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This study aims to develop a system dynamic (SD) forecasting model based on the STIRPAT model to forecast the effect of an IDR 30 per kg CO2e carbon tax on carbon emissions, estimate future carbon emissions under ten scenarios, without and with the carbon tax, and estimate the environmental Kuznets curve (EKC) to predict Indonesia’s carbon emission peak. Carbon emission drivers in this study are decomposed into several factors, namely energy structure, energy intensity, industrial structure, GDP per capita, population, and fixed-asset investment. This study included nuclear power utilization starting in 2038. The research gaps addressed by this study compared to previous research are (1) use of the ex-ante approach, (2) inclusion of nuclear power plants, (3) testing the EKC hypothesis, and (4) contribution to government policy. The simulation results show that under the carbon tax, carbon emissions can be reduced by improving renewable energy structures, adjusting industrial structures to green businesses, and emphasizing fixed asset investment more environmentally friendly. Moreover, the result approved the EKC hypothesis. It shows an inverse U-shaped curve between GDP per capita and CO2 emissions in Indonesia. Indonesia’s fastest carbon emission peak is under scenario seven and is expected in 2040. Although an IDR 30 per kg CO2e carbon tax and nuclear power will take decades to reduce carbon emissions, the carbon tax can still be a reference and has advantages to implement. This result can be a good beginning step for Indonesia, which has yet to gain experience with a carbon tax that can be implemented immediately and is helpful to decision-makers in putting into practice sensible measures to attain Indonesia’s carbon emission peaking. This research provides actionable insights internationally on carbon tax policies, nuclear energy adoption, EKC dynamics, global policy implications, and fostering international cooperation for carbon emission reductions. |
