Rounding methods for protecting EU-aggregates

In the European Statistical System the statistical information is collected by the National Statistical Institutes (NSIs). The NSIs produce aggregate tables at the national level. They are also responsible for proper protection of these tables and hence they have to keep certain cells confidential, suppressing them from publications. Eurostat produces statistical information at the EU-level. However, the national suppressions hamper very much the publication of EU-aggregates although it is often only a few smaller countries having to keep their contribution to the EU-total confidential. This paper reports on a research-project that aims for making more EU aggregates available whilst at the same time guaranteeing the national suppressed figures to remain confidential.Postprint (published version

Using BCD-CTA for difficult tables: a practical experiment with a real Eurostat table

CTA is a post-tabular perturbative approach for statistical disclosure control. Its purpose is to compute the closest safe table to the original data, using some distance. Sensitive cells are adjusted either upwards or downwards (binary decision), and the resulting cells have to be accordingly (and minimally) modi_ed to preserve marginals. For real and large tables, CTA may result in a dicult mixed integer linear problem for some weights in the objective function. In those situations the Block Coordinate Descent (BCD) heuristic for CTA|which is included in the Tau-Argus CTA distribution|may be used to quickly obtain a feasible, hopefully close to optimality, solution. We present a practical experiment using a large and di_cult real-world table from Eurostat. We will show that, for unitary weights, while the standard CTA can not obtain a solution in about half an hour, the BCD-CTA approach provides a solution in few seconds.Peer ReviewedPostprint (author's final draft

Rounding methods for protecting EU-aggregates

In the European Statistical System the statistical information is collected by the National Statistical Institutes (NSIs). The NSIs produce aggregate tables at the national level. They are also responsible for proper protection of these tables and hence they have to keep certain cells confidential, suppressing them from publications. Eurostat produces statistical information at the EU-level. However, the national suppressions hamper very much the publication of EU-aggregates although it is often only a few smaller countries having to keep their contribution to the EU-total confidential. This paper reports on a research-project that aims for making more EU aggregates available whilst at the same time guaranteeing the national suppressed figures to remain confidential

Rounding methods for protecting EU-aggregates

In the European Statistical System the statistical information is collected by the National Statistical Institutes (NSIs). The NSIs produce aggregate tables at the national level. They are also responsible for proper protection of these tables and hence they have to keep certain cells confidential, suppressing them from publications. Eurostat produces statistical information at the EU-level. However, the national suppressions hamper very much the publication of EU-aggregates although it is often only a few smaller countries having to keep their contribution to the EU-total confidential. This paper reports on a research-project that aims for making more EU aggregates available whilst at the same time guaranteeing the national suppressed figures to remain confidential

Using BCD-CTA for difficult tables: a practical experiment with a real Eurostat table

CTA is a post-tabular perturbative approach for statistical disclosure control. Its purpose is to compute the closest safe table to the original data, using some distance. Sensitive cells are adjusted either upwards or downwards (binary decision), and the resulting cells have to be accordingly (and minimally) modi_ed to preserve marginals. For real and large tables, CTA may result in a dicult mixed integer linear problem for some weights in the objective function. In those situations the Block Coordinate Descent (BCD) heuristic for CTA|which is included in the Tau-Argus CTA distribution|may be used to quickly obtain a feasible, hopefully close to optimality, solution. We present a practical experiment using a large and di_cult real-world table from Eurostat. We will show that, for unitary weights, while the standard CTA can not obtain a solution in about half an hour, the BCD-CTA approach provides a solution in few seconds.Peer Reviewe