Abstract
Abstract The aim of this paper is to present an original approach to estimate the gender pay gap (GPG). We propose a model-based decomposition, similar to the most popular approaches, where the first component measures differences in group characteristics and the second component measures the unexplained effect; the latter being the real gap. The novel approach incorporates model selection and bias correction. The pay gap problem in a small area context is considered in this paper, although the approach is flexible to be applied to other contexts. Specifically, the methodology is validated for analysing wage differentials by economic activities in the region of Galicia (Spain) and by analysing simulated data from an experimental design that imitates the generation of real data. The good performance of the proposed estimators is shown in both cases, specifically when compared with those obtained from the widely used Oaxaca–Blinder approach.
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