具体的模型

Darrell Swenson
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引用次数: 1

摘要

官方统计机构,如人口普查局,在统计调查中收集大量的微观数据。这些数据对经济研究、市场和政策分析都很有价值。然而,由于对个别受访者的保密承诺,这些数据不能向公众公布。这些承诺,加上对微数据的强烈研究需求,促使各机构考虑发布公共使用微数据的各种建议。大多数提案都要求开发替代数据来掩盖原始数据。因此,它们涉及到在数据中添加测量误差。在本文中,我们研究了披露问题,并探索了可以发布给研究人员的有用经济微观数据面板的替代掩盖方法。虽然我们的分析适用于所有微数据,但在整个讨论过程中,使用了使用人口普查局纵向研究数据库(LRD)的应用程序来进行说明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Specific Models
Official statistical agencies such the Census and collect enormous quantities of microdata in statistical surveys. These data are valuable for economic research and market and policy analysis. However, the data cannot be released to the public because of confidentiality commitments to individual respondents. These commitments, coupled with the strong research demand for microdata, have led the agencies to consider various proposals for releasing public use microdata. Most proposals for call for the development of surrogate data that disguise the original data. Thus, they involve the addition of measurement errors to the data. In this paper, we examine disclosure issues and explore alternative masking methods for generating panels of useful economic microdata which can be released to researchers. While our analysis applies to all microdata, applications using the Census Bureau's Longitudinal Research Data Base (LRD) are used for illustrative purposes throughout the discussion.
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