Gender wage gaps are typically measured by the means of decomposition. Proliferation of methods makes the choice of the correct estimator for a given data a conceptual challenge, especially if data availability necessitates simplifications. The challenge lies in accounting for observable differences adequately, which in itself is not only a data issue, but also a conceptual issue. Ideally, one would want to compare men and women actually “alike” in terms of all relevant characteristics, including hours effectively worked, commitment, talent. However, many of these characteristics are not observable (or are imperfectly measured, e.g. human capital).

Decompositions are prone to multiple risks. For example, the urge to compare only the comparable implies that a decision needs to be made about the use of observations which clearly are not comparable. Nopo (2008) proposes to use these observations to infer about the possible selectivity in this process, but alternative approaches consist of reweighing or neglecting this issue. Similar choices concern the treatment of distributional issues. Finally, for the parametric methods, the dependence on the functional form may influence the results as well. Consequently, depending on the features of a given labor market, an estimate of gender wage gap obtained with a given method is likely to overstate or understate the extent of true unjustified inequality in wages.

We make available a dataset which provides a full selection of gender wage gap estimates for the EU countries, using data from EU-SILC. Across countries and years, everybody can see for themselves, what is the source of the gender wage inequality in a given European country. We provide a compressed file containing:

• A dta file with the full set of estimates for the gender wage gaps
• Codes for replicating the findings of the paper from raw data (dofiles)
• Data documentation