Weiterbilden und Weiterkommen? Non-formale berufliche Weiterbildung und Arbeitsmarktmobilität in Deutschland

Politicians and the business leaders regularly stress the importance of (further) education for individual life chances. Still, it is far from clear whether non-formal further training, i.?e. short training courses, which are the most common forms of further education in Germany, lead to career advancement. In this study, we analyze the impact of non-formal further training on labor market mobility using data from the German National Educational Panel Study (NEPS) over the period from 2009 to 2016. Event history models for discrete time intervals show that employer-provided courses reduce mobility and promote career stability, which contradicts hypotheses derived from human capital theory, which is commonly used in the literature. More concretely, employer-provided courses prevent downward mobility (safety net function), but also reduce upward mobility and firm changes. Based on these findings, we suggest that future research should consider transaction costs and the firm context as well as the distinction between employer-provided and non-employer-provided training.     

Estimation of Causal Odds of Concordance using the Aalen Additive Model

A simple summary of a treatment effect is attractive, which is part of the explanation of the success of the Cox model when analysing time‐to‐event data since the relative risk measure is such a convenient summary measure. In practice, however, the Cox model may fail to give a reasonable fit, very often because of time‐changing treatment effect. The Aalen additive hazards model may be a good alternative as time‐changing effects are easily modelled within this model, but results are then evidently more complicated to communicate. In such situations, the odds of concordance measure (OC) is a convenient way of communicating results, and recently Martinussen & Pipper (2012) showed how a variant of the OC measure may be estimated based on the Aalen additive hazards model. In this study, we propose an estimator that should be preferred in observational studies as it always estimates the causal effect on the chosen scale, only assuming that there are no un‐measured confounders. The resulting estimator is shown to be consistent and asymptotically normal, and an estimator of its limiting variance is provided. Two real applications are provided.     

Health Promotion and Flexibility: Extending and Obscuring Power in Organizations

This paper explores the intersection between pursuits of improving organizational flexibility and pursuits of improving employees' health. It is argued that health promotion programmes have the potential of operating as mechanisms of power, which assist organizations in making up self-governing employees who flexibly adapt their lifestyles to the criteria of health and professional success. The paper shows how the fact that health promotion programmes are handled by 'independent' and legitimate health experts, and are provided to employees in the name of their health and well-being, obscures the forces of power in them, making them seem merely as informed ways of helping employees help themselves towards healthier and more successful lives. The paper concludes that health promotion programmes help to establish a new work ethic that challenges the boundary between work and private life. Furthermore, they make a healthy lifestyle part of the competencies that employees are responsible for developing and nurturing.     

Flexible Copula Density Estimation with Penalized Hierarchical B‐splines

The paper introduces a new method for flexible spline fitting for copula density estimation. Spline coefficients are penalized to achieve a smooth fit. To weaken the curse of dimensionality, instead of a full tensor spline basis, a reduced tensor product based on so called sparse grids (Notes Numer. Fluid Mech. Multidiscip. Des., 31, 1991, 241‐251) is used. To achieve uniform margins of the copula density, linear constraints are placed on the spline coefficients, and quadratic programming is used to fit the model. Simulations and practical examples accompany the presentation.