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Job retention schemes (Kurzarbeit) have been a key policy tools to contain the employment and social fallout of the COVID-19 crisis in a number of OECD countries. By May 2020, job retention schemes supported about 50 million jobs across the OECD, about ten times as many as during the global financial crisis of 2008-09.

The schemes prevented a surge in unemployment, mitigated financial hardship and stabilized demand. However, as the COVID-19 crisis moved into its second wave, deeper structural changes are becoming more likely. Job retention schemes should respond to this new situation, become more targeted and attention should shift towards supporting workers, rather than their jobs.

Based on an OECD policy brief, this online Seminar will give an overview on the use of job retention schemes in OECD countries and discuss in detail the schemes in France, Germany and the Netherlands.

The Institute of Employment Research (IAB), the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), and the Labour and Socio-Economic Research Center (LASER) are pleased to announce a workshop on machine learning in economics. Empirical research in economics typically focuses on the unbiased estimation of causal effects. In contrast, statistics and computer science place more value on prediction (especially out-of-sample) and data-driven selection of models and variables. So far, only few studies apply these methods in empirical economic research, but their importance is growing. This holds in particular with the increasing availability of big data for economic research. The two-day workshop seeks to bring together researchers who apply machine learning methods in the following fields: Labor economics, economics of education and health economics.

Aims and Topics

During Germany’s EU Council Presidency in 2020, the Institute for Employment Research (IAB) will host an interdisciplinary labour market conference. This conference will focus on labour market transitions and on the evaluation of policies that governments implement to smooth such transitions.

Collection of abstracts (Abstracts der Vorträge)

Programme highlights

The conference features keynotes by Jutta Allmendinger, President of the WZB Berlin Social Science Center and Professor of Educational Sociology and Labour Market Research at the Humboldt University Berlin, and Christian Dustmann, Professor of Economics at the University College London and Director of CReAM – Centre for Research and Analysis of Migration. Two other keynotes will be presented by Dennis Radtke, Member of the European Parliament, and Prof László Andor (PhD) of Corvinus University of Budapest and former EU Commissioner for Employment, Social Affairs and Inclusion. The conference also includes a political key note and a panel discussion with Dr Nicola Brandt, Head of OECD Berlin Centre, Christian Dustmann und Bernd Fitzenberger, Director of IAB and Professor of Econometrics at the Humboldt University Berlin about “Vocational Training and labor market transitions: The future model for Europe?”

We estimate heterogeneous returns to a STEM education in Switzerland based on individual-level data, exploiting the regional distribution of relative distances to technical and cantonal universities as a cost factor driving college major choice.

Overall, individuals strongly gain in terms of earnings by graduating from a STEM major, with equally large effects for men and women. Ascending Marginal Treatment Effect curves suggest heterogeneous returns while inverse selection on gains implies that individuals with a higher resistance for a STEM education gain the most, where the latter emerges stronger for men. Eventually, we utilize the recent formation of the University of Lucerne, changing relative distances, to estimate the policy-relevant treatment effect for a counterfactual scenario that this university had been established as a technical one: people shifted into a STEM education significantly gain in terms of earnings, with stronger effects for men.

This paper studies the adoption of local preferences and norms by refugees over time. Exploiting plausibly exogenous variation in the allocation of refugees across German regions between 2013 and 2018, we examine the path of their convergence towards local culture in the short-run. We assemble a novel data set on values, habits, and preferences for 8,000 refugees, and combine it with information on more than 34,000 locals. We find strong evidence that refugees converge to local culture, closing the gap by 5% every year. This effect is stronger for regions whose culture is more distinct from the national one and more internally homogeneous. We also provide evidence that refugees' cultural convergence is faster where support for anti-immigrant parties is stronger, where there are more hate-crimes against refugees, and where locals are less open to diversity - patterns consistent with what we label the ``threat hypothesis''. Despite the positive effect of a threatening environment on the pace of refugees' cultural convergence, we document that the former slows down their economic integration.

The California Policy Lab (CPL) is part of a growing number of research centers in the United States that do applied economic research in partnership with local or state government agencies. The goals of such long-term research partnerships is to work on problems that are directly policy relevant, help implement relevant findings, and integrate administrative data that otherwise would be difficult to access. The presentation reviews CPL’s approach to government partnerships and reviews examples of joint research projects, including nudge experiments, predictive work on homelessness, COVID-19 related projects, with particular focus on studies of unemployment insurance benefits

Employment and Social Developments in Europe (ESDE) 2020: “Leaving no one behind and striving for more: fairness and solidarity in the European social market economy”

The review provides evidence-based analysis on how to achieve greater fairness across the EU in the face of crises such as the COVID-19 pandemic and of long-term challenges arising from structural change due to demographic ageing, climate change and digitalisation.

The COVID-19 pandemic is having profound health, economic, employment and social effects, hitting society’s most vulnerable disproportionately hard and threatening much of the progress that the EU had achieved previously in labour markets and social outcomes. Against this background, this year’s ESDE analyses the state of play of and challenges to social fairness and inclusivity of growth in the EU. It also explores specific policies and tools that can improve the prospects of greater social fairness and enhanced solidarity in the future. ESDE provides evidence-based groundwork for the reflection on how policy can help achieve recovery and further normalisation while meeting Europeans’ expectations regarding fairness and solidarity.

We analyze workers' risk preferences and training investments. Our conceptual framework differentiates between the investment risk and insurance mechanisms underpinning training decisions. Investment risk leads risk-averse workers to train less; they undertake more training if it insures them against future losses. We use the German Socioeconomic Panel (SOEP) to demonstrate that risk-affinity is associated with more training, implying that, on average, investment risks dominate the insurance benefits of training. Crucially, this relationship is evident only for general training; there is no relationship between risk attitudes and specific training. Thus, as expected, risk preferences matter more when skills are transferable - and workers have a vested interest in training outcomes - than when they are not. Finally, we provide evidence that the insurance benefits of training are concentrated among workers with uncertain employment relationships or limited access to public insurance schemes.

The wage gap between newly arriving immigrants and comparable natives in the United States has widened substantially over the last few decades while the subsequent speed of convergence has declined. These patterns have led to a pessimistic view regarding wage assimilation prospects of immigrants. This paper unravels an unexplored mechanism that can explain an important part of these regularities: labor market competition. Because immigrants and natives are imperfect substitutes in production, increasing immigrant inflows exert stronger labor market competition on previous cohorts of immigrants than on natives, contributing to a widening wage gap. We quantify the importance of this mechanism using a model that accounts for the main features of the literatures on the wage impact of immigration and immigrant wage assimilation. Our results suggest that, if competition and composition effects are netted out, immigrant cohorts are more positively selected in recent decades, with these differences disappearing after 10 years, implying a lower relative wage growth for recent cohorts.

In this paper, we investigate wage losses from displacement in the manufacturing sector. We start by documenting that manufacturing firms traditionally employed low- and high-wage workers (measured as an AKM worker fixed effect) in similar proportions and paid substantial wage premiums (measured as an AKM firm fixed effect) to both types of workers. Over time, manufacturing jobs disproportionally disappeared over time, particularly so for low wage workers. We find that even though low and high wage workers suffer similar wage losses upon displacement on average, low wage workers experience substantially larger losses in their firm wage premiums, in part because they are more likely to move out of manufacturing and into low knowledge service sectors where firm wage premiums are low. Wage losses and losses in firm wage premiums upon displacement have increased over time especially for low wage workers, in part because low wage workers are increasingly re-employed in low knowledge service jobs.