In addition, Gini indices of earnings inequality for different population subgroups (from full-time employee, to the entire working age population, assigning zero income to the inactive and the unemployed) are highly correlated (Koske, Fournier and Wanner, 2012), although the reference population can make a difference in some countries, particularly those with a higher incidence of part-time workers.6 The information collected in PIAAC refers to gross (pre-tax) earnings. This can potentially bias the cross-country comparison of wage dispersion, to the extent that different countries differ in the degree of progressivity of their tax system. Fournier and Koske (2012) work with eight different household survey data, the largest of which (the EU-SILC) contains data on 21 EU member countries. Indeed, the use of pre-tax earnings has the advantage of capturing inequality in how the market rewards certain characteristics, before the mediating effect of the tax system.