An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices
An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices
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DOI：
10.1257/aer.20170627
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发表时间：
2019-01-01
影响因子：
10.7
通讯作者：
Schmutte, Ian M.
中科院分区：
文献类型：
--
作者：
Abowd, John M.;Schmutte, Ian M.
统计机构面临双重任务，既要公布准确的统计数据，又要保护被调查者的隐私。增加隐私保护需要降低准确性。认识到这是一个资源分配问题，我们提出了一个经济解决方案：在增加隐私的边际成本等于边际收益的情况下运作。我们的生产模型来自计算机科学，假设数据是使用有效的差分私有算法发布的。最优选择权衡了对准确统计数据的需求和对隐私的需求。来自美国统计项目的例子展示了我们的框架如何指导决策。进一步的进展需要更好地理解为隐私和统计准确性付费的意愿。
Statistical agencies face a dual mandate to publish accurate statistics while protecting respondent privacy. Increasing privacy protection requires decreased accuracy. Recognizing this as a resource allocation problem, we propose an economic solution: operate where the marginal cost of increasing privacy equals the marginal benefit. Our model of production, from computer science, assumes data are published using an efficient differentially private algorithm. Optimal choice weighs the demand for accurate statistics against the demand for privacy. Examples from US statistical programs show how our framework can guide decision-making. Further progress requires a better understanding of willingness-to-pay for privacy and statistical accuracy.