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Veranstaltungsformat: Online

We argue that skill-biased technological change not only affects wage gaps between skill groups, but also increases wage inequality within skill groups, across workers in different firms. Building on a heterogeneous firm framework with labor market frictions, we show that an industry-wide skill-biased technological change shock will increase between-firm wage inequality within the industry through four main channels: changes in the skill wage premium (as in traditional models of technological change); increased employment concentration in more productive firms; increased wage dispersion between firms for workers of the same skill type; and increased dispersion in the skill mix that firms employ, due to more sorting of skilled workers into more productive firms. Importantly, a simultaneous increase in the supply of skilled workers does not offset the technology- induced rise in inequality. Using rich administrative matched employer-employee data from Germany, we provide empirical evidence of establishment-level adjustments that are in line with the predictions of the model. We further document that industries with more technological adoption exhibit particularly pronounced adjustment patterns along the dimensions highlighted by the model. 

We study the importance of firm sorting for spatial inequality. If productive locations are able to attract the most productive firms, then firm sorting acts as an amplifier of spatial inequality. We develop a novel model of spatial firm sorting, in which heterogeneous firms first choose a location and then hire workers in a frictional local labor market. Firms’ location choices are guided by a fundamental trade-off: Operating in productive locations increases output per worker, but sharing a labor market with other productive firms makes it hard to poach and retain workers, and hence limits firm size. We show that sorting between firms and locations is positive—i.e., more productive firms settle in more productive locations—if firm and location productivity are complements and labor market frictions are sufficiently large. We estimate our model using administrative data from Germany and find that highly productive firms indeed sort into the most productive locations. In our main application, we quantify the role of firm sorting for wage differences between East and West Germany, which reveals that firm sorting accounts for 17%-27% of the West-East wage gap.

During recessions, a larger fraction of non-employed workers actively search for a job. Simultaneously, the premium in the job-finding probability for active relative to passive search declines. I document this novel finding and show that it is symptomatic of a “crowding-out” of active search that is not accommodated under the standard approach of the literature. I estimate a declining marginal efficiency of active search, and I show that, during a recession, active search plays a less important role for finding a job. The findings emphasize the importance of the participation margin in understanding unemployment dynamics and the role of policy.

Agenda:

  • Introduction: Research projects with labor market-related topics at the BiB (including research on education, families and human potential)
  • Individual consequences of international migration across the life course / Cultural diversity in public and private labour market organisations
  • Transitions to retirement and health / Working beyond retirement age
  • Trends in working life expectancy / Regional population projections
  • A future Research Data Centre (FDZ) at the BiB

It is a pleasure for us to announce the program of the 6th User Conference of the IAB-FDZ, which will be held virtually on 21-22 November 2022.
The conference will feature sessions focusing on regional economics, human capital and the family context.

There will also be a special session dedicated to research using the LPP.

We are looking forward to two days of excellent research using IAB data, and we invite you to join us. You can register via Xing.
For more information and registration visit: https://www.xing-events.com/UserConferenceFDZ.html

We are pleased to announce the 6th user conference of the Research Data Centre (FDZ) of the Federal Agency (BA) at the Institute for Employment Research (IAB). The aim of the conference is to bring together researchers who work with the data provided by the FDZ and to promote exchange between researchers and FDZ staff. The program committee invites submissions on any topic related to labor markets using FDZ data.

This year’s conference will also host an extra session on the Linked Personnel Panel (LPP) to celebrate the 10th anniversary of the panel. Therefore, submissions relying on the LPP or LPP-ADIAB data are especially welcome.

We also plan an extra session on data from other data providers within the International Data Access Network (IDAN). Therefore, we are looking forward to submissions relying on country comparisons. 

The opening of refugee shelters is regularly met with protest from the surrounding community. Often, such opposition is driven by the fear that the presence of a shelter devalues the neighbourhood, either because of a concrete decrease in the quality of local amenities and public life, or because of neighbours and prospective residents’ prejudicial beliefs (or a combination of both). At the same time, it is unclear whether protests by individual residents reflect the preferences of the entire community, and whether fears over the arrival of refugees are held strongly enough to affect residents’ concrete decisions over where to live. In this article I combine information on property listings between 2012 and 2019 with data on all refugee accommodation facilities in Munich, Germany to examine whether the opening of a refugee shelter affects the desirability of the surrounding neighbourhood, decreasing local property prices relative to elsewhere. Results from the staggered difference-in-difference design find no evidence that the presence of a shelter impacts the value of surrounding properties, or changes the demand for or supply of local housing. Complementary survey findings suggest that increased contact may be driving this null effect: the presence of a nearby refugee shelter increases casual encounters between natives and refugees, which may reduce prior fears over refugees’ negative impact on the local community.

Recent evidence on the gender pay gap has shown that while it is narrowing for the least educated, it has remained stagnant for those with a university degree and is largest for those at the top of the earnings distribution. Attempts to explain the gap using non-cognitive traits have been limited despite a literature highlighting the fact that some of the gap may be attributable to women not “leaning in” while men are more overconfident in their abilities. We probe this hypothesis using longitudinal data from childhood into mid-career and construct a measure of overconfidence using multiple measures of objective cognitive ability and subjective estimated ability. Our measure confirms previous findings that men are more overconfident than women. We then use linear regression and decomposition techniques to account for the gender pay gap including our measure of overconfidence. Our results show that overconfidence captured in adolescence explains a significant portion of the gender wage gap at age 25, which decreases in importance by age 34 and age 42. This highlights the importance of overconfidence in helping individuals to get on a trajectory of higher earnings early in career.

We investigate the role of information frictions in the US labor market using a new nationally representative panel dataset on individuals' labor market expectations and realizations. We find that expectations about future job offers are, on average, highly predictive of actual outcomes. Despite their predictive power, however, deviations of ex post realizations from ex ante expectations are often sizable. The panel aspect of the data allows us to study how individuals update their labor market expectations in response to such shocks. We find a strong response: an individual who receives a job offer one dollar above her expectation subsequently adjusts her expectations upward by $0.47. We embed the empirical evidence on expectations and learning into a model of search on- and off- the job with learning, and show that it is far better able to fit the data on reservation wages relative to a model that assumes complete information. We use the framework to gauge the welfare costs of information frictions which arise because individuals make uninformed job acceptance decisions and find that the costs due to information frictions are sizable, but mitigated by the presence of learning.

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