IDEAS home Printed from https://ideas.repec.org/a/sae/engenv/v35y2024i6p3065-3086.html

Energy-saving effect of financial development and its dynamic heterogeneity: Empirical evidence from the dynamic panel quantile model

Author

Listed:
  • Xiaorui Liu
  • Wen Guo
  • Yuyu Chen
  • Qiang Feng
  • Xiutian Zheng

Abstract

The energy-saving effect of financial development is directly related to the formulation and implementation of financial policies. Considering the inertial characteristics of energy consumption, this study tested the energy-saving effect of financial development and examined its heterogeneity in terms of low-carbon cleaning and policy change. The results were as follows: First, when energy consumption was at the lower quantile, as consumption increased, the promoting impact of financial development on energy consumption decreased. When energy consumption was at the upper quantile, as consumption increased, the restraining impact of financial development on energy consumption increased. Second, an increase in the quantile level showed that financial development exerted an increasingly stronger influence on promoting clean energy consumption. When non-clean energy consumption was at the upper quantile, financial development exerted an increasingly strong inhibitory effect on non-clean energy consumption. Third, before green credit policy changed, the energy-saving effect of financial development was not widespread and obvious. After green credit policy changed, the restraining impact of financial development on energy consumption increased with the level of consumption. Fourth, after green credit policy changed, compared with the increase of financial development toward promoting clean energy consumption, the inhibitory effect of financial development on non-clean energy consumption significantly improved relative to the second case.

Suggested Citation

  • Xiaorui Liu & Wen Guo & Yuyu Chen & Qiang Feng & Xiutian Zheng, 2024. "Energy-saving effect of financial development and its dynamic heterogeneity: Empirical evidence from the dynamic panel quantile model," Energy & Environment, , vol. 35(6), pages 3065-3086, September.
  • Handle: RePEc:sae:engenv:v:35:y:2024:i:6:p:3065-3086
    DOI: 10.1177/0958305X231164686
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0958305X231164686
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0958305X231164686?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Gregori, Tullio & Tiwari, Aviral Kumar, 2020. "Do urbanization, income, and trade affect electricity consumption across Chinese provinces?," Energy Economics, Elsevier, vol. 89(C).
    2. Galvao, Antonio F. & Gu, Jiaying & Volgushev, Stanislav, 2020. "On the unbiased asymptotic normality of quantile regression with fixed effects," Journal of Econometrics, Elsevier, vol. 218(1), pages 178-215.
    3. Zheng, Wei & Walsh, Patrick Paul, 2019. "Economic growth, urbanization and energy consumption — A provincial level analysis of China," Energy Economics, Elsevier, vol. 80(C), pages 153-162.
    4. repec:rza:wpaper:685 is not listed on IDEAS
    5. Zhao, Bingyu & Yang, Wanping, 2020. "Does financial development influence CO2 emissions? A Chinese province-level study," Energy, Elsevier, vol. 200(C).
    6. Lahiani, Amine & Mefteh-Wali, Salma & Shahbaz, Muhammad & Vo, Xuan Vinh, 2021. "Does financial development influence renewable energy consumption to achieve carbon neutrality in the USA?," Energy Policy, Elsevier, vol. 158(C).
    7. Galvao Jr., Antonio F., 2011. "Quantile regression for dynamic panel data with fixed effects," Journal of Econometrics, Elsevier, vol. 164(1), pages 142-157, September.
    8. Zhou, Guangyou & Zhu, Jieyu & Luo, Sumei, 2022. "The impact of fintech innovation on green growth in China: Mediating effect of green finance," Ecological Economics, Elsevier, vol. 193(C).
    9. Mello, Marcelo & Perrelli, Roberto, 2003. "Growth equations: a quantile regression exploration," The Quarterly Review of Economics and Finance, Elsevier, vol. 43(4), pages 643-667.
    10. Ross Levine & Norman Loayza & Thorsten Beck, 2002. "Financial Intermediation and Growth: Causality and Causes," Central Banking, Analysis, and Economic Policies Book Series, in: Leonardo Hernández & Klaus Schmidt-Hebbel & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Se (ed.),Banking, Financial Integration, and International Crises, edition 1, volume 3, chapter 2, pages 031-084, Central Bank of Chile.
    11. Koenker, Roger, 2004. "Quantile regression for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 74-89, October.
    12. Anton, Sorin Gabriel & Afloarei Nucu, Anca Elena, 2020. "The effect of financial development on renewable energy consumption. A panel data approach," Renewable Energy, Elsevier, vol. 147(P1), pages 330-338.
    13. Komal, Rabia & Abbas, Faisal, 2015. "Linking financial development, economic growth and energy consumption in Pakistan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 211-220.
    14. Wang, You & Gong, Xu, 2020. "Does financial development have a non-linear impact on energy consumption? Evidence from 30 provinces in China," Energy Economics, Elsevier, vol. 90(C).
    15. Xie, Lunyu & Yan, Haosheng & Zhang, Shuhan & Wei, Chu, 2020. "Does urbanization increase residential energy use? Evidence from the Chinese residential energy consumption survey 2012," China Economic Review, Elsevier, vol. 59(C).
    16. Wahidin, Deni & Akimov, Alexandr & Roca, Eduardo, 2021. "The impact of bond market development on economic growth before and after the global financial crisis: Evidence from developed and developing countries," International Review of Financial Analysis, Elsevier, vol. 77(C).
    17. Li, Ke & Lin, Boqiang, 2015. "Impacts of urbanization and industrialization on energy consumption/CO2 emissions: Does the level of development matter?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1107-1122.
    18. Sadorsky, Perry, 2013. "Do urbanization and industrialization affect energy intensity in developing countries?," Energy Economics, Elsevier, vol. 37(C), pages 52-59.
    19. Fan, Haichao & Peng, Yuchao & Wang, Huanhuan & Xu, Zhiwei, 2021. "Greening through finance?," Journal of Development Economics, Elsevier, vol. 152(C).
    20. Yue, Shujing & Lu, Rou & Shen, Yongchang & Chen, Hongtao, 2019. "How does financial development affect energy consumption? Evidence from 21 transitional countries," Energy Policy, Elsevier, vol. 130(C), pages 253-262.
    21. Chiu, Yi-Bin & Lee, Chien-Chiang, 2020. "Effects of financial development on energy consumption: The role of country risks," Energy Economics, Elsevier, vol. 90(C).
    22. Qu, Xiaobo & Yu, Yang & Zhou, Mofan & Lin, Chin-Teng & Wang, Xiangyu, 2020. "Jointly dampening traffic oscillations and improving energy consumption with electric, connected and automated vehicles: A reinforcement learning based approach," Applied Energy, Elsevier, vol. 257(C).
    23. Cieplinski, A. & D’Alessandro, S. & Distefano, T. & Guarnieri, P., 2021. "Coupling environmental transition and social prosperity: a scenario-analysis of the Italian case," Structural Change and Economic Dynamics, Elsevier, vol. 57(C), pages 265-278.
    24. Araç, Ayşen & Hasanov, Mübariz, 2014. "Asymmetries in the dynamic interrelationship between energy consumption and economic growth: Evidence from Turkey," Energy Economics, Elsevier, vol. 44(C), pages 259-269.
    25. Pan, Xiongfeng & Uddin, Md. Kamal & Han, Cuicui & Pan, Xianyou, 2019. "Dynamics of financial development, trade openness, technological innovation and energy intensity: Evidence from Bangladesh," Energy, Elsevier, vol. 171(C), pages 456-464.
    26. Lamarche, Carlos, 2010. "Robust penalized quantile regression estimation for panel data," Journal of Econometrics, Elsevier, vol. 157(2), pages 396-408, August.
    27. Duan, Yuwan & Jiang, Xuemei, 2021. "Pollution haven or pollution halo? A Re-evaluation on the role of multinational enterprises in global CO2 emissions," Energy Economics, Elsevier, vol. 97(C).
    28. Chernozhukov, Victor & Hansen, Christian, 2006. "Instrumental quantile regression inference for structural and treatment effect models," Journal of Econometrics, Elsevier, vol. 132(2), pages 491-525, June.
    29. Hu, Guoqiang & Wang, Xiaoqi & Wang, Yu, 2021. "Can the green credit policy stimulate green innovation in heavily polluting enterprises? Evidence from a quasi-natural experiment in China," Energy Economics, Elsevier, vol. 98(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shunan Fan & Yuhuan Zhao & Sumin Zuo, 2025. "Financial Development and Energy Transition: A Literature Review," Energies, MDPI, vol. 18(15), pages 1-28, August.
    2. Uddin, Md. Kamal & Pan, Xiongfeng & Saima, Umme & Zhang, Chengming, 2022. "Influence of financial development on energy intensity subject to technological innovation: Evidence from panel threshold regression," Energy, Elsevier, vol. 239(PD).
    3. Panagiotidis, Theodore & Printzis, Panagiotis, 2021. "Investment and uncertainty: Are large firms different from small ones?," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 302-317.
    4. Appiah-Otoo, Isaac & Chen, Xudong & Ampah, Jeffrey Dankwa, 2023. "Does financial structure affect renewable energy consumption? Evidence from G20 countries," Energy, Elsevier, vol. 272(C).
    5. Islam, Md. Monirul & Irfan, Muhammad & Shahbaz, Muhammad & Vo, Xuan Vinh, 2022. "Renewable and non-renewable energy consumption in Bangladesh: The relative influencing profiles of economic factors, urbanization, physical infrastructure and institutional quality," Renewable Energy, Elsevier, vol. 184(C), pages 1130-1149.
    6. Shabir, Mohsin & Jiang, Ping & Hashmi, Shujahat Haider & Bakhsh, Satar, 2022. "Non-linear nexus between economic policy uncertainty and bank lending," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 657-679.
    7. Zhongye Sun & Xin Zhang & Yifei Gao, 2023. "The Impact of Financial Development on Renewable Energy Consumption: A Multidimensional Analysis Based on Global Panel Data," IJERPH, MDPI, vol. 20(4), pages 1-20, February.
    8. Li Tao & Lingnan Tai & Manling Qian & Maozai Tian, 2023. "A New Instrumental-Type Estimator for Quantile Regression Models," Mathematics, MDPI, vol. 11(15), pages 1-26, August.
    9. Harding, Matthew & Lamarche, Carlos, 2014. "Estimating and testing a quantile regression model with interactive effects," Journal of Econometrics, Elsevier, vol. 178(P1), pages 101-113.
    10. Jiang, Hai & Zhang, Jinyi, 2017. "Bank capital buffer, franchise value, and risk heterogeneity in China," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1455-1466.
    11. Li, Guoxiang & Wu, Haoyue & Jiang, Jieshu & Zong, Qingqing, 2023. "Digital finance and the low-carbon energy transition (LCET) from the perspective of capital-biased technical progress," Energy Economics, Elsevier, vol. 120(C).
    12. Li Tao & Yuanjie Zhang & Maozai Tian, 2019. "Quantile Regression for Dynamic Panel Data Using Hausman–Taylor Instrumental Variables," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1033-1069, March.
    13. James, Emmanuel O. & Bakas, Dimitrios & Thompson, Piers & Ebireri, John, 2025. "Who Benefits the Most from Micro-Credit? Micro-Level Evidence from Sub-Saharan Africa," World Development, Elsevier, vol. 193(C).
    14. Harold D. Chiang & Antonio F. Galvao & Chia-Min Wei, 2026. "Panel Quantile Regression with Common Shocks," Papers 2602.19201, arXiv.org.
    15. David Powell & Joachim Wagner, 2021. "The Exporter Productivity Premium Along the Productivity Distribution: Evidence from Quantile Regression with Nonadditive Firm Fixed Effects," World Scientific Book Chapters, in: Joachim Wagner (ed.), MICROECONOMETRIC STUDIES OF FIRMS’ IMPORTS AND EXPORTS Advanced Methods of Analysis and Evidence from German Enterprises, chapter 9, pages 121-149, World Scientific Publishing Co. Pte. Ltd..
    16. Sherrilyn Billger & Carlos Lamarche, 2015. "A panel data quantile regression analysis of the immigrant earnings distribution in the United Kingdom and United States," Empirical Economics, Springer, vol. 49(2), pages 705-750, September.
    17. You, Wan-Hai & Zhu, Hui-Ming & Yu, Keming & Peng, Cheng, 2015. "Democracy, Financial Openness, and Global Carbon Dioxide Emissions: Heterogeneity Across Existing Emission Levels," World Development, Elsevier, vol. 66(C), pages 189-207.
    18. Ali Aghamohammadi, 2018. "Bayesian analysis of dynamic panel data by penalized quantile regression," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(1), pages 91-108, March.
    19. Denis Chetverikov & Bradley Larsen & Christopher Palmer, 2016. "IV Quantile Regression for Group‐Level Treatments, With an Application to the Distributional Effects of Trade," Econometrica, Econometric Society, vol. 84, pages 809-833, March.
    20. repec:prg:jnlpep:v:preprint:id:646:p:1-21 is not listed on IDEAS
    21. Wang, Yajun & Yuan, Zheng & Luo, Hanyu & Zeng, Hui & Huang, Junbing & Li, Yulin, 2024. "Promoting low-carbon energy transition through green finance: New evidence from a demand-supply perspective," Energy Policy, Elsevier, vol. 195(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:engenv:v:35:y:2024:i:6:p:3065-3086. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.