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Veranstaltungsreihe: IAB-Colloquium (en)

The discussion series “Labour Market and Occupational Research (IAB-Colloquium zur Arbeitsmarkt- und Berufsforschung)” is a forum where primarily external researchers present the results of their work and discuss these with experts from IAB. Practitioners from the political, administrative and business fields are naturally also welcome.

The paper develops a theoretical framework to study the effect of minimum wages on poverty and bring this framework to the data.

We develop a theoretical framework to study the effect of minimum wages on poverty and bring this framework to the data using a detailed individual-level panel dataset combined with information on county-level minimum wages from urban China and both a first-differenced multinomial logit model and a difference-in-differences approach. We show that theoretically the impact of minimum wages on poverty is ambiguous while empirically China’s minimum wages have had a moderate yet significant poverty reducing effect.

Digging deeper, we demonstrate two countervailing mechanisms at work: higher minimum wages help pull some workers out of poverty, while simultaneously pushing a smaller number of workers into poverty. Results are robust to a wide range of sensitivity checks including using various different poverty lines, while subgroup analyses notably show that the effect of minimum wages on poverty is most pronounced for women.

Joint with:
Sylvie Démurger, École Normale Supérieure de Lyon and CNRS
Carl Lin, Bucknell University
Dewen Wang, The World Bank

This study is about linking post-partum experience to fertility intentions on over forties.

While motherhood is often portrayed positively, many women experience significant emotional post-partum challenges. These negative experiences may shape future family planning decisions, yet their impact on fertility intentions remains understudied.
Using a sample of Italian mothers, emotional distress was measured using a four-item scale assessing tiredness, sadness, inadequacy, and loneliness. Regression analyses were conducted to assess the relationship between emotional distress and fertility intentions, controlling for relevant socio-demographic factors.

A significant negative association was found between post-partum emotional distress and fertility intentions. Mothers experiencing higher levels of emotional distress reported lower intentions for subsequent childbearing, with this effect primarily driven by mothers over 35 years old.
Post-partum emotional distress is associated with a reduction in mothers' fertility intentions, particularly among older mothers, challenging idealized narratives of motherhood and highlighting the need for a more nuanced understanding of maternal experiences.
These findings underscore the importance of addressing maternal emotional well-being in reproductive health policies and suggest the need for enhanced post-partum support services, especially for older mothers.

In this talk, a larger project that seeks to understand the role of employers in the inheritance of economic status, is discussed.

Intergenerational mobility, the extent to which individuals can achieve economic success regardless of their family background, is a key indicator of equality of opportunity. While labor market outcomes reflect both individual traits and firm-level pay-setting, research on intergenerational mobility has largely focused on the former.

In this talk, I discuss a larger project that seeks to understand the role of employers in the inheritance of economic status. In contemporary Sweden, sorting across workplaces accounts for between one-quarter (employers) and two-fifths (establishments) of the intergenerational correlation in labor earnings. Privileged workers tend to sort into firms that both generate higher value-added and distribute a larger share of surplus to employees. Although workers from less advantaged backgrounds benefit equally when employed by high-paying firms, they are much less likely to gain access to them. I quantify the roles of education, occupation, parental job networks, and the inheritance of industry, employer, and local labor market. I then conclude by outlining a broader research agenda using linked employer-employee data to systematically assess how workplace-level mechanisms shape inequality by social origin.

Why do only few couples choose the female spouse as main provider of labour income?

Why do only few couples choose the female spouse as main provider of labour income? To understand gender imbalances among family breadwinners, I present a collective household production model with identity concerns that illuminates different channels through which gender norms can affect household specialisation decisions. To test the predictions of the model regarding identity, I develop a novel experimental paradigm to study the specialisation choices of real heterosexual couples in the lab.

Women are less likely to become breadwinners than men are, but this is mainly due to gender differences in productivity. While I find little evidence that concerns for gender identity affect specialisation choices, the results suggest they amplify gender differences in labour supply at the intensive margin. The design further allows me to shed light on two additional factors that contribute to the gender imbalance among breadwinners: men’s overconfidence and women’s reluctance to assume sole responsibility for household income.

This paper investigates whether power vacua lead to collective action of marginalised groups.

In this paper, we investigate whether power vacua lead to collective action of marginalised groups. Specifically, we examine whether the large share of men missing during WWI in Germany led to an increase in the suffragette movement fighting for women's right to vote. We exploit exogenous variation in the drafting probability arising from regional differences in recruitment responsibility and link it to the presence of local suffragette clubs.

Our results suggest that women were more likely to keep open local suffragette clubs in regions with higher male absences during the war. We further explore two additional outcomes of male absences related to women's empowerment. First, we show that male absences led to increased political participation among women once female voting rights were introduced. Second, using data on employment by industry and gender, we show that missing men contributed to the growing importance of women in the economic sphere.

This study shows how new digital technology reshapes vocational training and skill acquisition.

We study how new digital technology reshapes vocational training and skill acquisition and its impact on workers' careers. We construct a novel database of legally binding training curricula and changes therein, spanning the near universe of vocational training in Germany over five decades, and link curriculum updates to breakthrough technologies using Natural Language Processing techniques.

Our findings reveal that technological advances drive training updates, with curriculum content evolving towards greater use of digital and social skills, and less routine intensive tasks, mostly through new skill emergence. Using administrative employer-employee data, we show that educational updates help workers adapt to new demands for their expertise, and earn higher wages compared to workers with outdated skills. These findings highlight the role of changes in within-occupational skill supply in meeting evolving labor market demands for non-college educated workers.

Joint with Anna Salomons and Ulrich Zierahn-Weilage.

This study examines the case of a multilingual digital information platform designed to support migrant integration.

This study examines the case of a multilingual digital information platform designed to support migrant integration at the level of German districts and cities. Utilizing a dataset of 11.8 million website logs from 2018 to 2024, covering over 100 participating regions, the research investigates how local administrations prioritize information provision given their typically limited capacities - and to what extent this prioritization aligns with users' demands.

Descriptive findings reveal significant disparities in thematic focus and language offerings across districts. Additionally, multivariate logistic regressions are employed to map the probability of users' page views (demand) over 20 topics and levels of content provision (supply). Thus, topics providing immediate practical value, such as opening hours and mobility information, show high demand relative to supply. Topics representing the acquisition of key resources or knowledge - like language learning, housing, or legal issues - demonstrate both high demand and responsiveness to increased supply. This indicates that users are motivated to navigate even through detailed, deeply nested pages for these topics.

Furthermore, the research reveals varying information demand across language groups, likely reflecting their distinct integration contexts. Overall, the findings highlight the need for tailored, demographically informed content strategies that account for language-specific needs in supporting refugee integration locally. Multilingual and locally relevant information is in high demand by newcomers, but providing it effectively requires careful attention, especially given local administrations’ limited resources.

This paper addresses the gap by exploring how immigration background intersects with gender wage inequalities.

Worldwide, significant progress has been made towards gender equality in recent decades. However, persistent disparities remain: women continue to earn less than men and face greater obstacles in career advancement. The enduring issue of the "gender pay gap" reflects these challenges. Surprisingly, despite the growing gender-migrational diversity of the European workforce, research has largely treated women as a homogeneous group, overlooking critical intersections between gender and immigration background.
This paper addresses this gap by exploring how immigration background intersects with gender wage inequalities and how these inequalities vary across European countries. Using pooled data from the European Union Statistics on Income and Living Conditions (EU-SILC, 2011–2020), it seeks to enhance our understanding of cross-national differences in wage disparities between immigrant and native women. Specifically, it addresses two key questions: (1) To what extent do European countries differ in the wage penalties faced by immigrant women compared to their native counterparts? (2) To what extent can these cross-national differences be explained by structural features of the labour market?

The findings reveal that immigrant women, particularly those from non-EU countries, experience the most pronounced wage penalties compared to native women, with substantial variation across EU countries. These disparities appear partly attributable to structural labour market factors, underscoring the need for nuanced, intersectional analyses.

Can marriage increase gender equality by estimating the causal effect of marriage vs cohabitation on labour market trajectories of new parents.

Traditionally, a "marriage surplus" was created through specialization of household activities, but in modern times gains from a more egalitarian marriage can be through increased coordination.

We ask for the first time whether marriage can increase gender equality by estimating the causal effect of marriage vs cohabitation on labour market trajectories of new parents. Applying a Marginal Treatment Effects framework, the average treatment effect of marriage is consistent with specialization - marriage causes women to work less and men more. This average effect hides treatment effect heterogeneity across unobservables, whereby the couples "more resistant" to marry - i.e. the more modern couples, exhibit coordination of labour market activities.

There is no longer a marriage penalty to women and the coordinating men earn less if married than if cohabiting. Given this, we ask whether increased gender equality for the coordinators lowers or raises household welfare, finding no effect of marriage on children for specializers or coordinators, and a reduction in separation from marriage for coordinators - suggesting that moving away from masculine male breadwinner norms can improve relationship contentedness.

Advancements in Artificial Intelligence (AI) such as Large Language Models (LLM) promise to open unprecedented possibilities in applications with the potential to fundamentally change social research methods. Simultaneously, its development is currently dominated by venture-backed 'BigTech' companies, and it's once again a winner-take-all race. The scientific community is mostly only consumer and not driver of changes, especially from the domains of social science.
These developments do not go without critique. A key concern with AI for social scientists is how to evade methodological black boxes and resist the illusion of Emily Bender's stochastic parrots with their potential risks of hidden biases. The dangers of systems that are not understood sufficiently and that potentially breach privacy, data protection and research ethics principles are crucial.

Some scholars suggest, therefore, that this might be avoidable by gaining a profound understanding of the AI systems' training models and data. However, our understanding of LLM and their training data, for instance, is often limited by proprietary information and business secrets. Hence, we can almost only trust companies with what happens to our data.
Questions on the effectiveness of new laws on the digital frontier (e.g. EU AI Act) to make the principles within these programs understandable by obliging transparency arise, as well as the difficulties of grasping (arithmetic) biases and inequalities, despite their well-documented existence.

Discussing awareness of (arithmetic) biases questions knowledge and resources. Who can really understand LLM? Where do sociologists find resources and time for such an endeavour on top of their research? Should sociology trust computer science with this issue to bridge epistemological differences with another discipline?

This presentation will cover potentials and challenges of AI in societal analysis, especially with qualitative methods, questions of trust and knowledge and will explore possible solutions for feasible sociological AI application.