Despite a long-term trend towards reduction, the gender gap in employment keeps standing in Southern Europe. Numerous potential causes have been individuated, such as the household configuration, women’s human capital, or the institutions that regulate the labour market. Less is known about the role of the locality. This paper explores what covariates influence women’s access to labour markets, and whether it is unevenly distributed across different countries and regions in Southern Europe. The analysis is based on the dataset round 9 (2018) from the European Social Survey. We focus on the following countries available in the dataset: Cyprus, Italy, Spain and Portugal. Italy and Spain are further differentiated into vulnerable and affluent regions according to the regional GDP in 2018. We apply a regression model for the binary response that is the indicator of having been doing paid work for the last 7 days of each individual in the sample. We adopt the Bayesian approach, to derive conclusions via a whole probability distribution, i.e., the posterior of all parameters, given data. The statistical goal is the selection of the most important covariates for access to the labour market, focusing on gender differences. Our analysis finds out that individual characteristics are mediated by household composition. Even though higher education increases women’s employment, the presence of children and having an employed partner reduce such involvement. Moreover, a larger gender gap is detected in vulnerable regions rather than affluent ones, especially in Italy.

Original languageEnglish
Number of pages26
Early online dateApr 2023
Publication statusPublished - 18 Apr 2023


  • Bayesian approach
  • Covariate selection
  • Gender gap
  • Labour market
  • Regression models


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