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Archives: IAB-Veranstaltungen

A typical reaction in unemployment insurance (UI) is to impose requirements (backed by sanctions) on the quantity of job search. We evaluate the job seeker’s reaction.

A typical reaction to the moral hazard problem in unemployment insurance (UI) is to impose requirements (backed by sanctions) on the quantity of job search, aimed at ensuring sufficient levels of effort. However, is this the most effective policy strategy? It does neither take into account the intrinsic motivation of the job seeker nor the quality of the targeted search. An alternative policy strategy that encompasses such goals is to focus on job search autonomy.

Exploiting a policy change in a region in Switzerland which followed this aim, we evaluate the job seeker’s reaction to being granted more autonomy. Using rich procedural register data, we document the effects on quantitative effort, scope of search and ultimately on unemployment duration and earnings in the found job.

Our results show that the policy change increased the average duration of unemployment spells in the area by about 8%, while increasing average re-employment earnings by about 3%. Results are heterogenous, a main driver of the variety is the interplay of effort delivery and local labour market conditions, notably tightness. This finding highlights the relevance of search externalities. Furthermore, we provide some evidence of labour demand effects.

Joint work: Patrick Arni, Amelie Schiprowski

The effectiveness of the minimum wage on gender wage differences is examined.

With its introduction in 2015, the national minimum wage intends to benefit primarily low-wage workers in Germany. I examine the effectiveness of the minimum wage on gender wage gaps of full-time workers among the lower half of the wage distribution. Using administrative data, distinct regional differences in the extent of wage differentials and responses to the minimum wage occur. Overall, wage gaps between men and women at the 10th percentile decrease by 2.46 and 6.34 percentage points in the West and East of Germany after 2015. Applying counterfactual wage distributions, I provide new evidence that the introduction of the minimum wage decreases wage differentials by 60% to 95%. Group-specific analyses show various responses on the basis of age, educational level and occupational activity. Counterfactual aggregate Oaxaca-Blinder decompositions indicate a decrease in discriminatory remuneration structures in the West of Germany resulting from the introduced minimum wage.

The authors use employer-employee data to follow US workers' long-run employment flows and earnings after trade liberalization with China.

We use employer-employee data to follow US workers' long-run employment flows and earnings after trade liberalization with China. We find that manufacturing workers in more exposed counties flow disproportionately into low-skill services such as retail and temp agencies, and are more likely to exhibit nominal wage declines after seven years. Formal difference-in-differences analysis reveals that exposure to this shock operates predominantly through workers' local labor market versus industry, that greater upstream exposure via suppliers can offset the adverse impact of own and downstream exposure, and that workers initially employed outside manufacturing generally exhibit relative earnings growth as a result of the liberalization.

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 16th 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:

  • Labor supply, labor demand, and unemployment
  • Evaluation of labor market institutions and policies
  • Education, qualification, and job tasks
  • Wage determination and life-cycle earnings
  • Gender, family, and labor market discrimination
  • Inequality, poverty, and intergenerational mobility
  • Migration and international labor markets
  • Regional labor markets and spatial disparities
  • Impact of technological change, digitalization, and climate change on the labor market

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

This study sheds light on the impact of different types of job retention programs such as short-time work.

This study sheds light on the impact of different types of job retention programs such as short-time work (STW).

We analyze the causal effect of an episode of STW on labor market outcomes up to five years later and compare this to the effects of sudden unemployment episodes. Using data from German Socio-Economic Panel (1992–2022), we employ an event-study approach to analyze the effect of unemployment and STW on career trajectories and unpaid care work.

Results show that workers with periods of short-time work have higher employment and wage stability than workers with periods of unemployment. There are no gender differences in the effects of STW on employment and hours worked.

This paper estimates experimental impacts of a supported work program on employment, earnings, benefit receipt, and other outcomes over a four-year follow-up period.

This paper estimates experimental impacts of a supported work program on employment, earnings, benefit receipt, and other outcomes over a four-year follow-up period.

Case managers addressed employment barriers and provided targeted financial assistance while participants were eligible for 30 weeks of fully subsidized employment. Program access increased employment rates by 21 percent and earnings by 16 percent while participants were receiving services. Though gains attenuated after services stopped, treatment group members experienced lasting improvements in employment stability, job quality, and well-being, and we estimate the program's marginal value of public funds to be in line with other adult workforce programs. Post-program impacts are concentrated among participants who were hired by their host-site employer post-program, suggesting that encouraging employer learning about potential match quality is a key mechanism underlying the program’s impact, and additional descriptive evidence supports this interpretation.

Machine learning methods provide no evidence of treatment effect heterogeneity in a broad sample of job seekers using a rich set of baseline characteristics from a detailed application survey. We conclude that subsidized employment programs with a focus on creating permanent job matches can be beneficial to a wide variety of unemployed workers in the low-wage labor market.

This study documents how the application of causal machine learning methods can successfully increase sales revenue.

If treatment effects vary systematically, customizing treatment status at the individual level may help increasing the overall effectiveness of an intervention. We document how the application of causal machine learning methods can successfully increase sales revenue generated within a loss framing treatment in an online field experiment. We combine this data with a behavioral experiment measuring sensitivity to loss aversion at the individual level. Our results show that treatment status as assigned by causal machine learning is consistent with treatment assignment based on economic theory.

Joint: Kevin Bauer, Andreas Grunewald, Florian Hett, Johanna Jagow, Maximilian Speicher

"New work" - we develop an algorithm that identifies new job-titles in the US economy based on their vector distance from the closest existing job title in the previous census.

"New work", namely the introduction of types of jobs that did not exist earlier, is an essential part of innovation and employment growth for advanced economies. Using text analysis, we develop an algorithm that identifies new job-titles in the US economy based on their vector distance from the closest existing job title in the previous census. We use this method to generate a measure of "new work" from 1980 to 2010 in each of 354 occupations and we construct its distribution across 766 commuting zones. We first show how this measure of "new work" is associated to task and skill characteristics of workers in the occupations and to employment growth, skill bias and innovation in the commuting zones. Then we analyze whether local population density, human capital and manufacturing intensity in the 1980, and/or local exposure to structural "shocks" in the 1980-2010, relating to trade competition, technological change, immigration and age changes predict the creation of new work.

Our main findings are that the share of college educated and the density of population in 1980 are the strongest predictors of New Work creation in the 1980-2010 period. The aging of population and exposure to computer adoption were also associated to New Work creation, while robot adoption was negatively associated to it. The exposure to immigration and trade had a more nuanced and differentiated correlation to new work.

This paper studies the allocation of time among workers across jobs that vary in their remote intensity.

The proportion of employees who work remotely has surged from under 5% to over 60% between January to March 2020, converging to roughly 28% of days working from home versus in the office as of 2023. Motivated by these large structural shifts in the nature of work, this paper studies the allocation of time among workers across jobs that vary in their remote intensity. Drawing on the American Time Use Survey between 2019 and 2022, I document three main results. First, time allocated to leisure increased and to work decreased among more remote jobs with no significant change in home production. Second, these changes were concentrated among males, singles, and those without children. Third, these declines in labor supply cannot explain the recent decline in productivity; in contrast, sectors with greater remote work intensity exhibited greater productivity growth. In addition, I will also present results from a complementary paper that draws on employee engagement and labor market data from over 70,000 workers. While there is a positive association between always WFH and satisfaction, it vanishes after controlling for employee compensation, occupation, demographics, and workplace environment characteristics (e.g., feeling appreciated at work). Employees who always WFH also have a higher intention to leave their job than employees who never work from home. In contrast, less frequent WFH arrangements relate to higher satisfaction but no difference in intention to leave, and their impact is limited relative to workplace environment characteristics.