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Statistical Disclosure Control for Microdata: A Practice Guide

Releasing data in a safe way is required to protect the integrity of the statistical system, by ensuring agencies honor their commitment to respondents to protect their identity. Agencies do not widely share, in substantial detail, their knowledge and experience using SDC and the processes for creating safe data with other agencies. This makes it difficult for agencies new to the process to implement solutions. To fill this experience and knowledge gap, we evaluated the use of a broad suite of SDC methods on a range of survey microdata covering important development topics related to health, labor, education, poverty and inequality. The data we used were all previously treated to make them safe for release. Given that their producers had already treated these data, it was not possible, nor was it our goal, to pass any judgment on the safety of these data, many of which are in the public domain The focus was rather on measuring the effects that various methods would have on the risk-utility trade-off for microdata produced to measure common development indicators. We used the experience from this large-scale experimentation to inform our discussion of the processes and methods in this guide.
Author: 
Thijs Benschop, Cathrine Machingauta, Matthew Welch
Publication date: 
June 2016
File size: 
8 MB
Version: 
1.0