The Census Bureau plans a new approach to disclosure control for the 2020 census that will add noise to every statistic the agency produces for places below the state level. The Bureau argues the new approach is needed because the confidentiality of census responses is threatened by “database reconstruction,” a technique for inferring individual-level responses from tabular data. The Census Bureau constructed hypothetical individual-level census responses from public 2010 tabular data and matched them to internal census records and to outside sources. The Census Bureau did not compare these results to a null model to demonstrate that their success in matching would not be expected by chance. This is analogous to conducting a clinical trial without a control group. We implement a simple simulation to assess how many matches would be expected by chance. We demonstrate that most matches reported by the Census Bureau experiment would be expected randomly. To extend the metaphor of the clinical trial, the treatment and the placebo produced similar outcomes. The database reconstruction experiment therefore fails to demonstrate a credible threat to confidentiality.

人口普查局为 2020 年人口普查计划了一种新的信息披露控制方法，该方法将为该机构为州级以下地区编制的每项统计数据增加噪音。该局认为，需要新方法是因为人口普查答复的机密性受到“数据库重建”的威胁，这是一种从表格数据中推断个人级别答复的技术。人口普查局根据 2010 年公开的表格数据构建了假设的个人层面的人口普查回答，并将其与内部人口普查记录和外部来源相匹配。人口普查局没有将这些结果与空模型进行比较，以证明它们在匹配方面的成功并非偶然。这类似于在没有对照组的情况下进行临床试验。我们实施了一个简单的模拟来评估有多少次匹配是偶然的。我们证明，人口普查局实验报告的大多数匹配都是随机预期的。为了扩展临床试验的比喻，治疗和安慰剂产生了相似的结果。因此，数据库重建实验未能证明对机密性的可信威胁。