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<p>Saudi Arabia’s per capita carbon emissions have risen persistently since the 1970s, driven by energy-intensive industrialisation and a structural reliance on oil. Existing studies have largely treated energy consumption as a direct, additive driver of emissions, overlooking how its environmental impact depends on the industrial structure that absorbs it. This study proposes a conditional emissions framework and tests it on Saudi annual data for 1970–2024, combining an autoregressive distributed lag (ARDL) model with an explicit energy–manufacturing interaction term, quantile regression across τ = 0.1–0.9, and Toda–Yamamoto causality analysis. In the long-run ARDL specification, the standalone coefficient on energy consumption is negative; however, the implied marginal effect at the sample-mean manufacturing share is positive (≈ 0.43), and rises monotonically with the manufacturing share of GDP, confirming that energy becomes emissions-intensive only within industrial production (interaction coefficient = 2.49, <i>p</i> &lt; 0.01). The quantile regression results refine rather than overturn this picture: the energy–manufacturing interaction is most evident in the lower-emission regimes and attenuates toward the upper tail. At the same time, oil dependence exerts a consistent positive effect across most of the distribution. A 1984 structural break, linked to the oil-price collapse and the policy pivot toward subsidised industrial energy, is significant across all emission regimes, providing empirical support for carbon lock-in theory. These findings imply that effective decarbonisation under Saudi Arabia’s Vision 2030 requires restructuring industrial energy use rather than simply reducing its aggregate volume.</p>

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Industrial energy use and oil dependence as conditional drivers of carbon emissions in Saudi Arabia — evidence from quantile regression

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  • 发表日期：

    2026年5月27日

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  • Uzma Khan,
  • Sahar Abdo Mohamed Elsayed,
  • Aarif Mohammad Khan

摘要

Saudi Arabia’s per capita carbon emissions have risen persistently since the 1970s, driven by energy-intensive industrialisation and a structural reliance on oil. Existing studies have largely treated energy consumption as a direct, additive driver of emissions, overlooking how its environmental impact depends on the industrial structure that absorbs it. This study proposes a conditional emissions framework and tests it on Saudi annual data for 1970–2024, combining an autoregressive distributed lag (ARDL) model with an explicit energy–manufacturing interaction term, quantile regression across τ = 0.1–0.9, and Toda–Yamamoto causality analysis. In the long-run ARDL specification, the standalone coefficient on energy consumption is negative; however, the implied marginal effect at the sample-mean manufacturing share is positive (≈ 0.43), and rises monotonically with the manufacturing share of GDP, confirming that energy becomes emissions-intensive only within industrial production (interaction coefficient = 2.49, p < 0.01). The quantile regression results refine rather than overturn this picture: the energy–manufacturing interaction is most evident in the lower-emission regimes and attenuates toward the upper tail. At the same time, oil dependence exerts a consistent positive effect across most of the distribution. A 1984 structural break, linked to the oil-price collapse and the policy pivot toward subsidised industrial energy, is significant across all emission regimes, providing empirical support for carbon lock-in theory. These findings imply that effective decarbonisation under Saudi Arabia’s Vision 2030 requires restructuring industrial energy use rather than simply reducing its aggregate volume.