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How China's Aging Consumption Drives Socioeconomic and Emissions Trends: Insights From a Structural Decomposition Analysis

Yafei Wang et al.

Review of Income and Wealth2026https://doi.org/10.1111/roiw.70059article
AJG 3
Weight
0.50

What the paper says

China, accounting for one‐quarter of the world's elderly, is projected to transition to a super‐aged society by 2035, with major socio‐economic and environmental implications. This study links Chinese provincial multi‐regional input–output (MRIO) tables with the global input–output system, integrating SNA and SEEA satellite accounts (value added, employment, and carbon emissions) and applying a seven‐factor structural decomposition analysis (SDA) to capture effects by aging population consumption in 2005–2020. Results show a shift from output‐led to demography‐driven growth, with the aging ratio adding USD 516 billion to value added during 2015–2020, surpassing per capita elderly consumption. Aging demand drives heterogeneous interprovincial impacts and large international spillovers, shaped by trade‐linked economies and global supply chains. Case studies of Jiangsu and Guangdong reveal distinct import linkages and decarbonization trajectories. Findings highlight strategies to expand high‐value‐added, labor‐intensive, low‐carbon sectors, strengthen interprovincial coordination, and reorient trade policy toward imports that deliver integrated sustainability benefits.

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https://doi.org/https://doi.org/10.1111/roiw.70059

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@article{yafei2026,
  title        = {{How China's Aging Consumption Drives Socioeconomic and Emissions Trends: Insights From a Structural Decomposition Analysis}},
  author       = {Yafei Wang et al.},
  journal      = {Review of Income and Wealth},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/roiw.70059},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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