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Archives: IAB-Veranstaltungen

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.

This study is about the return intentions of Ukrainians and how these intentions may depend on the feeling of national identity and pride.

We conducted a poll of 1139 Ukrainians who currently live in Poland. 937 of them took refuge after the start of the full-scale russian invasion on Feb. 24, 2022, and the other 202 migrated earlier. Our major focus was on the return intentions of Ukrainians and how these intentions may depend on the feeling of national identity and pride. In the pre-registered hypotheses, we stated that a stronger national identity was positively associated with the willingness to return home and that we could amplify this willingness by making the identity more salient.

In the survey, we randomly exposed individuals to three priming settings. Two of them primed subjects towards enhancing identity and pride feelings, while the third group contained neutral questions for a control group. Then, we measured the key variables of interest (return intentions) and found strong support for the first hypothesis and unexpected results for the other.

One of the most unexpected findings is the negative average effect of “pride priming” on return intentions of forced displaced persons, with a positive gradient along the levels of national pride. In fact, people with initially low levels of pride express strictly negative return intentions, whereas people with high pride are more likely to return. At the same time, pre-war migrants have not been affected by our priming experiment, which suggests more stable staying preferences in this group.

This study is about moving an establishment survey from telephone administration to online administration.

The European Company Survey (ECS) 2019 – commissioned by two European Agencies, Eurofound and Cedefop, and carried out by Ipsos – was the first large-scale, cross-national survey of establishments to use a push-to-web approach. Establishments across all EU Member States were contacted via telephone to identify a management respondent, and, where possible, an employee representative respondent. Respondents are then asked to fill out the 20-25 minute survey questionnaire online. The questionnaire captured a wide range of practices and strategies implemented by European companies in terms of work organisation, human resource management, skills use and skills development, and employee voice. Fieldwork for the survey took place in the first half of 2019, in all EU Member States.

Around a quarter of respondents to the ECS 2019 consented to being re-contacted for follow-up research. In November 2020 Eurofound and Cedefop approached these respondents, inviting them to complete a 10-15-minute follow-up questionnaire on the impact of COVID-19 on workplace practices.
In my presentation I will discuss the survey design, fieldwork outcomes, and the lessons we have drawn from conducting the ECS 2019 and the ECS 2020 follow-up – including the results from an experiment we ran as part of the ECS 2020 follow-up with offering customised reports to entice survey respondents. I will also briefly reflect on our plans for the next ECS which is scheduled for 2028.

This paper estimates the medium-run effect of duration of residence in reception centers of asylum seekers.

After arrival, asylum seekers are often housed in reception centers. The type, quality and duration of stay in such centers varies considerably across or within countries. In the context of the so-called “EU refugee crisis” in 2014-2016, reports emerged that some asylum seekers remained in reception centers for several years due to limited capacity of municipalities, lengthy asylum procedures and tight housing markets. It is often argued that reception centers have a detrimental effect on integration processes of asylum seekers and refugees, yet empirical, inferential evidence is still lacking. This paper estimates the medium-run effect of duration of residence in reception centers on language skills, contacts to the host population, and employment status. We use high-quality panel data on refugees living in Germany and apply inverse-probability-weighting (IPW). The results suggest that a quick transition from reception centers into private housing modestly increases refugees’ interactions with the host population and their language proficiency. We find no effects on labor market participation. Using additional analyses, we find that moving into private housing is often associated with a shift to more precarious neighborhoods, potentially hindering a stronger realization of the benefits linked to independent living in general.

This study is about the influence of family members, neighbors and coworkers on retirement behavior.

We study the influence of family members, neighbors and coworkers on retirement behavior. To estimate causal retirement spillovers between individuals, we exploit a pension reform in the Netherlands that creates exogenous variation in peers' retirement ages, and we use administrative data on the full Dutch population.

We find large spillovers in couples, primarily due to women reacting to their husband's retirement choices. Consistent with homophily in social interactions, the influence of the average sibling, neighbor and coworker is modest, but sizable spillovers emerge between similar individuals in these groups.

Additional evidence suggests both leisure complementarities and the transmission of social norms as mechanisms behind retirement spillovers. Our findings imply that pension reforms have a large social multiplier, amplifying their overall impact on retirement behavior by 40%.

The principal effects on the probability of engagement in the criminal justice system are much larger for Black than for non-Black males.

Using rich Texas administrative data, we estimate the impact of middle school principals on post-secondary schooling, employment, and criminal justice outcomes. The results highlight the importance of school leadership, though striking differences emerge in the relative importance of different skill dimensions to different outcomes. The estimates reveal large and highly significant effects of principal value-added to cognitive skills on the productive activities of schooling and work but much weaker effects of value-added to noncognitive skills on these outcomes.

In contrast, there is little or no evidence that middle school principals affect the probability a male is arrested and has a guilty disposition by raising cognitive skills but strong evidence that they affect these outcomes through their impacts on noncognitive skills, especially those related to the probability of an out-of-school suspension. In addition, the principal effects on the probability of engagement in the criminal justice system are much larger for Black than for non-Black males, corresponding to race differences in engagement with the criminal justice system.

Stressing strict privacy policies and changing the location of the survey URL have no response-enhancing effect.

Researchers collect data in most experiments not all at once but sequentially over a period of time. This allows to observe outcomes early and to adapt the treatment assignment to reduce the costs of inferior treatments. This talk discusses multi-armed-bandit-type adaptive experimental designs and algorithms for balancing exploration of treatment effects and exploitation of better treatments. By design, bandits break usual asymptotic and make inference difficult. We show how a batched bandit design allows for valid confidence intervals and compare coverage of the batched bandit estimator in Monte Carlo simulations. In a real-world application, we investigate elements of a survey invitation message targeted to businesses. We implement a full factorial experiment with five elements adaptively.

Our results indicate that personalizing the message, emphasizing the authority of the sender, and pleading for help increase survey starting rates, while stressing strict privacy policies and changing the location of the survey URL have no response-enhancing effect. As a tool for researchers, we introduce bandits in Stata, which facilitates running Monte Carlo simulations to assist the design and implementation of experiments before data are collected, interactively running own bandit experiments, and analyzing adaptively collected data. Bandits implement three popular treatment assignment algorithms: ε-first, ε-greedy, and Thompson sampling. Bandits facilitates estimation, inference, and visualization.

The results indicate an important role played by union wage spillovers in lowering wages over the 1980-2010 period.

In this paper we provide new estimates of the impact of unions on nonunion wage setting. We allow the presence of unions to affect nonunion wages both through the typically discussed channel of nonunion firms emulating union wages in order to fend off the threat of unionisation and through a bargaining channel in which nonunion workers use the presence of union jobs as part of their outside option.
We specify these channels in a search and bargaining model that includes union formation and, in our most complete model, the possibility of nonunion  firm responses to the threat of unionisation.

Our results indicate an important role played by union wage spillovers in lowering wages over the 1980-2010 period. We  find de-unionisation can account for 38% of the decline in the mean hourly wage between 1980 and 2010, with two-thirds of that effect being due to spillovers. Both the traditional threat and bargaining channels are operational, with the bargaining channel being more important.

IAB and the Network of European Labour Market Research Institutes (ELMI) organise a policy-oriented conference on `Securing Skilled Workforces in Europe´ in Brussels.

IAB and the Network of European Labour Market Research Institutes (ELMI) organise a policy-oriented conference on 'Securing Skilled Workforces in Europe' in Brussels on October 1st and 2nd, 2024. The event is open to EU policy makers and representatives of the European Commission as well as the Directorates-General.

This lecture examines the patterns and paradoxes in observed educational and labour market attainment of migrants and minorities.

The inequalities faced by immigrants and ethnic minorities are topics of substantial salience across Europe, reflected in an every-growing body of research. Despite the insights shed by this burgeoning literature there remain a number of outstanding debates and puzzles about what leads to better or worse outcomes and the underlying mechanisms.

The UK is an interesting case for illuminating some of these debates and puzzles, due to: the diversity of its immigrant and ethnic minority population, the richness of research base, and certain counter-intuitive findings that are at odds with theoretical expectations as well as evidence from other European countries. It thus has the potential to shed further light on what drives more or less unequal outcomes in different contexts.

Drawing on a range of research from across the last 20-years, in this lecture I examine the patterns and paradoxes in observed educational and labour market attainment of migrants and minorities, with reference to the role of class background, educational aspirations, neighbourhoods and social networks, cohort change and return migration, discrimination and policy to. I explore the gendered differences in such outcomes, and what that implies for our understanding of wider national ‘gender orders’. I reflect on what this body of work can tell us about the factors that shape economic outcomes in different settings, the need for greater attention to both migrant success as well as migrant disadvantage; and I assess the key outstanding questions and implications for future research.