A new approach to the gender pay gap decomposition by economic activity

TL;DR

This paper introduces a novel model-based decomposition method for estimating the gender pay gap that incorporates model selection and bias correction, improving accuracy over traditional approaches.

Contribution

It presents an original approach to gender pay gap decomposition that addresses limitations of existing methods by including model selection and bias correction techniques.

Findings

The proposed estimators outperform Oaxaca-Blinder in simulations.

Validated the approach on wage data by economic activity in Galicia, Spain.

Effective in small area analysis with improved accuracy.

Abstract

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.