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

TL;DR

This paper models the trade-off between privacy protection and statistical accuracy in data publication as an economic resource allocation problem, proposing an optimal operating point based on marginal costs and benefits.

Contribution

It introduces an economic framework for balancing privacy and accuracy in statistical agencies using differential privacy principles.

Findings

Guides decision-making in privacy-accuracy trade-offs

Illustrates the framework with U.S. statistical programs

Highlights need for understanding willingness-to-pay for privacy and accuracy

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.