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Statistical Disclosure Control Methods for Microdata from the Labour Force Survey
[journal article]
Abstract The aim of this article is to analyse the possibility of applying selected perturbative masking methods of Statistical Disclosure Control to microdata, i.e. unit‑level data from the Labour Force Survey. In the first step, the author assessed to what extent the confidentiality of information was prot... view more
The aim of this article is to analyse the possibility of applying selected perturbative masking methods of Statistical Disclosure Control to microdata, i.e. unit‑level data from the Labour Force Survey. In the first step, the author assessed to what extent the confidentiality of information was protected in the original dataset. In the second step, after applying selected methods implemented in the sdcMicro package in the R programme, the impact of those methods on the disclosure risk, the loss of information and the quality of estimation of population quantities was assessed. The conclusion highlights some problematic aspects of the use of Statistical Disclosure Control methods which were observed during the conducted analysis.... view less
Keywords
methodological research; data processing; data protection; data preparation; data security
Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Free Keywords
Statistical Disclosure Control; perturbative methods; PRAM; Additive Noise; Rank Swapping; microdata; Labour Force Survey; sdcMicro package
Document language
English
Publication Year
2020
Page/Pages
p. 7-24
Journal
Acta Universitatis Lodziensis. Folia Oeconomica, 3 (2020) 348
DOI
https://doi.org/10.18778/0208-6018.348.01
ISSN
2353-7663
Status
Published Version; peer reviewed