Exploring the link between technological innovation, economic development, and CO2 emissions in the US. Application of the ANN and EKC techniques

Authors

  • Seun Adebowale Adebanjo Statistical training and consultation, Nigeria https://orcid.org/0000-0002-2423-363X
  • Wasiu Babajide Akintunde Texas Tech University, United States

DOI:

https://doi.org/10.56556/jescae.v3i1.809

Keywords:

Technological innovation, Economic development, CO2 emissions, EKC, ANN

Abstract

The developed world, which includes the United States of America (US), constantly works to reduce carbon dioxide emissions for the benefit of its people's health while advancing technical innovation to achieve impressive economic development. This motivates this study to use artificial neural network (ANN) and the Environmental Kuznets Curve (EKC) technique to explore the relationship between technological innovation, economic development, and CO2 emissions in the US in order to add to the body of knowledge already in existence. For this study, secondary data from 1990 to 2023 was gathered from the World Bank and globaleconomy.com. The results show that, whereas the artificial neural network shows that economic development contributes more to C02 emissions, the Environmental Kuznets Curve shows that higher levels of technical innovation and economic development lower C02 emissions. Hence, in order to maintain C02 emissions at the lowest possible level and improve the nation's atmospheric conditions, the US government should guarantee sustainable policies that will promote economic development and technological innovation.

Author Biographies

Seun Adebowale Adebanjo, Statistical training and consultation, Nigeria

Statistical training and consultation, Nigeria

Wasiu Babajide Akintunde, Texas Tech University, United States

Texas Tech University, United States

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Published

2024-03-12

How to Cite

Adebanjo, S. A., & Wasiu Babajide Akintunde. (2024). Exploring the link between technological innovation, economic development, and CO2 emissions in the US. Application of the ANN and EKC techniques. Journal of Environmental Science and Economics, 3(1), 65–77. https://doi.org/10.56556/jescae.v3i1.809

Issue

Section

Research Article