IAB-Veranstaltungen Archiv - Page 6 of 33 - IAB - Institut für Arbeitsmarkt- und Berufsforschung

Skill-Replacing Technology and Bottom-Half Inequality

In this model, technology substitutes the usage of skill in routine tasks in contrast to standard RBTC models.

I propose a model of a skill-replacing routine-biased technological change (SR-RBTC). In this model, technology substitutes the usage of skill in routine tasks in contrast to standard RBTC models, which assume technology replaces the workers themselves.

The SR-RBTC model explains three key trends that are inconsistent with standard RBTC models: 1) why specifically middle wages declined even though workers in routine occupations are dispersed across the entire bottom half of the wage distribution, 2) why middle wages stopped declining while the technological change continued, and 3) why there is no substantial decline in the average wage of workers inroutine occupations. I derive two new testable predictions from the model: a decreasein return to skill and a decrease in skill level in routine occupations. I use an interactive fixed-effects model to confirm both predictions.

Since SR-RBTC violates the ignorability assumption required by standard decomposition methods, I introduce a “skewness decomposition” to show that SR-RBTC is the main driver of bottom-half inequality trends.

Prosociality and Layoffs

This study is about layoffs by U.S. public firms using NLP techniques, which allows to establish several facts that are jointly hard to reconcile with existing models.

Many managers describe layoffs as the hardest and most painful decisions of their careers; yet,
standard economic models treat human and physical capital adjustments alike. We collect novel
data on layoffs by U.S. public firms using NLP techniques, which allows us to establish several
facts that are jointly hard to reconcile with existing models. First, firing decisions have large
adverse healthof effects on CEOs, with distress-induced layoffs estimated to reduce CEO lifespan
by 1.85 years. Second, CEOs become more reluctant to make layoffs over their tenure as they
form more connections inside the firm. After plausibly-exogenous CEO changes, instead, new
CEOs make more and shareholder value-increasing layoff decisions. Third, CEOs’ increasing
reluctance to lay off employees intensifies when layoffs are more painful for employees, such as
during recessions or the holiday season, or more painful for managers to witness, such as when
they affect socially or geographically close employees. Fourth, the documented layoff reluctance is
substantially more pronounced among CEOs with higher empathy-related traits. We also show
that long-tenured CEOs are more likely to cut R&D spending during recessions, offsetting forgone
savings from layoffs. Our results imply the need to adjust models of managerial decision-making
for a “human” component of layoff avoidance. Prosocial, or empathy-related, motives provide a
unifying explanation.

17th interdisciplinary PhD-Workshop – Perspectives On (Un-)Employment

The workshop provides an opportunity for graduate students to present their ongoing work in the field of theoretical and empirical labor market research.

The IAB’s Graduate School (GradAB) and the FAU invites young researchers to its 17th interdisciplinary Ph.D. workshop “Perspectives on (Un-)Employment”. The workshop provides an opportunity for graduate students to present their ongoing work in the field of theoretical and empirical labor market research and receive feedback from leading scholars in the discipline. The workshop will focus on but not be limited to empirical research in the following fields:

Inequality, poverty, and intergenerational mobility
Labor supply, labor demand, and unemployment
Gender, family, and discrimination
Evaluation of labor market institutions and policies
Health, labor market integration, and job security
Globalization, international trade and labor markets
Education, qualification, and job tasks
Wage determination and life-cycle earnings
Migration and international labor markets
Establishments and the workplace
Regional labor markets and spatial disparities
Technological change and digitalization
The impact of climate change on the labor market

We welcome papers that apply quantitative, qualitative or mixed methods.

The Second Spanish Immigration Boom

This paper explains why Spain became the fourth most attractive country in the world for international migrants in the period 2015-2024.

International migrants choose their country of residence to maximize their utility. As a result, their choices are informative about the relative attractiveness of countries. This paper explains why Spain became the fourth most attractive country in the world for international migrants in the period 2015-2024, what I define as the Second Spanish Immigration Boom of the century.

First, an accounting decomposition shows how, contrary to other destinations, Spanish-specific factors, correlated with economic conditions and general migration policies, have a larger weight in explaining immigration to Spain than origin-specific factors. Second, the causal relevance of bilateral visa policies is also shown, particularly in the context of Latin American immigrants, by using origins that are required a visa to enter Spain as a control for visa-free access countries in a generalized differences-in-differences setting. Finally, the effects of the Boom on immigrant selection are also analyzed, finding that the Second Boom was different from the first because educational selection improved.

Filling in the Gaps: Designing and Imputing Missing Data in Split Questionnaire Surveys

This talk will present findings from previous research, which explores how to effectively implement split questionnaire designs and impute the resulting data.

In light of challenges such as declining response rates and rising data collection costs, approaches like split questionnaire designs or planned missing data designs offer a promising strategy for survey projects to reduce respondent burden while still collecting data on a broad range of topics. They achieve this by administering only randomly selected parts of the full questionnaire to each respondent, effectively reducing questionnaire length for each respondent. This comes at the cost of large amounts of missing data, which must be imputed to make the data analyzable.

In this talk, I will present findings from my previous research, which explores how to effectively implement split questionnaire designs and impute the resulting data in the context of social surveys. Using Monte Carlo simulations grounded in real-world data from the German Internet Panel and the European Social Survey, I evaluate how different design and imputation choices affect the accuracy of estimates. The presentation will address key methodological questions, including how to construct questionnaire modules, how planned missingness interacts with traditional item nonresponse, and how general-purpose versus analysis-specific imputation strategies influence results. The goal is to provide practical insights and evidence-based recommendations for researchers considering split questionnaire designs in their own survey work.

How to control for (pre-)trends?

This paper assesses the performance of classical strategies to control for (pre-)trends in difference-in-differences designs.

We focus on three main approaches: controlling for or matching on pre-trends, extrapolating linear trends, and controlling for group-by-time fixed effects. Through Monte Carlo simulations using real labor market data, we examine incidental trends that may emerge due to correlations between treatment and unobserved characteristics.

Drawing on these simulations and supporting analytical results, we provide intuitive insights into the performance of these methods and further formalize the conditions that justify their application.

New Hires’ Informal Training and Turnover

This study analyses the relationship between informal on-the-job training and turnover of new hires.

We analyze the relationship between informal on-the-job training and turnover of new hires. To this end, we use unique survey data about different aspects of informal co-worker training and link it to both firm-level and individual-level administrative data.

We find that informal training is negatively associated with turnover of new hires six months after entering the firm. However, this relationship becomes smaller and statistically weaker after 12 months.

Further heterogeneity analysis reveals a trade-off after one year, as onboarding can, to some extent, contribute to increased retention in firms with a lower wage premium and thereby help to mitigate costly worker turnover in these firms.

Joint work with Didier Fouarge and Carolin Linckh.

Project MARS: Mentoring for Disadvantaged Adolescents at Real Scale – a project design

This study investigates how mentoring programs can be successfully scaled to transform the education system in Germany.

The shortage of skilled workers is a central challenge for the German labor market – 18% of young adults (20-34 years) do not have any occupational degree, and this proportion is up to twice as high for those from disadvantaged backgrounds.

One promising approach to tackle this challenge is through individual mentoring programs. The project team investigates how mentoring programs can be successfully scaled to transform the education system in Germany and promote social equality. Whether, and to what extent, such programs have a positive impact is crucial to the successful design of societal transformation processes. The research team is cooperating with a leading mentoring provider and conducting a randomized controlled trial with 3,000 disadvantaged young people to analyze the causal effects of mentoring. We plan to examine four key areas of scale-up: recruitment of mentors, general equilibrium effects, replacement of high-cost matching methods with machine learning, and the horizontal expansion of mentoring to vocational schools and apprentices.

The results will provide both scientific and practical insights into optimal technologies for rolling out interventions that serve societal transformation and the promotion of equal opportunities.

Monetary policy, the bank-lending channel and labor market adjustment of firms

This paper studies the real effects of monetary policy on firms' labor adjustment.

This paper studies the real effects of monetary policy on firms' labor adjustment. Using detailed bank data together with administrative firm and worker data for Germany, we find that firms reduce employment in response to contractionary monetary policy.

We show that this employment reduction results from a relative decline in inflows rather than outflows. Inflows fall in particular for low-wage workers, whereas firms retain high-wage workers. Outflows for transitions to unemployment increase, while employment-to-employment outflows falls.

We interpret this as evidence for labor hoarding. Using variation in the bank exposure to monetary policy, we show that these results are driven by the exposure of the firm to the bank-lending channel.