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Archives: IAB-Veranstaltungen

Linked employer-employee data offer a wide range of possibilities for researchers.

Linked employer-employee data offer a wide range of possibilities for researchers. For example, this type of data is used to understand the role of worker and firm quality in the development of wage inequality, as for example in Card, Heining, Kline (2013). A widely used approach to identify worker and firm quality was developed by Abowd, Kramarz and Margolis (1999) who decomposed earnings in a worker-specific component, a firm-specific component and an error term in a two-way fixed effects model. Since then, many researchers have used the AKM model to study worker and firm heterogeneity in wages, as well as the importance of labour market sorting. While the model continues to be heavily used until today, recent developments discuss potential biases and propose corrections (for example Abowd et al, 2004; Andrews et al, 2008, 2012; Kline, Saggio, Sølvsten 2020; Bonhomme et al, 2023). The purpose of this workshop is to bring together researchers working with these models to present and discuss current work. Possible topics for the workshop are:

  • How important are worker and firm heterogeneity for the variation of wages?
  • How do wage premia differ for worker subgroups?
  • How persistent are wage premia?
  • How important is worker-firm sorting?
  • Is there assortative matching in the labour market?
  • Are there persistent penalties to working in low-quality firms?

In this conference, which will be part of a two-day celebration of the 20th anniversary of the Research Data Centre of the BA at the IAB (IAB-FDZ).

Rising costs of living and the lack of affordable housing have brought social inequalities back to the centre of political debates in many countries. Large, high quality survey and register data provide social scientists with a solid foundation to explore topics in inequality research and to gain unique and valuable insights fostering both scholarly and public discussion.

In this conference, which will be part of a two-day celebration of the 20th anniversary of the Research Data Centre of the BA at the IAB (IAB-FDZ), we bring together scholars from various disciplines to discuss their work based on IAB-FDZ data products or similar research data made available by other national or international data providers.

We invite empirical contributions on all topics addressing social inequalities connected to labour markets, demographic change, as well as occupational or educational choice. This might include (but is not limited to) effects of labour market interventions, technological change (greening economy, digitalisation, AI), voluntary and forced migration, social stratification, working and living conditions and gender topics.

Furthermore, the Journal for Labour Market Research (JLMR) plans a Special Issue celebrating 20 years of IAB-FDZ with Till von Wachter (UCLA) as guest editor. The Journal for Labour Market Research is an interdisciplinary, peer reviewed, open access journal in the field of labour market research and publishes papers in English language concerning the labour market, employment, education/training and careers (https://labourmarketresearch.springeropen.com/). All presenters are invited to submit their manuscripts emerging from the presented research to this Special Issue by December 1st, 2024. Acceptance is contingent on successful peer review.

Skills for the Future: Navigating the Digital, Green and Social Transitions in European Labour Markets is to bring together leading national and international scholars in the social sciences to address the challenges of the digital, green and social transitions for the labour market, society and education.

Organised by the Luxembourg Institute of Socio-Economic Research (LISER) and co-funded by Luxembourg’s National Research Fund (FNR), the objective of the international scientific conference Skills for the Future: Navigating the Digital, Green and Social Transitions in European Labour Markets is to bring together leading national and international scholars in the social sciences to address the challenges of the digital, green and social transitions for the labour market, society and education.

The conference marks the first international conference of the ELMI Network (Network of European Labour Market Research Institutes) initiated in October 2022 by the Luxembourg Institute of Socio-Economic Research (LISER) and the Institute for Employment Research (IAB). The network is currently composed of 11 research institutes from all over Europe to facilitate the international exchange of best practices, ideas and people. It promotes multi-disciplinary research collaborations, especially at the EU level, and the exchange of best practices in data management, data access and discussions with policy-makers and stakeholders.

Big Data and the analysis thereof is considered of increasing importance, not only for big (tech) companies.

Big Data (BD) and the analysis thereof (i.e., Big Data Analytics, BDA) is considered of increasing importance, not only for big (tech) companies but also for small/medium-sized companies and, in particular, for new ventures. Despite or precisely due to its generally presumed relevance, the question arises whether applying BDA leads to better firm performance. Based on a large, representative sample of 3,700 German start-ups, we specifically study the adoption of BDA among start-ups and analyze its economic effects using various short- and longer-term performance measures. We show that start-ups adopting BDA significantly differ from non-adopters regarding their founders' age, education, team composition, and experience. Accounting for these differences, we then investigate the effect of adopting BDA on the new ventures' operating costs, sales, profits, survival rate, and (employee) growth. Our findings show that using BDA does not lead to a competitive advantage in terms of the classical short-term performance measures but is rather associated with greater sales/profit uncertainty, higher (personnel) costs, and a higher probability of failure. Yet, the increased risk of adopting BDA is at the same time compensated by a prospect for higher excess performance -- BDA-adopting start-ups perform significantly better than their peers at the 90%-quantile -- as well as by better expected longer-term performance, as measured by the start-ups' growth and by their ability to secure Venture Capital (VC). Our findings support the concept of a few Schumpeterian Entrepreneurs who adopt technology at the frontier of innovation and found high-risk start-ups with the prospect of high rewards.

A proposal for an occupation-specific end-of-life and late-life perspective on retirees.

Retirement marks a significant life transition, signaling the end of one's active work engagement and the beginning of a new phase of life. In the best-case scenario post-retirement life is characterized by increased time spend with friends and family, and a purpose in life that is perceived as meaningful. The reduced work load should be associated with improved health, because sources of physical and psychological stress should have far less impact. However, reality paints a different picture: The research on retirement shows a lot variation in retirement experiences, financial well-being, mental and physical health, social engagement, and overall life satisfaction.
The importance of pre-retirement occupations on individuals' lives cannot be overstated. However, the impact of occupations on people’s lives does not end with their retirement. Hence, I will propose a new perspective on employment and occupations by focusing on the retirees’ late life and end of life. In my presentation I will provide the theoretical foundations, why occupations (should) have a lasting impact. I will present a data source with which such analyses could be done and discuss outcome variables of interest. Examples for occupation-specific outcomes of interest are: years of life remaining after retirement, years in good health after retirement, years spend in loneliness, wealth, poverty, depression, political attitudes, decrease in cognitive capabilities, social networks, free-time activities, volunteering, housing, life satisfaction, etc.
From a policy perspective, understanding how different occupations influence post-retirement lives can inform retirement planning initiatives and social safety nets as well as occupation-specific training and safety regulations. On an individual level, insights gained from such research can assist individuals in making informed decisions about their vocational aspirations, careers, planned changes of occupations, retirement age, and financial preparations.

The literature on alternative methods for accounting for sample-independent variability is reviewed, a typology of sources of sample-independent variation is developed, and an empirical investigation is conducted estimating the relative and absolute importance of the different types of sample-independent variation.

Empirical economics papers report standard errors to take into account uncertainty associated with sampling variation but rarely consider non-sampling variation from researcher choices about measurement of key variables, functional form choice, identification strategy, and data set. In this paper, we review the literature on alternative methods for taking account of non-sampling variability, develop a typology of sources of non-sampling variation, and conduct an empirical exercise in which we estimate the relative and absolute importance of different types of non-sampling variation. The empirical exercise proceeds in the context of the literature that seeks to estimate the causal effect of college quality on educational and labor market outcomes.

This paper analyzes the open-economy spillover effects of labor market reforms under incomplete insurance. Using microeconomic data, we document a boost in the tradable sector in the aftermath of the German Hartz IV reform. In our model, this phenomenon can be explained by an increase in household savings due to higher precautionary savings in response to the reduction in the generosity of unemployment insurance (Hartz IV). Besides reducing unemployment in the reforming country, lower unemployment benefits generate long-run negative consumption spillovers in a monetary union, which we call the dark shadow of labor market reforms. Our model can match various German trends post Hartz IV reform, such as: i) a lasting increase in net foreign asset position, ii) short-term expansion of the tradable sector relative to the non-tradable sector, and iii) continued depreciation of the real exchange rate. By contrast, simulations of German wage moderation result in qualitatively different open-economy effects that are not in line with the empirical patterns for Germany.

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.