DRIVERS OF CO2 EMISSIONS: EVIDENCE FROM BANKING, DIGITALIZATION, AND RESOURCE DEPLETION

Abstract

This study analyzes the environmental impacts of banking, digitalization, and natural resource depletion in line with sustainable development goals for 94 countries covering the period 2014-2021. For this purpose, index values for banking and digitalization variables were generated using principal component analysis (PCA). Subsequently, econometric analysis was conducted using quantile regression and the IV-2SLS method as a supplementary method, considering the heterogeneous nature of carbon emissions. The findings reveal that digitalization and natural resource depletion increase carbon emissions at every quantile. The increasing carbon emissions impact of digitalization points to a rebound effect, which has recently gained support in the literature. The IV-2SLS findings also support these findings. However, as carbon emissions reach higher quantiles, the effects of digitalization decrease, while the effects of natural resource depletion increase. While banking initially has a reducing effect on carbon emissions, its effect appears to become insignificant as carbon emissions reach higher quantiles. The IV-2SLS findings, however, reveal a negative relationship for the overall panel. This suggests that the banking variable has different effects on carbon emissions for different emission levels. Considering the findings, we contribute to the literature by presenting important policy recommendations that are consistent and complementary to the findings.

Keywords

• sustainable development
• carbon emissions
• banking
• digitalization
• Natural Resource Depletion

References

1. Adha, R., Hong, C.Y., Agrawal, S. and Li, L.H. (2023). ICT, carbon emissions, climate change, and energy demand nexus: The potential benefit of digitalization in Taiwan. Energy & Environment, 34(5), 1619-1638. https://doi.org/10.2139/ssrn.4104936
2. Afjal, M., Kathiravan, C., Dana, L.P. and Nagarajan, C.D. (2023). The dynamic impact of financial technology and energy consumption on environmental sustainability. Sustainability, 15(12), 9327. https://doi.org/10.3390/su15129327
3. Ahakwa, I., Xu, Y., Tackie, E.A., Odai, L.A., Sarpong, F.A., Korankye, B. and Ofori, E.K. (2023). Do natural resources and green technological innovation matter in addressing environmental degradation? Evidence from panel models robust to cross-sectional dependence and slope heterogeneity. Resources Policy, 85, 103943. https://doi.org/10.1016/j.resourpol.2023.103943
4. Alin, A. (2010). Multicollinearity. Wiley Interdisciplinary Reviews: Computational Statistics, 2(3), 370-374. https://doi.org/10.1002/wics.84
5. Al-Mulali, U., Sheau-Ting, L. and Ozturk, I. (2015). The global move toward Internet shopping and its influence on pollution: An empirical analysis. Environmental Science and Pollution Research, 22, 9717-9727. https://doi.org/10.1007/s11356-015-4142-2
6. Altavilla, C., Boucinha, M., Pagano, M. and Polo, A. (2024). Climate risk, bank lending and monetary policy (ECB Working Paper No. 2969). https://doi.org/10.2139/ssrn.5230061
7. Altın, H. (2024). The impact of energy efficiency and renewable energy consumption on carbon emissions in G7 countries. International Journal of Sustainable Engineering, 17(1), 134-142. https://doi.org/10.1080/19397038.2024.2319648
8. Amer, E.A.A.A., Meyad, E.M.A., Meyad, A.M. and Mohsin, A.K.M. (2024). The impact of natural resources on environmental degradation: A review of ecological footprint and CO2 emissions as indicators. Frontiers in Environmental Science, 12, 1368125. https://doi.org/10.3389/fenvs.2024.1368125

9. Audi, M., Poulin, M., Ahmad, K. and Ali, A. (2025). Modeling disaggregate globalization to carbon emissions in BRICS: A panel quantile regression analysis. Sustainability, 17(6), 2638. https://doi.org/10.3390/su17062638
10. Avenyo, E.K. and Tregenna, F. (2022). Greening manufacturing: Technology intensity and carbon dioxide emissions in developing countries. Applied Energy, 324, 119726. https://doi.org/10.1016/j.apenergy.2022.119726
11. Axenbeck, J., Berner, A. and Kneib, T. (2024). What drives the relationship between digitalization and energy demand? Exploring heterogeneity in German manufacturing firms. Journal of Environmental Management, 369, 122317. https://doi.org/10.1016/j.jenvman.2024.122317
12. Batool, Z., Ali, S. and Rehman, A. (2022). Environmental impact of ICT on disaggregated energy consumption in China: A threshold regression analysis. Sustainability, 14(23), 15600. https://doi.org/10.3390/su142315600
13. Baum, C.F. (2006). An introduction to modern econometrics using Stata. Texas: Stata press.
14. Bolea, L., Duarte, R. and Sánchez-Chóliz, J. (2020). Exploring carbon emissions and international inequality in a globalized world: A multiregional-multisectoral perspective. Resources, Conservation and Recycling, 152, 104516. https://doi.org/10.1016/j.resconrec.2019.104516
15. Bondell, H.D., Reich, B.J. and Wang, H. (2010). Noncrossing quantile regression curve estimation. Biometrika, 97(4), 825-838. https://doi.org/10.1093/biomet/asq048
16. Boyce, S. and He, F. (2023). Quantifying the drivers of CO2 emissions across Canadian communities using quantile regression. Environmental Impact Assessment Review, 101, 107144. https://doi.org/10.1016/j.eiar.2023.107144
17. Byaro, M., Nkonoki, J. and Mafwolo, G. (2022). Exploring the nexus between natural resource depletion, renewable energy use, and environmental degradation in sub-Saharan Africa. Environmental Science and Pollution Research, 30(8), 19931-19945. https://doi.org/10.1007/s11356-022-23104-7
18. Cameron, A.C. and Trivedi, P.K. (2005). Microeconometrics: Methods and applications. UK: Cambridge university press.
19. Chancel, L. (2022). Global carbon inequality over 1990–2019. Nature Sustainability, 5(11), 931-938. https://doi.org/10.1038/s41893-022-00955-z
20. Charfeddine, L. and Kahia, M. (2019). Impact of renewable energy consumption and financial development on CO2 emissions and economic growth in the MENA region: A panel vector autoregressive (PVAR) analysis. Renewable Energy, 139, 198-213. https://doi.org/10.1016/j.renene.2019.01.010
21. Chen, C., Pinar, M. and Stengos, T. (2022). Renewable energy and CO2 emissions: New evidence with the panel threshold model. Renewable Energy, 194, 117-128. https://doi.org/10.1016/j.renene.2022.05.095
22. Chernozhukov, V. and Hansen, C. (2008). Instrumental variable quantile regression: A robust inference approach. Journal of Econometrics, 142(1), 379-398. https://doi.org/10.1016/j.jeconom.2007.06.005
23. Chernozhukov, V., Fernández‐Val, I. and Galichon, A. (2010). Quantile and probability curves without crossing. Econometrica, 78(3), 1093-1125. https://doi.org/10.3982/ecta7880
24. Clarke, D., Llorca Jaña, M. and Pailañir, D. (2023). The use of quantile methods in economic history. Historical Methods: A Journal of Quantitative and Interdisciplinary History, 56(2), 115-132. https://doi.org/10.2139/ssrn.3908874
25. Cowell, F. A. (2011). Measuring inequality. Oxford: Oxford University Press.
26. Dahal, A.K., Bhattarai, G. and Budhathoki, P.B. (2023). CO2 emissions, industrial output, and economic growth nexus: Evidence from Nepalese economy. Environmental Economics, 14(2), 1. https://doi.org/10.21511/ee.14(2).2023.01
27. Danish, Khan, N., Baloch, M.A., Saud, S. and Fatima, T. (2018). The effect of ICT on CO 2 emissions in emerging economies: Does the level of income matters? Environmental Science and Pollution Research, 25, 22850-22860. https://doi.org/10.1007/s11356-018-2379-2
28. Destek, M.A., Degirmenci, T. and Kocak, E. (2025). How does bank loans affect carbon emissions? A comparison of household and business loans. Environment, Development and Sustainability, Advance online publication. https://doi.org/10.1007/s10668-025-06232-1
29. Dogan, E. and Turkekul, B. (2016). CO2 emissions, real output, energy consumption, trade, urbanization and financial development: Testing the EKC hypothesis for the USA. Environmental Science and Pollution Research, 23(2), 1203-1213. https://doi.org/10.1007/s11356-015-5323-8
30. Ehigiamusoe, K.U. and Lean, H.H. (2019). Effects of energy consumption, economic growth, and financial development on carbon emissions: Evidence from heterogeneous income groups. Environmental Science and Pollution Research, 26(22), 22611-22624. https://doi.org/10.1007/s11356-019-05309-5
31. Ganda, F. (2019). The environmental impacts of financial development in OECD countries: A panel GMM approach. Environmental Science and Pollution Research, 26(7), 6758-6772. https://doi.org/10.1007/s11356-019-04143-z
32. Ghorashi, N. and Alavi Rad, A. (2018). Impact of financial development on CO2 emissions: Panel data evidence from Iran’s economic sectors. Journal of Community Health Research, 7(2), 127-133. Retrieved from https://jhr.ssu.ac.ir/
33. Gök, A. (2020). The role of financial development on carbon emissions: A meta regression analysis. Environmental Science and Pollution Research, 27(11), 11618-11636. https://doi.org/10.1007/s11356-020-07641-7
34. Gujarati, D.N. and Porter, D.C. (2009). Basic Econometrics. Ohio: McGraw-Hill.
35. Haldar, A. and Sethi, N. (2022). Environmental effects of information and communication technology-Exploring the roles of renewable energy, innovation, trade and financial development. Renewable and Sustainable Energy Reviews, 153, 111754. https://doi.org/10.1016/j.rser.2021.111754
36. Haldar, A., Sucharita, S., Dash, D.P., Sethi, N. and Padhan, P.C. (2023). The effects of ICT, electricity consumption, innovation and renewable power generation on economic growth: An income level analysis for the emerging economies. Journal of Cleaner Production, 384, 135607. https://doi.org/10.1016/j.jclepro.2022.135607
37. Han, D., Sheng, P., Xing, R. and Xu, F. (2025). Study on the influence of new quality productivity on carbon emissions of the manufacturing industry. Scientific Reports, 15(1), 26180. https://doi.org/10.1038/s41598-025-10827-z
38. Hanif, S., Bakar, A. and Nawaz, M.A. (2022). Relationship between information and communication technologies and sustainable development: Fresh evidence from group of seven (G-7) countries. iRASD Journal of Economics, 4(3), 517-526. https://doi.org/10.52131/joe.2022.0403.0096
39. Hao, Y., Zhang, Z.Y., Yang, C. and Wu, H. (2021). Does structural labor change affect CO2 emissions? Theoretical and empirical evidence from China. Technological Forecasting and Social Change, 171, 120936. https://doi.org/10.1016/j.techfore.2021.120936
40. Haseeb, A., Xia, E., Saud, S., Ahmad, A. and Khurshid, H. (2019). Does information and communication technologies improve environmental quality in the era of globalization? An empirical analysis. Environmental Science and Pollution Research, 26, 8594-8608. https://doi.org/10.1007/s11356-019-04296-x
41. He, H. (2024). Nexus of natural resources exploitation, social protection, and sustainable environment: COP27 is a sufficient solution? Resources Policy, 96, 105190. https://doi.org/10.1016/j.resourpol.2024.105190
42. He, Y., Wang, S. and Chen, N. (2024). Mineral rents, natural resources depletion, and ecological footprint nexus in high emitting countries: Panel GLM analysis. Resources Policy, 89, 104472. https://doi.org/10.1016/j.resourpol.2023.104472
43. Higón, D.A., Gholami, R. and Shirazi, F. (2017). ICT and environmental sustainability: A global perspective. Telematics and Informatics, 34(4), 85-95. https://doi.org/10.1016/j.tele.2017.01.001 Ho, K. and Wong, A. (2023). Effect of climate-related risk on the costs of bank loans: Evidence from syndicated loan markets in emerging economies. Emerging Markets Review, 55, 100977. https://doi.org/10.1016/j.ememar.2022.100977
44. Hotelling, H. (1931). The economics of exhaustible resources. Journal of Political Economy, 39(2), 137-175. https://doi.org/10.1086/254195
45. Huang, M.L. and Nguyen, C. (2018). A nonparametric approach for quantile regression. Journal of Statistical Distributions and Applications, 5(1), 3. https://doi.org/10.1186/s40488-018-0084-9
46. Huang, S.Z., Sadiq, M. and Chien, F. (2023). The impact of natural resource rent, financial development, and urbanization on carbon emission. Environmental Science and Pollution Research, 30(15), 42753-42765. https://doi.org/10.1007/s11356-021-16818-7
47. Hubacek, K., Baiocchi, G., Feng, K., Muñoz Castillo, R., Sun, L. and Xue, J. (2017). Global carbon inequality. Energy, Ecology and Environment, 2(6), 361-369. https://doi.org/10.1007/s40974-017-0072-9
48. Huo, J. and Peng, C. (2023). Depletion of natural resources and environmental quality: Prospects of energy use, energy imports, and economic growth hindrances. Resources Policy, 86, 104049. https://doi.org/10.1016/j.resourpol.2023.104049
49. Hussain, J., Khan, A. and Zhou, K. (2020). The impact of natural resource depletion on energy use and CO2 emission in Belt & Road Initiative countries: A cross-country analysis. Energy, 199, 117409. https://doi.org/10.1016/j.energy.2020.117409
50. International Resource Panel. (2024). Global resources outlook 2024: Bend the trend. Retrieved from https://www.resourcepanel.org/reports/global-resources-outlook-2024
51. Jan, A., Rahman, H.U., Zahid, M., Salameh, A.A., Khan, P.A., Al-Faryan, M.A.S., ... and Ali, H.E. (2023). Islamic corporate sustainability practices index aligned with SDGs towards better financial performance: Evidence from the Malaysian and Indonesian Islamic banking industry. Journal of Cleaner Production, 405, 136860. https://doi.org/10.1016/j.jclepro.2023.136860
52. Jiang, C. and Ma, X. (2019). The impact of financial development on carbon emissions: A global perspective. Sustainability, 11(19), 5241. https://doi.org/10.3390/su11195241
53. Justice, G., Nyantakyi, G. and Isaac, S. H. (2024). The effect of renewable energy on carbon emissions through globalization. Heliyon, 10(5), e26894. https://doi.org/10.1016/j.heliyon.2024.e26894
54. Kennedy, P. (2008). A guide to econometrics. New York: John Wiley & Sons.
55. Khan, I., Muhammad, I., Sharif, A., Khan, I. and Ji, X. (2024). Unlocking the potential of renewable energy and natural resources for sustainable economic growth and carbon neutrality: A novel panel quantile regression approach. Renewable Energy, 221, 119779. https://doi.org/10.1016/j.renene.2023.119779
56. Khazzoom, J.D. (1980). The incorporation of new technologies in energy supply estimation. In W.T. Ziemba, S.L. Schwartz and E. Koenigsberg (Eds.), Energy policy modeling: United States and Canadian experiences: Volume I specialized energy policy models (pp. 209-219). Dordrecht: Springer Netherlands.
57. Kitahara, D., Leng, K., Tezuka, Y. and Hirabayashi, A. (2021). Simultaneous spline quantile regression under shape constraints. Papers presented at the 2020 28th European Signal Processing Conference (EUSIPCO). Amsterdam, The Netherlands. https://doi.org/10.23919/eusipco47968.2020.9287462
58. Koenker, R. (2004). Quantile regression for longitudinal data. Journal of Multivariate Analysis, 91(1), 74-89. https://doi.org/10.1016/j.jmva.2004.05.006
59. Koenker, R. (2005). Quantile regression (Vol. 38). Cambridge: Cambridge university press.
60. Kongkuah, M. and Alessa, N. (2025). Renewable energy and carbon intensity: Global evidence from 184 countries (2000–2020). Energies, 18(13), 3236. https://doi.org/10.3390/en18133236
61. Kuznets, S. (1955). Economic growth and income inequality. The American Economic Review, 45(1), 1-28. Retrieved from https://www.jstor.org/journal/amereconrevi
62. Lange, S. and Berner, A. (2022). The growth rebound effect: A theoretical–empirical investigation into the relation between rebound effects and economic growth. Journal of Cleaner Production, 371, 133158. https://doi.org/10.1016/j.jclepro.2022.133158
63. Lee, J.W. and Brahmasrene, T. (2014). ICT, CO2 emissions and economic growth: Evidence from a panel of ASEAN. Global Economic Review, 43(2), 93-109. https://doi.org/10.1080/1226508x.2014.917803
64. Li, L., Liu, W., Khalid, S. and Mahmood, H. (2025). Investigating the role of natural resource depletion and consumption expenditures in escalating carbon inequality. International Journal of Finance & Economics, Advance online publication. https://doi.org/10.1002/ijfe.3145
65. Li, S. and Tang, Y. (2024). The impact of the digital economy on carbon emission levels and its coupling relationships: Empirical evidence from China. Sustainability, 16(13), 5612. https://doi.org/10.3390/su16135612
66. Li, X., Liu, J. and Ni, P. (2021). The impact of the digital economy on CO2 emissions: A theoretical and empirical analysis. Sustainability, 13(13), 7267. https://doi.org/10.3390/su13137267
67. Liu, Z., Li, J. and Sun, H. (2024). Climate transition risk and bank risk-taking: The role of digital transformation. Finance Research Letters, 61, 105028. https://doi.org/10.1016/j.frl.2024.105028
68. Luo, B., Khan, A.A., Wu, X. and Li, H. (2023). Navigating carbon emissions in G-7 economies: A quantile regression analysis of environmental-economic interplay. Environmental Science and Pollution Research International, 30(47), 104697–104712. https://doi.org/10.1007/s11356-023-29722-z
69. Machado, J.A. and Silva, J.S. (2019). Quantiles via moments. Journal of Econometrics, 213(1), 145-173. https://doi.org/10.1016/j.jeconom.2019.04.009
70. Magee, C.L. and Devezas, T.C. (2017). A simple extension of dematerialization theory: Incorporation of technical progress and the rebound effect. Technological Forecasting and Social Change, 117, 196-205. https://doi.org/10.1016/j.techfore.2016.12.001
71. Majeed, M.T. (2018). Information and communication technology (ICT) and environmental sustainability in developed and developing countries. Pakistan Journal of Commerce and Social Sciences, 12(3), 758-783. Retrieved from https://www.jespk.net/
72. Majeed, M.T. and Mazhar, M. (2019). Financial development and ecological footprint: A global panel data analysis. Pakistan Journal of Commerce and Social Sciences (PJCSS), 13(2), 487-514. https://www.jespk.net/
73. Mathieux, F., Ardente, F. and Bobba, S. (2020). Ten years of scientific support for integrating circular economy requirements in the EU ecodesign directive: Overview and lessons learnt. Procedia CIRP, 90, 137-142. https://doi.org/10.1016/j.procir.2020.02.121
74. Mehmood, U. (2023). Environmental sustainability through renewable energy and banking sector development: Policy implications for N-11 countries. Environmental Science and Pollution Research, 30(9), 22296-22304. https://doi.org/10.1007/s11356-022-23738-7
75. Murugesan, S. (2008). Harnessing green IT: Principles and practices. IT professional, 10(1), 24-33. https://doi.org/10.1109/mitp.2008.10
76. Omoke, P.C., Nwani, C., Effiong, E.L., Evbuomwan, O.O. and Emenekwe, C.C. (2020). The impact of financial development on carbon, non-carbon, and total ecological footprint in Nigeria: New evidence from asymmetric dynamic analysis. Environmental Science and Pollution Research, 27(17), 21628-21646. https://doi.org/10.1007/s11356-020-08382-3
77. Omri, A., Daly, S., Rault, C. and Chaibi, A. (2015). Financial development, environmental quality, trade and economic growth: What causes what in MENA countries. Energy Economics, 48, 242-252. https://doi.org/10.2139/ssrn.2575048
78. Ozcan, B. and Apergis, N. (2018). The impact of internet use on air pollution: Evidence from emerging countries. Environmental Science and Pollution Research, 25, 4174-4189. https://doi.org/10.1007/s11356-017-0825-1
79. Ozturk, I. and Acaravci, A. (2013). The long-run and causal analysis of energy, growth, openness and financial development on carbon emissions in Turkey. Energy Economics, 36, 262-267. https://doi.org/10.1016/j.eneco.2012.08.025
80. Parveen, S., Khan, S., Kamal, M.A., Abbas, M.A., Aijaz Syed, A. and Grima, S. (2023). The influence of industrial output, financial development, and renewable and non-renewable energy on environmental degradation in newly industrialized countries. Sustainability, 15(6), 4742. https://doi.org/10.3390/su15064742
81. Peng, H.R., Zhang, Y.J. and Liu, J.Y. (2023). The energy rebound effect of digital development: Evidence from 285 cities in China. Energy, 270, 126837. https://doi.org/10.1016/j.energy.2023.126837
82. Pu, G., Wong, W.K., Du, Q., Al Shraah, A., Alromaihi, A. and Muda, I. (2024). Asymmetric impact of natural resources, fintech, and digital banking on climate change and environmental sustainability in BRICS countries. Resources Policy, 91, 104872. https://doi.org/10.1016/j.resourpol.2024.104872
83. Rafique, M.Z., Li, Y., Larik, A.R. and Monaheng, M.P. (2020). The effects of FDI, technological innovation, and financial development on CO 2 emissions: Evidence from the BRICS countries. Environmental Science and Pollution Research, 27, 23899-23913. https://doi.org/10.1007/s11356-020-08715-2
84. Rosselot, K.S., Allen, D.T. and Ku, A.Y. (2021). Comparing greenhouse gas impacts from domestic coal and imported natural gas electricity generation in China. ACS Sustainable Chemistry & Engineering, 9(26), 8759-8769. https://doi.org/10.1021/acssuschemeng.1c01517
85. Salahuddin, M., Alam, K. and Ozturk, I. (2016). Is rapid growth in Internet usage environmentally sustainable for Australia? An empirical investigation. Environmental Science and Pollution Research, 23, 4700-4713. https://doi.org/10.1007/s11356-015-5689-7
86. Sastry, P.R., Verner, E. and Marques-Ibanez, D. (2024). Business as usual: Bank net zero commitments, lending, and engagement (NBER Working Paper No. 32402). https://doi.org/10.3386/w32402
87. Shang, X. and Niu, H. (2023). Does the digital transformation of banks affect green credit? Finance Research Letters, 58, 104394. https://doi.org/10.1016/j.frl.2023.104394
88. Stevens, P., Lahn, G. and Kooroshy, J. (2015). The resource curse revisited. London: Chatham House for the Royal Institute of International Affairs.
89. Sun, J. and Wu, X. (2024). Digital economy, energy structure and carbon emissions: Evidence from China. Sage Open, 14(2), 21582440241255756. https://doi.org/10.1177/21582440241255756
90. Teng, F., He, J., Pan, X. and Zhang, C. (2011). Metric of carbon equity: Carbon Gini index based on historical cumulative emission per capita. Advances in Climate Change Research, 2(3), 134-140. https://doi.org/10.3724/sp.j.1248.2011.00134
91. UNCTAD. (2024). Digital economy report 2024. Retrieved from https://unctad.org/system/files/official-document/der2024_en.pdf
92. Valadkhani, A., Smyth, R. and Nguyen, J. (2019). Effects of primary energy consumption on CO2 emissions under optimal thresholds: Evidence from sixty countries over the last half century. Energy Economics, 80, 680-690. https://doi.org/10.1016/j.eneco.2019.02.010
93. Vardar, S., Demirel, B. and Onay, T.T. (2022). Impacts of coal-fired power plants for energy generation on environment and future implications of energy policy for Turkey. Environmental Science and Pollution Research, 29(27), 40302-40318. https://doi.org/10.1007/s11356-022-19786-8
94. Voumik, L.C., Islam, M.A., Ray, S., Mohamed Yusop, N.Y. and Ridzuan, A.R. (2023). CO2 emissions from renewable and non-renewable electricity generation sources in the G7 countries: Static and dynamic panel assessment. Energies, 16(3), 1044. https://doi.org/10.3390/en16031044
95. Wagner, U.J., Kassem, D., Gerster, A., Jaraite, J., Klemetsen, M.E., Laukkanen, M., ... and Schusser, S. (2020). Carbon footprints of European manufacturing jobs: Stylized facts and implications for climate policy (Collaborative Research Center Discussion Paper No. 250). Retrieved from https://www.wiwi.uni-bonn.de/bgsepapers/boncrc/CRCTR224_2020_250.pdf
96. Wang, H., Fu, Z., Wang, S. and Zhang, W. (2021). Analysis of CO2 emissions in the whole production process of coal-fired power plant. Sustainability, 13(19), 11084. https://doi.org/10.3390/su131911084
97. Wooldridge, J.M. (2016). Introductory econometrics a modern approach. Boston: South-Western Cengage Learning.
98. World Bank. (2021). The changing wealth of Nations 2021: Managing assets for the future (Executive summary & main findings). Retrieved from https://www.worldbank.org/en/publication/changing-wealth-of-nations
99. Xie, X., Shen, Y., Zhang, H. and Guo, F. (2018). Can digital finance promote entrepreneurship? Evidence from China. China Economic Quarterly, 17(4), 1557-1580. Retrieved from https://scispace.com/
100. Xu, J., Chen, F., Zhang, W., Liu, Y. and Li, T. (2023). Analysis of the carbon emission reduction effect of Fintech and the transmission channel of green finance. Finance Research Letters, 56, 104127. https://doi.org/10.2139/ssrn.4432596
101. Xu, Y., Jia, J., Mahmood, H. and Khalid, S. (2024). Natural resource depletion and carbon inequality: An empirical insight from developed and developing countries. Energy & Environment, 0958305X241256551. https://doi.org/10.1177/0958305x241256551
102. Yang, C., Qi, H., Jia, L., Wang, Y. and Huang, D. (2024). Impact of digital technologies and financial development on green growth: Role of mineral resources, institutional quality, and human development in south Asia. Resources Policy, 90, 104699. https://doi.org/10.1016/j.resourpol.2024.104699
103. Yang, D., Yang, Z. and Wu, H. (2025). Effects and mechanisms of digital economy development on corporate carbon emission intensity: Empirical evidence from cross-country data. Digital Economy and Sustainable Development, 3(1), 3. https://doi.org/10.1007/s44265-024-00047-0
104. Zhang, Z., Chen, L., Li, J. and Ding, S. (2024). Digital economy development and carbon emission intensity—mechanisms and evidence from 72 countries. Scientific Reports, 14(1), 28459. https://doi.org/10.1038/s41598-024-78831-3
105. Zhou, B., Thies, S., Gudipudi, R., Lüdeke, M.K., Kropp, J.P. and Rybski, D. (2020). A Gini approach to spatial CO2 emissions. Plos One, 15(11), e0242479. https://doi.org/10.1371/journal.pone.0242479