Towards sustainable labour market: Spatial analysis of the differences in the employment of women and men across the EU regions

Research background: Reducing the gender employment gap (GEG) is a key challenge in the context of achieving the Sustainable Development Goals (SDGs), particularly in the area of decent work and equal opportunities (SDG8, decent work and economic growth and SDG5, gender equality). This multidimensional problem plays a critical role in regional policy, which is reflected in the legislative and executive measures taken at the level of the European Union (EU). Purpose of the article: The aim of this article is to analyse the relationship between the employment gap and selected socio-economic factors in the regions of the EU at NUTS 2 level, with a particular focus on spatial interactions. This is particularly important for regional policy and the creation of a sustainable labour market. Methods: The analysis is based on aggregated Eurostat data at NUTS 2 level. The statistical and spatial econometric tools used for the empirical part are the spatial correlation coefficients of Moran’s I and Geary’s C, local Moran’s I, and two spatial econometric models (Spatial Durbin Model, SDM, and Spatial Durbin Error Model, SDEM). Findings & value added: Using spatial regression models, the study identifies key labour market factors affecting GEG. A higher share of part-time workers and longer working hours per employee are linked to increased GEG, while a greater share of women with higher education and a higher old-age dependency ratio (ODR) correlate with a reduction in this gap. In turn, industrialisation impacts GEG indirectly, influencing neighbouring regions. These findings highlight the systemic nature of the GEG, emphasising its economic, educational, and demographic drivers. The study underscores the need for regionally coordinated policies to address gender disparities in the labour market and support the achievement of the sustainable development goals (SDG4, SDG5, SDG8).