In diesem Beitrag werden Arbeitsanforderungen, Ressourcen und Gesundheit von Basisarbeitenden in den Dienstleistungssektoren Handel, Finanzwesen und öffentliche Dienstleistungen untersucht. Als Datengrundlage dient die aktuelle Erhebung der BIBB/BAuA-Erwerbstätigenbefragung 2018, eine...

Principal Component Analysis (PCA) is a common procedure for the analysis of financial market data, such as implied volatility smiles or interest rate curves. Recently, Pelsser and Lord [11] raised the question whether PCA results may not be 'facts but artefacts'. We extend this line of research...

Starting from the Merton framework for firm defaults, we provide the analytics and robustness of the relationship between default correlations. We show that loans with higher default probabilities will not only have higher variances but also higher correlations between loans. As a consequence,...

Datasets in a variety of disciplines require methods where both the sample size and the dataset dimensionality are allowed to be large. This framework is drastically different from the classical asymptotic framework where the number of observations is allowed to be large but the dimensionality...

The paradigm of a factor model is very appealing and has been used extensively in economic analyses. Underlying the factor model is the idea that a large number of economic variables can be adequately modelled by a small number of indicator variables. Throughout this extensive research activity...

Recently the topic of global warming has become very popular. The literature has concentrated its attention on the evidence of such effect, either by detecting regime shifts or change points in time series. The majority of these methods are designed to find shifts in mean, but only few can do...

Crop models are a key tool to develop adaptation strategies in the agriculture sector. With their evolution over time, crop models have been incorporating new approaches and tools. This paper proposes an innovative non-linear methodology to simulate crop's performance including non-linear...

We study potential impacts of future climate change on U.S. agricultural productivity using county-level yield and weather data from 1950 to 2015. To account for adaptation of production to different weather conditions, it is crucial to allow for both spatial and temporal variation in the...