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Recent studies have proposed causal machine learning (CML) methods to estimate conditional average treatment effects (CATEs). In this study, I investigate whether CML methods add value compared to conventional CATE estimators by re-evaluating Connecticut’s Jobs First welfare experiment. This experiment entails a mix of positive and negative work incentives. Previous studies show that it is hard to tackle the effect heterogeneity of Jobs First by means of CATEs. I report evidence that CML methods can provide support for the theoretical labor supply predictions. Furthermore, I document reasons why some conventional CATE estimators fail and discuss the limitations of CML methods.

The presentation is about the nature and how to clean errors in occupational coding in order to measure patterns of occupational mobility (US, UK and Canada). Furthermore it is shed light on how occupational mobility matters for cyclical earnings inequality (based on Carrillo-Tudela, Visschers and Wiczer, 2019), unemployment and its duration distribution (based on Carrillo-Tudela and Visschers, 2019) and cleansing and sullying effects of the business cycle (based on Carrillo-Tudela, Sumerfield and Visschers, 2019).

Starting with a comparison between the life-course approach and Bourdieu, the study focuses the relation between social origin and habitus on typical patterns of education- and employment trajectories. Therefore, it tries to provide a test of the social reproduction theory of Pierre Bourdieu using a subsample of longitudinal data from the adult cohort of the German National Educational Panel Study (NEPS). Theoretically, we assume that the social class of one’s origin-family defines the process of socialization and hence the habitus of its members and is cumulative predictive for the generalizable patterns of educational- and employment sequences starting with school entry up to age 30. The individual or class-specific habitus as a “whole set of practices (or those of a whole set of agents produced by similar conditions)” (Bourdieu 1984:170) should hence correspond to differences in successful sequence-patterns, measured personality-traits and attitudes suggesting a stable class-specific realization of the habitus.

This talk will summarize two studies, which respectively study the role of caseworkers and public employment services for the labor market outcomes of unemployment benefit recipients. A first study asks whether and how much caseworkers matter for the outcomes of unemployed individuals. It exploits exogenous variation in unplanned absences among Swiss unemployment insurance caseworkers. A second study evaluates a large-scale policy change in which the public employment service of one Swiss canton changed its strategy by removing restrictions on job search and granting increased autonomy to job seekers.

The Luxembourg Institute of Socio-Economic Research (LISER) and the Institute for Employment Research (IAB) are pleased to announce the 1st LISER-IAB Conference on Digital Transformation and the Future of Work. The objective of the conference is to bring together researchers in social sciences to discuss their more recent research related to digital transformation and the future of work. Researchers interested in presenting at the LISER-IAB conference are invited to submit theoretical, empirical and experimental contributions.

Is corona the great leveller? Rich or poor, everyone can get sick from the virus. The measures to deal with the pandemic affect everyone equally: We all wear masks and the lockdown banishes us all to our homes. Or is corona an amplifier of existing and a cause for new inequalities? Important social and economic resources for coping with burdens, economic risks and availability of support by the welfare state are unequally distributed.

At the same time, new and old social divides are breaking open: Parents, especially working parents, face a particular burden in view of the closures of schools and childcare facilities and must often take over the schooling and care of children themselves. Also, people in large cities might be more affected by the crisis than people outside metropolitan areas. But the crisis also contributes to inequalities directly in the labor market: Many of the workers affected by the closures are found in the food service and personal services industries. But those particularly affected also include already disadvantaged groups such as temporary and marginal workers, who are more often in danger of losing their jobs and have less access to social protection. Low-income earners and people living in poverty may suffer particularly from the restrictions, as they have significantly fewer resources to cope with stress or deal with new challenges like home schooling. They may even be hit more often directly by the virus if they have to economize on personal protective measures. Similarly, self-employed face also specific challenges as they have often limited funding and assistance programs were not tailored to this group. At the same time, international comparisons reveal differences – not only are countries affected by the pandemic to varying degrees, but the economic and social consequences are also uneven. This raises the question of the role of social security systems and the labor market and economic policy responses.

Shortly after the pandemic, many researchers turned their attention to such and similar questions, and initial results were available in a short time. After a year of research, however, it is also clear that the observed effects of the crisis are not always uniform, but can differ significantly by the dimensions of inequality under study, by country, and also among different groups of people. In addition, aspects of data collection or measurement and the resulting possibilities for analysis are also likely to play a role. Against this background, this seminar series aims to bring together empirically rigorous contributions from the fields of sociology, economics and related fields on issues of social policy, social ad economic inequality following the Corona Crisis.

The conference focuses on technology, trade, and demographic changes and the ways they interact with employment, wages, and participation in the labor market, with a particular emphasis on the role of institutions. Understanding these relationships is key in assessing the performance of the labor market and for the design of effective labor market policies.

The conference will also host the 6th user conference of the Research Data Centre (FDZ) of the Federal Employment Agency (BA) at the Institute for Employment Research (IAB), bringing together researchers who work with the data provided by the FDZ, and facilitating exchange between researchers and FDZ staff.