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Veranstaltungsformat: Hybrid

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 proposes novel natural language methods to measure worker rights from collective bargaining agreements (CBAs) for use in empirical economic analysis.

This paper proposes novel natural language methods to measure worker rights from collective bargaining agreements (CBAs) for use in empirical economic analysis. Applying unsupervised text-as-data algorithms to a new collection of 30,000 CBAs from Canada in the period 1986-2015, we parse legal obligations (e.g. “the employer shall provide...”) and legal rights (e.g. “workers shall receive...”) from the contract text. We validate that contract clauses provide worker rights, which include both amenities and control over the work environment. Worker-rights clauses increase with firm size, and companies that provide more worker rights score highly on a survey indicating pro-worker management practices. Using time-varying province-level variation in labor income tax rates, we find that higher taxes increase the share of worker-rights clauses while reducing pre-tax wages in unionized firms, consistent with a substitution effect away from taxed compensation (wages) toward untaxed amenities (worker rights). Further, an exogenous increase in the value of outside options (from a Bartik instrument for labor demand) increases the share of worker rights clauses in CBAs. Combining the regression estimates, we infer that a one-standard-deviation increase in worker rights is valued at about 5.4% of wages.

How does labor demand and the generosity of welfare benefits affect the labor market integration of refugees? We analyze the effect of both factors in a common framework.

How does labor demand and the generosity of welfare benefits affect the labor market integration of refugees? We analyze the effect of both factors in a common framework. For identification, we exploit the exogenous placement of refugees in Austria, business cycle fluctuations, and large variation in benefit levels between federal states and type of protection. Higher labor demand at the time of receiving protection status increases employment rates and decreases the likelihood to receive welfare benefits. But the effects are short-lived. Higher benefit levels reduce employment rates initially but the effect is economically small and also temporary. Higher benefit levels also reduce marginal effects of variation in labor demand. Both shocks do not affect the likelihood of remaining in Austria but do affect internal migration.

This paper studies the long-term consequences on firms and workers of the credit crunch triggered by the 2007-2008 global financial crisis.

This paper studies the long-term consequences on firms and workers of the credit crunch triggered by the 2007-2008 global financial crisis. Relying on a unique matched bank-employer-employee administrative dataset, we construct a firm-specific credit supply shock and examine firms’ and workers’ outcomes for 11 years after the crisis. We find that highly-exposed firms shrink permanently and invest less; these effects are larger for high capital-intensive firms. The impact on workers’ earnings is also long-lasting, especially for high skilled workers, who are more complementary to capital. Displaced workers reallocate mostly to low capital-intensive firms, experiencing persistent wage losses.

This paper investigates whether task overlap can equalize the effects of automation for unemployed job seekers displaced from routine jobs.

This paper investigates whether task overlap can equalize the effects of automation for unemployed job seekers displaced from routine jobs. Using a language model, we establish a novel job-to-job task similarity measure. Exploiting the resulting job network to define job markets flexibly, we find that only the most similar jobs affect job finding. Since automation-exposed jobs overlap with other highly exposed jobs, task-based reallocation provides little relief for affected job seekers. We show that this is not true for more recent software exposure, for which task overlap mitigates the distributional consequences.

We harness detailed administrative data from Finland to provide new empirical facts on the economic effect of rape on victims and its spillovers.

Rape and sexual assault are common worldwide: one in twelve women across 28 EU countries have experienced a rape (European Institute for Gender Inequality, 2012). Yet there is no systematic evidence on how sexual violence affects women's economic outcomes.

We harness detailed administrative data from Finland to provide new empirical facts on the economic effect of rape on victims and its spillovers. A third of police reports for rape involved victims younger than 21 years old at the time of the assault. We show that the age-25 employment and college completion rates of younger victims are 12.8 p.p and 10 p.p lower respectively than those of other young women with the same (pre-event) GPA and family background. For older victims, we use a matched difference-in-difference design to show that rape has a large and persistent economic impact on women: victims' employment falls by 7.8 percentage points and their labor market earnings decline 16.5 % relative to observationally equivalent women in the five years following the assault.

These results are robust to controlling for a variety of shocks preceding rape that could make it more likely for a woman to be victimized and independently suppress her economic outcomes. We also document important spillovers of these crimes to the victim's parents and peers. Mothers and fathers experience significant declines in their employment and female schoolmates experience a deterioration in mental health. Last, we show that higher clearance rates of rape cases mitigate the negative impacts on victims. Together, these results indicate that preventing and addressing sexual violence is a vital economic issue.

This study examines the impact of early education and care services on the labour market integration of Ukrainian refugee mothers in Germany.

This study examines the impact of early education and care services on the labour market integration of Ukrainian refugee mothers in Germany. The analysis uses a new, large and representative panel data set (IAB-BiB/FReDA-BAMF-SOEP Survey) of refugees arriving in Germany after the Russian invasion in Ukraine. Our empirical approach exploits regional differences in child care availability and the age of the youngest child to generate exogenous variation in children’s access to early education and care services.

Our results reveal very strong effects on mothers’ participation in language classes, work intentions and actual employment, as well as their time with Germans. Placebo checks using mothers with older children support a causal interpretation of our findings. Our study highlights the importance of investing in early education and care services to facilitate the integration of refugee mothers in host societies.

Joint work with Ludovica Gambaro, Sophia Schmitz, C. Katharina Spieß and Mathias Hübener.

We study how firms adjust the bundles of management practices they adopt over time, using repeated survey data collected in Germany from 2012 to 2018.

We study how firms adjust the bundles of management practices they adopt over time, using repeated survey data collected in Germany from 2012 to 2018. By employing unsupervised machine learning, we leverage high-dimensional data on human resource policies to describe clusters of management practices (management styles).

Our results suggest that two management styles exist, one of which employs many and highly structured practices, while the other lacks these practices but retains training measures. We document sizeable differences in styles across German firms, which can (only) partially be explained by firm characteristics. Further, we show that management is highly persistent over time, in part because newly adopted practices are discontinued after a short time.

We suggest miscalculations of cots-benefit trade-offs and non-fitting corporate culture as potential hindrances of adopting structured management. In light of previous findings that structured management increases firm performance, our findings have important policy implications since they show that firms which are managed in an unstructured way fail to catch up and will continue to underperform.