Stochastic foundations of dynamic trade and labor market models

This dissertation consists of three self-contained papers that are related to two main topics. In particular, the first and third studies focus on labor market modeling, whereas the second essay presents a dynamic international trade setup.rnrnIn Chapter "Expenses on Labor Market Reforms during Transitional Dynamics", we investigate the arising costs of a potential labor market reform from a government point of view. To analyze various effects of unemployment benefits system changes, this chapter develops a dynamic model with heterogeneous employed and unemployed workers.rn rnIn Chapter "Endogenous Markup Distributions", we study how markup distributions adjust when a closed economy opens up. In order to perform this analysis, we first present a closed-economy general-equilibrium industry dynamics model, where firms enter and exit markets, and then extend our analysis to the open-economy case.rn rnIn Chapter "Unemployment in the OECD - Pure Chance or Institutions?", we examine effects of aggregate shocks on the distribution of the unemployment rates in OECD member countries.rn rnIn all three chapters we model systems that behave randomly and operate on stochastic processes. We therefore exploit stochastic calculus that establishes clear methodological links between the chapters.

Visualization and validation of (Q)SAR models

Analyzing and modeling relationships between the structure of chemical compounds, their physico-chemical properties, and biological or toxic effects in chemical datasets is a challenging task for scientific researchers in the field of cheminformatics. Therefore, (Q)SAR model validation is essential to ensure future model predictivity on unseen compounds. Proper validation is also one of the requirements of regulatory authorities in order to approve its use in real-world scenarios as an alternative testing method. However, at the same time, the question of how to validate a (Q)SAR model is still under discussion. In this work, we empirically compare a k-fold cross-validation with external test set validation. The introduced workflow allows to apply the built and validated models to large amounts of unseen data, and to compare the performance of the different validation approaches. Our experimental results indicate that cross-validation produces (Q)SAR models with higher predictivity than external test set validation and reduces the variance of the results. Statistical validation is important to evaluate the performance of (Q)SAR models, but does not support the user in better understanding the properties of the model or the underlying correlations. We present the 3D molecular viewer CheS-Mapper (Chemical Space Mapper) that arranges compounds in 3D space, such that their spatial proximity reflects their similarity. The user can indirectly determine similarity, by selecting which features to employ in the process. The tool can use and calculate different kinds of features, like structural fragments as well as quantitative chemical descriptors. Comprehensive functionalities including clustering, alignment of compounds according to their 3D structure, and feature highlighting aid the chemist to better understand patterns and regularities and relate the observations to established scientific knowledge. Even though visualization tools for analyzing (Q)SAR information in small molecule datasets exist, integrated visualization methods that allows for the investigation of model validation results are still lacking. We propose visual validation, as an approach for the graphical inspection of (Q)SAR model validation results. New functionalities in CheS-Mapper 2.0 facilitate the analysis of (Q)SAR information and allow the visual validation of (Q)SAR models. The tool enables the comparison of model predictions to the actual activity in feature space. Our approach reveals if the endpoint is modeled too specific or too generic and highlights common properties of misclassified compounds. Moreover, the researcher can use CheS-Mapper to inspect how the (Q)SAR model predicts activity cliffs. The CheS-Mapper software is freely available at http://ches-mapper.org.

Length scales of dynamic heterogeneities of low and high molecular weight glass formers from multidimensional NMR

Das Ziel der vorliegenden Arbeit ist die Untersuchung der räumlichen und zeitlichen Aspekte der heterogenen Dynamik in Modellglasbildnern. Dabei wird vor allem die langsame alpha-Relaxationsdynamik oberhalb des Glasüberganges Tg untersucht. Die nukleare Magnetresonanz zeigt ihre einmalige Vielseitigkeit bei der Untersuchung molekularer Dynamik, wenn die angewandten Techniken und Experimente durch Simulationen unterstützt werden. Die räumliche Aspekt dynamischer Heterogenitäten wird untersucht durch ein reduziertes vierdimensionales Spindiffusionsexperiment (4D3CP), ein Experiment, das Reorientierungsraten örtlich korreliert. Eine Simulation dieses Experimentes an einem System harter Kugeln liefert wertvolle Informationen über die Auswertemethode des 4D3CP Experiments. Glycerol und o-terphenyl werden durch das 4D3CP Experiment untersucht. Die erhaltenen Resultate werden mit bereits publizierten Daten des polymeren Glasbildners PVAc verglichen. Während PVAc und o-terphenyl eine Längenskale von 3.7 nm bzw. 2.9 nm aufweisen, ist die Längenskale von Glycerol signifikant kleiner bei 1.1 nm. Ein neues Experiment, welches sensitiv auf Translationsbewegung reagiert, wird vorgestellt. Durch Verwendung eines pi-Impulszuges kann eine separate Evolution unter dem Hamiltonian der dipolaren Kopplung und der chemischen Verschiebungsanisotropie erreicht werden.