ESRA 2017 Programme

Tuesday 18th July      Wednesday 19th July      Thursday 20th July      Friday 21th July     

     ESRA Conference App

Wednesday 19th July, 09:00 - 10:30 Room: F2 104

Life course research 1

Chair Ms Katharina Burgdorf (University of Mannheim )

Session Details

Paper Details

1. Explaining Scientists’ Plans for International Mobility from a Life Course Perspective
Mr Nicolai Netz (DZHW)
Mr Steffen Jaksztat (DZHW)

We identify factors influencing young scientists’ plans for research stays abroad by embedding theories of social inequality, educational decision making, and migration into a life course framework.
We test the developed model of international academic mobility using cross-sectional data from an online survey of scientists employed at German universities below the rank of full professor (WiNbus). This survey placed special emphasis on the international orientation and mobility of young scientists and therefore allows us to adequately operationalise our theoretical constructs.
We test our theoretical model by calculating a structural equation model (SEM). In contrast to conventional regression procedures, an SEM allows us to easily observe both the direct and indirect effects of certain variables and to estimate their total effect on the likelihood of planning a research stay abroad. It additionally allows us to examine how well our theoretical model fits the examined survey data. This method thus permits us to test the developed life course model of international academic mobility on the whole.
Our results show that that earlier international mobility mobilises scientists to plan a research stay abroad. This turns out to be a potential channel of social inequality reproduction, as individuals from a high social origin in particular spend time abroad in their early life course. Moreover, scientists’ research contexts play a vital role: Internationalised institutional environments and academic disciplines as well as the embeddedness in personal international networks create opportunity structures that ease research stays abroad. Similarly, the current social context matters: Parenthood decreases the likelihood of plans for international mobility among female scientists. This may entail long-lasting gender inequalities. Finally, young scientists striving for an academic career are more likely to plan a research stay abroad than those with exit plans.
On a broader theoretical level, our results back the view that the decision to become internationally mobile is the consequence of a succession of events and decisions over time rather than the outcome of a conscious deliberation at a single point in time. Beyond the current context, both past life events and future life goals shape scientists’ decisions about international mobility.

2. Optimal duration of participation in a job training program that promotes positive youth development
Dr Youngjo Im (University of Chicago)
Dr Ming-Long Lam (SAS Institute & University of Chicago)

This project seeks to contribute to an understanding of how youth development programs can be improved to better support youth ages 16 to 24 who are disconnected, that is, who are neither enrolled in school nor participating in the U.S. labor market. To achieve this goal, the project re-analyzes data from the National Job Corps Study, funded by the U.S. Department of Labor and carried out by Mathematica from 1994 to mid-2003. Job Corps is the nation’s largest, most comprehensive education and job training program for disadvantaged youth, primarily in a residential setting.

Job Corps has a distinctive open-entry, open-exit educational philosophy, where instruction is individualized and self-paced. Because the enrollment in Job Corps does not require a fixed duration, participants enroll for different lengths of time. We hypothesize that this heterogeneous duration of stay may lead to heterogeneous treatment effects. More generally, we would expect program impact on outcome to vary with different length of stay. Unlike prior evaluation research based on average length of stay, we consider the different duration of stay in the program as a potential mechanism that explains the link between program effect and youth outcome.

Our analysis includes two main steps. In the first, we separate the length of stay into a number of different parts by employing data mining technique: regression tree. In the second stage of our analysis, we evaluate the main effect of length of stay, and interaction effects between length of stay and subdivided length of stay, controlling for demographic information and classes taken by participants. In doing so, we construct Generalized Linear Models under Poisson and gamma distributions by utilizing high performance analytical procedure: hpgenselect.

In support of our hypothesis, results indicate that length of stay plays a key role in determining the program effect on youth outcome. Our piecewise interaction effects provide evidence that five comparted length of stay has differential effects on youth outcome. The optimal length of stay that leads to higher earnings is 6-8 months, whereas 8-14 months of stay leads to a decrease in criminal behavior. Finally, staying in a program less than 2 months is linked to unfavorable employment and crime outcomes. This project therefore provides a unique opportunity to assess the Job Corps experience as a turning point, highlighting the possibility of overcoming prior disadvantages, in the life course of disadvantaged youth.

3. Well-being over the Life Course: Analytical Strategies, Explaining Mechanisms and Evidence from Germany
Dr Fabian Kratz (LMU Munich)
Professor Josef Brüderl (LMU Munich)

1 Introduction
While previous research investigating well-being over the life course has reported mixed empirical evidence, the role of methodology in producing these divergent findings has remained largely unexplored. This contribution examines the questions of (1) which potential methodological pitfalls exist when estimating age well-being trajectories (2) what is the correct analytical strategy (3) which intervening mediating mechanisms explain the age well-being trajectory and (4) which methodological fallacies have produced the mixed evidence.

2 Previous literature
Some studies find that well-being remains fairly stable with rising age (e.g. Lykken/Tellegen 1996; Kurland et al. 2006). Other studies report a decrease (e.g. Gerstorf et al. 2010; Kassenboehmer/Haisken-DeNew 2012) while some report an increase (e.g. Yang 2008; Sutin et al. 2013). The most prominent finding by now appears to be a U-shape in happiness (e.g. Blanchflower/Oswald 2008; Weiß et al. 2012). But there are also studies reporting an inverse U-shape (Easterlin 2006; Glenn 2009). Recent panel studies report curvilinear relationships with different periods of well-being over the life course (e.g. Baird et al. 2010; Gwozdz/Sousa-Poza 2010; Frijters/Beatton 2012; Wunder et al. 2013).

3 Data, Measures and Methods
We employ data from the German Socio-Economic Panel Study (GSOEP v29) covering the years of 1984 to 2012 (Wagner, Frick, and Schupp 2007). We restrict the sample to person-years with information on life satisfaction in the age range 18–90 and draw on a sample of 470,022 person-years stemming from 57,758 persons.
Dependent variables: Well-being is measured by answers to the following question: “How satisfied are you currently, all in all, with your life?” Respondents answered this question on a scale ranging from 0 to 10, where 0 denotes ‘completely dissatisfied’ and 10 means ‘completely satisfied’.
Explanatory variables: We capture each age year by a dummy variable. This approach enables us to identify several turning points or discontinuities in the development of inequality in well-being over the life course and to avoid committing the pitfall of predetermining our results by simply imposing a specific functional form.
To answer our research questions we estimate what we consider the correct analytical strategy—hierarchically nested fixed effects growth curve models (FE)—and contrast the results to other approaches in the literature.

4 Results and Conclusions
Our results are consistent with the notion that rising age brings about physical and social losses and these losses cause a decrease in well-being. The most important mechanisms in explaining decreasing life satisfaction is declining health. We further show that the most prominent finding in the literature, namely a U-shaped age well-being profile, is a result of diverse methodological pitfalls.