Abstract:
Due to G-7 countries' commitment to sustaining United Nations Sustainable Development Goal 8, which focuses on sustainable economic growth, there is a need to investigate the impact of tax revenue and institutional quality on economic growth,
considering the role of artificial intelligence (AI) in the G-7 countries from 2012 to 2022. Cross-Sectional Augmented
Autoregressive Distributed Lag (CS-ARDL) technique is used to analyze the data. The study's findings indicate a long-run
equilibrium relationship among the variables under examination. The causality results can be categorized as bidirectional,
unidirectional, or indicating no causality. Based on the CS-ARDL results, the study recommends that G-7 governments and
policymakers prioritize and strengthen the integration of AI into their institutions to stimulate growth in both the short and long-term. However, the study cautions against overlooking the interaction between AI and tax revenue, as it did not
demonstrate support for economic growth. While the interaction between AI and institutional quality shows potential for
contributing to growth, it is crucial to implement robust measures to mitigate any potential negative effects that may arise
from AI's interaction with tax systems. Therefore, the study suggests the development of AI-friendly tax policies within the
G-7 countries, considering the nascent nature of the AI sector/industry.
Description:
DATA AVAILABITY STATEMENT: All data generated or analyzed during this study are
not included in this submission but can be made available upon reasonable request. Additionally, the data are publicly available.
