Quasi-experimental analysis reveals low-carbon pilot programs reduced carbon emissions by 30.52% in China, highlighting demand-side measures for governance.
Understanding how climate policies shape local emissions, population dynamics, and consumption patterns is essential for achieving carbon peaking and neutrality goals. As the climate change governance regime evolves, it is inevitable that, in addition to the central government, county-level regulatory actors will be involved in decision-making. This study utilizes a quasi-natural experiment to analyze county-level panel data from 2007 to 2017 as research objects. The nationwide low-carbon pilot policies established in 2010 and 2012 serve as the primary focus of this study. We employ a staggered Difference-in-Differences model to empirically analyze the impact of these pilot programs on carbon emission reductions. The results show that the policy significantly reduces carbon emissions by 30.52% on average, with pronounced spatial heterogeneity across central, suburban, and remote counties. Population redistribution contributes to emission reductions but raises equity concerns in remote counties. Meanwhile, residents remain in a high-carbon consumption phase, revealing the limitations of production-focused policies. These findings highlight the importance of integrating demand-side measures and spatially differentiated strategies into China’s climate governance framework.
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Yanmin He (2025) studied this question.
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