The role of electricity mix and transportation sector in designing a green-growth strategy in Iran
Muhammad Kamran Khan and
Seyed Mohammadreza Mahdavian
Energy, 2021, vol. 233, issue C
This study used the Autoregressive Distributed Lag (ARDL), The Error Correction Model (ECM), and ECM-Granger Causality to investigate the short and long-run environmental impact of renewable power and the transportation sectors in Iran over 1971 to 2015. The robustness of the results was checked by estimating three cointegration regression models. The empirical finding of this study confirmed the long-run cointegration among the variables. Indeed, the positive and significant impact of real GDP per capita, the number of vehicles, and urbanization on the CO2 emissions per capita were supported. Furthermore, the potential for renewable electricity in improving the environmental quality was proved in the long-run. Residual diagnostic tests and sensitivity analysis supported the appropriateness of the model and the robustness of the results from the ARDL. The Granger Causality supported: (1) one-way causality flowing from the share of renewable electricity to the CO2 emissions per capita (2) the complementary linkage between the number of vehicles and CO2 emissions per capita; (3) the bidirectional causality between the share of renewable electricity and the real GDP per capita. Therefore, to achieve sustainable development goals, the government and policymakers need to: increase and promote the share of renewable electricity and shift away from Internal Combustible Engine Vehicles to Alternative Fuel Vehicle.
Keywords: Green-growth strategy; Renewable electricity; Transportation sector; ARDL; ECM; Co-integration regressions (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:233:y:2021:i:c:s0360544221014262
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