华盛顿州不同共享社会经济途径下的预计收入数据
Heng Wan1, Sumitrra Ganguli2, Narmadha Meenu Mohankumar3
1Earth Systems Predictability & Resiliency Group, Pacific Northwest National Laboratory, Richland, WA, 99352, USA. heng.wan@pnnl.gov.
Scientific data
|January 18, 2024
概括
研究人员开发了一种方法,利用GDP数据和就业统计数据,在人口普查区级预测华盛顿州的家庭收入. 这种经过验证的方法支持气候变化适应和城市规划.
科学领域:
- 气候科学 气候科学
- 社会经济建模 社会经济建模
- 地理空间分析的研究.
背景情况:
- 高分辨率的收入预测对于气候变化适应和减缓战略至关重要.
- 现有的方法缺乏局部规划所需的细节细节.
研究的目的:
- 开发和验证一种方法来缩小州级收入预测到华盛顿州的人口普查区级别.
- 为气候变化研究和政策制定提供必要的准确收入数据.
主要方法:
- 利用州一级的人均GDP预测,并将其转换为家庭收入.
- 使用纵向来源-目的地就业统计 (LODES) 数据集,将数据缩小到人口普查区级.
- 通过缩小历史收入数据并将其与实际LODES和美国社区调查数据进行比较来验证方法.
主要成果:
- 在缩小规模和参考收入数据之间取得了强烈一致,平均R平方值为0.67 (区级),0.8 (区组级) 和0.99 (县级).
- 通过不同地理细分度验证了缩放方法的准确性.
结论:
- 开发的方法提供了一种可靠的方法,用于生成高分辨率的收入预测.
- 这种方法可转移到其他州,并有利于人口分析,经济研究和城市规划.
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