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Veranstaltungsreihe: IAB-Colloquium (en)

The discussion series “Labour Market and Occupational Research (IAB-Colloquium zur Arbeitsmarkt- und Berufsforschung)” is a forum where primarily external researchers present the results of their work and discuss these with experts from IAB. Practitioners from the political, administrative and business fields are naturally also welcome.

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.

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.

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).

Often asked questions concerning business surveys are:

  • What will be the increase in response rates if we apply such-and-such measure(s)?
  • What would be perfect timing for these measures? And,
  • What will be the costs?

Basically these questions ask for an efficient strategy to get response, aiming for a cost-efficient survey design both for the survey organisation (like a National Statistical Institute) and businesses alike, not burdening and chasing businesses too much. The effects of measures to get response for business surveys have not been studied systematically as much as for social surveys. Obvious reasons for this may be the fact that business surveys are mandatory by law, and the costs involved in getting response are not as
high as for social surveys using CAPI or CATI. Nowadays however, with ever decreasing budgets, and the pressure to reduce response burden even more efficient business surveys designs are required. An overview of various measures has been presented by Snijkers et al. (2013), but quantitative information to answer the above mentioned questions was to a large extend still lacking. In a study conducted at Statistics Netherlands (Snijkers et al., 2018) the effects of various measures to get response have been analysed for a number of business surveys, without doing an experiment. These measures include the obvious measures, like sending advance letters to
businesses introducing the survey and soliciting survey response, sending pre-due data reminders, and after the due date sending one or more reminder letters. For one survey (the Survey on International Trade in Goods) we modelled the effects of these measures using survival analysis, to find out what would have happened without any of these measures. At the
lecture the results will be presented.

Almost eight million forced migrants arrived in West Germany after WWII. We study empirically how regional conditions affected their economic, social and political integration. We first document large cross-regional differences in integration outcomes. We then show that high inflows of migrants and a large agrarian base hampered integration. Religious differences between migrants and natives had no effect on economic integration. Yet, they decreased intermarriage rates and strengthened anti-migrant parties. Based on our estimates, we simulate the regional distribution of migrants that maximizes their labor force participation. Inner-German migration in the 1950s brought the actual distribution closer to its optimum.

While R&D tax credits appear to increase R&D expenditures, how they change search strategies and impact private and public value creation remains less clear. We develop a simple model that predicts a stronger focus on exploitation, due to increased opportunity costs and the need to generate profit in order to take the credit. We empirically validate greater exploitation for firms in states that offered credits, and illustrate further implications including increased defensive patenting, decreased new market entry, an increase in valuation, and increased markups and profit margins. Technologically close industry peers exhibit a decrease in valuation. We provide evidence that the subsequent introduction of R&D tax credits in other states had qualitatively similar, although quantitatively smaller, effects. Our results indicate that although R&D tax credits create value, they also have unintended consequences.

In light of the debate over inclusive education, this paper evaluates the impact of exposure to special needs (SN) peers. More classroom peers with SN lower performance, the probability of entering postcompulsory education, and earnings at ages 17-25. SN students and students at the lower end of the achievement distribution suffer most from higher inclusion. We analyze reallocation policies and government interventions to alleviate negative externalities. We demonstrate that inclusion is preferable to segregation in terms of maximizing average test scores and that teacher quality is key to alleviating negative classroom externalities, while financial resources are not.

We present evidence on the employment outcomes among refugees who obtained legal access to the Austrian labour market between 2001 and 2017. The analyses are based on comprehensive administrative data sets from Austrian social security registers matched to process-based data from the Public Employment Service. We focus on prime-working age refugees from 31 origin countries. Our presentation will elaborate on three factors related to differential employment outcomes: The role of the education attained in the source country, the role of source country characteristics, and the length of the asylum proceedings. We find that higher levels of education are not associated with better employment outcomes. Instead, we find higher educated male refugees to be less successful on the Austrian labour market compared to their counterparts with compulsory education. This pattern of findings holds across different source countries. Moreover, there is some evidence that female refugees from countries with a low rate of female labour force participation (proxy for gender culture) are less likely to enter the host labour market. We also find that the length of the asylum proceedings is positively related to employment outcomes following legal labour market access. Related employment gaps, which are robust to various specifications and outcome measures, are larger among men than among women.

Replicability is at the core of the scientific enterprise. In the past 30 years, recurring concerns about the extent of replicability (or lack thereof) of the research in various disciplines have surfaced, including in economics.

In this talk, I describe the context in which the current discussion in the social science is occurring: what are the definitions of replicability and reproducibility, what is failing, and to what extent. In particular, I discuss the concerns in economics: to what extent is this a problem in economics, what are the approaches that are being considered, and what are the possible broader implications of those approaches. Finally, I discuss the concrete measures that are being implemented under my guidance at the American Economic Association, and that are being discussed in the broader economics community.

The solutions to these problems will change the way research will be taught and conducted, in economics in particular, and in the social sciences more broadly. The implications affect undergraduate and graduate teaching, research infrastructure, and habits.

About 1.4 million refugees and irregular migrants arrived in Europe in 2015 and 2016. We model how refugees and irregular migrants are self-selected. Using unique datasets from the International Organization for Migration and Gallup World Polls, we provide the first large-scale evidence on reasons to emigrate, and the self-selection and sorting of refugees and irregular migrants for multiple origin and destination countries. Refugees and female irregular migrants are positively self-selected with respect to education, while male irregular migrants are not. We also find that both male and female migrants from major conflict countries are positively self-selected in terms of their predicted income. For countries with minor or no conflict, migrant and non-migrant men do not differ in terms of their income distribution. We also analyze how border controls affect destination country choice.