Evaluation of the effect of a low-carbon green city policy on carbon abatement in South Korea: A city-level analysis based on PSM-DID and LSA models

Abstract

Climate change response is a long-term, stage-specific global challenge that necessitates ongoing research on its routes. Although previous research has examined policy planning and indicator development for a low-carbon transition based on a variety of macropolicies, more research is needed to determine whether such policies can help reduce carbon emissions and accelerate urban transitions. Based on 2015–2021 panel data covering 17 South Korean first-level administrative districts, we employ a propensity score matching-difference in difference (PSM-DID) model and a mediating effect model to address issues of interregional development faults and policy feasibility and to investigate the impacts of the low-carbon green city (LCGC) policy in different regions on urban carbon emissions. To address the development gap and policy feasibility across regions, this study investigates the mechanism and path of the effect of the LCGC policy on urban carbon dioxide emissions in various regions, ultimately incorporating local spatial autocorrelation (LSA) to investigate the characteristics of the differences at the spatial level. The findings demonstrate that (1) the present regulations effectively limit total urban carbon emissions but are characterized by strong rebound elasticity and a short period. (2) Energy use and renewable energy production have the greatest influence on reducing total urban carbon emissions. (3) The local spatial autocorrelation clustering characteristics present the clustering characteristics of being high in the east and low in the north. The HH agglomerations have the largest coverage and are mainly distributed in the southeast and southwest directions of the study area. The results of the study provide a decision-making basis and theoretical support for relevant decision-makers to formulate differentiated carbon emission reduction policies and to eliminate the current transition dilemma with a new research methodology.