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計算可能一般均衡モデルにおけるエネルギー・社会会計行列データ更新が緩和シナリオ分析に与える影響

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

Nishiura, Osamu

Zenodoプレプリント2026-11-12#気候科学Origin: JP
DOI: 10.5281/zenodo.24162006
原典: https://zenodo.org/records/24162006
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🤖 gxceed AI 要約

日本語

動学的CGEモデルを核とするIAM（AIM-Hub）のエネルギー・SAMデータを更新し、較正期間の違いが緩和シナリオの定量結果に与える影響を分析した研究。OECD・EU地域では較正年を新しくすると2025年の最終エネルギー消費とCO2排出が減少し、2100年の緩和コスト（GDP損失）が軽減される。15年の較正期間差で今世紀末のGDP損失推計が12.5%変化することを示し、モデル更新頻度と基準年設定の重要性を強調する。

English

This study updates energy and Social Accounting Matrix data in AIM-Hub, a recursive dynamic CGE-based IAM, and examines how calibration period choice affects mitigation scenario quantification. In the OECD & EU region, calibrating to more recent years lowers 2025 final energy use and CO2 emissions and reduces the estimated 2100 GDP loss from mitigation policy; a 15-year calibration gap shifts end-of-century GDP loss estimates by 12.5%. The author argues IAMs must be updated more frequently and that historical data should be retained to avoid overlooking pre-base-year mitigation effects.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本はAIMモデルを気候政策・長期戦略の検討に活用しており、モデル較正の更新が国内の緩和シナリオや政策コスト推計の精度に直結する。脱炭素政策の費用対効果を議論する際の基礎データ整備の重要性を示す。

In the global GX context

As ISSB/TCFD scenarios and transition planning increasingly rely on IAM outputs, this paper highlights that scenario results are sensitive to calibration vintage—relevant to how corporates and regulators interpret mitigation cost estimates and net-zero pathway assumptions.

👥 読者別の含意

🔬研究者:IAM/CGEモデルの較正データ更新がシナリオ結果に与える感度を定量化した点が、モデル比較研究の基準となる。

🏢実務担当者:シナリオ分析で参照するIAMの基準年・更新頻度の違いが緩和コスト推計を大きく変えうる点を理解しておくべき。

🏛政策担当者:長期脱炭素戦略や炭素価格の費用推計に用いるモデルの定期的更新と履歴データ保持の必要性を示す。

📄 Abstract（原文）

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.

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