Natural Resource Rents, Renewable Energy Transition, and Carbon Footprint in ASEAN Economies: Testing the Environmental Kuznets Curve
DOI:
https://doi.org/10.52131/jee.2024.0502.0049Keywords:
CO₂ emissions, GDP Per Capita, Natural Resource Rents, Renewable Energy Consumption, ASEAN EconomiesAbstract
Environmental degradation has turned into a significant policy issue in ASEAN economies since the rapid economic growth, natural resource exploitation, energy consumption, and trade development can result in carbon emissions. This study aims to examine the effects of GDP per capita, GDP², total natural resource rents, renewable energy consumption, and trade openness on CO? emissions in selected ASEAN economies from 1995 to 2023. The study is based on the Environmental Kuznets Curve framework, where GDP per capita and GDP² are used to test the non-linear relationship between economic growth and CO? emissions. Annual panel data are used for Cambodia, Indonesia, Malaysia, the Philippines, Singapore, Thailand, and Vietnam. The research uses the cross-sectional dependence test, Pesaran CIPS second-generation panel unit root test, and CS-ARDL estimation method. The findings confirm that there is cross-sectional dependence on most of the variables and that the variables are mixed in their order of integration. The CS-ARDL results support the Environmental Kuznets Curve hypothesis, as GDP per capita has a positive effect on CO? emissions, while GDP² has a negative effect. The findings also show that total natural resource rents increase CO? emissions, indicating that resource dependence creates environmental pressure in ASEAN economies. In contrast, renewable energy consumption reduces CO? emissions in both the short run and long run. Trade openness has an insignificant effect on CO? emissions. The research suggests that the economies of ASEAN need to enhance natural resource management, increase investment in renewable energy, and harmonize economic growth and trade policies with low-carbon development policies.
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Copyright (c) 2024 Muhammad Azhar Bhatti, Tusawar Iftikhar Ahmad, Amina Alamgir

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.


