Revisiting growth dynamics in G7: an econometric critique of AI, education and industrialization interactions

Purpose This study explores the key determinants of GDP growth in G7 countries (Canada, France, Germany, Italy, Japan, the UK and the United States). The analysis spans annual data from 2010 to 2023, emphasizing the roles of AI innovation, education, industrialization, governance and trade in shaping economic growth within G7 economies. Design/methodology/approach A dynamic panel data regression model is applied using the Arellano and Bond (1991) generalized method of moments (GMM) estimator to address endogeneity, autocorrelation and heteroskedasticity. Robustness checks include re-estimations with robust standard errors and Driscoll–Kraay standard errors to correct for cross-sectional dependence and further strengthen the validity of the results. Findings The results reveal that industrial value added, trade openness and investment growth significantly and positively influence GDP growth in G7 economies. Conversely, AI patent applications and government expenditure on education have negative effects, which may reflect short-term inefficiencies, resource diversion or misalignment between spending and labor market demands. Originality/value This study contributes to the literature by providing updated empirical evidence on growth drivers in advanced economies. It highlights the importance of balancing innovation and education spending with effective policy frameworks to maximize their long-term contribution to economic growth.