Linear and Nonlinear Relationships Between Energy Consumption, Renewable Energy, Greenhouse Gas Emissions, and Economic Growth in Saudi Arabia: A Combined ARDL and Threshold Approach

The shift toward renewable energy is a priority for many countries seeking to mitigate climate change, support sustainable economic growth, and enhance energy security. This study examines the relationships between fossil fuel energy consumption, renewable energy, CO2 emissions, CH4 emissions, and economic growth in Saudi Arabia over 1990–2022, using an Autoregressive Distributed Lag (ARDL) model and a Threshold Regression (TR) model. The bounds test indicates a long-run relationship among the variables, while the error-correction term suggests that approximately 52.7% of short-run deviations from long-run equilibrium are corrected within one year. Renewable energy is positively and significantly associated with economic growth in both the short and long run. However, the threshold analysis provides insufficient statistical evidence of a nonlinear relationship: the estimated split at 0.0425 yields a wild-bootstrap p-value of 0.943, while the levels specification yields a p-value of 0.483. Accordingly, the estimated split is not established as a statistically significant threshold. CO2 emissions are positively associated with economic growth in both renewable-energy regimes, whereas CH4 emissions show a positive and significant long-run association but negative short-run dynamics, with no statistically significant regime-specific effects. Overall, the findings support a positive association between renewable energy and economic growth in the linear model but do not establish a significant threshold effect. These results inform the discussion of energy-transition policies in Saudi Arabia.