When Green Accounting Fails to Drive Green Energy: Institutional Quality and China’s Renewable Energy Transition
Abstract
This study examines how institutional quality, government R&D expenditure, and SEEA-aligned environmental asset indicators are associated with renewable energy adoption in China from 1999 to 2023. It addresses the puzzle that environmental accounting signals and innovation investment do not automatically translate into renewable energy use. Annual data from the World Development Indicators and Worldwide Governance Indicators were analyzed using a hybrid empirical strategy. The Autoregressive Distributed Lag approach was applied to estimate short-run and long-run relationships, while Double Machine Learning, Random Forest, Gradient Boosting, and SHAP interpretability were used as supplementary tools for robustness and predictive importance. Given the limited sample size, machine-learning results are interpreted as orthogonalized associations and as predictive evidence rather than as definitive causal effects. ARDL results show that regulatory quality has a positive and statistically significant long-run association with renewable energy adoption. In contrast, government R&D expenditure and adjusted net savings show negative associations, suggesting that innovation spending and fiscal capacity may not support renewable energy adoption unless directed toward deployment and energy-system substitution. Energy resource depletion is statistically insignificant, while natural resource rents show a weak positive long-run association. Machine-learning results identify government R&D expenditure as the strongest predictor, although its direction remains negative. The findings indicate that China’s renewable energy transition depends less on fiscal or technological inputs alone and more on the institutional capacity to convert these inputs into adoption outcomes. The study implies that SEEA-based indicators should be integrated with regulatory mechanisms, deployment-oriented innovation policy, and outcome-based evaluation of energy transition.
Article information
https://doi.org/10.36923/ie-frontiers.v29i1.426
How to Cite
Full text article
References
Aboulajras, A. S. A., Khalifa, W. M. S., & Kareem, P. H. (2025). Environmental sustainability in emerging economies: The impact of natural resource rents, energy efficiency, and economic growth via quantile regression analysis. Sustainability, 17(8), 3670. https://doi.org/10.3390/su17083670
Adu, D., Li, N., Liu, H., & Spio-Kwofie, A. (2024). FinTech and sustainable development: A systematic thematic review. International Review of Financial Analysis, 95(Part B), Article 103541. https://doi.org/10.1016/j.irfa.2024.103541
Andriamahery, A., & Qamruzzaman, M. (2022). A symmetry and asymmetry investigation of the nexus between environmental sustainability, renewable energy, energy innovation, and trade: Evidence from the environmental Kuznets curve hypothesis in selected MENA countries. Frontiers in Energy Research, 9, Article 778202. https://doi.org/10.3389/fenrg.2021.778202
Atuahene, S. O. O., Owusu, G. M. Y., & Agyenim-Boateng, C. (2025). The effect of environmental taxes on sustainable energy transition prospects. Sustainability Accounting, Management and Policy Journal. Advance online publication. https://doi.org/10.1108/SAMPJ-12-2024-1453
Ayaz Atalan, Y., Şahin, H., Keskin, A., & Atalan, A. (2025). Strategic forecasting of renewable energy production for sustainable electricity supply: A machine learning approach considering environmental, economic, and oil factors in Türkiye. PLOS ONE, 20(1), Article e0328290. https://doi.org/10.1371/journal.pone.0328290
Berrich, J., Aoun, S. B., & Doula, M. (2024). Renewable energy transition and the Paris Agreement: How governance quality makes a difference. Energies, 17(17), Article 4238. https://doi.org/10.3390/en17174238
Breusch, T. S., & Godfrey, L. G. (1978). Misspecification tests and their uses in econometrics. Journal of Statistical Planning and Inference, 49, 241-260. https://doi.org/10.1016/0378-3758(95)00039-9
Breusch, T. S., & Pagan, A. R. (1979). A simple test for heteroscedasticity and random coefficient variation. Econometrica, 47, 1287-1294. https://doi.org/10.2307/1911963
Brown, R. L., Durbin, J., & Evans, J. M. (1975). Techniques for testing the consistency of regression relationships over time. Journal of the Royal Statistical Society: Series B (Methodological), 37, 149-163. https://doi.org/10.1111/j.2517-6161.1975.tb01532.x
Chen, N., & Usman, M. (2025). Energy use, energy depletion, and environmental degradation: Exploitation of natural resources. Natural Resources Forum. Advance online publication. https://doi.org/10.1111/1477-8947.12591
Chernozhukov, V., Chetverikov, D., Demirer, M., Duflo, E., Hansen, C., Newey, W., & Robins, J. (2018). Double/debiased machine learning for treatment and structural parameters. The Econometrics Journal, 21(1), C1-C68. https://doi.org/10.1111/ectj.12097
Dawo, K. A. A., & Khalifa, W. M. S. (2025). Do green innovation, environmental governance, and renewable energy transition drive trade-adjusted resource footprints in the top Sub-Saharan African countries? Sustainability, 17(11), Article 4907. https://doi.org/10.3390/su17114907
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366a), 427-431. https://doi.org/10.1080/01621459.1979.10482531
Epis, J. (2025). Ethical dilemmas in renewable energy transition in Siargao Island: Balancing innovation, justice, and environmental responsibility. International Journal of Management and Applied Information Technology for Future Advances, 19, Article 00. https://doi.org/10.69481/ijomaitffa1900
Fernandes, C. P., Saraf, P., & Rao, P. (2025). Evaluating the role of government expenditure in promoting renewable energy and economic growth in India. Environmental Economics, 16(2), 12-25. https://doi.org/10.21511/ee.16(2).2025.02
Ganda, F. (2022). The nexus of financial development, natural resource rents, technological innovation, foreign direct investment, energy consumption, human capital, and trade on environmental degradation in the new BRICS economies. Environmental Science and Pollution Research, 29, 74442-74457. https://doi.org/10.1007/s11356-022-20976-7
Goodland, R., & Daly, H. (1996). Environmental sustainability: Universal and non negotiable. Ecological Applications, 6(4), 1002-1017. https://doi.org/10.2307/2269583
Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424-438. https://doi.org/10.2307/1912791
Hacıimamoğlu, T., & Cengiz, V. (2024). Are natural resource rents and renewable energy consumption solutions for environmental degradation? Fresh insights from a modified ecological footprint model. Sustainability, 16(7), Article 2736. https://doi.org/10.3390/su16072736
Huang, Z., & Ren, X. (2024). Impact of natural resources, resilient economic growth, and energy consumption on CO2 emissions. Resources Policy, 90, 104714. https://doi.org/10.1016/j.resourpol.2024.104714
International Energy Agency. (2023). World Energy Outlook 2023. Retrieved from https://www.iea.org/reports/world-energy-outlook-2023
Kukharets, V., Čingiene, R., Juočiūnienė, D., Kukharets, S., Blažauskas, E., Szufa, S., Muzychenko, A., Beleі, S., Lahodyn, N., & Hutsol, T. (2024). Regression analysis of the impact of foreign direct investments, adjusted net savings, and environmental tax revenues on the consumption of renewable energy sources in EU countries. Energies, 17(17), 4465. https://doi.org/10.3390/en17174465
Latif, M. I., Mughal, K., Afzal, M., & Gillani, D. Q. (2025). Natural resource wealth and depletion: Exploring the economic, energy, and environmental impacts of mineral rents and mineral depletion. Journal of Economic Impact, 7(1), 11-22. https://doi.org/10.52223/econimpact.2025.7111
Li, W., Cao, S., & Tang, Y. (2024). Can the energy transition drive economic development? Empirical evidence from China. Technological Forecasting and Social Change, 198, Article 123456. https://doi.org/10.1016/j.techfore.2023.123456
Liu, J., Cai, Y., & Shen, X. (2025). Integrating machine learning, SHAP interpretability, and deep learning approaches in the study of environmental and economic factors: A case study of residential segregation in Las Vegas. Land, 14(5), Article 957. https://doi.org/10.3390/land14050957
Lundberg, S. M., & Lee, S.-I. (2017). A unified approach to interpreting model predictions. Advances in Neural Information Processing Systems, 30, 4765-4774. Retrieved from https://proceedings.neurips.cc/paper_files/paper/2017/file/8a20a8621978632d76c43dfd28b67767-Paper.pdf
Lütkepohl, H. (2005). New introduction to multiple time series analysis. Springer Science & Business Media. https://doi.org/10.1007/978-3-540-27752-1
Megnidio-Tchoukouegno, M., & Adedeji, J. A. (2023). Machine learning for road traffic accident improvement and environmental resource management in the transportation sector. Sustainability, 15(3), Article 2014. https://doi.org/10.3390/su15032014
Narang, H. (2025). China's energy transition: Domestic policy and international context. In The intersection of global energy politics and climate change: A comprehensive analysis of energy markets and economics (pp. 235-251). Springer Nature Singapore. https://doi.org/10.1007/978-981-96-0535-4_11
North, D. C. (1990). Institutions, institutional change, and economic performance. Cambridge University Press. https://doi.org/10.1017/CBO9780511808678
Olaniyi, C. O., & Odhiambo, N. M. (2024). Do natural resource rents aid renewable energy transition in resource-rich African countries? The roles of institutional quality and its threshold. Natural Resources Forum, 48(2), 430-456. https://doi.org/10.1111/1477-8947.12430
Ozkan, C., & Okay, N. (2024). Renewable energy, economic policy uncertainty, and climate policy uncertainty: New evidence for the environmental Kuznets curve from emerging and developed countries. Sustainability, 16(14), Article 6049. https://doi.org/10.3390/su16146049
Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326. https://doi.org/10.1002/jae.616
Qu, R., Kou, R., & Zhang, T. (2024). The impact of weather variability on renewable energy consumption: Insights from explainable machine learning models. Sustainability, 17(1), Article 87. https://doi.org/10.3390/su17010087
Ramsey, J. B. (1969). Tests for specification errors in classical linear least-squares regression analysis. Journal of the Royal Statistical Society Series B, 31(2), 350-371. https://doi.org/10.1111/j.2517-6161.1969.tb00796.x
Robinson, J. A., & Acemoglu, D. (2012). Why Nations Fail: The Origins of Power, Prosperity, and Poverty (pp. 45-47). Profile. https://doi.org/10.1355/ae29-2j
Rubanenko, O. (2024). Determination of conditions for the optimal power generation PV system for the energy community and citizens' energy in Ukraine by the criterion programming method. Renewable Energies, Environment and Power Quality Journal, 24, Article 411. https://doi.org/10.24084/reepqj24.411
Sarosh, S., & Yen, C. M. (2024). The impact of natural resource rents on environmental degradation in the case of the USA: The role of technological innovation and renewable energy consumption. Asian Journal of Economics and Empirical Research, 11(2), 90-99. https://doi.org/10.20448/ajeer.v11i2.6390
Shang, F., Akhtar, R., Masud, M. M., & Salahuddin, S. (2025). The role of natural resource rent, economic sustainability, and renewable energy consumption on greenhouse gas emissions: An asymmetric analysis. Environmental Research Communications, 7(1), Article 019e8b. https://doi.org/10.1088/2515-7620/ad9e8b
Sibanda, K., Garidzirai, R., Mushonga, F., & Gonese, D. (2023). Natural resource rents, institutional quality, and environmental degradation in resource-rich Sub-Saharan African countries. Sustainability, 15(2), Article 1141. https://doi.org/10.3390/su15021141
Szetela, B., Majewska, A., Jamroz, P., Djalilov, B., & Salahodjaev, R. (2022). Renewable energy and CO2 emissions in top natural resource rents depending on countries: The role of governance. Frontiers in Energy Research, 10, Article 872941. https://doi.org/10.3389/fenrg.2022.872941
Tang, Z., Zhang, Z., & Deng, W. (2024). Government environmental expenditure, budget management, and regional carbon emissions: Provincial panel data from China. Sustainability, 16(15), 6707. https://doi.org/10.3390/su16156707
Tang, W., & Zhou, Q. (2025). Can green financial policy drive urban carbon unlocking efficiency? A causal inference approach based on double machine learning. Frontiers in Environmental Science, 13, 1608475. https://doi.org/10.3389/fenvs.2025.1608475
Tashbaeva, R., Sterzinger, H., Ruzimov, U., & Isokhujaeva, M. (2024). Enhancing environmental statistics based on the System of Environmental-Economic Accounting 2012 (SEEA) in the Republic of Uzbekistan. In E3S Web of Conferences (Vol. 574, p. 07006). EDP Sciences. https://doi.org/10.1051/e3sconf/202457407006
United Nations. (2012). *System of environmental-economic accounting 2012: Central framework*. United Nations. https://doi.org/10.18356/9789210559232
Vasa, L., Kubatko, O., Sotnyk, I., Piven, V., Trypolska, G., & Pysmenna, U. (2024). Economic and environmental drivers of renewable energy transition in the EU. Environmental Economics, 15(2), 16-25. https://doi.org/10.21511/ee.15(2).2024.16
Wang, Q., Wang, X., & Li, R. (2025). Energy transition and environmental sustainability: The interplay with natural resource rents and trade openness. Humanities and Social Sciences Communications, 12(1), Article 5521. https://doi.org/10.1057/s41599-025-05521-4
Wang, Y., Chen, X., & Li, J. (2025). The impact of political, financial, and economic risks on energy transition: The role of natural resource rents. Humanities and Social Sciences Communications, 12(1), Article 4370. https://doi.org/10.1057/s41599-025-04370-5
World Bank. (2023). World development indicators. World Bank Group. Retrieved from https://databank.worldbank.org/source/world-development-indicators
Wu, Y., Li, Z., & Chen, X. (2025). Navigating environmental concerns: Unveiling the role of economic governance, energy transition, and population aging on transport-based CO2 emissions in China. Energies, 18(7), Article 1748. https://doi.org/10.3390/en18071748
Yuan, H. (2024). Investigating the nexus between environmental information disclosure and green development efficiency: The intermediary role of green technology innovation – A PSM-DID analysis. Journal of the Knowledge Economy, 15(3), 11653-11683. https://doi.org/10.1007/s13132-023-01535-y
Zhang, H., Wang, Y., Qi, R., He, C., Yang, M., Cai, Y., & Chai, G. (2024). Natural resource accounting for urban ecosystem: A case study in Central China based on the System of Environmental-Economic Accounting. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4713236
Zhang, J., Muhammad, T., Dai, W., Khan, Q. R., & Ahmad, M. (2024). How does the resource curse influence economic performance? Exploring the role of natural resource rents and renewable energy consumption in South Asia. Sustainability, 16(24), Article 11138. https://doi.org/10.3390/su162411138
Zhang, L., Godil, D. I., Badr, M., & Lu, W. (2024). Do regulatory affairs, political stability, and renewable energy matter for green economic growth? Evidence from South Asia. Energy & Environment, 35(3), 1236-1270. https://doi.org/10.1177/0958305X241236270
Zhang, Y., Li, L., & Zhang, J. (2023). Influencing factors of green energy transition: The role of economic policy uncertainty, technology innovation, and ecological governance in China. Frontiers in Environmental Science, 10, Article 1058967. https://doi.org/10.3389/fenvs.2022.1058967
Zhao, C., Ju, S., Xue, Y., Ren, T., Ji, Y., & Chen, X. (2022). China's energy transitions for carbon neutrality: Challenges and opportunities. Carbon Neutrality, 1(1), 7. https://doi.org/10.1007/s43979-022-00010-y
Zhao, Y., Li, X., & Chen, W. (2023). Emission reduction with hybrid mechanisms in civil aviation. Frontiers in Environmental Science, 11, Article 1138931. https://doi.org/10.3389/fenvs.2023.1138931
Authors
How to Cite
License
Copyright (c) 2026 Saqib Munir, Mushab Rashid, Abdul Ghaffar
This work is licensed under a Creative Commons Attribution 4.0 International License.
This journal provides immediate and free open access to all its content and is distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0). This means readers are permitted to read, download, copy, distribute, print, search, or link to the full texts of articles, or use them for any other lawful purpose, without asking prior permission from the publisher or the author, as long as proper attribution is given. This policy is consistent with the Budapest Open Access Initiative (BOAI) definition of open access.
Metrics
Similar Articles
- Syeda Anam Hassan, Inayatul Haq, Alamzeb Aamir, Ihtisham ul Haq, Khalid Zaman, Exploring How Income Inequality, Education, and Policy Shape Energy Access Disparities in Southeast Asia , Innovation Economics Frontiers: Vol. 28 No. 2 (2025)
- Anthony Orji, Elis Moses Onoh, Onyinye Imelda Anthony-Orji, Jonathan Emenike Ogbuabor, Oluchi Okoro, Joseph Fanen Akpesue, Tourism, Migration, And Productive Capacity Growth In Sub-Saharan Africa , Innovation Economics Frontiers: Vol. 28 No. 2 (2025)
- Abdelkader Mohamed Sghaier Derbali, An Asymmetrical Relationship Between Oil Price Fluctuations And Geopolitical Tensions Between China And The United States , Innovation Economics Frontiers: Vol. 29 No. 1 (2026)
- Fentahun Admassu Yayeh, From Peg to Float: Economic and Political Implications of the Ethiopian Birr Flotation , Innovation Economics Frontiers: Vol. 28 No. 1 (2025)
- Shuhua Zhang, Impact of Urban Digital Economy on ESG Performance: Do Technological and Business Model Innovation Matter , Innovation Economics Frontiers: Vol. 28 No. 1 (2025)
- Fentahun Admassu Yayeh, Wondaferahu Mulugeta Demissie, Social Capital and Saving Behavior in Ethiopia: Evidence from the Amhara National Regional State , Innovation Economics Frontiers: Vol. 28 No. 1 (2025)
- Obed Ifeanyichukwu Ojonta, Jonathan Emenike Ogbuabor, Technological Innovation, Governance Institutions, Infrastructure Development, and Economic Complexity in Africa: Evidence from Dynamic Panel Data , Innovation Economics Frontiers: Vol. 29 No. 1 (2026)
- Njong Mom Aloysius, Ndamsa Dickson Thomas, Abety Paul, Nguena Christian-Lambert, The Impact of School Infrastructure on Academic Performance in Cameroon: Empirical Evidence From Cameroon , Innovation Economics Frontiers: Vol. 28 No. 1 (2025)
- Anthony Orji, Jovita Nneka Uwakwe, Onyinye Imelda Anthony-Orji, Jonathan Emenike Ogbuabor, Juliana Ngozi Obiorah, Foreign Direct Investment, Capital Flows, and Sectoral Growth in Nigeria: A Comparative Analysis of Agriculture and Manufacturing , Innovation Economics Frontiers: Vol. 28 No. 2 (2025)
- Lanchun Huang, Zhan Wang, ESG and Administrative Costs in Equity Trading: Evidence from China , Innovation Economics Frontiers: Vol. 27 No. 2 (2024)
You may also start an advanced similarity search for this article.