article · Sustainability
An analysis of data from 1980 to 2020 examines how renewable energy, green finance, and public health expenditure affect environmental quality, measured through the ecological footprint, in Saudi Arabia. The research uses both linear and nonlinear autoregressive distributed lag models to observe short-term and long-term dynamics. Findings from the linear model indicate that all three variables have an impact on long-term environmental quality, which improved over the period studied. Furthermore, the nonlinear model demonstrates that positive and negative shocks create an unbalanced, asymmetric relationship between the variables across both time horizons. Overall, the analysis highlights the influential role these factors play in altering environmental conditions, supporting recommendations for policymakers to accelerate the deployment of renewable energy sources to reduce environmental harm.
Understanding how national spending, financing mechanisms, and clean energy adoption interact helps guide environmental protection strategies. This research reveals how specific economic and energy factors influence a country's ecological footprint over decades. These insights enable authorities to design targeted interventions that account for both predictable long-term trends and disruptive economic shocks when managing environmental sustainability.
This work represents early-stage macroeconomic research rather than a commercial technology or product. The insights may assist government bodies, environmental agencies, and public finance planners in designing national renewable energy incentives and public health spending frameworks. The abstract does not indicate a direct commercialisation pathway or application for private enterprise.
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This study uses data from 1980 to 2020 to analyze the explanatory power of renewable energy (RE), green finance (GF), and public health expenditure (PUHE) for environmental quality (ecological footprint: EF) in the Kingdom of Saudi Arabia (KSA). In order to examine the long- and short-term effects, we ran both linear autoregressive distribution (ARDL) and nonlinear autoregressive distribution (NARDL) models. The empirical results showed that, when estimating the ARDL model, all variables have an impact on the environment’s long-term quality, which has increased. Furthermore, the NARDL model supports the existence of significant positive or negative shocks that support an unbalanced relationship with the movement of variables over the short and long term. Overall, the study demonstrates the critical role of factors that can enhance the environment in the KSA setting. In light of this, we advise policymakers to encourage the use of additional renewable energy sources and to expedite their efforts to do so in order to slow down environmental damage.
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DOI: 10.3390/su15054286
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