Raffaele Ventura (p), Mira Manini Tiwari, Gaby Umbach, Carmen Ramirez Folch, Jaromír Harmáček, Bogna Kietlińska, Laura Rahm

Stephan Brunow

This research investigates the demand for, availability of, and pathways to sex- and gender-disaggregated data (S/GDD) for social policy with a focus on EU and national levels. It begins with charting the more institutionalised roots of S/GDD in terms of global charters, agreements, and goals at the United Nations (UN) level. This is followed by a descriptive analysis of the availability of S/GDD in the Sustainable Development Goals (SDGs) . This is followed by a descriptive analysis of the availability of S/GDD in the SDGs. Our research then mirrors this at the EU level, outlining how S/GDD is positioned and addressed in official mandates, and how the EU’s statistical system and national statistical offices have implemented the mandate of collecting S/GDD to improve gender equality. Progress measurement at the EU level concerning gender equality is addressed by an analysis of the EU Social Progress Index and Regional Competitiveness Index, illustrating thea contextualisation of global ambitions to inform regional social policy. The research's second part focuses on global, EU, and national data pathways, beginning with an outline of key concepts and actors involved in data pathways in the EU. A combination of survey and interview data was collected, from June 2024 to February 2025, and analyzed to address the research questions. The two surveys explore the S/GDD pathways, usage, and challenges at the regional and member-state levels. The first survey investigates the data collection processes and the availability and accessibility of S/GDD at the EU national statistical offices (NSOs) and Eurostat. The second survey collects data from S/GDD users at the EU level. Finally, a national case study, comprising interviews with researchers and statistical actors in Poland, is investigated in-depth to gather context-specific insights, offering a more qualitative understanding of the S/GDD pathways and challenges. Both the results of the surveys and the case study illustrate the complexities of data pathways and explain the significant variability in S/GDD experiences across different EU member states.

Stephan Brunow (p), Alina Sorgner, Michaela Fuchs

Valentina Cattivelli

The reduction of gender inequalities in labour market outcomes is stongly debated in the EU and in Germany. All these studies consider obviously the distinction between women and men. The empirical evidence shows, which characteristics are correlated with the observed differences. There might be discrimination, glass-ceiling effects, and other factors to the disadvantage for females. Alternatively, there might be self-selection and gender-specific differences in tastes and preferences, leading to inequality (which is not driven by lower chances).
This contribution focusses on females in leadership positions. Several studies highlight gender differences and conclude lower chances for females to get into a leadership position. Depending on the study design, however, it is very cumbersome or even impossible, to achieve deeper insights into the question, which females get in leadership positions. This is the departure of our research and we focus on females in leadership positions and compare them with females (instead of males) in non-leadership positions. This consideration enables us to identify characteristics that are correlated with the chance to become employed in a leadership position. With this evidence, we derive policy measures that focusses on females that are more prone to get a leadership position. Our first evidence shows that there are region-specific patterns. Especially females in peripheral regions are more likely to hold a leadership position compared to agglomerated, dense areas. In our study, we intent to disentangle the regional composition in more detail. However, our first evidence suggests that better skilled females of age 45 to 54 and which are mothers, are most likely to get into a leadership position; besides the regional heterogeneity.
We derive these results with a Panel of 10% of all females working in Germany subject to social security contributions, which is provided by the German Institute for Employmen Research (IAB). We cover the years 2012-2018 and intent to prolong the data basis up to 2023. Besides unobserved female and employer characteristics, we consider several groups of females at the labour market and their likelihood to become into a leadership position by using logit and multinomial logit models.

Currently only a German Bachelor Thesis covers the results in a written form. We apologize this inconvenience.

Alessandra Micalizzi, Valentina Cattivelli (p)

Pablo Casas

See long abstract

Pablo Casas (p), Marie Lalanne, Tryfonas Christou, Abián García Rodríguez, Nicholas Lazarou, Simone Salotti

Raffaele Ventura

This paper sheds light on the potential impact of AI on gender inequality in regional EU labour markets. To conduct the analysis, we use a spatial general equilibrium model calibrated for the EU NUTS2 regions in which male and female workers are characterised by AI exposure levels across regions and sectors. We use four different occupation-specific AI exposure measures to simulate how the EU workforce is expected to evolve due to the integration of AI into occupations. We then assess the impact of this AI exposure on disposable income by men and women, as well as on the gender employment and wage gaps. We find that men and women are differentially exposed to AI. These differences mainly result from the fact that men and women work in different occupations and sectors, and occupations and sectors are differentially exposed to AI. Preliminary results suggest that, ceteris paribus, the integration of AI in the economy is expected to increase both the gender pay gap and the gender employment gap, as male workers are on average more exposed to AI than female workers. This overall effect masks regional and sectoral heterogeneity.