Stochastic forecasting of long-term greenhouse gas emissions and energy transitions: A comparative analysis of the US, EU, China, and Korea

Societal actors must incorporate climate risks into their macroeconomic forecasts to support adaptive decision-making in response to climate change and subsequent socioeconomic shifts. This study proposes a stochastic forecasting framework that delivers robust long-term forecasts by incorporating feature engineering, dimensionality reduction, and stochastic process modeling. We provide probabilistic greenhouse gas (GHG) emissions projections for major economic regions and evaluate the likelihood of achieving zero GHG emissions by 2050. Developed economies like the EU and the US have already peaked in emissions. They are forecasted to continue decreasing GHG emissions until 2050, driven by their service-oriented industry structure, greener energy mix, and stringent climate policies. The Republic of Korea is nearing an inflection point and is forecasted to transition from being a carbon-intensive GHG emitter to a country with decreasing emissions. The likelihood of China reversing its trend of increasing emissions by 2050 is considered to be extremely low despite substantial investments in green technologies. Our results indicate that maintaining the current emissions trends poses substantial challenges for all economic regions in achieving carbon neutrality by 2050, although the magnitudes and uncertainties of their emissions reductions vary significantly depending on factors such as economics, energy mix, and climate policies.