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差异性隐私和县级净移民估计的准确性
Richelle L Winkler1, Jaclyn L Butler2, Katherine J Curtis3
1Michigan Technological University, Houghton, MI USA.
Population research and policy review
|October 18, 2024
概括
2020年人口普查数据中的差异性隐私可能会降低美国各县净移民估计的准确性. 这影响了小县,老年人群和西班牙裔人口,可能会限制详细的人口分析.
科学领域:
- 人口统计学 人口统计学
- 数据 隐私 数据 隐私 数据
- 地理空间分析是什么
背景情况:
- 从历史上看,十年人口普查数据为美国各县提供了高质量的净移民估计.
- 这些估计对于规划,各种应用和研究至关重要.
- 预计2020年人口普查数据将继续这一系列,但可能会受到新的避免披露技术的影响.
研究的目的:
- 估计差异性私有 (DP) 避免披露技术对县级净迁移估计的准确性的影响.
- 评估假设DP净迁移估计2000-2010十年的可用性.
主要方法:
- 使用差异化私人人口普查2010示范数据.
- 构建了2000-2010年的假设DP净迁移估计.
- 使用准确度指标和空间分析,将假设的DP估计与已发布的估计进行比较.
主要成果:
- 实施DP可能会将准确的净移民估计限制在美国大约一半的县.
- 在人口在5万以下的县,65岁及以上的个人以及西班牙裔人口中,不准确性更为明显.
- 在特定的地理区域观察到错误集群.
- 更广泛的年龄组聚合并没有完全解决准确性问题.
结论:
- 2020年人口普查数据中的差异性隐私技术可能会严重影响县级净迁移估计的准确性.
- 这些估计对于详细的人口统计分析的有用性处于危险之中,特别是在弱势群体和较小的县里.
- 未来的准确性取决于人口普查局对隐私损失预算的管理.
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