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Statistical agencies face a dual mandate to publish accurate statistics whileprotecting respondent privacy. Increasing privacy protection requires decreasedaccuracy. Recognizing this as a resource allocation problem, we propose aneconomic solution: operate where the marginal cost of increasing privacy equalsthe marginal benefit. Our model of production, from computer science, assumesdata are published using an efficient differentially private algorithm. Optimalchoice weighs the demand for accurate statistics against the demand forprivacy. Examples from U.S.\ statistical programs show how our framework canguide decision-making. Further progress requires a better understanding ofwillingness-to-pay for privacy and statistical accuracy.

An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices