都市化と道路輸送の炭素排出：STIRPATモデルに基づく空間操作変数アプローチ
Urbanization and road transport carbon emissions: A spatial instrumental variable approach based on the STIRPAT model (原題)
Sohee Kim, Sangwon Choi, Brian H. S. Kim
🤖 gxceed AI 要約
日本語
韓国225の市郡区の2019年クロスセクションデータを用い、STIRPAT枠組みと空間操作変数モデルで都市化率と運輸部門CO2の関係を分析。空間的自己相関を確認し、空間誤差モデルが最適。都市化率は一貫して排出を有意に減少させ、人口・GRDP・地方所得税は正、高齢者比率は負に作用する。コンパクトな都市構造と公共交通の効率性が排出削減に寄与する可能性を示す。
English
Using 2019 cross-sectional data for 225 Si-Gun-Gu districts in South Korea, this study applies the STIRPAT framework and spatial instrumental-variable models to examine how urbanization affects transport-sector carbon emissions. Spatial autocorrelation is significant, and the spatial error model fits best. Urbanization rate consistently reduces emissions, while population, GRDP per capita, and local income tax raise them; elderly share lowers them. Compact urban form and efficient public transport likely drive the reduction.
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
日本でもコンパクトシティ・立地適正化計画と運輸部門脱炭素は重要政策課題であり、都市化率と排出の負の関係は国内自治体の都市計画・交通政策の議論に参照価値がある。SSBJや有報のScope 3・運輸排出開示を検討する企業にも、地域特性を踏まえた排出要因分析の示唆を与える。
In the global GX context
While focused on South Korea, the paper adds to global evidence that compact urbanization can lower transport emissions, relevant to TCFD/ISSB transition planning and city-level climate disclosure. It offers a spatial-econometric template for linking urban form to sectoral emissions that can inform CSRD-style local climate reporting and sustainable urban policy.
👥 読者別の含意
🔬研究者:空間操作変数とSTIRPATを組み合わせ、都市化と運輸排出の因果的関係を検証する実証手法の参考になる。
🏢実務担当者:都市部の物流・通勤排出をScope 3で評価する際、都市化・人口構成・所得水準が排出に与える影響を踏まえた地域別リスク把握に使える。
🏛政策担当者:コンパクトシティ政策や公共交通投資が運輸部門CO2削減に寄与する可能性を示し、都市計画と気候政策の統合に示唆を与える。
📄 Abstract（原文）
Climate change mitigation has become a global priority, and the transport sector is a major source of carbon emissions. Although urbanization is often associated with increased energy consumption and environmental pressure, it may also reduce emissions by improving spatial efficiency and transport systems. However, empirical evidence regarding this relationship remains limited in South Korea. This study examines the relationship between urbanization and transport-sector carbon emissions across 225 Si-Gun-Gu districts in South Korea using cross-sectional data from 2019. Based on the STIRPAT framework, the analysis incorporates population size, the elderly population share, gross regional domestic product (GRDP) per capita, local income tax per capita, and the urbanization rate. To address spatial dependence and endogeneity, spatial instrumental-variable models are estimated using queen-contiguity and inverse-distance weight matrices. The share of parking area in 2009 is used as an instrument for the urbanization rate. The results reveal significant spatial autocorrelation in transport-sector carbon emissions and confirm that the spatial error model is more appropriate than the spatial lag and ordinary least squares models. Population size, GRDP per capita, and local income tax per capita are positively associated with emissions, whereas the elderly population share is negatively associated with them. The urbanization rate has a consistently significant negative effect across all model specifications. These findings suggest that urbanization helps reduce transport-sector carbon emissions in South Korea. This effect may be explained by shorter travel distances in compact urban areas, more efficient public transport, and shared infrastructure. The study provides empirical evidence that urbanization can support climate change mitigation and offers policy implications for sustainable urban planning.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.15531/ksccr.2026.17.4.825first seen 2026-09-30 04:51:05
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