Pathways to Carbon Neutrality in the United States: Evaluating Private AI Investment, Financial Development, and Macroeconomic Forces

Abstract

This study analyzes the impact of private investment in artificial intelligence (PAI) and financial development (FD) on carbon dioxide (CO₂) emissions in the United States as well as the contribution of foreign direct investment (FDI), economic growth, and population growth. The analysis uses the annual data of 1996-2022 to test the short- and long-run dynamics using the STIRPAT framework with the ARDL bounds testing technique. The ARDL methodology is confirmed through unit root analyses, which support the presence of a mixed-order integration. The findings indicate that GDP, FDI, and population growth serve as principal factors influencing CO2 emissions in both the short and long term, thereby suggesting that environmental pressures persist amidst economic and demographic progression. In contrast, PAI has a negative and statistically significant impact on emissions, which underscores the prospects of developed technologies to increase energy efficiency and contribute to environmental sustainability. FD also helps minimize emissions in the long run, which highlights the beneficial impact of financial systems in facilitating cleaner patterns of investment. Further, the results of Granger causality indicate numerous unidirectional relationships, especially between GDP, PAI, FDI, population and CO₂ emissions.

Keywords

• Private AI Invesment
• Financial Development
• Carbon Emissions
• STIRPAT Model
• ARDL Approach

Amerika Birleşik Devletleri'nde Karbon Nötrlüğüne Giden Yollar: Özel Yapay Zeka Yatırımlarının, Finansal Gelişmenin ve Makroekonomik Güçlerin Değerlendirilmesi

Abstract

Bu çalışma, özel yapay zekâya yatırımların (ÖYZ) ve finansal kalkınmanın (FK) Amerika Birleşik Devletleri'ndeki karbondioksit (CO₂) emisyonları üzerindeki etkisini ve ayrıca yabancı doğrudan yatırımın (DYY), ekonomik büyümenin ve nüfus artışının katkısını analiz etmektedir. Analiz, 1996-2022 yılları arasındaki yıllık verileri kullanarak, ARDL sınır testi tekniği ile STIRPAT çerçevesini kullanarak kısa ve uzun vadeli dinamikleri test etmektedir. ARDL metodolojisi, karma dereceli entegrasyonun varlığını destekleyen birim kök analizleri ile doğrulanmıştır. Bulgular, GSYİH, DYY ve nüfus artışının hem kısa hem de uzun vadede CO₂ emisyonlarını etkileyen temel faktörler olduğunu ve böylece ekonomik ve demografik ilerlemeye rağmen çevresel baskıların devam ettiğini göstermektedir. Buna karşılık, ÖYZ'nin emisyonlar üzerinde negatif ve istatistiksel olarak anlamlı bir etkisi vardır; bu da gelişmiş teknolojilerin enerji verimliliğini artırma ve çevresel sürdürülebilirliğe katkıda bulunma potansiyelini vurgulamaktadır. FK ayrıca uzun vadede emisyonları en aza indirmeye yardımcı olur; bu da finansal sistemlerin daha temiz yatırım modellerini kolaylaştırmadaki faydalı etkisini vurgulamaktadır. Ayrıca, Granger nedensellik analizinin sonuçları, özellikle GSYİH, ÖYZ, DYY, nüfus ve CO₂ emisyonları arasında çok sayıda tek yönlü ilişki olduğunu göstermektedir.

Keywords

• Özel Yapay Zeka Yatırımları
• Finansal Gelişme
• Karbon Emisyonlar
• STIRPAT Modeli
• ARDL Yaklaşımı

References

1. Abid, A., Mehmood, U., Tariq, S., & Haq, Z. U. (2022). The effect of technological innovation, FDI, and financial development on CO2 emission: Evidence from the G8 countries. Environmental Science and Pollution Research, 29(8), 11654-11662. https://doi.org/10.1007/s11356-021-15993-x
2. Ahmad, S., Raihan, A., & Ridwan, M. (2024). Role of economy, technology, and renewable energy toward carbon neutrality in China. Journal of Economy and Technology, 2, 138-154. https://doi.org/10.1016/j.ject.2024.04.008
3. Alam, M. M., Murad, M. W., Noman, A. H. M., & Ozturk, I. (2016). Relationships among carbon emissions, economic growth, energy consumption and population growth: Testing Environmental Kuznets Curve hypothesis for Brazil, China, India and Indonesia. Ecological Indicators, 70, 466-479. https://doi.org/10.1016/j.ecolind.2016.06.043
4. Anser, M. K., Alharthi, M., Aziz, B., & Wasim, S. (2020). Impact of urbanization, economic growth, and population size on residential carbon emissions in the SAARC countries. Clean Technologies and Environmental Policy, 22(4), 923-936. https://doi.org/10.1007/s10098-020-01833-y
5. Balli, E., Sigeze, C., Ugur, M. S., & Çatık, A. N. (2023). The relationship between FDI, CO2 emissions, and energy consumption in Asia-Pacific economic cooperation countries. Environmental Science and Pollution Research, 30(15), 42845-42862. https://doi.org/10.1007/s11356-021-17494-3
6. Baloch, M. A., Zhang, J., Iqbal, K., & Iqbal, Z. (2019). The effect of financial development on ecological footprint in BRI countries: Evidence from panel data estimation. Environmental Science and Pollution Research, 26(6), 6199-6208. https://doi.org/10.1007/s11356-018-3992-9
7. Begum, R. A., Sohag, K., Abdullah, S. M. S., & Jaafar, M. (2015). CO2 emissions, energy consumption, economic and population growth in Malaysia. Renewable and Sustainable Energy Reviews, 41, 594-601. https://doi.org/10.1016/j.rser.2014.07.205
8. British Petroleum (2022). Energy data. Available at: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/downloads.html

9. Chen, P., Gao, J., Ji, Z., Liang, H., & Peng, Y. (2022). Do artificial intelligence applications affect carbon emission performance?—Evidence from panel data analysis of Chinese cities. Energies, 15(15), 5730. https://doi.org/10.3390/en15155730
10. Dehdar, F., Fuinhas, J. A., Karimi Alavijeh, N., Nazeer, N., & Zangoei, S. (2023). Investigating the determinants of carbon emissions in the USA: A state-level analysis. Environmental Science and Pollution Research, 30(9), 23023-23034. https://doi.org/10.1007/s11356-022-23831-x
11. Delanoë, P., Tchuente, D., & Colin, G. (2023). Method and evaluations of the effective gain of artificial intelligence models for reducing CO2 emissions. Journal of Environmental Management, 331, 117261. https://doi.org/10.1016/j.jenvman.2023.117261
12. Dong, M., Wang, G., & Han, X. (2023). Artificial intelligence, industrial structure optimization, and CO2 emissions. Environmental Science and Pollution Research, 30(50), 108757-108773. https://doi.org/10.1007/s11356-023-29859-x
13. Harris, B. (2020). The Biden plan for a clean energy revolution and environmental justice. Available at: https://htv-prod-media.s3.amazonaws.com/files/bidenclimateplan-1559610636.pdf
14. Lahiani, A. (2020). Is financial development good for the environment? An asymmetric analysis with CO2 emissions in China. Environmental Science and Pollution Research, 27(8), 7901-7909. https://doi.org/10.1007/s11356-019-07467-y
15. Liu, J., Liu, L., Qian, Y., & Song, S. (2022). The effect of artificial intelligence on carbon intensity: Evidence from China's industrial sector. Socio-Economic Planning Sciences, 83, 101002. https://doi.org/10.1016/j.seps.2020.101002
16. Mehmood, U., & Tariq, S. (2020). Globalization and CO2 emissions nexus: Evidence from the EKC hypothesis in South Asian countries. Environmental Science and Pollution Research, 27(29), 37044-37056. https://doi.org/10.1007/s11356-020-09774-1
17. Mehmood, U., Tariq, S., Ul-Haq, Z., & Meo, M. S. (2021). Does the modifying role of institutional quality remains homogeneous in GDP-CO2 emission nexus? New evidence from ARDL approach. Environmental Science and Pollution Research, 28(8), 10167-10174. https://doi.org/10.1007/s11356-020-11293-y
18. Mehmood, U. (2024). Analyzing the role of political risk, GDP, and eco-innovations towards CO2 emissions in South Asian countries. Journal of the Knowledge Economy, 15(1), 2121-2135. https://doi.org/10.1007/s13132-023-01292-y
19. Nassef, A. M., Olabi, A. G., Rezk, H., & Abdelkareem, M. A. (2023). Application of artificial intelligence to predict CO2 emissions: Critical step towards sustainable environment. Sustainability, 15(9), 7648. https://doi.org/10.3390/su15097648
20. Pachiyappan, D., Ansari, Y., Alam, M. S., Thoudam, P., Alagirisamy, K., & Manigandan, P. (2021). Short and long-run causal effects of CO2 emissions, energy use, GDP and population growth: Evidence from India using the ARDL and VECM approaches. Energies, 14(24), 8333. https://doi.org/10.3390/en14248333
21. Pattak, D. C., Tahrim, F., Salehi, M., Voumik, L. C., Akter, S., Ridwan, M., ... & Zimon, G. (2023). The driving factors of Italy’s CO2 emissions based on the STIRPAT model: ARDL, FMOLS, DOLS, and CCR approaches. Energies, 16(15), 5845. https://doi.org/10.3390/en16155845
22. Raihan, A., Atasoy, F. G., Atasoy, M., Ridwan, M., & Paul, A. (2022). The role of green energy, globalization, urbanization, and economic growth toward environmental sustainability in the United States. Journal of Environmental and Energy Economics, 1(2), 8-17. https://doi.org/10.56946/jeee.v1i2.377
23. Raihan, A., Ridwan, M., Tanchangya, T., Rahman, J., & Ahmad, S. (2023). Environmental effects of China's nuclear energy within the framework of Environmental Kuznets Curve and Pollution Haven Hypothesis. Journal of Environmental and Energy Economics, 2(1), 1-12. https://doi.org/10.56946/jeee.v2i1.346
24. Ridwan, M., Urbee, A. J., Voumik, L. C., Das, M. K., Rashid, M., & Esquivias, M. A. (2024). Investigating the Environmental Kuznets Curve hypothesis with urbanization, industrialization, and service sector for six South Asian countries: Fresh evidence from Driscoll Kraay standard error. Research in Globalization, 8, 100223. https://doi.org/10.1016/j.resglo.2024.100223
25. Rjoub, H., Odugbesan, J. A., Adebayo, T. S., & Wong, W. K. (2021). Sustainability of the moderating role of financial development in the determinants of environmental degradation: Evidence from Turkey. Sustainability, 13(4), 1844. https://doi.org/10.3390/SU13041844
26. Saadaoui, H., Dogan, M., & Omri, E. (2024). The impacts of hydroelectricity generation, financial development, geopolitical risk, income, and foreign direct investment on carbon emissions in Turkey. Environmental Economics and Policy Studies, 26(2), 239-261.https://doi.org/10.1007/s10018-023-00384-y
27. Salahuddin, M., Alam, K., Ozturk, I., & Sohag, K. (2018). The effects of electricity consumption, economic growth, financial development and foreign direct investment on CO2 emissions in Kuwait. Renewable and Sustainable Energy Reviews, 81, 2002-2010. https://doi.org/10.1016/j.rser.2017.06.009
28. Shahbaz, M., Gozgor, G., Adom, P. K., & Hammoudeh, S. (2019). The technical decomposition of carbon emissions and the concerns about FDI and trade openness effects in the United States. International Economics, 159, 56-73. https://doi.org/10.1016/j.inteco.2019.05.001
29. Suhrab, M., Soomro, J. A., Ullah, S., & Chavara, J. (2023). The effect of gross domestic product, urbanization, trade openness, financial development, and renewable energy on CO2 emission. Environmental Science and Pollution Research, 30(9), 22985-22991. https://doi.org/10.1007/s11356-022-23761-8
30. Tamazian, A., & Rao, B. B. (2010). Do economic, financial and institutional developments matter for environmental degradation? Evidence from transitional economies. Energy Economics, 32(1), 137-145. https://doi.org/10.1016/j.eneco.2009.04.004
31. Tiba, S., & Omri, A. (2017). Literature survey on the relationships between energy, environment and economic growth. Renewable and Sustainable Energy Reviews, 69, 1129-1146. https://doi.org/10.1016/j.rser.2016.09.113
32. US EIA. (Energy Information Administration). (2019). International energy outlook. Available at: https://www.eia.gov/outlooks/ieo/pdf/ieo2019.pdf
33. US EPA. (Environmental Protection Agency). (2020). Sources of greenhouse gas emissions. Available at: https://www.epa.gov/ghgemissions/sources-greenhouse-gas-emissions#carbon-dioxide
34. UN. (2017). The emissions gap report 2017, a UN environment synthesis report. United Nations Environment Programme. Available at: https://digitallibrary.un.org/record/3894804?v=pdf
35. Voumik, L. C., & Ridwan, M. (2023). Impact of FDI, industrialization, and education on the environment in Argentina: ARDL approach. Heliyon, 9(1). https://doi.org/10.1016/j.heliyon.2023.e12872
36. Voumik, L. C., Rahman, M. H., Rahman, M. M., Ridwan, M., Akter, S., & Raihan, A. (2023a). Toward a sustainable future: Examining the interconnectedness among Foreign Direct Investment (FDI), urbanization, trade openness, economic growth, and energy usage in Australia. Regional Sustainability, 4(4), 405-415. https://doi.org/10.1016/j.regsus.2023.11.003
37. Voumik, L. C., Ridwan, M., Rahman, M. H., & Raihan, A. (2023b). An investigation into the primary causes of carbon dioxide releases in Kenya: Does renewable energy matter to reduce carbon emission?. Renewable Energy Focus, 47, 100491. https://doi.org/10.1016/j.ref.2023.100491
38. Voumik, L. C., Ghosh, S., Rashid, M., Das, M. K., Esquivias, M. A., & Rojas, O. (2024). The effect of geopolitical risk and green technology on load capacity factors in BRICS. Utilities Policy, 88, 101757. https://doi.org/10.1016/j.jup.2024.101757
39. Wang, Q., Jiang, X. T., Ge, S., & Jiang, R. (2019). Is economic growth compatible with a reduction in CO2 emissions? Empirical analysis of the United States. Resources, Conservation and Recycling, 151, 104443. https://doi.org/10.1016/j.resconrec.2019.104443
40. World Bank. (2022). GDP current US$. Available at: https://data.worldbank.org
41. Yang, L., Hui, P., Yasmeen, R., Ullah, S., & Hafeez, M. (2020). Energy consumption and financial development indicators nexuses in Asian economies: A dynamic seemingly unrelated regression approach. Environmental Science and Pollution Research, 27(14), 16472-16483. https://doi.org/10.1007/s11356-020-08123-6
42. Zafar, M. W., Saud, S., & Hou, F. (2019). The impact of globalization and financial development on environmental quality: Evidence from selected countries in the Organization for Economic Co-operation and Development (OECD). Environmental Science and Pollution Research, 26(13), 13246-13262. https://doi.org/10.1007/s11356-019-04761-7
43. Zafar, M. W., Zaidi, S. A. H., Khan, N. R., Mirza, F. M., Hou, F., & Kirmani, S. A. A. (2019a). The impact of natural resources, human capital, and foreign direct investment on the ecological footprint: The case of the United States. Resources Policy, 63, 101428. https://doi.org/10.1016/j.resourpol.2019.101428
44. Zhao, P., Gao, Y., & Sun, X. (2023). The impact of artificial intelligence on pollution emission intensity—Evidence from China. Environmental Science and Pollution Research, 30(39), 91173-91188. https://doi.org/10.1007/s11356-023-28866-2
45. Zhu, H., Duan, L., Guo, Y., & Yu, K. (2016). The effects of FDI, economic growth and energy consumption on carbon emissions in ASEAN-5: Evidence from panel quantile regression. Economic Modelling, 58, 237-248. https://doi.org/10.1016/j.econmod.2016.05.003