Abstract
This study investigates the existence of long-run relationship between CO2 emissions, economic growth, energy use, and urbanization in Saudi Arabia over the period 1971–2014. The autoregressive distributed lag (ARDL) approach with structural breaks, where structural breaks are identified with the recently impulse saturation break tests, is applied to conduct the analysis. The bounds test result supports the existence of long-run relationship among the variables. The existence of environmental Kuznets curve (EKC) hypothesis has also been tested. The results reveal the non-validity of the EKC hypothesis for Saudi Arabia as the relationship between GDP and pollution is positive in both the short and the long run. Moreover, energy use increases pollution both in short and long run in the country. On the contrary, the results show a negative and significant impact of urbanization on carbon emissions in Saudi Arabia, which means that urban development is not an obstacle to the improvement of environmental quality. Consequently, policy-makers in Saudi Arabia should consider the efficiency enhancement, frugality in energy consumption, and especially increase the share of renewable energies in the total energy mix.
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Notes
Saudi Arabia Monetary Agency (2014): Forty Nineth Annual Report, Government of Saudi Arabia. Available at http://www.sama.gov.sa/sites/SAMAEN/ ReportsStatistics/Pages/AnnualReport.aspx.
STIRPART Stochastic Impacts by Regression on Population, Affluence, and Technology.
Gulf Cooperation Council is a regional intergovernmental union consisting of Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates
Organization of the Petroleum Exporting Countries
Middle East and North Africa countries
Multicollinearity exists when two or more of the independent variables in a regression model are highly correlated.
In a recent paper, Narayan et al. (2016) proposed a different method to testing EKC hypothesis, based on cross-correlation: EKC exists if there is a positive cross-correlation between the current level of income and the past level of CO2 emissions and a negative cross-correlation between the current level of income and the future CO2 emissions.
The break date was identified by the impulse saturation break test (see the “Impulse saturation break tests for multiple breaks detection” section)
World Bank’s WDIs. http://databank.worldbank.org/data/home.aspx
The choice of the Narayan and Popp (2010) break test is motivated by the fact that this test chooses the break dates most accurate compared to the two existing and widely used unit root tests of Lumsdaine and Papell (1997) and Lee and Strazicich (2003). For more details, see Narayan and Popp (2013).
McKinsey Global Institute report, Saudi Arabia beyond oil: The investment and productivity transformation.
Following Narayan and Smyth (2004), the maximum number of lags in the ARDL was set equal to 2 given that annual data are used.
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The author would like to thank Deanship of Scientific Research at Majmaah University for supporting this work under Project Number 37/108.
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Raggad, B. Carbon dioxide emissions, economic growth, energy use, and urbanization in Saudi Arabia: evidence from the ARDL approach and impulse saturation break tests. Environ Sci Pollut Res 25, 14882–14898 (2018). https://doi.org/10.1007/s11356-018-1698-7
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DOI: https://doi.org/10.1007/s11356-018-1698-7