Population growth and economic development

The paper deals with the relationship between the population growth and economic development in Yugoslavia and its republics, covering the period after the Second World War. Yugoslavia is a developing country with a specific demographic and economic structure which makes her unique in Europe. Its territory is comprised of both relatively developed regions where demographic transition is over, and underdeveloped regions with high natural increase of population where the demographic transition is only just beginning. Correlation and regression methods were used to quantify this relationship. The economic development and structural changes are discussed, relating to human factor. An adequate population policy through family planning is stressed as important in obtaining an increased return to scale with a more positive role of demographic factor.     

Introvision in der Arbeitsvermittlung für Fallmanager und Arbeitslose

In the context of a pilot study the effects of the educational-psychological intervention Introvision were tested with older long-term unemployed people. The project was accomplished in the time by 1.4.2010 to 31.12.2010 in co-operation between ARGE Paderborn and the research group Introvision. In the context of the project 16 employees of ARGE Paderborn participated in an advanced training to Introvision, 31 customers of ARGE Paderborn began a coaching to get introduction in Introvision and 20 have also finished. Nine customers decided to participate five individual coachings. The results show, that the offers have a high individual use for the participants. To the central changes belong improved handling of stress, decrease of social isolation, improved (self-) perception as well as a higher self-confidence and a more open co-operation between customers and employees of ARGE Paderborn. Besides four participation began a job on the first labour market and two could be connected to a honorary activity.     

Data-driven Kriging models based on FANOVA-decomposition

Kriging models have been widely used in computer experiments for the analysis of time-consuming computer codes. Based on kernels, they are flexible and can be tuned to many situations. In this paper, we construct kernels that reproduce the computer code complexity by mimicking its interaction structure. While the standard tensor-product kernel implicitly assumes that all interactions are active, the new kernels are suited for a general interaction structure, and will take advantage of the absence of interaction between some inputs. The methodology is twofold. First, the interaction structure is estimated from the data, using a first initial standard Kriging model, and represented by a so-called FANOVA graph. New FANOVA-based sensitivity indices are introduced to detect active interactions. Then this graph is used to derive the form of the kernel, and the corresponding Kriging model is estimated by maximum likelihood. The performance of the overall procedure is illustrated by several 3-dimensional and 6-dimensional simulated and real examples. A substantial improvement is observed when the computer code has a relatively high level of complexity.     

Inference for $$L_2$$L2 -Boosting

We propose a statistical inference framework for the component-wise functional gradient descent algorithm (CFGD) under normality assumption for model errors, also known as $$L_2$$-Boosting. The CFGD is one of the most versatile tools to analyze data, because it scales well to high-dimensional data sets, allows for a very flexible definition of additive regression models and incorporates inbuilt variable selection. Due to the variable selection, we build on recent proposals for post-selection inference. However, the iterative nature of component-wise boosting, which can repeatedly select the same component to update, necessitates adaptations and extensions to existing approaches. We propose tests and confidence intervals for linear, grouped and penalized additive model components selected by $$L_2$$-Boosting. Our concepts also transfer to slow-learning algorithms more generally, and to other selection techniques which restrict the response space to more complex sets than polyhedra. We apply our framework to an additive model for sales prices of residential apartments and investigate the properties of our concepts in simulation studies.     

On MLEs of the parameters of a modified Weibull distribution based on record values

The modified Weibull distribution can be used quite effectively to model complex data from mechanical engineering or survival analysis studies that posses a monotonic or a bathtub-shape hazard rate. In this paper, we study the MLEs of the parameters of a modified Weibull distribution model in the presence of upper kth record values. The existence and uniqueness of the MLEs are proven in this case. Real data analysis is performed for illustrative purposes.     

Is the Education of Local Children Influenced by Living near a Refugee Camp? Evidence from Host Communities in Rwanda

This article studies the extent to which educational services and schooling outcomes of local children are influenced by the presence of a refugee camp in or near their community. Investigating Congolese refugees in Rwanda and relying on a mixed‐method approach, we examine schooling rates and access to school‐based feeding programmes in communities closer to and further away from three refugee camps. We conduct cohort analyses to compare the schooling outcomes of Rwandans residing at different distances from each of these camps. Our results highlight that children residing closer to the camps have better schooling outcomes and that locals residing closer to the camps have mostly positive views regarding the effects of refugees on local education. These results contribute to the literature on the effects of refugees on host communities and inform policy debates on how refugees need not be a “burden” if a long‐term vision shapes educational investments.     

The relationship between reputation,employer branding and corporate social responsibility

Reputation management requires coordination between internal understanding and external expectations (Cornelissen, 2011). The focus of this study were external expectations of potential employees. The main goal of the study was to contribute to the understanding of corporate reputation and its connections with perceived corporate social responsibility and employer brands. All three concepts were investigated amongst 550 senior college business students. The units of analysis were top twenty national organizations, rated according to a syndicated study on employer attractiveness. The results show that students assign good reputation to those organizations that are perceived as socially responsible and with a good employer brand. Reputation, at least according to our results, seems to be the umbrella concept that encompasses both perceived corporate social responsibility and perceived employer brands. Organizations that develop different strategies, policies and practices with regards to socially responsible behavior and nurturing employer brands have higher levels of perceived reputation among students. Additionally, students' perceptions and position on the list of the most attractive employers is consistent.     

Ground beetle (Coleoptera: Carabidae) communities on green roofs in Switzerland: synthesis and perspectives

Urban Ecosystems - Green roofs have recently gained recognition for their potential contribution to urban ecosystems by providing, among other services, habitat for plants and animals, and stepping...