利用公共使用数据插值总体分布：美国社区调查数据在收入隔离中的应用
Interpolating Population Distributions using Public-use Data: An Application to Income Segregation using American Community Survey Data
摘要：
收入隔离衡量的是家庭在多大程度上选择住在收入类似的其他家庭附近。社会学家从理论上认为，收入隔离会加剧收入不平等的影响，并制定了在大都市地区一级衡量收入不平等的指数，包括\citet{reardon2011income}中引入的信息理论指数和\citet{roberto2015divergence}中提出的分歧指数。为了研究它们的差异，我们使用最近的美国社区调查（ACS）估计的收入分配特征来构建这两个指数。由于取消了十年一次的人口普查长表，计算这些估计数的方法必须更新，以使用ACS估计数并考虑调查误差。我们提出了一种基于模型的方法来插值收入分配特征的估计，以解释此误差。这种方法改进了以前的方法，允许使用更多类型的估计，并提供不确定性量化。我们应用这种方法来估计美国人口普查区一级的收入分配使用ACS制表，并反过来使用这些来构建收入隔离指数。我们发现这两个指数之间的主要差异在大都市地区的相对排名，以及这两个指数如何与基尼系数相关的差异。
英文摘要：
Income segregation measures the extent to which households choose to live near other households with similar incomes. Sociologists theorize that income segregation can exacerbate the impacts of income inequality, and have developed indices to measure it at the metro area level, including the information theory index introduced in \citet{reardon2011income}, and the divergence index presented in \citet{roberto2015divergence}. To study their differences, we construct both indices using recent American Community Survey (ACS) estimates of features of the income distribution. Since the elimination of the decennial census long form, methods of computing these estimates must be updated to use ACS estimates and account for survey error. We propose a model-based method to interpolate estimates of features of the income distribution that accounts for this error. This method improves on previous approaches by allowing for the use of more types of estimates, and by providing uncertainty quantification. We apply this method to estimate U.S. census tract-level income distributions using ACS tabulations, and in turn use these to construct both income segregation indices. We find major differences between the two indices in the relative ranking of metro areas, as well as differences in how both indices correlate with the Gini index.
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