Speaker
Description
Data in tables published for the Swedish R&D survey in the business enterprise sector (BERD) were previously protected by cell suppression to prevent disclosure of sensitive information. In order to avoid cell suppression, key respondents were asked to sign waivers allowing the publication of their data. However, consent was rarely given to disseminate cells where an enterprise’s data potentially could be disclosed. The steps undertaken to ensure confidentiality were extensive, involving multiple staff and requiring a significant amount of time during production. For users, this resulted in the withholding of statistical information, particularly in tables presenting industry-specific data and its combination with other domains of interest. Consequently, the usefulness and relevance of the published statistics on a granular level were reduced despite the efforts made.
To address these challenges, the BERD survey became the first survey at Statistics Sweden to use a perturbative method for disclosure limitation in magnitude tables . The EZS-method, introduced by Evans, Zayatz, and Slanta (1998: Journal of Official Statistics, 14, 537-551), adds noise to microdata to ensure table additivity and preserve links among tables. Each enterprise is assigned random values for the direction and noise factor, which are kept confidential. Perturbed values are calculated as
$$perturbed\ value=original\ value*(1+direction*noise\ factor/100), $$ where both the direction and noise factor are applied to all values reported by the object. The distribution of directions of perturbation is chosen so that it is symmetric around 0 and thus does not introduce any consistent bias. Cells with one object or dominant contributions receive more noise to protect individual data, while noise in cells with many smaller contributions cancels out. The balancing procedure proposed by Massell and Funk (2007: Proceedings of the 2007 Third International Conference on Establishment Surveys (ICES-III), Montreal, Canada) is used to reduce overall noise, applied only to cells without risk of disclosure.
The method was tested on 2021 data from the BERD survey and successfully used for 2023 data published in autumn 2024. It allows for disseminating tables with approximate values without suppressing any cells and is simple to implement without specialized software. The method works well for high-dimensional tables or tables with hierarchies and is more effective than cell suppression.