State level income distributions for net income deciles for the US for historical years (2011-2014) and projections for different SSP scenarios (2015-2100)

This dataset is documented in this manuscript here- https://iopscience.iop.org/article/10.1088/1748-9326/acf9b8/meta Income distributions are a growing area of interest in the examination of equity impacts brought on by climate change and its responses. We project US state level income distributions using a PCA-based approach, applying a downscaled version of the approach employed by Narayan et al. (2022, in-prep). A state-level dataset had to be synthesized and projected based on existing sources. We apply a PC-based model to our derived state-level dataset, employing projected GINI’s from the SSP scenarios. We produce projected income distribution by income decile for three SSPs to year 2100. For the purpose of the projections, we developed a consistent set of tax adjusted net income deciles for all states from 2011 to 2014. This dataset was used for initialization of the projections and for validation. If/when using this dataset, please cite this paper- https://iopscience.iop.org/article/10.1088/1748-9326/acf9b8/meta本数据集的相关说明已刊载于以下手稿：https://iopscience.iop.org/article/10.1088/1748-9326/acf9b8/meta 收入分布是当前气候变化及其应对措施所引发公平性影响研究中的热点领域。我们采用基于主成分分析（Principal Component Analysis，PCA）的方法，对美国各州层面的收入分布开展投影预测，该方法是对Narayan等人（2022，待出版）所使用方法的降尺度应用。鉴于现有数据源的局限性，我们需基于已有来源合成并推导得到州级数据集。我们将基于主成分的模型应用于构建完成的州级数据集，并采用共享社会经济路径（Shared Socioeconomic Pathways，SSPs）情景下的基尼系数（GINI）预测值。针对三种共享社会经济路径情景，我们生成了截至2100年的按收入十等分划分的预测收入分布。为开展本次投影预测，我们构建了2011至2014年覆盖全美所有州的经税收调整的统一净收入十等分数据集，该数据集用于投影预测的初始化及模型验证。 若使用本数据集，请引用以下论文：https://iopscience.iop.org/article/10.1088/1748-9326/acf9b8/meta