Jamshid Pardaev

Type of the article: Research Article

Abstract
This paper investigates the impact of oil, coal, renewable energy consumption, CO₂ emissions in the ASEAN-5 countries for the period from 1971 to 2020 utilizing the panel ARDL and MMQR models. The panel autoregressive distributed lag (ARDL) model estimates average short- and long-run effects, whereas the method of moments quantile regression (MMQR), a panel quantile technique, estimates how these effects vary across the distribution of emissions. The MMQR results shed light on the impacts of variables on CO₂ emissions estimated at different emission levels. The results show that oil, coal consumption, and GDP are significant factors influencing CO₂ emissions. Conversely, renewable energy sources contribute significantly to reductions in CO₂ emissions. Also, the results reveal that trade activities have a significant impact on emissions in countries exhibiting high emission levels. In particular, the effects of GDP and renewable energy become stronger at higher quantiles, whereas those of oil and coal remain relatively stable. Furthermore, the panel causality tests reveal bidirectional causality between CO₂ emissions and oil consumption and economic growth. The results also support unidirectional causality from coal consumption to emissions, and causality from emissions to renewable energy. The results indicate the need for comprehensive efforts across various policy areas to reduce emissions and address climate change. Reducing coal and oil dependence should be a priority for all ASEAN-5 countries, while faster renewable deployment matters most for high emitters.

Acknowledgment
Esra Balli would like to acknowledge the financial support provided by the Council of Higher Education (YÖK) through the Academic Development Program (AKAP).