Impact of updates to the energy and Social Accounting Matrix data in Computable General Equilibrium on mitigation scenario analysis

Integrated assessment models (IAMs) with computable general equilibrium (CGE) models at their core, have provided important insights into climate policy formulation. To estimate mitigation scenarios that reflect the current situation, the information used to calibrate the IAM needs to be updated. Model updates can affect estimation results by reflecting recent socioeconomic changes and the implementation status of mitigation policies across countries. The purpose of this study is to analyze the impact on quantification of mitigation scenarios by updating the energy and social accounting matrix (SAM) data for an IAM with a dynamic CGE model at its core. To this end, I use the AIM-Hub model, a recursive dynamic CGE model, to estimate multiple mitigation scenarios with varying calibration periods. Results show that, in the OECD & EU region, adjusting parameters to more recent years leads to decreases in final energy consumption and CO2 emissions in 2025 and a reduction in the economic impact of mitigation policies in 2100. In this region, a 15-year difference in parameter adjustment periods results in a 12.5% change in the estimated GDP loss at the end of this century.

    Many countries and regions have set net-zero targets. If large-scale mitigation policies are implemented and the socio-economic and energy systems change dramatically, IAMs with dynamic CGE models at their core will need to be updated more frequently. Furthermore, the latest data used in the model update already includes the implementation and impact of mitigation policies. If the base year is changed to a more recent year and the analysis is conducted only for the period after that base year when updating the model data, the impact of mitigation policies prior to that base year will be overlooked. Therefore, it will be important to include historical statistical information in future analyses of mitigation scenarios.