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Archives: IAB-Veranstaltungen

Exploiting prospective data on a cohort born in 1958 we estimate the gender wage gap over the life-course between age 23 and 63, departing from the literature in two ways.

Most studies estimating the gender wage gap rely on linear regression of log hourly earnings.  Estimates often condition on potentially endogenous regressors such as labour market experience and family formation.  Exploiting prospective data on a cohort born in 1958 we estimate the gender wage gap over the life-course between age 23 and 63, departing from the literature in two ways.  First, we use matching estimators which are rarely used in the literature.  Like regression analyses matching relies on observed data to recover the effect of gender on earnings, but by explicitly considering the issue of common support it is more transparent in its treatment of men as counterfactuals for women.  We examine the importance of the common support issue for the size of the gender wage gap.  Second, we condition on pre-labour market variables to avoid conditioning on endogenous choice variables, such as family formation, which are made, in part, with knowledge regarding one’s potential earnings.  We argue our data are well-suited to the task because they contain a wide array of prospective data collected at birth, then at ages 7, 11 and 16, which might conceivably confound estimates of the GWG.  In contrast to findings in the literature in which the regression-adjusted GWG is considerably smaller than the raw gap, we find differences in log hourly mean earnings between men and women are of roughly similar size and, in some cases, wider than raw gaps conditioning on pre-labour market variables.  This is the case whether we use matching or linear estimation techniques. However, the PSM estimated GWG is above the raw gap when cohort members are in their 40s, 50s and 60s.  The implication is that women have pre-labour market traits which reduce their earnings later in life relative to men.  The gap follows an inverted-u shape over the life-course, reaching its maximum of around. .45 log points at age 42, after which it begins to decline, though it remains large among cohort members in their 60s.

Joint work with: Francesca Foliano, Heather Joshi, Bozena Wielgoszewska and David Wilkinson

In this study, we examine how the same vacating opportunity translates differently for male and female full-time workers.

In this study, we examine how the same vacating opportunity translates differently for male and female full-time workers. By utilizing matched employer-employee data from Germany, our empirical approach leverages 30,000 unforeseen worker deaths spanning from 1980 to 2016 which enables us to explore how firms react to exogenous vacancies. We find that when a position becomes vacant, female replacements have starting wages that are 20 log points lower compared to their male counterparts. Even after considering the pre-hire wage of replacement workers, half of this gap persists. The gender disparity in opportunities cannot be attributed to workload redistribution among other coworkers. Over time, the gap tends to widen on average and remains stable even for those who remain employed full-time in the subsequent five years after being hired.​

We study the role of labor market beliefs in the gender pay gap. We find that, on average, women expect to receive lower salaries than men and also expect to receive fewer offers when employed. 

We study the role of labor market beliefs in the gender pay gap. We find that, on average, women expect to receive lower salaries than men and also expect to receive fewer offers when employed. Gender differences in expectations explain a sizable fraction of the residual gap in reservation wages. We estimate a partial equilibrium job search model that incorporates worker heterogeneity in beliefs about the wage offer distribution, arrival rates, and separation rate. Counterfactual exercises show that labor market beliefs play an important role in the gender wage gap, but matter little for the gender differences in welfare. Eliminating gender differences in the actual offer distribution, by contrast, decreases the gender gap in pay and welfare.

Urban labor markets provide agglomeration advantages to workers and firms. However, the distributional consequences are not fully understood.

Urban labor markets provide agglomeration advantages to workers and firms. However, the distributional consequences are not fully understood. Agglomeration benefits are unevenly shared among low- and high-skilled workers. At the same time, many large urban labor markets around the world have experienced strongly rising housing costs in recent decades, especially for renters and young first-time homebuyers, putting these groups at risk of being priced out of the local labor market. The workshop aims to bring together junior and senior researchers working on these and related issues and welcomes both empirical and theoretical contributions. The list of topic includes, but is not limited to

  • Distributional consequences of agglomeration benefits
  • Labor market outcomes and housing affordability
  • Highly-local income inequality
  • Spatial extent of local labor markets and commuting patterns
  • Neighborhood effects and segregation
  • Interactions between local housing and labor markets

This workshop invites empirical contributions using either the IAB Establishment Panel, one of its derivatives (LPP/LIAB), or other matched employer-employee data.

Celebrating the 30th anniversary of the IAB Establishment Panel Survey, this workshop invites empirical contributions using either the IAB Establishment Panel, one of its derivatives (LPP/LIAB), or other matched employer-employee data. Research projects from all areas of labour market research are welcome, including personnel economics, sociology and economics of vocational education and training, industrial relations, or industrial economics. Papers may address research questions in any of these areas as well as methodological questions.

Numerous governments provide income-contingent childcare subsidies.

Numerous governments provide income-contingent childcare subsidies. In this paper, we estimate the dynamic marginal efficiency cost of redistribution (MECR) associated with a large-scale program of this kind in Germany, and compare them with the MECR associated with the benchmark redistributive tool, the income tax. To do so, we integrate methods from public finance theory into a dynamic structural heterogeneous-household model of childcare demand and maternal labor supply. We also incorporate social mobility concerns into the MECR and find the MECR of the childcare subsidies to be significantly lower at the margin, suggesting that childcare subsidies are the more efficient redistributive tool.

This lecture is about how artificial intelligence can be used to reduce friction in markets.

We explore how Artificial Intelligence can be leveraged to help frictional markets to clear. We design a collaborative-filtering machine-learning job recommender system that uses job seekers' click history to generate relevant personalised job recommendations. We deploy it at scale on the largest online job board in Sweden, and design a clustered two-sided randomised experiment to evaluate its impact on job search and labour-market outcomes. Combining platform data with unemployment and employment registers, we find that treated job seekers are more likely to click and apply to recommended jobs, and have 0.7 percent higher employment within the 6 months following first exposure to recommendations. At the job-worker pair level, we document that recommending a vacancy to a job seeker increases the probability to work at this workplace by 10 percent. We propose a decomposition exercise of the net employment effects into three channels. The most important channel corresponds to the increase in the number of applications due to recommendations (first channel), partly offset by the lower conversion into employment of marginal applications (second channel). Congestion effects (third channel) are not a significant contributor to the overall effect. We also find larger employment effects when recommended vacancies are less popular, and for recommendations that broaden search further away in geographical and occupational distance.

We study how online job search advice affects the job search strategies and labor market outcomes of unemployed workers.

We study how online job search advice affects the job search strategies and labor market outcomes of unemployed workers. In a large-scale field experiment, we provide job seekers with vacancy information and occupational recommendations on an online dashboard. A two-stage randomized design with regionally varying treatment intensities allows us to account for treatment spillovers. Our results show that online advice is highly effective when the share of treated workers is relatively low: in regions where less than less than 50% of job seekers are exposed to treatment, working hours and earnings of treated job seekers increase significantly in the year after the intervention. At the same time, we find substantial negative spillovers on other treated job seekers for higher treatment intensities, resulting from increased competition between treated job seekers who apply for similar vacancies.

This paper questions the design of job recommender systems (RS).

This paper questions the design of job recommender systems (RS). We argue that state of the art ML-based algorithmic recommendations aimed at identifying a hiring score from past successful matches do not always result in improved outcomes for job seekers (JS). This is because first, the objectives of these recommendations do not align with the ones of the JS and second, they are usually generated independently of each other, without considering competition. Using a theoretical model of a two-sided market with an application stage, we discuss the needs that RS should meet. We then show that the ML-based hiring score, from which recommendations are typically derived, is only one of the necessary ingredients to meet these needs. Additionally, a matching score between JS and job offer profiles must be considered, and the two should be combined to form a criterion that reflects the expected utility. Our empirical analysis confirms this quantitatively matters, using the RS designed as part of a long-term project in collaboration with the French Public Employment Service. This project leverages extensive and detailed data on applicants, firms, and past job searches. Moreover, we discuss how optimal transport can be leveraged to design RS that avoid congestion, viewing the recommendations as a collective problem rather than a series of individual programs.

EU Eastern Enlargement elicited a rise in (temporary) labour market oriented immigration to Germany starting in May 2011. Taking into account that not all immigrants stay permanently and that outmigration flows are selective, this paper classifies recent EU immigrants into “new arrivals” and “stayers” drawing on administrative social security data (2005-2017). This novel strategy allows us to separately identify their potentially opposing short- and medium-run effects on labour market outcomes in Germany. We find a transitory negative wage effect among German nationals, particularly at the bottom of the wage distribution; and a permanent positive effect on full-time employment.