Effect of Renewable Energy Consumption, Artificial Intelligence, and Education on Economic Growth for Period 1993-2023: Quantile Regression-ARDL Approach

Rejaul Karim (), Yahya Fikri (), Dinko Primorac (), Abdelhamid Nechad (), Sharmila Devi Ramachandaran () and Mohamed Rhalma ()
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Rejaul Karim: Department of Business Administration, Varendra University, Rajshahi-6204, Bangladesh; & Faculty of Business and Communications, INTI International University, Putra Nilai, 71800, Malaysia,
Yahya Fikri: National School of Business and Management Tangier, Research Laboratory of Governance and Organizations Performance (LRGPO), Abdelmalek Essaadi University Tetouan, Morocco,
Dinko Primorac: Dean of faculty of Economics. University North Croatia, Croatia,
Abdelhamid Nechad: ESCA School of Business and Management, Casablanca, Morocco,
Sharmila Devi Ramachandaran: Faculty of Business and Communications, INTI International University, Putra Nilai, 71800, Malaysia.
Mohamed Rhalma: Faculty of Business and Communications, INTI International University, Putra Nilai, 71800, Malaysia.

International Journal of Energy Economics and Policy, 2026, vol. 16, issue 2, 636-645

Abstract: Since education affects environmental practices, energy transition, and economic growth, it is a crucial part of sustainable development. The rise in the rate of solarization in Morocco is a result of public education activities that could boost technical innovation and productivity. The purpose of this study is to ascertain how Morocco affects economic growth (EG), education, general government consumption spending (GGCS), artificial intelligence (AI), and renewable energy consumption (REC). To assess the short- and long-term correlations between the model's variables, this study combined the least squares ordinary approach with a Quantile Regression-ARDL Approach for stationarity and distributed deterioration. Annual data from 1993 to 2023 from the International Energy Agency (IEA), World Development Indicators (WDI), and Energy Progress Report have been gathered for the study. Long-term relationships were evaluated using the bound test, and heteroscedasticity in the model residuals was examined using the White test. Numerous connections between independent and dependent variables were shown by empirical study. While the dependent variable was stationary in the first difference, the actual data demonstrated that the independent variables were not stationary in the first difference but became stationary in the second. A long-term association between independent and dependent variables was validated using the bound test-based model simulation. The short- and long-term connections between EG and schooling, however, were refuted. There were no indications of heteroscedasticity in the model residuals. The results show how education, AI, REC, GGCS, and economic growth interact in a multifaceted way in Morocco. When creating policies for sustainable development, policymakers should take these relationships into account, especially when attempting to strike a balance between environmental sustainability, educational advancement, and economic growth.

Keywords: Artificial Intelligence; Renewable Energy Consumption; Education; Economic Growth; Morocco (search for similar items in EconPapers)
Date: 2026
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DOI: 10.32479/ijeep.21799

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