This study assesses the impact of Saudi Arabia's Vision 2030 economic initiatives-diversification, foreign direct investment (FDI), power consumption, urbanization and industrialization-on carbon emissions across short- and long-term timeframes.
This study employs wavelet coherence analysis to explore time-frequency relationships and dynamic co-movements between Vision 2030 policies and environmental quality. Nonparametric Granger causality tests further validate these interactions, providing a nuanced, time-sensitive evaluation of policy impacts.
The study investigates the extent to which Vision 2030 contributes to addressing environmental degradation in Saudi Arabia. Wavelet analysis reveals an anti-phase episode between diversification and emissions in 1994–1997, where higher diversification coincides with lower emissions, and a later in-phase co-movement in 2016–2020 in which diversification and the carbon footprint move together and emissions appear to slightly lead diversification, indicating a transitional rather than fully decoupled relationship.
This study's findings are specific to Saudi Arabia's Vision 2030 context and may not generalize to other regions. It contributes to the body of knowledge by demonstrating wavelet analysis as a powerful tool for uncovering time-dependent policy impacts on environmental sustainability.
Findings from the wavelet analysis provide actionable insights for Saudi policymakers and economic institutions, highlighting the potential to direct economic diversification toward a lower carbon trajectory through targeted Vision 2030 initiatives, even though short-run co-movement between diversification and emissions can still occur during transitional phases.
The study methods, findings and results can benefit economic institutions and policymakers by improving the efficiency and effectiveness of the possibility for economic shifts to coexist with sustainable environmental practices and provide perspectives into the perfect integration of economic and environmental policies in Saudi Arabia. This will have a significant impact on social aspects.
This study provides a unique contribution by using wavelet coherence analysis to deliver the first quantitative, time-frequency evidence of Vision 2030’s effectiveness in balancing environmental sustainability with economic progress in Saudi Arabia.
