Abstract
Oman is committed to turning carbon neutral by 2040 whereby identifying the environmental sustainability-stimulating factors has become a critically important agenda for the nation. Against this backdrop, this study attempts to evaluate the marginal effects of economic growth, financial development, and low-carbon energy use on Oman’s carbon footprint levels using quarterly frequency data spanning from 1984Q1 to 2018Q4. Controlling for structural break concerns in the data, the results from the empirical analysis verify the carbon footprint-related environmental Kuznets curve hypothesis for Oman in the long-run. In this regard, the threshold level of per capita real GDP level of Oman is predicted at around US $23,500 which is below the average and maximum per capita real GDP level of Oman during the period considered in this study. Besides, the development of the financial sector and scaling up consumption of low-carbon energy resources are evidenced to boost and curb Oman’s short- and long-run carbon footprint figures, respectively. More importantly, the joint carbon footprint-mitigating impact of financial development and low-carbon energy use is also unearthed from the findings. In line with these major findings, a couple of relevant policy interventions are suggested to help Oman accomplish its 2040 carbon-neutrality agenda.
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NA conceptualized, conducted the econometric analysis, and wrote the introduction. NIH analyzed the findings and conducted the literature review. SAJ conducted the literature review and reviewed the draft. MM conceptualized, wrote the original draft, conducted the econometric analysis, highlighted the policy implications, supervised the work, and revised the manuscript. HM wrote the introduction and concluding remarks. MSA wrote the original draft and compiled the overall manuscript.
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Alam, N., Hashmi, N.I., Jamil, S.A. et al. The marginal effects of economic growth, financial development, and low-carbon energy use on carbon footprints in Oman: fresh evidence from autoregressive distributed lag model analysis. Environ Sci Pollut Res 29, 76432–76445 (2022). https://doi.org/10.1007/s11356-022-21211-z
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DOI: https://doi.org/10.1007/s11356-022-21211-z