I have data on disposable income, where some households have negative income. Albeit I can immediately compute the Gini with these dataset (e.g. with
fastgini in Stata), it is well known that Gini with some negative values could be higher than 1. An example from such reference:
Is there an "optimal" method to deal with such observations?
I can think of some approaches like:
- truncating: eliminating all observations with negative income
- censoring: assign zero income to all negative income
- translation: add to every observation the largest negative income, so that the poorest observation has zero income
- some type of normalisation, like the one the reference above gives:
In all these cases, the Gini will now be between 0 and 1. Is there a "preferred" or an "usual" method? (perhaps by multilateral organisations like IMF, OECD, etc)
As a secondary question, is there an inequality index that is better poised to deal with negative income?