Anne Ardila Brenøe, Brothers increase women’s gender conformity, Journal of Population Economics, Vol. 35 (4), 2022. (Journal Article)
 
I examine how one central aspect of the family environment - sibling sex composition - affects women’s gender conformity. Using Danish administrative data, I causally estimate the effect of having a second-born brother relative to a sister for first-born women. I show that women with a brother acquire more traditional gender roles as measured through their choice of occupation and partner. This results in a stronger response to motherhood in labor market outcomes. As a relevant mechanism, I provide evidence of increased gender-specialized parenting in families with mixed-sex children. Finally, I find persistent effects on the next generation of girls. |
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Lorenzo Casaburi, Tristan Reed, Using individual-level randomized treatment to learn about market structure, American Economic Journal: Applied Economics, Vol. 14 (4), 2022. (Journal Article)
 
Interference across competing firms in RCTs can be informative about market structure. An experiment that subsidizes a random subset of traders who buy cocoa from farmers in Sierra Leone illustrates this idea. Interpreting treatment-control differences in prices and quantities purchased from farmers through a model of Cournot competition reveals differentiation between traders is low. Combining this result with quasi-experimental variation in world prices shows that the number of traders competing is 50 percent higher than the number operating in a village. Own-price and cross-price supply elasticities are high. Farmers face a competitive market in this first stage of the value chain. |
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Mariia Lapaeva, Agustina La Greca Saint-Esteven, Philipp Wallimann, Manuel Günther, Ender Konukoglu, Nicolaus Andratschke, Matthias Guckenberger, Stephanie Tanadini-Lang, Riccardo Dal Bello, Synthetic computed tomography for low-field magnetic resonance-guided radiotherapy in the abdomen, Physics and imaging in radiation oncology, Vol. 24, 2022. (Journal Article)
 
Background and purpose
The requirement of computed tomography (CT) for radiotherapy planning may be bypassed by synthetic CT (sCT) generated from magnetic resonance (MR), which has recently led to the clinical introduction of MR-only radiotherapy for specific sites. Further developments are required for abdominal sCT, mostly due to the presence of mobile air pockets affecting the dose calculation. In this study we aimed to overcome this limitation for abdominal sCT at a low field (0.35 T) hybrid MR-Linac.
Materials and methods
A retrospective analysis was conducted enrolling 168 patients corresponding to 215 MR-CT pairs. After the exclusion criteria, 152 volumetric images were used to train the cycle-consistent generative adversarial network (CycleGAN) and 34 to test the sCT. Image similarity metrics and dose recalculation analysis were performed.
Results
The generated sCT faithfully reproduced the original CT and the location of the air pockets agreed with the MR scan. The dose calculation did not require manual bulk density overrides and the mean deviations of the dose-volume histogram dosimetric points were within 1 % of the CT, without any outlier above 2 %. The mean gamma passing rates were above 99 % for the 2 %/ 2 mm analysis and no cases below 95 % were observed.
Conclusions
This study presented the implementation of CycleGAN to perform sCT generation in the abdominal region for a low field hybrid MR-Linac. The sCT was shown to correctly allocate the electron density for the mobile air pockets and the dosimetric analysis demonstrated the potential for future implementation of MR-only radiotherapy in the abdomen. |
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Florian Spychiger, Claudio Tessone, Liudmila Zavolokina, Gerhard Schwabe, Incentivizing Data Quality in Blockchain-Based Systems – The Case of the Digital Cardossier, Distributed Ledger Technologies: Research and Practice, Vol. 1 (1), 2022. (Journal Article)
 
Inspired by an industry initiative to address the celebrated market for lemons (poor-quality used cars), we investigate how incentives for a permissioned blockchain-based system in the automobile ecosystem can be designed to ensure high-quality data storage and use by different stakeholders. The peer-to-peer distributed ledger platform connects organizations and car owners with disparate interests and hidden intentions. While previous literature has chiefly examined incentives for permissionless platforms, we leverage studies about crowdsensing applications to stimulate research on incentives in permissioned blockchains. This paper uses the action design research approach to create an incentive system featuring a rating mechanism influenced by data correction measures. Furthermore, we propose relying on certain institutions capable of assessing data generated within the system. This combined approach of a decentralized data correction and an institutionalized data assessment is distinct from similar incentive systems suggested by literature. By using an agent-based model with strategy evolution, we evaluate the proposed incentive system. Our findings indicate that a rating-based revenue distribution leads to markedly higher data quality in the system. Additionally, the incentive system reveals hidden information of the agents and alleviates agency problems, contributing to an understanding of incentive design in inter-organizational blockchain-based data platforms. Furthermore, we explore incentive design in permissioned blockchains and discuss its latest implications. |
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Lorenz Honegger, Alexander Wagner, Der Kampf der Notenbanken gegen die Inflation zwingt Anleger und Hauskäufer zum Umdenken: Das sind die grössten Gefahren und Chancen im neuen Zinsumfeld, In: Neue Zürcher Zeitung, 23 September 2022. (Media Coverage)

Weltweit erhöhen die Zentralbanken die Leitzinsen: Die Konsequenzen für Aktionäre, Hypothekarnehmer und Sparer reichen weit. |
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Eryk Jerzy Schiller, Elfat Esati, Burkhard Stiller, IoT-Based Access Management Supported by AI and Blockchains, Electronics, Vol. 11 (18), 2022. (Journal Article)
 
Internet-of-Things (IoT), Artificial Intelligence (AI), and Blockchains (BCs) are essential techniques that are heavily researched and investigated today. This work here specifies, implements, and evaluates an IoT architecture with integrated BC and AI functionality to manage access control based on facial detection and recognition by incorporating the most recent state-of-the-art techniques. The system developed uses IoT devices for video surveillance, AI for face recognition, and BCs for immutable permanent storage to provide excellent properties in terms of image quality, end-to-end delay, and energy efficiency. |
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Fynn Bachmann, Philipp Hennig, Dmitry Kobak, Wasserstein t-SNE, In: ECMLPKDD 2022, 2022. (Conference or Workshop Paper published in Proceedings)
 
Scientific datasets often have hierarchical structure: for example, in surveys, individual participants (samples) might be grouped at a higher level (units) such as their geographical region. In these settings, the interest is often in exploring the structure on the unit level rather than on the sample level. Units can be compared based on the distance between their means, however this ignores the within-unit distribution of samples. Here we develop an approach for exploratory analysis of hierarchical datasets using the Wasserstein distance metric that takes into account the shapes of within-unit distributions. We use t-SNE to construct 2D embeddings of the units, based on the matrix of pairwise Wasserstein distances between them. The distance matrix can be efficiently computed by approximating each unit with a Gaussian distribution, but we also provide a scalable method to compute exact Wasserstein distances. We use synthetic data to demonstrate the effectiveness of our Wasserstein t-SNE, and apply it to data from the 2017 German parliamentary election, considering polling stations as samples and voting districts as units. The resulting embedding uncovers meaningful structure in the data. |
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Alexandra Stühff, Falko Paetzold, Julian Kölbel, Florian Heeb, Stefan Zeisberger, Nachhaltige Anlagen: Die Wirkung ist egal. Wichtig ist vor allem das gute Gefühl, In: NZZ, 16 September 2022. (Media Coverage)

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Patrick Lehnert, Curdin Pfister, Dietmar Harhoff, Uschi Backes-Gellner, Innovation effects and knowledge complementarities in a diverse research landscape, In: XII. Symposium zur ökonomischen Analyse der Unternehmung. 2022. (Conference Presentation)

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Christin Severin, Thorsten Hens, Der verpönte Fokus auf die Heimatbörse ist für Schweizer Anleger oft ein Vorteil, In: NZZ, 12 September 2022. (Media Coverage)

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Fabienne Kiener, Christian Eggenberger, Uschi Backes-Gellner, How IT progress affects Returns to Specialization and Social Skills, In: Annual Meeting of the German Economic Association (Verein für Socialpolitik). 2022. (Conference Presentation)

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Derivatus, Thorsten Hens, Ein Finanzprofessor macht sich auf die Suche nach dem besten strukturierten Produkt., In: Finanz und Wirtschaft, 10 September 2022. (Media Coverage)
 
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Daniel Hügli, Thorsten Hens, Finanzprofessor im Interview - Thorsten Hens: «Ich kaufe nach wie vor Aktien», In: cash.ch, 8 September 2022. (Media Coverage)

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Yuqing Zhou, Björn Lindström, Alexander Soutschek, Pyungwon Kang, Philippe Tobler, Grit Hein, Learning from ingroup experiences changes intergroup impressions, Journal of Neuroscience, Vol. 42 (36), 2022. (Journal Article)
 
Humans form impressions toward individuals of their own social groups (ingroup members) and of different social groups (outgroup members). Outgroup-focused theories predict that intergroup impressions are mainly shaped by experiences with outgroup individuals, while ingroup-focused theories predict that ingroup experiences play a dominant role. Here we test predictions from these two psychological theories by estimating how intergroup impressions are dynamically shaped when people learn from both ingroup and outgroup experiences. While undergoing fMRI, male participants had identical experiences with different ingroup or outgroup members and rated their social closeness and impressions toward the ingroup and the outgroup. Behavioral results showed an initial ingroup bias in impression ratings which was significantly reduced over the course of learning, with larger effects in individuals with stronger ingroup identification. Computational learning models revealed that these changes in intergroup impressions were predicted by the weight given to ingroup prediction errors. Neurally, the individual weight for ingroup prediction errors was related to the coupling between the left inferior parietal lobule and the left anterior insula, which, in turn, predicted learning-related changes in intergroup impressions. Our findings provide computational and neural evidence for ingroup-focused theories, highlighting the importance of ingroup experiences in shaping social impressions in intergroup settings. |
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Patricia Pálffy, Patrick Lehnert, Uschi Backes-Gellner, Countering gender typicality in occupational choices: An information intervention targeted at adolescents, In: 1st Workshop on Field Experiments in Economics and Business. 2022. (Conference Presentation)

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Nadine Hietschold, Christian Vögtlin, Blinded by a social cause? Differences in cognitive biases between social and commercial entrepreneurs, Journal of Social Entrepreneurship, Vol. 13 (3), 2022. (Journal Article)
 
How are social entrepreneurs different from commercial entrepreneurs? This study sheds light on this issue by applying the perspective of entrepreneurial cognition and by arguing that social entrepreneurs are even more susceptible to cognitive biases than commercial entrepreneurs. The empirical study of 205 Swiss entrepreneurs could confirm that social entrepreneurs tend to be more overconfident and prone to escalation of commitment than commercial entrepreneurs, while the study found no differences for illusion of control. The findings indicate that cognitive biases are an important puzzle piece to understand the differences between social and commercial entrepreneurs. |
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Danilo Matic, Statistical Learning for Trend-Following and Momentum Strategies, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Bachelor's Thesis)
 
Although momentum strategies are widely used and discussed in the finance literature,
the issue of look-back period selection is often put on the back burner.
Based on the idea of Levy and Lopes (2021), various methodologies will be used
in order to dynamically choose the most effective look-back period. Compared
to the above-mentioned paper, different statistically based strategies will be
analysed and the case of cross-sectional strategies will also be explored. The results
say that more or less complex statistical models lead to better performance
for both the time-series and cross-sectional approaches. |
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Erdinc Akyildirim, Oguzhan Cepni, Linh Pham, Gazi Salah Uddin, How connected is the agricultural commodity market to the news-based investor sentiment?, Energy Economics, Vol. 113, 2022. (Journal Article)

Previous studies indicate a substantial time-variation in the co-movement of commodity futures markets and economic fundamentals. This paper examines the connectedness and directional spillovers for both the agricultural commodity futures markets and the corresponding sentiment indices. We first construct dynamic time-varying connectedness measures both for the agricultural commodity returns and sentiments. Then, we use panel data regressions and time-varying Granger causality tests to evaluate whether the spillovers between these returns and sentiments are influenced by the economic and financial uncertainties, including the global COVID-19 pandemic. In particular, we document that the COVID-19 induced uncertainty influences agricultural commodity returns and sentiments significantly around the first cycle of the pandemic in 2020. Last but not least, economic policy and financial market uncertainty are also found to be significant determinants of the connectedness between agricultural commodity returns and sentiment spillovers. |
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Stefanie Krohmann, Design And Development of a Medical Supply Manager for a Community-based Health Care System in Lesotho, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Bachelor's Thesis)
 
Nicht übertragbare Krankheiten (NCDs) breiten sich in Afrika südlich der Sahara rasch aus. Diese rasante Ausbreitung führt dazu, dass Gesundheitssysteme Mühe haben den damit anfallenden Behandlungsbedarf zu decken. In Lesotho zielt das Projekt Community Based Chronic Care Lesotho (ComBaCaL) darauf ab, die NCD-Epidemie zu bekämpfen. Mithilfe von Chronic Care Workers (CCWs) bietet ComBaCal Leistungen in der Prävention, dem Screening und der Diagnose an. Um die CCWs dabei in ihrem Arbeitsalltag effizient zu unterstützen, wurde ein mHealth-Tool eingeführt, mit welchem die CCWs all Ihre Patienten und Untersuchungen verwalten können. Jedoch fehlt dem Tool eine Unterstützung für die Verwaltung ihrer medizinischen Arbeitsmaterialien was dazu führt, dass die benötigten Materialien fehlen, worunter die Qualität der Arbeit leidet. Daraus resultiert eine erhöhte Belastung und Demotivation für die CCWs. Da die vorhandene Literatur zu mHealth das Lieferkettenmanagement für gemeindebasierte Interventionen nicht ausreichend berücksichtigt, zielt diese Arbeit darauf ab diese Lücke zu schließen, indem ein Medical Supply Manager entwickelt wird, welcher an den lokalen Kontext in Lesotho angepasst ist und der die CCWs bei der Verwaltung ihrer medizinischen Vorräte effektiv unterstützt. |
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Luca Huber, Supporting behavior change by digital health for people with non-communicable diseases: A literature review, University of Zurich, Faculty of Business, Economics and Informatics, 2022. (Bachelor's Thesis)
 
Non-communicable diseases are the cause for 71% of global deaths. Cases of non-communicable diseases are rising. To fight non-communicable diseases, changing behavior that is causing the disease like tabaco use, physical inactivity, and unhealthy nutrition, is essential. One big problem is that adherence to interventions is bad at only around 50% in developed countries. This bad adherence leads to suboptimal benefit and increases health care costs by a factor of 3-4 times in direct costs.
In this literature review our goal was to find how behavior change can be supported with digital health for people with non-communicable diseases. To do so we searched Scopus for relevant literature using a predefined search query. We systematically reduced the literature and ended up reviewing 65 papers.
By reviewing meta-analyses prior to our analysis, we found many strategies used to support behavior change using digital health for people with non-communicable diseases. This was the basis for our coding schema to support our analysis. We synthesized design principles from the reviewed literature for the different strategies. Further we categorize the strategies by assigning them to elements of the Fogg Behavior Model and to a phase of the plan-do-study-act cycle. This step allowed us to see the focus and potential gaps of recent literature.
We conclude that many areas are covered well but find some gaps, most importantly in the area or prompts. Further, a shortcoming of literature found were missing long-term studies. We also present what practitioners and developers can do to implement a digital agent. |
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