Migration and wage inequality : a detailed analysis for German regions over time

This study presents new evidence on immigrant-native wage differentials estimated in consideration of regional differences regarding the presence of Non-German population in metropolitan and non-metropolitan areas between 2000 and 2019 in Germany. Using linked employer-employee-data, unconditional quantile regression models are estimated in order to assess the degree of labor market integration of foreign workers. Applying an extended version of the Oaxaca-Blinder decomposition method, the results provide evidence on driving factors behind wage gaps along the entire wage distribution. There are not only changes in the relative importance of explanatory factors over time, but also possible sources of wage differentials shift between different points of the wage distribution. Differentiating between various areas in Germany, on average, larger wage gaps are revealed in metropolitan areas with at the same time a higher presence of the foreign population. Regarding the size of overall estimated wage gaps, after 2012 a reversal in trend and particular increasing tendencies around median wages are identified

Mind the gap: effects of the national minimum wage on the gender wage gap in Germany

With its introduction in 2015, the statutory minimum wage in Germany intends to benefit primarily low-wage workers. Thus, this paper aims at estimating the effectiveness of the implemented wage floor on gender wage gaps in the lower half of the wage distribution. Using administrative data, distinct regional differences regarding magnitudes of wage differentials and responses to the minimum wage are identified. Overall, wage gaps between men and women at the 10th percentile decrease by 2.46 and 6.34 percentage points respectively in the West and East of Germany after 2015. Applying counterfactual wage distributions, the study provides new evidence that around 60% and even 95% of the decline result from the introduction of the minimum wage in each region. Further, group-specific analyses identify concrete responses on the basis of age, educational level and occupational activity. Having yearly data, the study additionally reveals new results on the impact of the successive minimum wage raises in 2017 and 2019. Counterfactual aggregate decompositions of gender wage gaps finally indicate a decrease in discriminatory remuneration structures in the West of Germany due to the introduced wage floor

Three essays on wage inequality in Germany : the impact of automation, migration and the minimum wage

Economic inequality has increased in the majority of countries worldwide over the last three decades and is highly present in public discussion, political debate and scientific research. Due to the large number and complexity of driving forces behind changes in wage inequality, this cumulative dissertation focuses on three challenges of the German labour market. The first paper addresses the question to which extent automation and robotization impact wage inequality in the manufacturing sector in Germany between 1996 and 2017. Applying decomposition analyses along the entire wage distribution, driving factors behind changes in wage inequality are identified. On the basis of administrative data and a new introduced measure of automation threat, which combines occupation- and requirement-specific scores of automation risk with yearly sector-specific robot densities, the study provides new evidence to existing literature. Besides the traditional factors education and age, the detailed decomposition analysis provides evidence that automation threat contributes significantly to rising wage inequality. On the one hand, changes in the composition of the workforce that is exposed to automation and robotization led to significant increases in wage inequality in the German manufacturing sector during the last two decades. On the other hand, evidence of a growing wage dispersion between occupations with low automation threat (especially associated with non-routine tasks) and occupations with high automation threat (especially associated with routine tasks) is revealed. This trend contributes to rising wage inequality as predicted by routine-biased technological change. The second research study presents new evidence on immigrant-native wage differentials in consideration of regional differences between metropolitan and non-metropolitan areas between 2000 and 2019 in Germany. Since gaps in remuneration provide information on the effectiveness of immigration and labour market policies as well as identify the degree of economic integration of foreign workers, the analysis is currently of great importance. Using administrative data, aggregate decomposition results support the hypothesis that the majority of wage differentials can be explained by differences in observed characteristics. However, overall wage differentials at the median exhibit an increasing trend, and on average higher gaps in remuneration are revealed in urban areas. Detailed decomposition analyses show that the effects of explanatory factors not only change over time but the sources of gaps also vary along the wage distribution. Decisive explanatory variables in this context are the practised profession, the economic sector affiliation and labour market experience. Distinguishing between metropolitan and non-metropolitan areas provides evidence that especially differences in educational attainment impact immigrant-native wage gaps in urban areas. The third paper evaluates the effects of the introduced national minimum wage in 2015 on the gender wage gap in Germany. Being confronted with a low-wage sector of considerable extent and comparably high wage differentials between men and women, this study on Germany provides necessary new insights in this area of research. On the basis of administrative data and counterfactual difference-in-differences analyses significant decreases of wage gaps between men and women that can be traced back to the introduced statutory wage floor are revealed. Especially at the lowest observed wage level and in the East of Germany the highest decreases are observable. The analysis, differentiated by educational level, age and occupational activity, provides detailed information on the effectiveness of the wage floor for different target groups. In particular, at lower wage levels for the least educated and middle aged workers the introduction of the minimum wage is the driving factor that significantly lowers group-specific gender wage gaps. Counterfactual decomposition analyses finally provide first evidence that in the West of Germany possible discrimination against women at the lowest wages is restricted by the wage floor.In den letzten drei Jahrzehnten hat die wirtschaftliche Ungleichheit in den meisten Ländern der Welt zugenommen und ist in der öffentlichen Diskussion, politischen Debatte sowie wissenschaftlichen Forschung präsent. Aufgrund der Vielzahl und Komplexität der unterschiedlichen Einflussfaktoren auf Veränderungen der Lohnungleichheit, konzentriert sich diese kumulative Dissertation im Detail auf drei Herausforderungen des deutschen Arbeitsmarkts. Die erste Forschungsstudie befasst sich mit der Frage, inwieweit Automatisierung und Robotisierung die Lohnungleichheit im verarbeitenden Gewerbe in Deutschland zwischen 1996 und 2017 beeinflussen. Anhand von Zerlegungsanalysen entlang der gesamten Lohnverteilung werden erklärende Faktoren für Veränderungen der Lohnungleichheit identifiziert. Auf Grundlage administrativer Daten und einer neu definierten Kennzahl, die die Automatisierungsbedrohung von Arbeitnehmenden schätzt und dabei berufs- und anforderungsspezifische Automatisierungswahrscheinlichkeiten mit jährlichen sektorspezifischen Werten zur Roboterdichte kombiniert, trägt die Studie neue Erkenntnisse zur bestehenden Literatur bei. Neben den traditionellen Faktoren Bildung und Alter, liefert die Analyse Belege dafür, dass die Bedrohung durch die Automatisierung erheblich zur steigenden Lohnungleichheit beiträgt. Einerseits führen Veränderungen in der Zusammensetzung der Arbeitskräfte, die der Automatisierung und Robotisierung ausgesetzt sind, zu einem signifikanten Anstieg der Lohnungleichheit im verarbeitenden Gewerbe während der letzten zwei Jahrzehnte. Andererseits zeigt sich eine wachsende Kluft in der Lohnverteilung zwischen Berufen mit geringer Automatisierungsbedrohung (mit meist nicht-routinemäßigen Aufgaben) und Berufen mit hoher Automatisierungsbedrohung (mit meist routinemäßigen Aufgaben). Dieser Trend trägt zu einer zunehmenden Lohnungleichheit bei, wie es durch den sogenannten routine-biased technological change vorhergesagt wird. Die zweite Forschungsstudie präsentiert neue Erkenntnisse zu Lohnunterschieden zwischen ausländischen und deutschen Arbeitnehmenden unter Berücksichtigung regionaler Unterschiede in Metropol- und Nicht-Metropolregionen zwischen 2000 und 2019 in Deutschland. Da Lohnunterschiede Aufschluss über die Effektivität der Zuwanderungs- und Arbeitsmarktpolitik geben sowie den Grad der wirtschaftlichen Integration von Zuwanderern preisgeben, ist diese Analyse von aktueller Bedeutung. Unter Verwendung von administrativen Daten kann die Hypothese, dass der Großteil der Lohnlücke durch Unterschiede in beobachtbaren Merkmalen zwischen ausländischen und deutschen Arbeitnehmenden erklärt werden kann, mithilfe von Zerlegungsmethoden bestätigt werden. Insgesamt nehmen die Lohnunterschiede in der Mitte der Verteilung jedoch zu und in urbanen Gebieten werden im Durchschnitt größere Lohnunterschiede festgestellt. Detaillierte Zerlegungsanalysen zeigen, dass sich die Ausmaße der erklärenden Faktoren nicht nur im Laufe der Zeit ändern, sondern dass auch die Ursachen für Lohnunterschiede entlang der Lohnverteilung variieren. Entscheidende erklärende Variablen sind in diesem Zusammenhang der ausgeübte Beruf, die Zugehörigkeit zu einem bestimmten Wirtschaftszweig und die Arbeitsmarkterfahrung. Die getrennte Analyse von Metropol- und Nicht-Metropolregionen zeigt, dass insbesondere Unterschiede im Bildungsniveau die Lohnunterschiede in städtischen Gebieten beeinflussen. Die dritte Forschungsarbeit bewertet den Einfluss des neu eingeführten Mindestlohns im Jahr 2015 auf geschlechtsspezifische Lohnunterschiede in Deutschland. Angesichts eines Niedriglohnsektors von beträchtlichem Ausmaß und vergleichsweise hohen Lohnunterschieden zwischen Männern und Frauen liefert diese Studie im Fall von Deutschland notwendige und neue Erkenntnisse in diesem Forschungsbereich. Auf Grundlage administrativer Daten und kontrafaktischer Differenz-von-Differenzen-Analysen wird eine signifikante Abnahme der Lohnunterschiede zwischen Männern und Frauen festgestellt, die auf den gesetzlichen Mindestlohn zurückgeführt werden kann. Die größten Rückgänge des geschlechtsspezifischen Lohngefälles sind in diesem Zusammenhang für das niedrigste Lohnniveau, insbesondere in Ostdeutschland, zu beobachten. Differenziert nach Bildungsniveau, Alter und Tätigkeit im Beruf liefert die Analyse detaillierte Informationen über die Wirksamkeit der Lohnuntergrenze für verschiedene Gruppen der Arbeitskräfte. Vor allem für untere Lohnniveaus der am wenigsten gebildeten Arbeitnehmenden und der Gruppe mit mittlerem Alter ist die Einführung des Mindestlohns der treibende Faktor, der zur Reduktion gruppenspezifischer Lohnunterschiede zwischen den Geschlechtern beiträgt. Kontrafaktische Zerlegungsanalysen liefern schließlich erste Hinweise dafür, dass in Westdeutschland eine mögliche Diskriminierung gegenüber Frauen im untersten Lohnniveau durch die Lohnuntergrenze eingeschränkt wird

Automation, robots and wage inequality in Germany : a decomposition analysis

We analyze how and through which channels wage inequality is affected by the rise in automation and robotization in the manufacturing sector in Germany from 1996 to 2017. Combining rich linked employer-employee data accounting for a variety of different individual, firm and industry characteristics with data on industrial robots and automation probabilities of occupations, we are able to disentangle different potential causes behind changes in wage inequality in Germany. We apply the recentered influence function (RIF) regression based Oaxaca-Blinder (OB) decomposition on several inequality indices and find evidence that besides personal characteristics like age and education the rise in automation and robotization contributes significantly to wage inequality in Germany. Structural shifts in the workforce composition towards occupations with lower or medium automation threat lead to higher wage inequality, which is observable over the whole considered time period. The effect of automation on the wage structure results in higher inequality in the 1990s and 2000s, while it has a significant decreasing inequality effect for the upper part of the wage distribution in the more recent time period

Analyzing Compounds’ Mode of Action - A Use Case for New Approaches Utilizing Protein Interaction Networks and Prior Knowledge to Complement State-of-the-Art Gene Expression Analyses

Background: Scientists in pharmaceutical as well as academic research work together to solve the challenging puzzle from the basic causes of disease at the level of genes, proteins and cells up to a marketed new drug. Analyses of mode of action (MoA) of new chemical entities (NCEs) are a very important step in the development of new drugs. One distinguishes between effects induced by modulating the compounds’ actual target protein (on-target effects) and effects induced by additional, possibly unknown targets (off-target effects). Quite often knowledge about either of these effects is limited. Since MoA is mainly triggered by the interplay of proteins or signaling cascades, investigating the change and subsequent influence of the changed molecules in a protein interaction (PI) network is a promising initial step to further analyses. As more and more data from diverse sources becomes available, the integration of this knowledge is important for generating a deeper insight into biology. In addition, expression experiments based on disease tissue and/or compound treatment are frequently conducted to get insight into transcriptional changes that could explain compounds’ MoA. Status quo: MoA could be analyzed by investigating those parts of a PI network that show changes based on compound treatment. Mathematical or graph theoretical in silico methods to identify interesting parts of a network based on different criteria are widely used. Criteria range from detection of highly connected subgraphs to subgraphs maximizing weights assigned to parts of the network under investigation. These methods can be transferred to biology and can be used to, e. g. identify condition responsive subnetworks on various types of molecular networks. Present questions addressed mainly focus on the detection of subnetworks enriched in information from functional genomics, e.g. differentially expressed genes. They neglect the existence of distance regulatory functions on the post-transcriptional as well as post-translational level like miRNA interference or protein phosphorylation. Further, available methods usually detect relatively large modules. It is easily possible that more processes, i. e. the on- and several off-target effects, are covered by one larger module. Thus, the individual effects are difficult to detect and interpret. To be able to derive individual effects, it is necessary to reveal small modules that are related to the individual effects present in the biological system under investigation. Methods & Results: In this work, I made use of a gene expression data set investigating the inhibition of the TGF-beta signaling pathway by different compounds targeting TGF-betaR1. To gain a sound basis for follow-up analyses, different aspects of how to select the best suited normalization procedure for the underlying expression data are proposed in the first part of this thesis. To analyze compounds’ MoA, I propose a method that weights interactions between proteins based on different kinds of evidence. In this method, the relevance of the proteins is based on the biological relatedness to other possibly not deregulated protein coding genes. Thereby, analyses are expanded beyond transcriptional deregulation. To elucidate the biological relatedness, information on molecular function, biological processes and cellular compartment, information on transcription factor binding sites and literature-based confidence scores are integrated for weighting the edges between proteins. To transfer the network into the biological context of interest, expression experiments are used as anchoring points for the analyses. Further, I introduce modEx, a method to extract small modules out of a weighted protein interaction network. Modules extracted using modEx reflect the individual effects present in the biological system under investigation. For the expression data set used, the proposed edge scoring is shown to be superior to the widely accepted STRING scoring. Furthermore, modEx extracts modules that represent the underlying mechanism better than jActiveModule, a commonly used subgraph extraction method. These newly proposed approaches are applied to elucidate the MoA, i. e. the on- as well as off-target effects, of compounds. They are shown to grant a more focused view on the effects of compounds than current state-of-the-art methods applied for the analysis of gene expression data

Heat and shear stability of particle stabilised foams for application in gluten‑free bread

Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch) ​Bread forms an integral part of the daily diet in many cultures worldwide. At the same time, a signifcant number of people try to avoid wheat-based products for either health reasons or due to personal preferences. The absence of a protein network in gluten free bread afects its structure, taste, texture and shelf-life. This paper suggests a technological solution to this issue that uses a pre-foamed mass of gluten free raw materials which is mixed with the bread’s ingredients, then kneaded and baked to form a high quality gluten free bread. To survive the high shear stresses during kneading and temperature increase during baking, the foam requires exceptional stability. This stability was achieved through particle stabilisation of the bubble inter faces. Both of the tested foams (with and without particles) exhibited thermal stability up to 80 °C. However, resistance to shear stresses was higher in the particle stabilised foams. Of all the tested particles, linseed press cake and banana powder led to the best results. In conclusion, particle stabilised foams seem very well suited to applications in gluten free baked goods. Further application potential is seen for vegan foamed desserts

Effect of particle characteristics and foaming parameters on resulting foam quality and stability

Highlights: • Use of particles without emulsifier reduced median bubble size and improved foam stability. • Combining PGE emulsifier and particles resulted in higher foam stability. • Particularly low drainage was observed in particle stabilized foams using banana powder. • Increases in particle size and wetting angle correlated with reduced drainage. • High shear rates were strongly associated with narrower bubble size distributions.In this study, the effects of ten different food-grade particles on bubble quality and stabilization of particle-stabilized food foams in batch and continuous foaming with and without polyglycerol ester (PGE) as an emulsifier were investigated. Particle properties, such as contact angle and porosity, and varying process parameters, such as shear rate and gas fraction, were assessed with respect to their impact on bubble size x50,0, bubble size distribution width and drainage. The smallest bubble size x50,0 in foams without PGE could be achieved with banana powder (88 μm), calcium carbonate (89 μm) and microcrystalline cellulose (79 μm) particles. In comparison, the smallest size in the reference without particles were 105 μm. Combining the use of particles with PGE further reduced bubble size by up to 57% and drainage by up to 100%. Increasing the shear rate from 4922 s−1 (35 μm) to 9844 s−1 (14 μm) resulted in smaller mean bubble sizes and significantly narrower bubble size distributions whereas no distinct correlation between gas fraction and resulting bubble size was found. This study shows that using suitable particles in combination with an optimized foaming process promotes both bubble quality and the stability of foams

Evaluation of innovative technological approaches to replace palmoil with physically modified Swiss rapeseed oil in bakery products

Palm fat is often used in baked goods because of its relatively low cost, and its positive impact on texture and shelf life. Demand for alternatives has risen in recent years due to concerns about the ecological and social sustainability. This is a challenge for the bakery industry since palm oil possesses unique properties. In this study, unhydrogenated rapeseed oil was processed using novel physical technologies, such as wax crystallisation, stabilized foaming and Pickering emulsions, in order to simulate palm oil properties. Analysis showed that while the initial viscosity of the fat substitute products was low compared to palm fat, the fat replacement products behaved very similarly to palm fat in the baking experiments. The resulting biscuits baked with emulsified rapeseed oil and rapeseed oil complemented with wax crystals were judged to be suitable replacements for palm fat in terms of processability, as well as analytical and sensory assessment

The multilingual Twitter-discourse on vaccination in Germany during the COVID-19 pandemic

There is evidence that specific segments of the population were hit particularly hard by the Covid-19 pandemic (e.g., people with a migration background). In this context, the impact and role played by online platforms in facilitating the integration or fragmentation of public debates and social groups is a recurring topic of discussion. This is where our study ties in, we ask: How is the topic of vaccination discussed and evaluated in different language communities in Germany on Twitter during the Covid-19 pandemic? We collected all tweets in German, Russian, Turkish, and Polish (i.e., the largest migrant groups in Germany) in March 2021 that included the most important keywords related to Covid-19 vaccination. All users were automatically geocoded. The data was limited to tweets from Germany. Our results show that the multilingual debate on Covid-19 vaccination in Germany does not have many structural connections. However, in terms of actors, arguments, and positions towards Covid-19 vaccination, the discussion in the different language communities is similar. This indicates that there is a parallelism of the debates but no social-discursive integration

Phenocopy – A Strategy to Qualify Chemical Compounds during Hit-to-Lead and/or Lead Optimization

A phenocopy is defined as an environmentally induced phenotype of one individual which is identical to the genotype-determined phenotype of another individual. The phenocopy phenomenon has been translated to the drug discovery process as phenotypes produced by the treatment of biological systems with new chemical entities (NCE) may resemble environmentally induced phenotypic modifications. Various new chemical entities exerting inhibition of the kinase activity of Transforming Growth Factor β Receptor I (TGF-βR1) were qualified by high-throughput RNA expression profiling. This chemical genomics approach resulted in a precise time-dependent insight to the TGF-β biology and allowed furthermore a comprehensive analysis of each NCE's off-target effects. The evaluation of off-target effects by the phenocopy approach allows a more accurate and integrated view on optimized compounds, supplementing classical biological evaluation parameters such as potency and selectivity. It has therefore the potential to become a novel method for ranking compounds during various drug discovery phases