Essays in empirical macroeconomics

This Dissertation is composed of two Chapters which can be read independently. Each Chapter consists of a self-contained empirical study of an economic issue from the field of macroeconomics. The first Chapter of this Dissertation is concerned with the transmission of monetary policy decisions to real economic activity. I show that US manufacturing industries react vastly different to monetary policy shocks. I use the heterogeneity in output responses to monetary policy shocks across industries to test whether industries with a higher degree of price stickiness react more strongly to monetary policy shocks, as predicted by New Keynesian models of the monetary transmission mechanism. The second Chapter of my Dissertation provides new evidence on the extent and the geography of intergenerational mobility in Germany. We show that intergenerational mobility, measured by the association of the educational attainment of children in secondary school and their parents income, differs substantially across regions within Germany

Systematic Comparison of Software Agents and Digital Twins: Differences, Similarities, and Synergies in Industrial Production

To achieve a highly agile and flexible production, it is envisioned that industrial production systems gradually become more decentralized, interconnected, and intelligent. Within this vision, production assets collaborate with each other, exhibiting a high degree of autonomy. Furthermore, knowledge about individual production assets is readily available throughout their entire life-cycles. To realize this vision, adequate use of information technology is required. Two commonly applied software paradigms in this context are Software Agents (referred to as Agents) and Digital Twins (DTs). This work presents a systematic comparison of Agents and DTs in industrial applications. The goal of the study is to determine the differences, similarities, and potential synergies between the two paradigms. The comparison is based on the purposes for which Agents and DTs are applied, the properties and capabilities exhibited by these software paradigms, and how they can be allocated within the Reference Architecture Model Industry 4.0. The comparison reveals that Agents are commonly employed in the collaborative planning and execution of production processes, while DTs typically play a more passive role in monitoring production resources and processing information. Although these observations imply characteristic sets of capabilities and properties for both Agents and DTs, a clear and definitive distinction between the two paradigms cannot be made. Instead, the analysis indicates that production assets utilizing a combination of Agents and DTs would demonstrate high degrees of intelligence, autonomy, sociability, and fidelity. To achieve this, further standardization is required, particularly in the field of DTs.Comment: Manuscript submitted to Journal of Intelligent Manufacturing, Corresponding dataset: https://doi.org/10.5281/zenodo.8120623 Additional references in Sec. 1, some other minor change

Predictors of adherence to exercise interventions in people with schizophrenia

Exercise interventions are nowadays considered as effective add-on treatments in people with schizophrenia but are usually associated with high dropout rates. Therefore, the present study investigated potential predictors of adherence from a large multicenter study, encompassing two types of exercise training, conducted over a 6-month period with individuals with schizophrenia. First, we examined the role of multiple participants’ characteristics, including levels of functioning, symptom severity, cognitive performance, quality of life, and physical fitness. Second, we used K-means clustering to identify clinical subgroups of participants that potentially exhibited superior adherence. Last, we explored if adherence could be predicted on the individual level using Random Forest, Logistic Regression, and Ridge Regression. We found that individuals with higher levels of functioning at baseline were more likely to adhere to the exercise interventions, while other factors such as symptom severity, cognitive performance, quality of life or physical fitness seemed to be less influential. Accordingly, the high-functioning group with low symptoms exhibited a greater likelihood of adhering to the interventions compared to the severely ill group. Despite incorporating various algorithms, it was not possible to predict adherence at the individual level. These findings add to the understanding of the factors that influence adherence to exercise interventions. They underscore the predictive importance of daily life functioning while indicating a lack of association between symptom severity and adherence. Future research should focus on developing targeted strategies to improve adherence, particularly for people with schizophrenia who suffer from impairments in daily functioning

Exercise as an add-on treatment in individuals with schizophrenia: results from a large multicenter randomized controlled trial

Current treatment methods do not achieve recovery for most individuals with schizophrenia, and symptoms such as negative symptoms and cognitive deficits often persist. Aerobic endurance training has been suggested as a potential add-on treatment targeting both physical and mental health. We performed a large-scale multicenter, rater-blind, parallel-group randomized controlled clinical trial in individuals with stable schizophrenia. Participants underwent a professionally supervised six-month training comprising either aerobic endurance training (AET) or flexibility, strengthening, and balance training (FSBT, control group), follow-up was another six months. The primary endpoint was all-cause discontinuation (ACD); secondary endpoints included effects on psychopathology, cognition, functioning, and cardiovascular risk. In total, 180 participants were randomized. AET was not superior to FSBT in ACD and most secondary outcomes, with dropout rates of 59.55% and 57.14% in the six-month active phase, respectively. However, both groups showed significant improvements in positive, general, and total symptoms, levels of functioning and in cognitive performance. A higher training frequency additionally promoted further memory domains. Participants with higher baseline cognitive abilities were more likely to respond to the interventions. Our results support integrating exercise into schizophrenia treatment, while future studies should aim to develop personalized training recommendations to maximize exercise-induced benefits

Ranked retrieval of Computational Biology models

<p>Abstract</p> <p>Background</p> <p>The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. Deciding for potentially suitable models, however, becomes more challenging with the increasing number of computational models available, and even more when considering the models' growing complexity. Firstly, among a set of potential model candidates it is difficult to decide for the model that best suits ones needs. Secondly, it is hard to grasp the nature of an unknown model listed in a search result set, and to judge how well it fits for the particular problem one has in mind.</p> <p>Results</p> <p>Here we present an improved search approach for computational models of biological processes. It is based on existing retrieval and ranking methods from Information Retrieval. The approach incorporates annotations suggested by MIRIAM, and additional meta-information. It is now part of the search engine of BioModels Database, a standard repository for computational models.</p> <p>Conclusions</p> <p>The introduced concept and implementation are, to our knowledge, the first application of Information Retrieval techniques on model search in Computational Systems Biology. Using the example of BioModels Database, it was shown that the approach is feasible and extends the current possibilities to search for relevant models. The advantages of our system over existing solutions are that we incorporate a rich set of meta-information, and that we provide the user with a relevance ranking of the models found for a query. Better search capabilities in model databases are expected to have a positive effect on the reuse of existing models.</p

Evaluation der Berufseinstiegsbegleitung nach § 421s SGB III: Zwischenbericht 2011

Die Anforderungen an Schülerinnen und Schüler zwei Jahre vor ihrem Schulabschluss sind hoch. Schulisch sind sie mit vielen Prüfungen gefordert. Daneben müssen sie Bewerbungen für Ausbildungsplätze schreiben. Wenn es zum Bewerbungsgespräch kommt, stehen sie vor einer unbekannten Situation. Viele sind unsicher darüber, wie es nach der Schule weitergeht. Das Berufsleben - später meist selbstverständlich - ist die große Unbekannte. In dieser Phase hilft die Berufseinstiegsbegleitung nach dem Arbeitsförderungsrecht derzeit in einer modellhaften Erprobung an rund 1.000 Schulen denjenigen, die besondere Schwierigkeiten beim Schulabschluss und beim Übergang in die berufliche Zukunft haben. Bisher wurden dabei rund 37.000 Schülerinnen und Schülern durch die Bundesagentur für Arbeit gefördert. Die begleitende Wirkungsforschung (Evaluation) zeigt nun, dass sich bei den Teilnehmenden leichte Verbesserungen der Noten in Mathematik, Deutsch und Englisch zeigen. Von denjenigen, die die Schule „in Begleitung“ verlassen haben, haben 22,8 % eine betriebliche und 5,1 % eine schulische Berufsausbildung begonnen. Vergleichszahlen zu Übergängen von der Schule in den Beruf von jungen Menschen "ohne entsprechende Begleitung" liegen noch nicht vor. Nach der Schule verteilen sich die Schülerinnen und Schüler auf verschiedene Betriebe, Berufsschulen und andere Einrichtungen. Für die Tätigkeit der Berufseinstiegsbegleiterinnen und -begleiter stellt dies eine räumliche und eine organisatorische Herausforderung dar. Denn die Berufseinstiegsbegleitung endet in der Berufsausbildung normalerweise erst nach sechs Monaten. Damit soll die kritische Anfangsphase, in der die meisten Abbrüche stattfinden, stabilisiert werden. Die bisherigen positiven Erfahrungen mit der Berufseinstiegsbegleitung haben die Bundesregierung dazu veranlasst, im Entwurf eines Gesetzes zur Verbesserung der Eingliederungschancen am Arbeitsmarkt die Entfristung der Berufseinstiegsbegleitung vorzuschlagen. Der Deutsche Bundestag hat dieses Gesetz am 23. September 2011 verabschiedet

Cell cycle independent role of cyclin D3 in host restriction of influenza virus infection

To identify new host factors that modulate the replication of influenza A virus, we performed a yeast two-hybrid screen using the cytoplasmic tail of matrix protein 2 from the highly pathogenic H5N1 strain. The screen revealed a high-score interaction with cyclin D3, a key regulator of cell cycle early G1 phase. M2-cyclin D3 interaction was validated through GST pull-down and recapitulated in influenza A/WSN/33-infected cells. Knockdown of Ccnd3 by small interfering RNA significantly enhanced virus progeny titers in cell culture supernatants. Interestingly, the increase in virus production was due to cyclin D3 deficiency per se, and not merely a consequence of cell cycle deregulation. A combined knockdown of Ccnd3 and Rb1, which rescued cell cycle progression into the S phase, failed to normalize virus production. Infection by IAV triggered redistribution of cyclin D3 from the nucleus to the cytoplasm followed by its proteasomal degradation. When over-expressed in HEK 293T cells cyclin D3 impaired binding of M2 with M1, which is essential for proper assembly of progeny virions, lending further support to its role as a putative restriction factor. Our study describes the identification and characterization of cyclin D3 as a novel interactor of influenza A virus M2 protein. We hypothesize that competitive inhibition of M1-M2 interaction by cyclin D3 impairs infectious virion formation and results in attenuated virus production. In addition, we provide mechanistic insights into the dynamic interplay of influenza virus with the host cell cycle machinery during infection.This work was supported by the Research Fund for the Control of Infectious Diseases (Grant RFCID 11101332) and the Area of Excellence Scheme of the University Grants Committee (Grant AoE/M-12/06) and partially supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. T11-705/14N)

Examining the generalizability of research findings from archival data

This initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability—for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples

The Open Anchoring Quest Dataset: Anchored Estimates from 96 Studies on Anchoring Effects

People’s estimates are biased toward previously considered numbers (anchoring). We have aggregated all available data from anchoring studies that included at least two anchors into one large dataset. Data were standardized to comprise one estimate per row, coded according to a wide range of variables, and are available for download and analyses online (https://metaanalyses.shinyapps.io/OpAQ/). Because the dataset includes both original and meta-data it allows for fine-grained analyses (e.g., correlations of estimates for different tasks) but also for meta-analyses (e.g., effect sizes for anchoring effects)

SBML Level 3: an extensible format for the exchange and reuse of biological models

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution