Energy Poverty, Artificial Intelligence, Renewable Energy, and Education: Where is Economic Growth? Empirical Study via BVAR-ARDL Approaches

Abstract

Public education initiatives that have the potential to increase technical innovation and productivity are responsible for Morocco's increasing rate of solarization. The current study seeks to ascertain how Morocco's economic growth is impacted by renewable energy (GGCS), energy poverty, education, artificial intelligence (AI), and health. In order to collect annual data from 1993 to 2023, this study used the ARDL and Bayesian VAR approaches simultaneously for the first time with WDI and ODCE databases of these all variables in the Moroccan context. Form replication based on the bound test was used to confirm a long-term link between the endogenous and exogenous variables. All of our research's hypotheses, however, were eventually confirmed. The ramifications shed light on the intricate connections between Morocco's renewable energy, health, education, artificial intelligence, and economic growth (GGCS). Policymakers should consider these connections when developing sustainable development strategies, particularly when contrasting EG with renewable energy (GGCS), artificial intelligence (AI), health, and education. The current study contributes to the body of prior research by investigating the dynamics of education, AI, health, renewable energy (GGCS), and EG in the Moroccan environment for the first time. It provides empirical evidence of the long-term relationships between these factors while challenging certain conventional wisdoms.