An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices
John M. Abowd, Ian M. Schmutte
American Economic Review · 2019 · Volume 109 · Issue 1
Abstract
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 U.S. 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.
Keywords
Multiple or Simultaneous Equation Models: Classification Methods, Cluster Analysis, Principal Components, Factor Models, Methodology for Collecting, Estimating, and Organizing Microeconomic Data, Data Access, Search, Learning, Information and Knowledge, Communication, Belief, Unawareness
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