Provincial-level SPE, SSE, GRE, and CES indicators for multi-level carbon responsibility analysis in China's power sector (2012–2017)

This dataset provides aggregated provincial-level results derived from a carbon-extended multi-level dynamic input–output shift–share (MDIOSS) framework for China’s power sector. The data are constructed based on multi-regional input–output (MRIO) tables for the benchmark years 2012, 2015, and 2017.The dataset includes key decomposition indicators, namely the structural production effect (SPE), sectoral shift effect (SSE), growth rate effect (GRE), and structural change effect (CES), calculated for each province. In addition, it provides derived ranking patterns (e.g., W>R>PW > R > PW>R>P) that characterize the relative dominance of transmission effects across the provincial, regional, and national levels, as well as pairwise differences between hierarchical components.These data support the analysis of spatial carbon responsibility allocation under production-based and consumption-based accounting perspectives, and enable the identification of multi-level transmission mechanisms and structural constraints in carbon emission dynamics.The dataset contains only aggregated and derived results and does not include the original MRIO data due to licensing restrictions. It is intended to facilitate transparency, reproducibility, and further research on spatial carbon emissions and energy system transitions.本数据集提供基于碳扩展多级动态投入产出偏移-份额（MDIOSS）框架所得的中国电力行业省级汇总结果。本数据集以2012、2015及2017年基准年的多区域投入产出（MRIO）表为基础构建。本数据集包含针对各省份计算得到的四类核心分解指标：生产结构效应（SPE）、部门偏移效应（SSE）、增长率效应（GRE）以及结构变化效应（CES）。此外，数据集还提供衍生得到的层级排序模式（例如W>R>PW > R > PW>R>P），用以刻画省级、区域及国家层面传递效应的相对主导性，以及层级组分间的两两差异。上述数据可支撑基于生产端核算与消费端核算视角的空间碳责任分配分析，并可用于识别碳排放动态演化中的多级传递机制与结构约束。鉴于许可限制，本数据集仅包含汇总与衍生结果，未包含原始多区域投入产出数据。本数据集旨在提升空间碳排放与能源系统转型相关研究的透明度、可复现性，并助力相关领域的后续研究。