Dealing with Negative Contributions in Protecting Tabular Data

• Activity Number: 478
• Type: Topic Contributed
• Date/Time: Wednesday, August 7, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Survey Research Methods Section
• Author(s): Amang Sukasih*+ and John Czajka
• Companies: Mathematica Policy Research and Mathematica Policy Research
• Keywords: statistical disclosure limitation ; dominance rule ; p-percent

Abstract

Some variables in magnitude tables may have negative values: net income, net production, capital expenditures, and so on. Negative values pose a computational challenge for the application of disclosure-limitation techniques to tabular data. A table cell may be identified differently (as sensitive or not) if some of cell contributions are negative rather than positive. A negative value reduces rather than increases the cell magnitude, which increases the percentage contributions of the largest observations. There are three common strategies for dealing with variables with negative values: (1) taking absolute values of the negative contributions and applying sensitivity rules to these positive values, (2) increasing disclosure limitation by increasing or decreasing the parameters of the sensitivity rules, and (3) changing the variable to a positive variable and then applying the sensitivity rules as usual. This paper will discuss the application of sensitivity rules in statistical disclosure limitation to magnitude tabular data with negative values.