & Failler, P. (2019a). The non-linear effect of financial support on energy efficiency: Evidence from China. Sustainability, 11(7), Article 7. https://doi.org/10.3390/su11071959
Chen, Z., Huang, W., & Zheng, X. (2019b). The decline in energy intensity: Does financial development matter? Energy Policy, 134, 110945. https://doi.org/10.1016/j.enpol.2019.110945
Diallo, I. A. (2020). XTENDOTHRESDPD: Stata module to estimate a dynamic panel data threshold effects model with endogenous regressors. Statistical Software Components. https://ideas.repec.org//c/boc/bocode/s458745.html
Hachem, K. (2018). Shadow banking in China. Annual Review of Financial Economics, 10(Volume 10, 2018), 287–308. https://doi.org/10.1146/annurev-financial-110217-023025
Hansen, B. E. (1999). Threshold effects in non-dynamic panels: Estimation, testing, and inference. Journal of Econometrics. https://doi.org/10.1016/S0304-4076(99)00025-1
He, Y.-T., Zhang, Y.-C., Wu, R.-K., Huang, W., Wang, R.-N., He, L.-X., Li, B., & Zhang, Y.-L. (2024). Dynamic evolution and spatial difference of public health service supply in economically developed provinces of China: Typical evidence from guangdong province. Bmc Health Services Research, 24(1), 23. https://doi.org/10.1186/s12913-023-10444-4
Jafary, F., Ashani, A. N., & Afsharirad, M. (2024). Exploring the impact of financial development on energy intensity in a global study: Do levels of innovation and technology matter? Heliyon, 10(21), e39331. https://doi.org/10.1016/j.heliyon.2024.e39331
Kremer, S., Bick, A., & Nautz, D. (2013). Inflation and growth: New evidence from a dynamic panel threshold analysis. Empirical Economics, 44(2), Article 2. https://doi.org/10.1007/s00181-012-0553-9
Levine, R. (1997). Financial development and economic growth: Views and agenda. Journal of Economic Literature, 35(2), Article 2.
Li, B., & Dewan, H. (2017). Efficiency differences among China’s resource-based cities and their determinants. Resources Policy, 51, 31–38. https://doi.org/10.1016/j.resourpol.2016.11.003
Li, L., Chi, T., & Wang, S. (2016). Is energy utilization among chinese provinces sustainable? Technological Forecasting and Social Change, 112, 198–206. https://doi.org/10.1016/j.techfore.2016.07.003
Liang, H., Fang, Q., Wang, Q., & Liu, Z. (2026). Ownership and corporate green innovation: An inverted U-shaped relationship based on agency theory. Finance Research Letters, 95, 109713. https://doi.org/10.1016/j.frl.2026.109713
Liu, M., Xu, K., & Zhai, L. (2024). Bank-firm common ownership, green credit and enterprise green technology innovation: Evidence from Chinese credit markets. Energy Economics, 140, 108014. https://doi.org/10.1016/j.eneco.2024.108014
Liu, Y., Xiong, R., Lv, S., & Gao, D. (2022). The impact of digital finance on green total factor energy efficiency: Evidence at China’s city level. Energies, 15(15). https://doi.org/10.3390/en15155455
Ma, Y., Zhao, Y., Jia, R., Wang, W., & Zhang, B. (2022). Impact of financial development on the energy intensity of developing countries. Heliyon, 8(8), e09904. https://doi.org/10.1016/j.heliyon.2022.e09904
Qu, C., Shao, J., & Shi, Z. (2020). Does financial agglomeration promote the increase of energy efficiency in China? Energy Policy, 146, 111810. https://doi.org/10.1016/j.enpol.2020.111810
Saint-Paul, G. (1992). Technological choice, financial markets and economic development. European Economic Review, 36(4), 763–781. https://doi.org/10.1016/0014-2921(92)90056-3
Shi, Y., & Yang, B. (2024). How digital finance and green finance can synergize to improve urban energy use efficiency? New evidence from China. Energy Strategy Reviews, 55, 101553. https://doi.org/10.1016/j.esr.2024.101553
State Council of the People’s Republic of China. (2021). Full text: Working guidance for carbon dioxide peaking and carbon neutrality in full and faithful implementation of the new development philosophy. https://english.www.gov.cn/policies/latestreleases/202110/25/content_WS61760047c6d0df57f98e3c21.html
Uddin, Md. K., Pan, X., Saima, U., & Zhang, C. (2022). Influence of financial development on energy intensity subject to technological innovation: Evidence from panel threshold regression. Energy, 239, 122337. https://doi.org/10.1016/j.energy.2021.122337
United Nations. (n.d.). Goal 7 | department of economic and social affairs. Retrieved 14 July 2026, from https://sdgs.un.org/goals/goal7
Wang, E.-Z., & Lee, C.-C. (2023). The impact of commercial bank branch expansion on energy efficiency: Micro evidence from China. China Economic Review, 80, 102019. https://doi.org/10.1016/j.chieco.2023.102019
Wang, R., Wang, Q., & Yao, S. (2021). Evaluation and difference analysis of regional energy efficiency in China under the carbon neutrality targets: Insights from DEA and theil models. Journal of Environmental Management, 293, 112958. https://doi.org/10.1016/j.jenvman.2021.112958
Wang, S., & Xue, Z. (2023). Has the development of the digital economy improved green total factor productivity in China?—A study based on data at the provincial level in china. Frontiers in Environmental Science, 11. https://doi.org/10.3389/fenvs.2023.1073997
Wu, J., & Bai, Z. (2022). Spatial and temporal changes of the ecological footprint of China’s resource-based cities in the process of urbanization. Resources Policy, 75, 102491. https://doi.org/10.1016/j.resourpol.2021.102491
Xu, Y., Qiang, F., & Luo, W. (2024). Investigating the impact of heterogeneous environmental regulation on the ecological efficiency of industrial enterprises: A multivariate adjustment approach using the CLAD spatial durbin model. Sustainability, 16(6). https://doi.org/10.3390/su16062299
Xue, X., & Wang, Z. (2021). Impact of finance pressure on energy intensity: Evidence from China’s manufacturing sectors. Energy, 226, 120220. https://doi.org/10.1016/j.energy.2021.120220
Yang, S., & Xu, J. (2026). Science and technology finance policy and inclusive green growth in cities. International Review of Economics & Finance, 108, 105171. https://doi.org/10.1016/j.iref.2026.105171
Yu, A., & Li, H. (2025). Together or alone? Environmental regulations and energy consumption: Empirical evidence from 200 cities in China. Energy, 341, 139339. https://doi.org/10.1016/j.energy.2025.139339
Zhang, D., & Kong, Q. (2022). Credit policy, uncertainty, and firm R&D investment: A quasi-natural experiment based on the green credit guidelines. Pacific-Basin Finance Journal, 73, 101751. https://doi.org/10.1016/j.pacfin.2022.101751
Zhang, D., Li, J., & Ji, Q. (2020). Does better access to credit help reduce energy intensity in China? Evidence from manufacturing firms. Energy Policy, 145, 111710. https://doi.org/10.1016/j.enpol.2020.111710
Zhang, H., Lv, Y., Zhang, J. Z., & Fadil, P. (2025). Government science and technology spending and energy efficiency: An inverted U-shaped analysis. Energy Economics, 149, 108818. https://doi.org/10.1016/j.eneco.2025.108818
Zhao, X., Nakonieczny, J., Jabeen, F., Shahzad, U., & Jia, W. (2022). Does green innovation induce green total factor productivity? Novel findings from Chinese city level data. Technological Forecasting and Social Change, 185, 122021. https://doi.org/10.1016/j.techfore.2022.122021
Zheng, J., Niu, H., Lo, K., & Guo, M. (2026). Breaking the resource curse: The impact of green finance on the energy transition of resource-based cities. Energy Policy, 214, 115245. https://doi.org/10.1016/j.enpol.2026.115245
Zhou, G., Yu, J., Yue, Q., Xu, S., & Chen, X. (2026). A multi-sectoral framework for assessing water use efficiency and its drivers: Insights from China. Hydrological Sciences Journal, 71(2), 216–228. https://doi.org/10.1080/02626667.2025.2588419
Weng, J., & Law, C.-H. (2026). Does industrial Structure Upgrading Influence the Impact of Financial Development on Energy Efficiency? Evidence from Chinese Cities. International Journal of Academic Research in Business and Social Sciences, 16(7), 1244–1261.
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