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With free delivery of products virtually being a standard in E-commerce, product returns pose a major challenge for online retailers and society. For retailers, product returns involve significant transportation, labor, disposal, and administrative costs. From a societal perspective, product returns contribute to greenhouse gas emissions and packaging disposal and are often a waste of natural resources. Therefore, reducing product returns has become a key challenge. This paper develops and validates a novel smart green nudging approach to tackle the problem of product returns during customers’ online shopping processes. We combine a green nudge with a novel data enrichment strategy and a modern causal machine learning method. We first run a large-scale randomized field experiment in the online shop of a German fashion retailer to test the efficacy of a novel green nudge. Subsequently, we fuse the data from about 50,000 customers with publicly-available aggregate data to create what we call enriched digital footprints and train a causal machine learning system capable of optimizing the administration of the green nudge. We report two main findings: First, our field study shows that the large-scale deployment of a simple, low-cost green nudge can significantly reduce product returns while increasing retailer profits. Second, we show how a causal machine learning system trained on the enriched digital footprint can amplify the effectiveness of the green nudge by “smartly” administering it only to certain types of customers. Overall, this paper demonstrates how combining a low-cost marketing instrument, a privacy-preserving data enrichment strategy, and a causal machine learning method can create a win-win situation from both an environmental and economic perspective by simultaneously reducing product returns and increasing retailers’ profits.
Linear rational-expectations models (LREMs) are conventionally "forwardly" estimated as follows. Structural coefficients are restricted by economic restrictions in terms of deep parameters. For given deep parameters, structural equations are solved for "rational-expectations solution" (RES) equations that determine endogenous variables. For given vector autoregressive (VAR) equations that determine exogenous variables, RES equations reduce to reduced-form VAR equations for endogenous variables with exogenous variables (VARX). The combined endogenous-VARX and exogenous-VAR equations comprise the reduced-form overall VAR (OVAR) equations of all variables in a LREM. The sequence of specified, solved, and combined equations defines a mapping from deep parameters to OVAR coefficients that is used to forwardly estimate a LREM in terms of deep parameters. Forwardly-estimated deep parameters determine forwardly-estimated RES equations that Lucas (1976) advocated for making policy predictions in his critique of policy predictions made with reduced-form equations.
Sims (1980) called economic identifying restrictions on deep parameters of forwardly-estimated LREMs "incredible", because he considered in-sample fits of forwardly-estimated OVAR equations inadequate and out-of-sample policy predictions of forwardly-estimated RES equations inaccurate. Sims (1980, 1986) instead advocated directly estimating OVAR equations restricted by statistical shrinkage restrictions and directly using the directly-estimated OVAR equations to make policy predictions. However, if assumed or predicted out-of-sample policy variables in directly-made policy predictions differ significantly from in-sample values, then, the out-of-sample policy predictions won't satisfy Lucas's critique.
If directly-estimated OVAR equations are reduced-form equations of underlying RES and LREM-structural equations, then, identification 2 derived in the paper can linearly "inversely" estimate the underlying RES equations from the directly-estimated OVAR equations and the inversely-estimated RES equations can be used to make policy predictions that satisfy Lucas's critique. If Sims considered directly-estimated OVAR equations to fit in-sample data adequately (credibly) and their inversely-estimated RES equations to make accurate (credible) out-of-sample policy predictions, then, he should consider the inversely-estimated RES equations to be credible. Thus, inversely-estimated RES equations by identification 2 can reconcile Lucas's advocacy for making policy predictions with RES equations and Sims's advocacy for directly estimating OVAR equations.
The paper also derives identification 1 of structural coefficients from RES coefficients that contributes mainly by showing that directly estimated reduced-form OVAR equations can have underlying LREM-structural equations.
Large companies are increasingly on trial. Over the last decade, many of the world’s biggest firms have been embroiled in legal disputes over corruption charges, financial fraud, environmental damage, taxation issues or sanction violations, ending in convictions or settlements of record-breaking fines, well above the billion-dollar mark. For critics of globalization, this turn towards corporate accountability is a welcome sea-change showing that multinational companies are no longer above the law. For legal experts, the trend is noteworthy because of the extraterritorial dimensions of law enforcement, as companies are increasingly held accountable for activities independent of their nationality or the place of the activities. Indeed, the global trend required understanding the evolution of corporate criminal law enforcement in the United States in particular, where authorities have skillfully expanded its effective jurisdiction beyond its territory. This paper traces the evolution of corporate prosecutions in the United States. Analyzing federal prosecution data, it then shows that foreign firms are more likely to pay a fine, which is on average 6,6 times larger.
Im Zuge der fortlaufenden Digitalisierung im Mobilitätssektor werden aktuell besonders in Großstädten verstärkt geteilte on-demand Fahrdienstleistungen implementiert. Das sog. Ridepooling beschreibt eine dynamische und digitale Form des konventionellen Sammeltaxis, bei welcher durch eine intelligente Algorithmik mehrere voneinander unabhängige, zeitlich korrespondierende Fahrtwünsche in Echtzeit zu einer Route kombiniert werden. So können einander unbekannte Kund*innen gemeinsam und gleichzeitig nach ihren individuellen Bedürfnissen auf Direktverbindungen befördert werden. Viele der Ridepooling-Angebote werden in urban geprägten Raumstrukturen von privaten Verkehrsunternehmen - teilweise sogar eigenwirtschaftlich - betrieben und als nachhaltige Mobilitätsform beworben: Sie soll die sich individualisierenden Mobilitätsbedürfnisse der Bürger*innen befriedigen, dadurch städtische Problematiken wie hohe Luft- und Lärmbelastung, Staubildung sowie Flächenknappheit adressieren und zu einer umweltfreundlichen Verlagerung des lokalen Verkehrsaufkommens (Modal Shift) führen.
Die vorliegende Arbeit untersucht am Beispiel der Großstädte Berlin und Hamburg, wie und unter welchen Zielsetzungen der unterschiedlichen Akteure die neuen Angebotsformen implementiert wurden und welche Auswirkungen sie auf die städtischen Mobilitätssysteme haben.
Durch Expert*innen-Interviews mit städtischen Behörden, öffentlichen und privaten Verkehrsunternehmen, Verkehrsverbünden und Expert*innen für digitale und städtische Mobilität soll der aktuell noch geringe Forschungsstand über die Zielsetzungen, Formen und Auswirkungen von Ridepooling-Angeboten in städtischen Räumen um praxisnahe Betrachtungen und Erkenntnisse erweitert werden. Es kann angenommen werden, dass die unterschiedlichen Ausgestaltungen der untersuchten Angebote von ioki, CleverShuttle, MOIA und BerlKönig dabei durchaus voneinander differierende Effekte auf das Nutzungsverhalten der Kund*innen und die städtische Verkehrsgestaltung sowie deren ökologischen und sozialen Nachhaltigkeitsdimensionen haben.
Employing the art-collection records of Burton and Emily Hall Tremaine, we consider whether early-stage art investors can be understood as venture capitalists. Because the Tremaines bought artists’ work very close to an artwork’s creation, with 69% of works in our study purchased within one year of the year when they were made, their collecting practice can best be framed as venture-capital investment in art. The Tremaines also illustrate art collecting as social-impact investment, owing to their combined strategy of art sales and museum donations for which the collectors received a tax credit under US rules. Because the Tremaines’ museum donations took place at a time that U.S. marginal tax rates from 70% to 91%, the near “donation parity” with markets, creating a parallel to ESG investment in the management of multiple forms of value.
Central banks have faced a succession of crises over the past years as well as a number of structural factors such as a transition to a greener economy, demographic developments, digitalisation and possibly increased onshoring. These suggest that the future inflation environment will be different from the one we know. Thus uncertainty about important macroeconomic variables and, in particular, inflation dynamics will likely remain high.
This policy letter collects elementary economic statistics and provides a very basic look on Russian public finances (i) to inform the reader’s opinion on a possible planning process behind the war against Ukraine and (ii) to discuss prospects of an energy embargo and its capability to affect the stability of the Russian economy.
This note argues that in a situation of an inelastic natural gas supply a restrictive monetary policy in the euro zone could reduce the energy bill and therefore has additional merits. A more hawkish monetary policy may be able to indirectly use monopsony power on the gas market. The welfare benefits of such a policy are diluted to the extent that some of the supply (approximately 10 percent) comes from within the euro zone, which may give rise to distributional concerns.
We investigate whether the bank crisis management framework of the European banking union can effectively bar the detrimental influence of national interests in cross-border bank failures. We find that both the internal governance structure and decision making procedure of the Single Resolution Board (SRB) and the interplay between the SRB and national resolution authorities in the implementation of supranationally devised resolution schemes provide inroads that allow opposing national interests to obstruct supranational resolution. We also show that the Single Resolution Fund (SRG), even after the ratification of the reform of the European Stability Mechanism (ESM) and the introduction of the SRF backstop facility, is inapt to overcome these frictions. We propose a full supranationalization of resolution decision making. This would allow European authorities in charge of bank crisis management to operate autonomously and achieve socially optimal outcomes beyond national borders.
Spillovers of PE investments
(2022)
In this paper, we investigate a primary potential impact of leveraged buyout (LBOs) transactions: the effects of LBOs on the peers of the LBO target in the same industry. Using a data sample based on US LBO transactions between 1985 and 2016, we investigate the impact of the peer firms in the aftermath of the transaction, relative to non-peer firms. To account for potential endogeneity concerns, we employ a network-based instrumental variable approach. Based on this analysis, we find support for the proposition that LBOs do indeed matter for peer firms’ performance and corporate strategy relative to non-peer firms. Our study supports a learning factor hypothesis: peers gain by learning from the LBO target to improve their operational performance. Conversely, we find no evidence to support the conjecture that peers lose due to the increased competitiveness of the LBO target firm.
Common ownership and the (non-)transparency of institutional shareholdings: an EU-US comparison
(2022)
This paper compares the extent of common ownership in the US and the EU stock markets, with a particular focus on differences in the ap- plicable ownership transparency requirements. Most empirical research on common ownership to date has focused on US issuers, largely relying on ownership data obtained from institutional investors’ 13F filings. This type of data is generally not available for EU issuers. Absent 13F filings, researchers have to use ownership records sourced from mutual funds’ periodic reports and blockholder disclosures. Constructing a “reduced dataset” that seeks to capture only ownership information available for both EU and US issuers, I demonstrate that the “extra” ownership information introduced by 13F filings is substantial. However, even when taking differences in the transparency situation into due account, common ownership among listed EU firms is much less pronounced than among listed US firms by any measure. This is true even if the analysis is limited to non-controlled firms.
In the communication of the European Central Bank (ECB), the statement that „we act within our mandate“ is often referred to. Also among practitioners of the Eurosystem the term „mandate“ has become popular. In his Working Paper, Helmut Siekmann analyzes the legal foundation of the tasks and objectives of the Eurosysstem and price stability as a legal term. He finds that the primary law of the EU only very sparsely employs the term „mandate“. It is never used in the context of monetary policy and its institutions. Moreover, he comes to the conclusion that inflation targeting as a task, competence, or objective of the Eurosystem is legally highly questionable according to the common standards of interpretation.
Gegen den Landeshaushalt 2022 des Freistaats Thüringen bestehen nach Einschätzung von Helmut Siekmann erhebliche verfassungsrechtliche Bedenken. In einem Gutachten kommt Siekmann zu dem Schluss, dass sich die festgestellten globalen Minderausgaben im Vergleich zum gesamten Haushaltsvolumen nicht rechtfertigen lassen. Der verfassungsrechtlich gebotene Haushaltsausgleich sei nur dadurch erzielt worden, dass die eigentlich gebotenen Einzelkürzungen nicht vom Parlament entschieden, sondern der Exekutive überlassen worden seien. Durch Globale Minderausgaben soll der Ausgleich von Einnahmen und Ausgaben erreicht werden, ohne dafür erforderliche und politisch oft schwer durchsetzbare Kürzungen bei Einzeltiteln vornehmen zu müssen.
In Thüringen fehlen der Minderheitskoalition aus Linke, SPD und Grünen im Parlament vier Stimmen für eine eigene Mehrheit. Sie muss damit bei allen Entscheidungen eine Unterstützung der oppositionellen CDU aushandeln. Siekmann weist in seinem Gutachten darauf hin, dass die Veranschlagung von globalen Minderausgaben gleich welcher Art in keinem Fall die Exekutive ermächtigt, bestehende Verpflichtungen nicht zu erfüllen.
Today in the United States, the notion that ‘the rise of the far right’ poses the greatest threat to democratic values, and by extension, to the nation itself, has slowly entered into common sense. The antecedent of this development is the object of our study. Explored through the prism of what we refer to as the domestication of the War on Terror, this publication adopts and updates the theoretical approach first forwarded in Policing the Crisis: Mugging, the State, the Law and Order (Hall et al. 1978). Drawing on this seminal work, a sequence of three disparate media events are explored as they unfold in the United States in mid-2015: the rise of the Trump campaign; the release of an op-ed in The New York Times warning of a rise in right-wing extremsim; and a mass shooting at a historic African American church in Charleston, South Carolina. By the end of 2015, as these disparate events converge into what we call the public face of the rise of the far right phenomenon, we subsequently turn our attention to its origins in policing and the law in the wake of the global War on Terror and the Great Recession. It is only from there, that we turn our attention to the poltical class struggle as expressed in the rise of 'populism' on the one hand, and the domestication of the War on Terror on the other, and in doing so, attempt to situate the role of the rise of the far right phenomenon within it.
Socially responsible investing (SRI) continues to gain momentum in the financial market space for various reasons, starting with the looming effect of climate change and the drive toward a net-zero economy. Existing SRI approaches have included environmental, social, and governance (ESG) criteria as a further dimension to portfolio selection, but these approaches focus on classical investors and do not account for specific aspects of insurance companies. In this paper, we consider the stock selection problem of life insurance companies. In addition to stock risk, our model set-up includes other important market risk categories of insurers, namely interest rate risk and credit risk. In line with common standards in insurance solvency regulation, such as Solvency II, we measure risk using the solvency ratio, i.e. the ratio of the insurer’s market-based equity capital to the Value-at-Risk of all modeled risk categories. As a consequence, we employ a modification of Markowitz’s Portfolio Selection Theory by choosing the “solvency ratio” as a downside risk measure to obtain a feasible set of optimal portfolios in a three-dimensional (risk, return, and ESG) capital allocation plane. We find that for a given solvency ratio, stock portfolios with a moderate ESG level can lead to a higher expected return than those with a low ESG level. A highly ambitious ESG level, however, reduces the expected return. Because of the specific nature of a life insurer’s business model, the impact of the ESG level on the expected return of life insurers can substantially differ from the corresponding impact for classical investors.
Colocation services offered by stock exchanges enable market participants to achieve execution costs for large orders that are substantially lower and less sensitive to transacting against high-frequency traders. However, these benefits manifest only for orders executed on the colocated brokers' own behalf, whereas customers' order execution costs are substantially higher. Analyses of individual order executions indicate that customer orders originating from colocated brokers are less actively monitored and achieve inferior execution quality. This suggests that brokers do not make effective use of their technology, possibly due to agency frictions or poor algorithm selection and parameter choice by customers.
The authors focus on the stabilizing role of cash from a society-wide perspective. Starting with conceptual remarks on the importance of money for the economy in general, special attention is paid to the unique characteristics of cash. As these become apparent especially during crisis periods, a comparison of the Great Depression (1929 – 1933) and the Great Recession 2008/09 shows the devastating effects of a severe monetary contraction and how a fully elastic provision of cash can help to avoid such a situation.
The authors find interesting similarities to both crises in two separate case studies, one on the demonetization in India 2016 and the other on cash supply during various crises in Greece since 2008. The paper concludes that supply-driven cash withdrawals from circulation (either by demonetization or by capital controls) destabilize the economy if electronic payment substitutes are not instantly available.
However, as there is no perfect substitute for cash due to its unique properties, from the viewpoint of the society as a whole an efficient payment mix necessarily includes cash: It helps to stabilize the economy not only in times of crises in general, no matter which government is in place. The authors argue that it should be the undisputed task of central banks to ensure that cash remains in circulation in normal times and is provided in a fully elastic way in times of crisis.
The transition to a sustainable economy currently involves a fundamental transformation of our capital markets. Lawmakers, in an attempt to overcome this challenge, frequently seek to prescribe and regulate how firms may address environmental, social, and governance (ESG) concerns by formulating conduct standards. Deviating from this conceptual starting point, the present paper makes the case for another path towards achieving greater sustainability in capital markets, namely through the empowerment of investors.
This trust in the market itself is grounded in various recent developments both on the supply side and the demand side of financial markets, and also in the increasing tendency of institutional investors to engage in common ownership. The need to build coalitions among different types of asset managers or institutional investors, and to convince fellow investors of a given initiative, can then act as an in-built filter helping to overcome the pursuit of idiosyncratic motives and supporting only those campaigns that are seconded by a majority of investors. In particular, institutionalized investor platforms have emerged over recent years as a force for investor empowerment, serving to coordinate investor campaigns and to share the costs of engagement.
ESG engagement has the potential to become a very powerful driver towards a more sustainability-oriented future. Indeed, I show that investor-led sustainability has many advantages compared to a more prescriptive, regulatory approach where legislatures are in the driver’s seat. For example, a focus on investor-led priorities would follow a more flexible and dynamic pattern rather than complying with inflexible pre-defined criteria. Moreover, investor-promoted assessments are not likely to impair welfare creation in the same way as ill-defined legal standards; they will also not trigger regulatory arbitrage and would avoid deadlock situations in corporate decision-making. Any regulatory activity should then be limited to a facilitative and supportive role.
Despite the impressive success of deep neural networks in many application areas, neural network models have so far not been widely adopted in the context of volatility forecasting. In this work, we aim to bridge the conceptual gap between established time series approaches, such as the Heterogeneous Autoregressive (HAR) model (Corsi, 2009), and state-of-the-art deep neural network models. The newly introduced HARNet is based on a hierarchy of dilated convolutional layers, which facilitates an exponential growth of the receptive field of the model in the number of model parameters. HARNets allow for an explicit initialization scheme such that before optimization, a HARNet yields identical predictions as the respective baseline HAR model. Particularly when considering the QLIKE error as a loss function, we find that this approach significantly stabilizes the optimization of HARNets. We evaluate the performance of HARNets with respect to three different stock market indexes. Based on this evaluation, we formulate clear guidelines for the optimization of HARNets and show that HARNets can substantially improve upon the forecasting accuracy of their respective HAR baseline models. In a qualitative analysis of the filter weights learnt by a HARNet, we report clear patterns regarding the predictive power of past information. Among information from the previous week, yesterday and the day before, yesterday's volatility makes by far the most contribution to today's realized volatility forecast. Moroever, within the previous month, the importance of single weeks diminishes almost linearly when moving further into the past.
The article studies civil wars and trust dynamics from two perspectives. It looks, first, at rebel governance during ongoing armed conflict and, second, at mass mobilisation against the regime in post-conflict societies. Both contexts are marked by extraordinarily high degrees of uncertainty given continued, or collective memory of, violence and repression.
But what happens to trust relations under conditions of extreme uncertainty? Intuitively, one would assume that trust is shaken or even substantially eroded in such moments, as political and social orders are questioned on a fundamental level and threaten to collapse. However, while it is true that some forms of trust are under assault in situations of civil war and mass protests, we find empirical evidence which suggests that these situations also give rise to the formation of other kinds of trust. We argue that, in order to detect and explain these trust dynamics in contexts of extreme uncertainty, there should be more systematic studies of: (a) synchronous dynamics between different actors and institutions which imply trust dynamics happening simultaneously, (b) diachronous dynamics and the sequencing of trust dynamics over several phases of violent conflict or episodes of contention, as well as long-term structural legacies of the past. In both dimensions, microlevel relations, as well as their embeddedness in larger structures, help explain how episodes of (non-)violent contention become a critical juncture for political and social trust.
Der Beitrag stellt dar, wie Online-Plattformen in den Bereichen Urheberrecht, Hassrede und Desinformation in der EU reguliert wurden. Die Analyse ergibt einen Regulierungskreislauf, der in vier Phasen ablief. Bis zum Jahrtausendwechsel war es die Legislative, die einen allgemeinen gesetzlichen Rahmen für die Online-Kommunikation in Gestalt von Äußerungsverboten und Haftungsprivilegierungen definierte. Dieser Rahmen wurde im folgenden Jahrzehnt von den Betreibern der neu entstehenden Plattformen unter Ausnutzung ihres privatautonomen Gestaltungsspielraums implementiert. In der dritten Phase ab ca. 2010 verschärften die Judikative und die Exekutive die sich aus dem allgemeinen gesetzlichen Rahmen ergebenden Mindestanforderungen an die Bekämpfung von Urheberrechtsverletzungen, Hassrede und Desinformation. In der vorläufig letzten Phase des Regulierungskreislaufs ab 2017/2018 ergriff wieder der Gesetzgeber die Initiative, indem die Standards, die in den Phasen zwei und drei entwickelt worden waren, kodifiziert und teilweise nochmals angehoben wurden. Damit ist der Kreislauf der unionalen Plattformregulierung allerdings nicht zu seinem Ende gekommen. Vielmehr ist bereits erkennbar, dass sich nun wieder eine eher experimentell-tastende Phase privatautonomer Implementierung und ko-regulativer Fortentwicklung des neuen gesetzlichen Rahmens anschließt. Der Beitrag schließt mit einer kurzen Bewertung dieser Entwicklung hin zu mehr hoheitlicher Kommunikationskontrolle.
In den letzten zwei Jahrzehnten sind Anmeldungen von Rechten des geistigen Eigentums (intellectual property, IP) bzw. Verletzungsklagen wiederholt an der unzureichenden Bestimmtheit des exklusiv beanspruchten Gegenstands gescheitert. Ihren Ausgang nahm diese Entwicklung im Markenrecht mit Entscheidungen des EuGH (Stichworte: Sieckmann, Heidelberger Bauchemie, Dyson, IP Translator, Oy Hartwall) und später auch des BGH (Stichwort: UHU). Die markenrechtlichen Grundsätze strahlten auf das Designrecht (Stichworte: Sporthelm, Mast-Jägermeister) und zuletzt auch auf das Urheberrecht (Stichwort: Levola) aus. Im Folgenden werden die maßgeblichen Urteile zur Schutzfähigkeit von Zeichen, Designs und Werken zusammengetragen und systematisiert. Dabei treten zwei Aspekte eines Bestimmtheitsgebots zu Tage, die, wie abschließend zu zeigen sein wird, auch im Patentrecht gelten
Der Beitrag nimmt kritisch zum gegenwärtig anhängigen EU-Gesetz über digitale Dienste (Digital Services Act, DSA) Stellung. Die Kernthese lautet: Big Tech muss reguliert werden, aber nicht wie im DSA vorgesehen. Zur Untermauerung dieser Position werden fünf grundlegend problematische Aspekte des DSA benannt. Es wird gezeigt, dass die derzeit verhandelten Fassungen des DSA (1) die Vertragsfreiheit nicht kommunikationsmächtiger Vermittlungsdienste missachten, (2) automatisiertes Overblocking begünstigen, (3) auch legale, aber in unspezifischer Weise „schädliche“ Äußerungen ins Visier nehmen, (4) einen vagen und für die Kommunikationsregulierung generell unpassenden Risikopräventionsansatz verfolgen und (5) eine Kommunikationsüberwachungsbürokratie errichten, die ihrerseits keinen zureichenden öffentlich-demokratischen Kontrollen unterliegt. Als Reaktion auf diese Befunde wird vorgeschlagen, (1) nur sehr großen Online-Plattformen inhaltliche Vorgaben im Hinblick auf ihre AGB zu machen, (2) die Verpflichtung/Berechtigung zum Einsatz automatischer Moderationssysteme auf offensichtlich rechtswidrige Inhalte zu beschränken, (3) im DSA auch keine indirekten Pflichten zur Unterdrückung legaler, aber „schädlicher“ Inhalte vorzusehen, (4) das systemische Risiko des Art. 26 Abs. 1 Buchst. c DSA ersatzlos zu streichen und (5) die DSA-Bürokratie staatsfern auszugestalten und einer parlamentarischen Kontrolle zu unterwerfen.
Der Beitrag bietet eine Übersicht der unionalen und deutschen Rechtsbegriffe zur Bezeichnung von Diensten im Bereich der Informations- und Kommunikationstechnik (IKT). Neben Rechtsquellen der ersten Regulierungsgeneration (insbes. E-Commerce- und InfoSoc-Richtlinie) werden 26 Gesetze bzw. Gesetzesvorschläge aus den letzten fünf Jahren in die Bestandsaufnahme einbezogen. Die einzelnen Dienstebegriffe werden erläutert und nach Maßgabe ihrer technisch-sozialen Funktion klassifiziert. Die vergleichende Analyse arbeitet Unterschiede und Überschneidungen sowie allgemeine dogmatische Grundsätze heraus, etwa zur Beurteilung multifunktionaler Dienste. Besonderes Augenmerk gilt Diensten wie sozialen Netzwerken und Messengern, deren juristische Einordnung ungeklärt ist. Der Beitrag schließt mit begrifflichen Reformvorschlägen für das künftige Digitalrecht.
Der Beitrag bietet einen Überblick über den entstehungsgeschichtlichen Hintergrund sowie den Inhalt des ursprünglichen Netzwerkdurchsetzungsgesetzes (NetzDG) 2017, seine Wirkungen in der Praxis und die Änderungen durch die NetzDG-Reform 2021. Es wird gezeigt, dass aus einem Regelwerk mit engem Fokus auf die Durchsetzung des Strafrechts in OnlineNetzwerken ein Plattformregulierungsgesetz wurde, das sowohl Löschgebote (Strafrecht) als auch Löschverbote (Meinungsfreiheit) prozeduralisiert. Während das NetzDG 2017 keinen nennenswerten Niederschlag in gerichtlichen oder behördlichen Entscheidungen fand und inzwischen auch kaum noch eine Rolle in der Löschpraxis der Netzwerke spielt, dürfte es dazu beigetragen haben, dass die Netzwerkbetreiber ihre privaten Kommunikationsregeln verschärft haben. Hintergrund für diese „Flucht in die AGB“ ist, dass die großen Netzwerkbetreiber und der Gesetzgeber dasselbe Nahziel verfolgen: Einer Verrohung der Debattenkultur soll aus ökonomischen bzw. gesellschaftspolitischen Gründen entgegengewirkt werden. Der Beitrag schließt mit einem Ausblick auf den Digital Services Act (DSA), mit dem der Compliance-Ansatz des NetzDG europäisiert würde.
The sixth sanction package of the European Union in the context of the aggression against Ukraine excludes Sberbank, the largest Russian bank, from the SWIFT network. The increasing use of SWIFT as a tool for sanctions stimulates the rollout of alternative payment information systems by the governments of Russia and China. This policy white paper informs about the alternatives at hand, as well as their advantages and disadvantages. Careful reflection about these issues is particularly important, given the call for an “Economic Article 5” tabled for the next NATO meeting. Finally, the white paper highlights the need for institutional reforms, if policymakers decide to return SWIFT to the status of a global public good after the war.
We provide the first comprehensive analysis of option information for pricing the cross-section of stock returns by jointly examining extensive sets of firm and option characteristics. Using portfolio sorts and high-dimensional methods, we show that certain option measures have significant predictive power, even after controlling for firm characteristics, earning a Fama-French three-factor alpha in excess of 20% per annum. Our analysis further reveals that the strongest option characteristics are associated with information about asset mispricing and future tail return realizations. Our findings are consistent with models of informed trading and limits to arbitrage.
We investigate the link between Big Five personality traits and the marginal propensity to consume (MPC) for users of a German financial account aggregator app. We use 1,700 survey responses and transaction data of 56,000 app users to assess whether Big Five personality traits help explain MPC heterogeneity. We find that extraversion corresponds to an increase in consumption whereas agreeableness and neuroticism correspond to a decrease in consumption. We test this with trust and risk preferences and find that risk indicates more explanatory power in consumption response than the Big Five. Our findings help policy makers target individuals more efficiently.
With open banking, consumers take greater control over their own financial data and share it at their discretion. Using a rich set of loan application data from the largest German FinTech lender in consumer credit, this paper studies what characterizes borrowers who share data and assesses its impact on loan application outcomes. I show that riskier borrowers share data more readily, which subsequently leads to an increase in the probability of loan approval and a reduction in interest rates. The effects hold across all credit risk profiles but are the most pronounced for borrowers with lower credit scores (a higher increase in loan approval rate) and higher credit scores (a larger reduction in interest rate). I also find that standard variables used in credit scoring explain substantially less variation in loan application outcomes when customers share data. Overall, these findings suggest that open banking improves financial inclusion, and also provide policy implications for regulators engaged in the adoption or extension of open banking policies.
Many people do not understand the concepts of life expectancy and longevity risk, potentially leading them to under-save for retirement or to not purchase longevity insurance, which in turn could reduce wellbeing at older ages. We investigate alternative ways to increase the salience of both concepts, allowing us to assess whether these change peoples’ perceptions and financial decision making. Using randomly-assigned vignettes providing subjects with information about either life expectancy or longevity, we show that merely prompting people to think about financial decisions changes their perceptions regarding subjective survival probabilities. Moreover, this information also boosts respondents’ interest in saving and demand for longevity insurance. In particular, longevity information influences both subjective survival probabilities and financial decisions, while life expectancy information influences only annuity choices. We provide some evidence that many people are simply unaware of longevity risk.
The authors propose a new method to forecast macroeconomic variables that combines two existing approaches to mixed-frequency data in DSGE models. The first existing approach estimates the DSGE model in a quarterly frequency and uses higher frequency auxiliary data only for forecasting. The second method transforms a quarterly state space into a monthly frequency. Their algorithm combines the advantages of these two existing approaches.They compare the new method with the existing methods using simulated data and real-world data. With simulated data, the new method outperforms all other methods, including forecasts from the standard quarterly model. With real world data, incorporating auxiliary variables as in their method substantially decreases forecasting errors for recessions, but casting the model in a monthly frequency delivers better forecasts in normal times.
The authors present and compare Newton-based methods from the applied mathematics literature for solving the matrix quadratic that underlies the recursive solution of linear DSGE models. The methods are compared using nearly 100 different models from the Macroeconomic Model Data Base (MMB) and different parameterizations of the monetary policy rule in the medium-scale New Keynesian model of Smets and Wouters (2007) iteratively. They find that Newton-based methods compare favorably in solving DSGE models, providing higher accuracy as measured by the forward error of the solution at a comparable computation burden. The methods, however, suffer from their inability to guarantee convergence to a particular, e.g. unique stable, solution, but their iterative procedures lend themselves to refining solutions either from different methods or parameterizations.
Der Koalitionsvertrag 2021 sieht eine generationengerechte Absicherung des Rentenniveaus durch eine teilweise aus Haushaltsmitteln finanzierte Kapitaldeckung vor. Um dieses Ziel zu verwirklichen, wird hier die Einführung einer Generationenrente ab Geburt vorgeschlagen. Dabei wird aus Haushaltsmitteln ein Betrag von € 5.000 für jedes Neugeborene nach Grundsätzen des professionellen Anlagemanagements am globalen Kapitalmarkt angelegt. Konzeptionell soll sich diese Generationenrente am Modell der Basisrente(§10 Abs. 1 Nr. 2 b EStG) orientieren, d.h. die akkumulierten Gelder sind weder beleihbar, vererbbar noch übertragbar und können frühestens ab Alter 63 zugunsten einer lebenslangen Monatsrente verwendet werden. Unsere Berechnungen zeigen, dass durch die hier vorgeschlagene Generationenrente unabhängig vom Verlauf der individuellen Erwerbsbiographie, Altersarmut für die vom demographischen Wandel besonders betroffenen zukünftigen Generationen vermieden wird.
In times of increased political polarization, the continuing existence of a deliberative arena where people with antagonistic views may engage with each other in non-violent ways is critical for democracy to live on. Social media are usually not conceived as such arenas. On the contrary, there has been widespread worry about their role in increasing polarization and political violence. This paper suggests a more positive impact of social media on democracy. Our analysis focuses on the subreddit “r/WallStreetBets” (r/WSB) - a finance-related forum that came under the spotlight when its users coordinated a financial attack on hedge funds during the Gamestop saga in early 2021. Based on an original method attributing partisanship scores to users, we present a network analysis of interactions between users at the opposite sides of the political spectrum on r/WSB. We then develop a content analysis of politically relevant threads in which polarized users participate. Our analyses show that r/WSB provides a rare space where users with antagonistic political leanings engage with each other, debate, and even cooperate.
The European Central Bank (ECB) recently proclaimed a more active role for itself in the fight against climate change. Did the European Parliament (EP) play a part in this regard, and if so what was it? To answer this question, this paper builds on a multi-method text analysis of original datasets compiling communications between the ECB and the EP across three accountability forums between 2014 and 2021. The paper shows that there has been discursive convergence between central bankers and parliamentarians concerning the role of the ECB in combatting climate change. It argues that this convergence has resulted from a pragmatic (yet precarious) adoption of a common repertoire1 between ‘green’ central bankers and parliamentarians who have favored a more active role for the ECB in the fight against climate change. The adoption of a common repertoire is pragmatic, in that it results from the strategic use of specific discursive elements that are ambitious enough to address their respective opponents and trigger political change, yet vague enough to allow both sets of actors to converge on them momentarily. It is also precarious in the sense that it involves discarding fundamental political tensions, which is hardly tenable in the long term. The paper shows that both organizational and politicization dynamics have been at work in the emergence of this pragmatic yet precarious bedfellowship between ‘green’ central bankers and parliamentarians.
he ECB is independent, but it is also accountable to the European parliament (EP). Yet, how the EP has held the ECB accountable has largely been overlooked. This paper starts addressing this gap by providing descriptive statistics of three accountability modalities. The paper highlights three findings. First, topics of accountability have changed. Climate-related accountability has increased quickly and dramatically since 2017. Second, if the relationship between price stability and climate change remains an object of conflict among MEPs, a majority within the EP has emerged to put pressure for the ECB to take a more active stance against climate change, precisely on behalf of its price stability mandate. Third, MEPs engage with the climate topic in very specific ways. There is a gender divide between the climate and the price stability topics. Women engage more actively with climate-related topics. While the Greens heavily dominate the climate topic, parties from the Right dominate the topic of Price stability. Finally, MEPs adopt a more united strategy and a particularly low confrontational tone in their climate-related interventions.
Since the 2008 financial crisis, European largest banks’ size and business models have largely remained unchallenged. Is that because of banks’ continued structural power over States? This paper challenges the view that States are sheer hostages of banks’ capacity to provide credit to the real economy – which is the conventional definition of structural power. Instead, it sheds light on the geo-economic dimension of banks’ power: key public officials conceive the position of “their own” market-based banks in global financial markets as a crucial dimension of State power. State priority towards banking thus result from political choices over what structurally matters the most for the State. Based on a discourse analysis of parliamentary debates in France, Germany and Spain between 2010 and 2020 as well as on a comparative analysis of the implementation of a special tax on banks in the early 2010s, this paper shows that State’s Finance ministries tend to prioritize geo-economic considerations over credit to firms. By contrast, Parliaments tend to prioritize investment. Power dynamics within the State thus largely shape political priorities towards banking at the domestic and international levels.
Are we in a new “Polanyian moment”? If we are, it is essential to examine how “spontaneous” and punctual expressions of discontent at the individual level may give rise to collective discourses driving social and political change. It is also important to examine whether and how the framing of these discourses may vary across political economies. This paper contributes to this endeavor with the analysis of anti-finance discourses on Twitter in France, Germany, Italy, Spain and the UK between 2019 and 2020. This paper presents three main findings. First, the analysis shows that, more than ten years after the financial crisis, finance is still a strong catalyzer of political discontent. Second, it shows that there are important variations in the dominant framing of public anti-finance discourses on social media across European political economies. If the antagonistic “us versus them” is prominent in all the cases, the identification of who “us” and “them” are, vary significantly. Third, it shows that the presence of far-right tropes in the critique of finance varies greatly from virtually inexistent to a solid minority of statements.
There have been numerous attempts to reform the Economic and Monetary Union (EMU) after the Great Recession, however the reform success varies greatly among sub-fields. Additionally, the political science research community has engaged a diverse set of theory- driven explanations, causal mechanisms, and variables to explain respective reform success. This article takes stock of reform policies in the EMU from two angles. First, it outlines distinct theoretical approaches that seek to explain success and failure of reform proposals and second, it surveys how they explain policy output and policy outcome in four policy subfields: financial stabilization, economic governance, financial solidarity, and cooperative dissolution. Finally, the article develops a set of explanatory factors from the existing literature that will be used for a Qualitative Comparative Analysis (QCA).
This article compares the three initial safety nets spanned by the European Union in response to the Covid-19 crisis: SURE, the Pandemic Crisis Support, and the European Guarantee Fund. It compares their design regarding scope, generosity, target groups, implementation, the types of solidarity and conditionality, and asks how they reflect on core-periphery relations in the EU. The article finds that the most important factor in all three instruments is risk-sharing between member states, even though SURE and the EGF display elements of fiscal solidarity. Finally, the article shows that Euro crisis countries from the South are the main recipients of financial aid, while Central and East European countries receive significantly less assistance and core countries in the North and West have no need for them.
Financial ties between drug companies and medical researchers are thought to bias results published in medical journals. To enable readers to account for such bias, most medical journals require authors to disclose potential conflicts of interest. For such policies to be effective, conflict disclosure must modify readers’ beliefs. We therefore examine whether disclosure of financial ties with industry reduces article citations, indicating a discount. A challenge to estimating this effect is selection as drug companies may seek out higher quality authors as consultants or fund their studies, generating a positive correlation between disclosed conflicts and citations. Our analysis confirms this positive association. Including observable controls for article and author quality attenuates but does not eliminate this relation. To tease out whether other researchers discount articles with conflicts, we perform three tests. First, we show that the positive association is weaker for review articles, which are more susceptible to bias. Second, we examine article recommendations to family physicians by medical experts, who choose from articles that are a priori more homogenous in quality. Here, we find a significantly negative association between disclosure and expert recommendations, consistent with discounting. Third, we conduct an analysis within author and article, exploiting journal policy changes that result in conflict disclosure by an author. We examine the effect of this disclosure on citations to a previously published article by the same author. This analysis reveals a negative citation effect. Overall, we find evidence that disclosures negatively affect citations, consistent with the notion that other researchers discount articles with disclosed conflicts.
We analyze how market fragmentation affects market quality of SME and other less actively traded stocks. Compared to large stocks, they are less likely to be traded on multiple venues and show, if at all, low levels of fragmentation. Concerning the impact of fragmentation on market quality, we find evidence for a hockey stick effect: Fragmentation has no effect for infrequently traded stocks, a negative effect on liquidity of slightly more active stocks, and increasing benefits for liquidity of large and actively traded stocks. Consequently, being traded on multiple venues is not necessarily harmful for SME stock market quality.
Search costs for lenders when evaluating potential borrowers are driven by the quality of the underwriting model and by access to data. Both have undergone radical change over the last years, due to the advent of big data and machine learning. For some, this holds the promise of inclusion and better access to finance. Invisible prime applicants perform better under AI than under traditional metrics. Broader data and more refined models help to detect them without triggering prohibitive costs. However, not all applicants profit to the same extent. Historic training data shape algorithms, biases distort results, and data as well as model quality are not always assured. Against this background, an intense debate over algorithmic discrimination has developed. This paper takes a first step towards developing principles of fair lending in the age of AI. It submits that there are fundamental difficulties in fitting algorithmic discrimination into the traditional regime of anti-discrimination laws. Received doctrine with its focus on causation is in many cases ill-equipped to deal with algorithmic decision-making under both, disparate treatment, and disparate impact doctrine. The paper concludes with a suggestion to reorient the discussion and with the attempt to outline contours of fair lending law in the age of AI.
Search costs for lenders when evaluating potential borrowers are driven by the quality of the underwriting model and by access to data. Both have undergone radical change over the last years, due to the advent of big data and machine learning. For some, this holds the promise of inclusion and better access to finance. Invisible prime applicants perform better under AI than under traditional metrics. Broader data and more refined models help to detect them without triggering prohibitive costs. However, not all applicants profit to the same extent. Historic training data shape algorithms, biases distort results, and data as well as model quality are not always assured. Against this background, an intense debate over algorithmic discrimination has developed. This paper takes a first step towards developing principles of fair lending in the age of AI. It submits that there are fundamental difficulties in fitting algorithmic discrimination into the traditional regime of anti-discrimination laws. Received doctrine with its focus on causation is in many cases ill-equipped to deal with algorithmic decision-making under both, disparate treatment, and disparate impact doctrine. The paper concludes with a suggestion to reorient the discussion and with the attempt to outline contours of fair lending law in the age of AI.
We collect data on the size distribution of all U.S. corporate businesses for 100 years. We document that corporate concentration (e.g., asset share or sales share of the top 1%) has increased persistently over the past century. Rising concentration was stronger in manufacturing and mining before the 1970s, and stronger in services, retail, and wholesale after the 1970s. Furthermore, rising concentration in an industry aligns closely with investment intensity in research and development and information technology. Industries with higher increases in concentration also exhibit higher output growth. The long-run trends of rising corporate concentration indicate increasingly stronger economies of scale.
This paper provides a review of the development of the non-fungible tokens (NFTs) market, with a particular focus on its pricing determinants, its current applications and future opportunities. We investigate the current state of the NFT markets and highlight the perception and expectations of investors towards these products. We summarize and compare the financial and econometric models that have been used in the literature for the pricing of non-fungible tokens with a special focus on their predictive performance. Our intention is to design a framework that can help understanding the price formation of NFTs. We further aim to shed light on the value creating determinants of NFTs in order to better understand the investors’ behavior on the blockchain.
Venture capital (VC) funds backed by large multi-fund families tend to perform substantially better due to cross-fund cash flows (CFCFs), a liquidity support mechanism provided by matching distributions and capital calls within a VC fund family. The dynamics of this mechanism coincide with the sensitivity of different stage projects owing to market liquidity conditions. We find that the early-stage funds demand relatively more intra-family CFCFs than later-stage funds during liquidity stress periods. We show that the liquidity improvement based on the timing of CFCF allocation reflects how fund families arrange internal liquidity provision and explains a large part of their outperformance.
This study examines the recent literature on the expectations, beliefs and perceptions of investors who incorporate Environmental, Social, Governance (ESG) considerations in investment decisions with the aim to generate superior performance and also make a societal impact. Through the lens of equilibrium models of agents with heterogeneous tastes for ESG investments, green assets are expected to generate lower returns in the long run than their non- ESG counterparts. However, at the short run, ESG investment can outperform non-ESG investment through various channels. Empirically, results of ESG outperformance are mixed. We find consensus in the literature that some investors have ESG preference and that their actions can generate positive social impact. The shift towards more sustainable policies in firms is motivated by the increased market values and the lower cost of capital of green firms driven by investors’ choices.
This paper characterizes the stationary equilibrium of a continuous-time neoclassical production economy with capital accumulation in which households can insure against idiosyncratic income risk through long-term insurance contracts. Insurance companies operating in perfectly competitive markets can commit to future contractual obligations, whereas households cannot. For the case in which household labor productivity takes two values, one of which is zero, and where households have logutility we provide a complete analytical characterization of the optimal consumption insurance contract, the stationary consumption distribution and the equilibrium aggregate capital stock and interest rate. Under parameter restrictions, there is a unique stationary equilibrium with partial consumption insurance and a stationary consumption distribution that takes a truncated Pareto form. The unique equilibrium interest rate (capital stock) is strictly decreasing (increasing) in income risk. The paper provides an analytically tractable alternative to the standard incomplete markets general equilibrium model developed in Aiyagari (1994) by retaining its physical structure, but substituting the assumed incomplete asset markets structure with one in which limits to consumption insurance emerge endogenously, as in Krueger and Uhlig (2006).
Large technology firms («BigTechs») increasingly extend their influence in finance, primarily taking over market shares in payment services. A further expansion of their businesses into the territory of cryptocurrencies could entail new and unprecedented risks for the future, namely for financial stability, competition in the private sector and monetary policy. When creating a regulatory toolbox to address these risks, financial regulatory, antitrust, and platform-specific solutions should be closely intertwined in order to fully absorb all the potential threats and to take account of the complex risks these platform companies bear. This policy letter evaluates the solutions lately proposed by the European Commission, with specific focus on the upcoming regulation of Markets in crypto-assets (MiCA), but also the Digital Markets Act (DMA) and Digital services act (DSA), against the background of cryptocurrencies issued by BigTechs and sheds light on financial regulatory, competition and monetary law issues coming along with the possible designs of these cryptocurrencies.