An empirical analysis of the determinants of CO2 emissions in ‎GCC countries

ABSTRACT

Sustainable development has recently attracted growing attention on behalf of scientists and policymakers. One of the main pillars to achieve sustainable development goals is decidedly linked to the environment. This paper contributes to the existing literature by shedding light on the determinants of environmental degradation in Gulf ‎Cooperation Council countries between 1980 and 2017. More specifically, the effects of per capita ‎GDP, energy consumption, urbanization, international trade and foreign direct investments on CO2 ‎emissions are investigated. Using the Stochastic Impacts by Regression on Population, Affluence, ‎and Technology (STIRPAT) model and the PMG-ARDL approach, findings suggest the validity of ‎the Environmental Kuznets Curve hypothesis in GCC countries. Moreover, the income threshold ‎level is equal to US$56,350.928. It has been also revealed that energy consumption and foreign ‎direct investments led to more environmental degradation in the long run, while urbanization has a ‎positive impact on the environment. In the short-run, results show the validity of the Pollution Halo ‎Hypothesis, since more foreign direct investments flows have been associated with less ‎environmental pollution. Finally, while the estimation of country-specific error correction models ‎reveals the heterogeneity of results, the most important factor affecting the environment in the short-run is energy ‎consumption. The impact of international trade and foreign direct investment is mixed, while ‎urbanization has no significant impact. In the light of these findings, some policy recommendations ‎are designed.

KEYWORDS:

• Environmental degradation
• environmental Kuznets Curve
• STIRPAT
• GCC countries
• panel ARDL
• PMG

Acknowledgments

The authors gratefully acknowledge the approval and the support of this research study by the grant no. BA-2018-3-9-F-7727 from the Deanship of Scientific Research at Northern Border University, Arar, K.S.A.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. https://www.airvisual.com/world-most-polluted-cities.

2. More details of definitions and sources of variables are presented in Table A.1 in Appendix.

3. Since FDI net inflows as a share of GDP‎ may be negative, we follow many previous studies by using the logarithm of ‎‎(100+ FDI).‎

4. For more discussion of cross-sectional dependence tests, see Chudik and Hashem (2013).

5. For more discussion of panel unit root tests, see Hurlin and Mignon (2007).

6. For more discussion of the estimation of nonstationary heterogeneous panels, see Blackburne and Frank (2007).

7. The turning point is given by $x^{\ast }=exp\left(-\frac{{\alpha }_2}{2{\alpha }_3}\right)$, where ${\alpha }_2$and ${\alpha }_3$ are coefficients of per capita GDP (GDPPC) and square of per capita GDP (SQGDPPC) in Equation 4(4) $\mathrm{l}\mathrm{n}CO{E}_{it}={\alpha }_0+{\alpha }_1\mathrm{l}\mathrm{n}UR{B}_{it}+{\alpha }_2\mathrm{l}\mathrm{n}GDPP{C}_{it}+{\alpha }_3\mathrm{l}\mathrm{n}SQGDPP{C}_{it}+{\alpha }_4\mathrm{l}\mathrm{n}E{C}_{it}+{\alpha }_5\mathrm{l}\mathrm{n}T{R}_{it}+{\alpha }_6\mathrm{l}\mathrm{n}FD{I}_{it}+{\epsilon }_{it}$(4) .

Additional information

Funding

This work was supported by the Deanship of Scientific Research at Northern Border University, Arar, K.S.A‎ [BA-2018-3-9-F-7727 ‎].