  The aim of this paper is to present an original approach to estimate the
gender pay gap. 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. %, avoiding the main limitation of standard approaches, which
is the dependence on the choice of explanatory variables and the functional
form in regression. 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.
