Providing Data with High Utility and No Disclosure Risk for the Public and Researchers: An Evaluation by Advanced Statistical Disclosure Risk Methods

This paper addresses the central goal of statistical disclosure control: releasing microdata to the public and to researchers that remain highly useful for analysis while carrying negligible re-identification risk. It applies advanced disclosure-risk methods to evaluate candidate releases, showing how risk and utility can be measured jointly to judge whether a dataset is safe to publish. The study illustrates that, with appropriate methods, high analytical utility and strong protection need not be mutually exclusive. Published in the Austrian Journal of Statistics, it speaks directly to agencies producing public- and scientific-use files.