Einkommenseffekte beruflicher Weiterbildung

The claim for lifelong learning or vocational further training is most often set out without having clarified satisfactorily the individual gains which result from training activities. Based on human capital theory, which we extend by arguments from signaling- and game theory, the paper investigates for western and eastern Germany individual returns of training on income with longitudinal data (1996–1998) from the recently available “Mikrozensus-Panel”. A problem in identifying causal training effects is a selection bias caused by unobserved heterogeneity which – using conventional methods – leads to overestimation of the effects. Fixed- and Random-Effects-Models – which we discuss and confront empirically regarding the training issue – present a method for controlling the selection bias. The results show evidence for positive and significant training effects on income, although the actual amount of income growth is low. Whereas no differences by sex were found, separate analyses by age, skill levels and region indicate that not all of the subgroups benefit positively from further training activities. Therefore, the findings relativize the importance of social inequalities in the access to further training for the process of status attainment in general.     

Some coverage error models for census data

"Alternative models are presented for representing coverage error in surveys and censuses of human populations. The models are related to the capture-recapture models used in wildlife applications and to the dual-system models employed in the vital events literature. Estimation methodologies are discussed for one of the coverage error models." After a discussion of the theory underlying the methodology, "distinctions are made between two kinds of error: (a) sampling error and (b) error associated with the model. An example involving data from the 1980 U.S. census is presented. The problem of adjusting census and survey data for coverage error is also discussed."     

The drivers of work engagement: A meta-analytic review of longitudinal evidence

ABSTRACT

Work engagement is currently one of the most popular outcomes in occupational health psychology. According to the motivational process within the job demands-resources (JD-R) framework, job resources stimulate work engagement, which in turn fosters job performance. While the general positive impact of job resources on work engagement is well established, it remains unclear how different types of job resources differentially predict work engagement over time. In our meta-analytic review, we identified 55 longitudinal studies that investigate the impact of various job resources on work engagement. To uncover the drivers of work engagement, we examined the differential impact of job resources on work engagement at group level, leader level, and organisational level via meta-analytic structural equation modelling. The findings suggest that job resources at each of the three levels predict work engagement over time. However, organisational-level resources (reflecting how the work is organised, designed and managed) contribute much more strongly to work engagement than group-level, and leader-level resources. All three levels of job resources and work engagement are highly stable. We advocate for interventions at any of the three levels. However, interventions at the organisational-level are most promising for enhancing work engagement and we thus strongly recommend strengthening those job resources.     

A Probabilistic Approach for Deriving Acceptable Human Intake Limits and Human Health Risks from Toxicological Studies: General Framework

The use of uncertainty factors in the standard method for deriving acceptable intake or exposure limits for humans, such as the Reference Dose (RfD), may be viewed as a conservative method of taking various uncertainties into account. As an obvious alternative, the use of uncertainty distributions instead of uncertainty factors is gaining attention. This paper presents a comprehensive discussion of a general framework that quantifies both the uncertainties in the no-adverse-effect level in the animal (using a benchmark-like approach) and the uncertainties in the various extrapolation steps involved (using uncertainty distributions). This approach results in an uncertainty distribution for the no-adverse-effect level in the sensitive human subpopulation, reflecting the overall scientific uncertainty associated with that level. A lower percentile of this distribution may be regarded as an acceptable exposure limit (e.g., RfD) that takes account of the various uncertainties in a nonconservative fashion. The same methodology may also be used as a tool to derive a distribution for possible human health effects at a given exposure level. We argue that in a probabilistic approach the uncertainty in the estimated no-adverse-effect-level in the animal should be explicitly taken into account. Not only is this source of uncertainty too large to be ignored, it also has repercussions for the quantification of the other uncertainty distributions.     

Restructuring for import competition from developing countries,II: The case of the Federal Republic of Germany

Assistance legislation in Germany is not viewed as being effective because imports seem to be an interior source of displacement compared to productivity change and are not therefore the prime cause of adjustment difficulties. Moreover, programs aimed at specific individual industries do not seem warranted, as they operate to delay necessary restructuring, can easily turn into disguised or open protection, discriminate against the rest of the economy, and provoke retaliatory measures abroad.     

Parental unemployment and child health in China

This paper studies the causal effect of maternal and paternal unemployment on child health in China, analyzing panel data for the period 1997–2004, when the country underwent economic reforms leading to massive layoffs. Using a FE-IV strategy, we find that paternal unemployment reduces child health, while maternal unemployment has beneficial child health impacts. Analysis of channels shows that paternal and maternal unemployment have different effects on income, time use, and children’s diets. Though many estimates are imprecise, a key finding is that paternal unemployment significantly reduces children’s fat intake and dietary diversity. To the best of our knowledge, this is the first evidence on the causal effect of parental unemployment on the nutrient intake of children aged 0–17. In all, our estimates are consistent with the notion that traditional gender roles can explain why mothers’ and fathers’ unemployment affect child health differently.

     

An Empirical Analysis of the Decision to Train Apprentices

Abstract. It is a widely held belief that apprenticeship training represents a net investment for training firms, the cost of which needs to be recouped after the training period. A new firm‐level data set for Switzerland reveals large variation in net costs across firms and, remarkably, negative net costs for 60 per cent of all firms. We use these data to estimate the effect of net costs on the number of apprentices hired by a firm. The results show that the costs have a significant impact on the training decision but no significant influence on the number of apprentices, once the firm has decided to train. For policy purposes, these results indicate that subsidies for firms that already train apprentices would not boost the number of available training places.     

An Adversarial Risk Analysis Framework for Cybersecurity

Risk analysis is an essential methodology for cybersecurity as it allows organizations to deal with cyber threats potentially affecting them, prioritize the defense of their assets, and decide what security controls should be implemented. Many risk analysis methods are present in cybersecurity models, compliance frameworks, and international standards. However, most of them employ risk matrices, which suffer shortcomings that may lead to suboptimal resource allocations. We propose a comprehensive framework for cybersecurity risk analysis, covering the presence of both intentional and nonintentional threats and the use of insurance as part of the security portfolio. A simplified case study illustrates the proposed framework, serving as template for more complex problems.     

Statistics in the High School Curriculum

Recent work, spearheaded by Charles Dunnett (1980a), leads to the conclusion that the Tukey-Kramer (TK) method (popularly known as “Kramer's Method”) is the recommended multiple comparisons procedure for the simultaneous estimation of all pairwise differences of means in an imbalanced one-way ANOVA design with homogeneous variances. Nine other multiple comparisons methods are compared to each other and to the TK method using the criteria of conservativeness, narrowness of confidence intervals, robustness, and ease of use. The degree of superiority of the TK method over these methods, especially over the popular Bonferroni method, is sufficient to warrant recommending its use. Because of the lack of robustness of the TK method in heterogeneous variance cases, other methods are recommended.