Decomposition results of spatial Durbin model.

BackgroundWith the accelerated development of the aging trend in Chinese society, the aging problem has become one of the key factors affecting sustainable economic and social development. Given the importance of controlling carbon emissions for achieving global climate goals and China’s economic transformation, studying the spatial and temporal effects of population aging on carbon emissions and their pathways of action is of great significance for formulating low-carbon development strategies adapted to an aging society.ObjectiveThis paper aims to explore the spatial-temporal effects of population aging on carbon emissions, identify the key pathways through which aging affects carbon emissions, and further explore the variability of these effects across different regions. The findings will provide theoretical support and empirical evidence for government departments to formulate policies to promote the coordinated development of a low-carbon society and an aging society.MethodsBased on the panel data of 30 provinces in China from 2004 to 2022, this paper systematically investigates the impact of population aging on carbon emission intensity from both spatial and temporal dimensions by using the spatial Durbin model and the mediating effect model. The direct effect of aging on carbon emission intensity, the spatial spillover effect, and the indirect effect through mediating variables such as residents’ consumption, environmental regulation, and new urbanization are analyzed in depth.ResultsThe study found that population aging in China has significant spatial and temporal effects on carbon emissions. From the spatial dimension, there is a significant spatial spillover effect of the effect of aging on carbon emissions, and aging reduces local carbon emissions but increases carbon emissions in adjacent regions. From the time dimension, the effect of aging on carbon emissions shows a stage characteristic, initially it will reduce carbon emissions, but with the deepening of aging, its effect may tend to weaken. In addition, this study identifies a number of key pathways through which aging affects carbon emissions, including reducing residential consumption, promoting new urbanization, and increasing the intensity of environmental regulations. Finally, this study explores the regional heterogeneity of the impact of aging on carbon emissions and its mechanism of action.ConclusionThis study is instructive: first, the complex impact of population aging on carbon emissions should be fully recognized to formulate a comprehensive low-carbon development strategy; second, attention should be paid to the spatial spillover effect of aging on carbon emissions to strengthen inter-regional cooperation and coordination; and lastly, differentiated low-carbon policies should be formulated to address the characteristics of aging in different regions and stages in order to promote the synergistic development of a low-carbon society and an aging society.

背景：随着中国社会老龄化趋势加速演进，人口老龄化（population aging）问题已成为影响经济社会可持续发展的关键因素之一。鉴于控制碳排放（carbon emissions）对实现全球气候目标与中国经济转型的重要意义，研究人口老龄化对碳排放的时空效应及其作用路径，对制定适配老龄化社会的低碳发展战略具有重要价值。
研究目标：本研究旨在探究人口老龄化对碳排放的时空效应，识别老龄化影响碳排放的关键路径，并进一步剖析不同区域间该效应的异质性。研究结果可为政府部门制定政策以推动低碳社会与老龄化社会协同发展提供理论支撑与实证依据。
研究方法：本研究基于2004-2022年中国30个省份的面板数据（panel data），运用空间杜宾模型（spatial Durbin model）与中介效应模型（mediating effect model），从时空维度系统考察人口老龄化对碳排放强度的影响。本文深入剖析了老龄化对碳排放强度的直接效应、空间溢出效应（spatial spillover effect），以及通过居民消费、环境规制与新型城镇化等中介变量产生的间接效应。
研究结果：研究发现，中国人口老龄化对碳排放具有显著的时空效应。空间维度上，老龄化对碳排放的影响存在显著空间溢出效应：老龄化会降低本地碳排放水平，却会提升邻近区域的碳排放水平。时间维度上，老龄化对碳排放的影响呈现阶段性特征：初期会抑制碳排放，但随着老龄化程度加深，其影响效应可能趋于弱化。此外，本研究识别出老龄化影响碳排放的多条关键路径，包括降低居民消费、推动新型城镇化以及提升环境规制强度。最后，本研究探究了老龄化对碳排放影响的区域异质性及其作用机制。
研究结论：本研究具有如下启示：其一，应充分认识人口老龄化对碳排放的复杂影响，以制定全面的低碳发展战略；其二，需重视老龄化对碳排放的空间溢出效应，强化区域间协同合作；最后，应制定差异化低碳政策，适配不同区域与不同阶段的老龄化特征，以推动低碳社会与老龄化社会的协同发展。