Giulio Cornelli, Jon Frost, Leonardo Gambacorta, Raghavendra Rau, Robert Wardrop, Tania Ziegler, Fintech and big tech credit: drivers of the growth of digital lending, Journal of Banking and Finance, Vol. 148, 2023. (Journal Article)

Fintech and big tech companies are making rapid inroads into credit markets. We hand construct a global database of fintech and big tech lending volumes for 79 countries over 2013-2018. Using a panel regression analysis, we find these new forms of digital lending are larger in countries with higher GDP per capita (albeit at a declining rate), where banking sector mark-ups are higher, and where banking regulation is less stringent. We also find that these alternative forms of credit are more developed where the ease of doing business is greater, investor protection disclosure and the efficiency of the judicial system are more advanced, and where bond and equity markets are more developed. Overall, fintech and big tech credit seem to complement other forms of credit, rather than substitute for them. |
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Aurore Burietz, Steven Ongena, Matthieu Picault, Taxing banks leverage and syndicated lending: A cross-country comparison, International Review of Law and Economics, Vol. 73, 2023. (Journal Article)

Between 2010 and 2012 and with bank stability as the ultimate target, five European countries implemented a tax levy on banks’ liabilities thereby decreasing the cost of equity relative to the cost of debt. Using a difference-in-differences approach we assess the impact of this tax levy on banks’ participation in the syndicated loan market. We further investigate the impact of the tax levy along bank size and capital structure. We find that banks located in countries where the tax levy was implemented supply more credit. This increase is more significant for larger lenders and banks that are more capital constrained. |
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Björn Bartling, Yagiz Özdemir, The limits to moral erosion in markets: Social norms and the replacement excuse, Games and Economic Behavior, Vol. 138, 2023. (Journal Article)
 
This paper studies the impact of a key feature of competitive markets on moral behavior: the possibility that a competitor might step in and conclude the deal if a conscientious market actor forgoes a profitable business opportunity for ethical reasons. In a series of experiments, we study whether people invoke the replacement excuse, that is, the argument “if I don't do it, someone else will,” to justify narrowly self-interested actions. Our data are consistent with the possibility that the existence of a clear social norm of moral conduct can limit the impact of the availability of the replacement excuse on behavior. |
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Florian Herold, Nick Netzer, Second-best probability weighting, Games and Economic Behavior, Vol. 138, 2023. (Journal Article)
 
Non-linear probability weighting is an integral part of descriptive theories of choice under risk such as prospect theory. But why do these objective errors in information processing exist? Should we try to help individuals overcome their mistake of overweighting small and underweighting large probabilities? In this paper, we argue that probability weighting can be seen as a compensation for preexisting biases in evaluating payoffs. In particular, inverse S-shaped probability weighting is a flipside of S-shaped payoff valuation. Probability distortions may thus have survived as a second-best solution to a fitness maximization problem, and it can be counter-productive to correct them while keeping the value function unchanged. |
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Christian Eggenberger, Uschi Backes-Gellner, IT skills, occupation specificity and job separations, Economics of Education Review, Vol. 92, 2023. (Journal Article)
 
This paper examines how workers’ earnings change after involuntary job separations depending on the workers’ acquired IT skills and the specificity of their occupational training. We categorize workers’ occupational skill bundles along two independent dimensions. First, we distinguish between skill bundles that are more specific or less specific compared to the skill bundles needed in the overall labor market. Second, as digitalization becomes ever more important, we distinguish between skill bundles that contain two different types of IT skills, generic or expert IT skills. We expect that after involuntary separations, these different types of IT skills can have opposing effects, either reducing or amplifying earnings losses of workers with specific skill bundles. We find clearly opposing results for workers in specific occupations—but not in general occupations: Having more generic IT skills is positively correlated with earnings after involuntary separations, whereas more expert IT skills is negatively correlated. |
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Mariia Kaliuzhna, Matthias Kirschner, Philippe Tobler, Stefan Kaiser, Comparing adaptive coding of reward in bipolar I disorder and schizophrenia, Human Brain Mapping, Vol. 44 (2), 2023. (Journal Article)
 
Deficits in neural processing of reward have been described in both bipolar disorder (BD) and schizophrenia (SZ), but it remains unclear to what extent these deficits are caused by similar mechanisms. Efficient reward processing relies on adaptive coding which allows representing large input spans by limited neuronal encoding ranges. Deficits in adaptive coding of reward have previously been observed across the SZ spectrum and correlated with total symptom severity. In the present work, we sought to establish whether adaptive coding is similarly affected in patients with BD. Twenty-five patients with BD, 27 patients with SZ and 25 healthy controls performed a variant of the Monetary Incentive Delay task during functional magnetic resonance imaging in two reward range conditions. Adaptive coding was impaired in the posterior part of the right caudate in BD and SZ (trend level). In contrast, BD did not show impaired adaptive coding in the anterior caudate and right precentral gyrus/insula, where SZ showed deficits compared to healthy controls. BD patients show adaptive coding deficits that are similar to those observed in SZ in the right posterior caudate. Adaptive coding in BD appeared more preserved as compared to SZ participants especially in the more anterior part of the right caudate and to a lesser extent also in the right precentral gyrus. Thus, dysfunctional adaptive coding could constitute a fundamental deficit in severe mental illnesses that extends beyond the SZ spectrum. |
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Matt Levine, Alexander Wagner, Everything Is Also Bank Fraud, In: Bloomberg Opinion, 23 January 2023. (Media Coverage)

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Helmut Max Dietl, Markus Lang, Panlang Lin, The Effects of Introducing Advertising in Pay TV: A Model of Asymmetric Competition between Pay TV and Free TV, The B.E. Journal of Theoretical Economics, Vol. 23 (1), 2023. (Journal Article)
 
The television broadcasting industry is of crucial economic and social importance. Traditionally, this industry has been dominated by free-to-air TV (FTV) but due to technological progress, subscription-based pay TV (PTV) has emerged as a competing business model. A key question for the PTV broadcasters is whether to air commercials in addition to charging subscription fees. Based on a theoretical model of asymmetric competition between a PTV and an FTV broadcaster, we examine the effects of placing PTV advertising on broadcaster market strategies, viewer demands, broadcaster profits and consumer surplus. We find that introducing advertising on PTV can induce a higher viewer demand on this channel but a lower viewer demand on the FTV channel. Surprisingly, consumers can benefit through the introduction of advertising in PTV and broadcaster profits can increase if the viewer disutility of advertising is sufficiently large. Our study provides an analytical framework for choosing and implementing an optimal PTV strategy when an FTV competitor preexists in the market. Furthermore, our study derives implications for policymakers and regulatory authorities by showing that additional PTV advertising is not necessarily socially undesirable due to the strategic market reactions. |
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Redaktion, Ming Deng, Markus Leippold, Alexander Wagner, The ESG Observer: Was 2022 die ESG-Performance prägte, In: The Market / NZZ, 17 January 2023. (Media Coverage)

2022 war ein schwieriges Jahr für die Finanzmärkte. Vor besondere Herausforderungen stellte es aber die Investoren, die ihre Anlageentscheide mit Blick auf die Umwelt, die Gesellschaft und eine gute Unternehmensführung fällen - auf Englisch Environmental, Social and Governance, kurz: ESG. |
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Tobias Schultheiss, Uschi Backes‐Gellner, Different degrees of skill obsolescence across hard and soft skills and the role of lifelong learning for labor market outcomes, Industrial Relations, 2023. (Journal Article)
 
This paper examines the role of lifelong learning in counteracting skill depreciation and obsolescence. We differentiate between occupations with more hard skills versus more soft skills and draw on representative job advertisement data that contain machine-learning categorized skill requirements and cover the Swiss job market in great detail across occupations (from 1950 to 2019). We examine lifelong learning effects for “harder” versus “softer” occupations, thereby analyzing the role of training in counteracting skill depreciation in occupations that are differently affected by skill depreciation. Our results reveal novel empirical patterns regarding the benefits of lifelong learning, which are consistent with theoretical explanations based on structurally different skill depreciation rates: In harder occupations, with large shares of fast-depreciating hard skills, the role of lifelong learning is primarily as a hedge against unemployment risks rather than a boost to wages. By contrast, in softer occupations, in which workers build on more value-stable soft-skill foundations, the role of lifelong learning instead lies mostly in acting as a boost for upward career mobility and leads to larger wage gains. |
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Björn Bartling, Ernst Fehr, Yagiz Özdemir, Does market interaction erode moral values?, The Review of Economics and Statistics, Vol. 105 (1), 2023. (Journal Article)

The widespread use of markets leads to unprecedented material well-being in many societies. We study whether market interaction, as a side effect, erodes moral values. In an influential paper, Falk and Szech (2013) provide experimental data that seem to suggest that “market interaction erodes moral values.” Although we replicate their main treatment effect, we show that additional treatments are necessary to corroborate their conclusion. These treatments reveal that playing repeatedly, and not market interaction, causes the erosion of moral values. Our paper thus shows that neither Falk and Szech's data nor our data support the claim that markets erode morals. |
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Christian Hansen, Damian Kozbur, Sanjog Misra, Targeted undersmoothing: sensitivity analysis for sparse estimators, The Review of Economics and Statistics, Vol. 105 (1), 2023. (Journal Article)
 
This paper proposes a procedure for assessing sensitivity of inferential conclusions for functionals of sparse high-dimensional models following model selection. The proposed procedure is called targeted undersmoothing. Functionals considered include dense functionals that may depend on many or all elements of the highdimensional parameter vector. The sensitivity analysis is based on systematic enlargements of an initially selected model. By varying the enlargements, one can conduct sensitivity analysis about the strength of empirical conclusions to model selection mistakes. We illustrate the procedure's performance through simulation experiments and two empirical examples. |
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Liudmila Zavolokina, Kilian Sprenkamp, Birgit Schenk, Citizens' expectations about achieving public value and the role of digital technologies: It takes three to tango!, In: 56th Hawaii International Conference on System Sciences, s.n., Maui, HI, 2023. (Conference or Workshop Paper published in Proceedings)
 
Governments across the globe are facing pressure to increase the speed of their digital transformation to meet the needs of the digital society while fulfilling their primary task of delivering public value. While researchers agree on the importance of the public sector for public value creation, recently, more and more studies have recognized the criticality of collaboration between the public and private sectors for successful public value creation. In our research, we conduct a qualitative survey. We examine the idea of collaboration between the public and the private sectors in more detail and add the citizens' perspective. We highlight the need for joint forces for optimal public value creation, identify ways to achieve this, and determine what digital technologies can support this process. |
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Redaktion, Thorsten Hens, Games locken mit Investitionen in risikoreiche Kryptowährungen, In: Schweizer Radio und Fernsehen SRF, 3 January 2023. (Media Coverage)

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Andres Palechor, Annesha Bhoumik, Manuel Günther, Large-Scale Open-Set Classification Protocols for ImageNet, In: IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), IEEE, 2023-01. (Conference or Workshop Paper published in Proceedings)
 
Open-Set Classification (OSC) intends to adapt closed-set classification models to real-world scenarios, where the classifier must correctly label samples of known classes while rejecting previously unseen unknown samples. Only recently, research started to investigate on algorithms that are able to handle these unknown samples correctly. Some of these approaches address OSC by including into the training set negative samples that a classifier learns to reject, expecting that these data increase the robustness of the classifier on unknown classes. Most of these approaches are evaluated on small-scale and low-resolution image datasets like MNIST, SVHN or CIFAR, which makes it difficult to assess their applicability to the real world, and to compare them among each other. We propose three open-set protocols that provide rich datasets of natural images with different levels of similarity between known and unknown classes. The protocols consist of subsets of ImageNet classes selected to provide training and testing data closer to real-world scenarios. Additionally, we propose a new validation metric that can be employed to assess whether the training of deep learning models addresses both the classification of known samples and the rejection of unknown samples. We use the protocols to compare the performance of two baseline open-set algorithms to the standard SoftMax baseline and find that the algorithms work well on negative samples that have been seen during training, and partially on out-of-distribution detection tasks, but drop performance in the presence of samples from previously unseen unknown classes. |
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Andreas Bucher, Birgit Schenk, Gerhard Schwabe, When Learning Turns To Surveillance – Using Pedagogical Agents in Organizations, In: 56th Hawaii International Conference on System Sciences, Honolulu, USA, 2023. (Conference or Workshop Paper published in Proceedings)
 
Workplace learning is often used to train employees systematically. New in this context is workplace learning with the help of a pedagogical agent (PA). Following Actions Design Research (ADR), this paper describes organizational training for telephone service using such PA. To develop the training, existing employee telephone service problems were analyzed, and the content of the learning program was determined based on this analysis. Subsequently, a PA was developed, implemented, and used in three municipalities. The evaluation of the learning outcome shows promising results but also yields some challenges: even though the employees improved in various aspects of the learning, they also developed a perception of surveillance. This research concludes with the formulation of design principles and suggestions for the organizational embedding of a PA in a workplace setting. |
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Kilian Sprenkamp, Joaquin Delgado Fernandez, Sven Eckhardt, Liudmila Zavolokina, Federated Learning as a Solution for Problems Related to Intergovernmental Data Sharing, In: 56th Hawaii International Conference on System Sciences, 2023. (Conference or Workshop Paper published in Proceedings)

To address global problems, intergovernmental collaboration is needed. Modern solutions to these problems often include data-driven methods like artificial intelligence (AI), which require large amounts of data to perform well. However, data sharing between governments is limited. A possible solution is federated learning (FL), a decentralised AI method created to utilise personal information on edge devices. Instead of sharing data, governments can build their own models and just share the model parameters with a centralised server aggregating all parameters, resulting in a superior overall model. By conducting a structured literature review, we show how major intergovernmental data sharing challenges like disincentives, legal and ethical issues as well as technical constraints can be solved through FL. Enhanced AI while maintaining privacy through FL thus allows governments to collaboratively address global problems, which will positively impact governments and citizens. |
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Besnik Kqiku, Stablecoins and financial stability risks - evidence from the cryptocurrency market, University of Zurich, Faculty of Business, Economics and Informatics, 2023. (Bachelor's Thesis)

As digital assets are constantly growing, stablecoins have attracted remarkable attention from
central banks regarding financial stability risks. Focusing on 2018-2022, this study uses the
DCC-GARCH (1,1) model to analyze the conditional dynamic correlation between stablecoins
and traditional financial assets, specifically the energy market, Banks Index, DXY Index, and
gold. The results imply that stablecoins significantly correlate with the energy market and the
banking sector, while there is no significant co-movement with the DXY Index or gold.
Furthermore, the results disclose a strongly increased correlation between all assets during
financial market stress. These findings highlight that stablecoins are moving towards
integration with the traditional financial market. As policymakers have not yet regulated
stablecoins, this study suggests introducing appropriate regulation in the near future. |
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Pajtim Rexhepi, Von der Mindestreserve der Geschäftsbanken in der Schweiz zum Vollgeldsystem, University of Zurich, Faculty of Business, Economics and Informatics, 2023. (Bachelor's Thesis)

Die folgende Arbeit befasst sich mit dem Geldsystem der Schweiz. Sie beginnt mit einer
Einführung in das gegenwärtige Mindestreservesystem und diskutiert einen möglichen
Übergang zu einem Vollgeldsystem. Dabei werden die Auswirkungen eines Vollgeldsystems
auf die Bilanzen der Schweizerischen Nationalbank und der Geschäftsbanken untersucht und
die Vor- und Nachteile des Vollgeld- gegenüber des Mindestreservesystems erläutert. Anhand
aktueller Literatur wird aufgezeigt, dass sich die Bilanz der Schweizerischen Nationalbank
durch ein Vollgeldsystem verlängern würde, die Bilanzen von Geschäftsbanken sich aber weder
verlängern noch verkürzen würden. |
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Sophia Gläser, Carbon Tax Uncertainty Evidence from the Implied Volatility Surface, University of Zurich, Faculty of Business, Economics and Informatics, 2023. (Master's Thesis)
 
Climate policy uncertainty makes it difficult for investors to assess the impact of future climate
regulations. This thesis investigates how uncertainty about carbon taxation is priced in the option
market. The results show that the cost of protection against downside and jump risk is higher for
firms with high carbon intensity, and firms that do not report carbon emissions. The value of option
protection increases when attention to carbon taxation is high. |
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