Helge Pross-Preis 2007 der Universität Siegen an Cornelia Helfferich

Ohne Zusammenfassung     

Superior Sporting Performance in Athletics: Determinants and Sustainability

The article aims to contribute to the understanding of competitive dynamics and specialization in international sport by analyzing superior sporting performance (SSP) in international athletics in the period from 1999 to 2018. By applying iterative Kolmogorov‐Smirnov tests to annual bests, the study examines national SSPs. Contrary to theoretical considerations, less specialized countries are more likely to achieve SSP. Technical entry barriers and macrosocial factors also appear to play a limited role. SSP seems not to disappear due to increased international competition. The United States and Russia are identified as “sporting super powers,” able to persistently dominate a number of disciplines. The case of Russia poses fundamental questions concerning market distortions in international sport resulting from doping. The results come with substantial policy implications.     

Mixing Bismarck and child pension systems: an optimum taxation approach

Pensions with a strong tax–benefit link (Bismarck pensions) minimise the labour–leisure distortion of the public pension system. By contrast, pensions with a strong link of benefits to the number of children (child pensions) minimise the fertility distortion. When both types of distortion are present, we obtain a Corlett–Hague result regarding the optimal mix of the two pension formulae: the Bismack pension should be given a positive weight if and only if children are more complementary to leisure than consumption. Alternative fertility instruments such as child benefits turn out to be perfect substitutes to a child pension.     

Zu den Auswirkungen von Arbeitszeitmodellen im ärztlichen Dienst von Krankenhäusern

In 2004 a new working time law for physicians in hospitals was introduced, which has up until now been rarely researched in theory and is implemented in practice partially in form of new working time models, partially by relying on allowed variation rules within the law. Meanwhile, there are new discussions about changes of working time directives on the European level. This article aims to analyze the desired effects of the new working time law to decrease the workload, improve the possibilities of patient care and increase the working time satisfaction of physicians. To this end, a primary data collection is conducted in 15 hospitals and 35 hospital departments, generating 261 questionnaires, in order to empirically assess the theoretical model with the constructs working time model, workload, working time satisfaction, and possibilities of patient care using regression analyses. It can be shown that the new working time models decrease workload and enhance working time satisfaction of hospital physicians, but have no significant influence on the possibilities of patient care. These results are consistent for different ownerships and sizes of hospitals as well as for most services. No significant differences in the answers between various physician groups exist either.     

Rank covariance matrix estimation of a partially known covariance matrix

Classical multivariate methods are often based on the sample covariance matrix, which is very sensitive to outlying observations. One alternative to the covariance matrix is the affine equivariant rank covariance matrix (RCM) that has been studied in Visuri et al. [2003. Affine equivariant multivariate rank methods. J. Statist. Plann. Inference 114, 161–185]. In this article we assume that the covariance matrix is partially known and study how to estimate the corresponding RCM. We use the properties that the RCM is affine equivariant and that the RCM is proportional to the inverse of the regular covariance matrix, and hence reduce the problem of estimating the original RCM to estimating marginal rank covariance matrices. This is a great computational advantage when the dimension of the original data vector is large.     

Elicitation of Expert Judgments of Uncertainty in the Risk Assessment of Herbicide-Tolerant Oilseed Crops

One of the lay public's concerns about genetically modified (GM) organisms (GMO) and related emerging technologies is that not all the important risks are evaluated or even identified yet--and that ignorance of the unanticipated risks could lead to severe environmental or public health consequences. To some degree, even the scientists who participated in the analysis of the risks from GMOs (arguably the people most qualified to critique these analyses) share some of this concern. To formally explore the uncertainty in the risk assessment of a GM crop, we conducted detailed interviews of seven leading experts on GM oilseed crops to obtain qualitative and quantitative information on their understanding of the uncertainties associated with the risks to agriculture from GM oilseed crops (canola or rapeseed). The results of these elicitations revealed three issues of potential concern that are currently left outside the scope of risk assessments. These are (1) the potential loss of the agronomic and environmental benefits of glyphosate (a herbicide widely used in no-till agriculture) due to the combined problems of glyphosate-tolerant canola and wheat volunteer plants, (2) the growing problem of seed lot contamination, and (3) the potential market impacts. The elicitations also identified two areas where knowledge is insufficient. These are: the occurrence of hybridization between canola and wild relatives and the ability of the hybrids to perpetuate themselves in nature, and the fate of the herbicide-tolerance genes in soil and their interaction with soil microfauna and -flora. The methodological contribution of this work is a formal approach to analyzing the uncertainty surrounding complex problems.