Working Paper
Refine
Year of publication
- 2022 (126) (remove)
Document Type
- Working Paper (126) (remove)
Has Fulltext
- yes (126)
Is part of the Bibliography
- no (126)
Keywords
- Covid-19 (4)
- Digital Services Act (4)
- ESG (4)
- Digitalisierung (3)
- Mobilität (3)
- climate change (3)
- AI borrower classification (2)
- AI enabled credit scoring (2)
- Artificial Intelligence (2)
- Asset Pricing (2)
Institute
- Wirtschaftswissenschaften (99)
- Center for Financial Studies (CFS) (83)
- Sustainable Architecture for Finance in Europe (SAFE) (81)
- House of Finance (HoF) (69)
- Foundation of Law and Finance (24)
- Rechtswissenschaft (21)
- Institute for Monetary and Financial Stability (IMFS) (14)
- Exzellenzcluster Die Herausbildung normativer Ordnungen (6)
- Geographie (5)
- Gesellschaftswissenschaften (4)
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.
Consumers purchase energy in many forms. Sometimes energy goods are consumed directly, for instance, in the form of gasoline used to operate a vehicle, electricity to light a home, or natural gas to heat a home. At other times, the cost of energy is embodied in the prices of goods and services that consumers buy, say when purchasing an airline ticket or when buying online garden furniture made from plastic to be delivered by mail. Previous research has focused on quantifying the pass-through of the price of crude oil or the price of motor gasoline to U.S. inflation. Neither approach accounts for the fact that percent changes in refined product prices need not be proportionate to the percent change in the price of oil, that not all energy is derived from oil, and that the correlation of price shocks across energy markets is far from one. This paper develops a vector autoregressive model that quantifies the joint impact of shocks to several energy prices on headline and core CPI inflation. Our analysis confirms that focusing on gasoline price shocks alone will underestimate the inflationary pressures emanating from the energy sector, but not enough to overturn the conclusion that much of the observed increase in headline inflation in 2021 and 2022 reflected non-energy price shocks.
This paper examines optimal enviromental policy when external financing is costly for firms. We introduce emission externalities and industry equilibrium in the Holmström and Tirole (1997) model of corporate finance. While a cap-and- trading system optimally governs both firms` abatement activities (internal emission margin) and industry size (external emission margin) when firms have sufficient internal funds, external financing constraints introduce a wedge between these two objectives. When a sector is financially constrained in the aggregate, the optimal cap is strictly above the Pigouvian benchmark and emission allowances should be allocated below market prices. When a sector is not financially constrained in the aggregate, a cap that is below the Pigiouvian benchmark optimally shifts market share to less polluting firms and, moreover, there should be no "grandfathering" of emission allowances. With financial constraints and heterogeneity across firms or sectors, a uniform policy, such as a single cap-and-trade system, is typically not optimal.
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 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.
The Russian war of aggression against Ukraine since 24 February 2022 has intensified the discussion of Europe’s reliance on energy imports from Russia. A ban on Russian imports of oil, natural gas and coal has already been imposed by the United States, while the United Kingdom plans to cease imports of oil and coal from Russia by the end of 2022. The German Federal Government is currently opposing an energy embargo against Russia. However, the Federal Ministry for Economic Affairs and Climate Action is working on a strategy to reduce energy imports from Russia. In this paper, the authors give an overview of the German and European reliance on energy imports from Russia with a focus on gas imports and discuss price effects, alternative suppliers of natural gas, and the potential for saving and replacing natural gas. They also provide an overview of estimates of the consequences on the economic outlook if the conflict intensifies.
High-frequency changes in interest rates around FOMC announcements are an important tool for identifying the effects of monetary policy on asset prices and the macroeconomy. However, some recent studies have questioned both the exogeneity and the relevance of these monetary policy surprises as instruments, especially for estimating the macroeconomic effects of monetary policy shocks. For example, monetary policy surprises are correlated with macroeconomic and financial data that is publicly available prior to the FOMC announcement. The authors address these concerns in two ways: First, they expand the set of monetary policy announcements to include speeches by the Fed Chair, which essentially doubles the number and importance of announcements in our dataset. Second, they explain the predictability of the monetary policy surprises in terms of the “Fed response to news” channel of Bauer and Swanson (2021) and account for it by orthogonalizing the surprises with respect to macroeconomic and financial data. Their subsequent reassessment of the effects of monetary policy yields two key results: First, estimates of the high-frequency effects on financial markets are largely unchanged. Second, estimates of the macroeconomic effects of monetary policy are substantially larger and more significant than what most previous empirical studies have found.
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.
Mit dem Ziel, Erkenntnisse darüber zu gewinnen unter welchen Umständen verkehrspolitische Maßnahmen seitens der Bevölkerung befürwortet und angenommen werden, wurde im Hebst 2020 eine quantitative Haushaltsbefragung (N = 832) in vier Frankfurter Befragungsgebieten durchgeführt. Als Untersuchungsgegenstand wurde die Umwandlung von Auto- in Fahrradspuren ausgewählt – eine Maßnahme, die in Folge des Frankfurter Radentscheids entlang verschiedener Verkehrsachsen in Frankfurt geplant und teilweise bereits umgesetzt wurde. Dabei wurde deutlich, dass die Akzeptierbarkeit für die zukünftige Umsetzung einer solchen Maßnahme zur Neuaufteilung öffentlicher Räume in Frankfurt insgesamt sehr hoch ausfällt. Unter Heranziehung des stage model of self-regulated behavioural change (SSBC) konnte zudem aufgezeigt werden, dass sich eine starke Orientierung am Auto negativ auf die Höhe der Akzeptierbarkeit auswirkt, während eine regelmäßige Nutzung des Fahrrads höhere Zustimmungswerte für die Maßnahme hervorruft. In einem zweiten Schritt wurde weiterhin untersucht, inwiefern die bereits umgewandelten Radspuren zwischen der Alten Brücke am Main und dem Friedberger Platz im Frankfurter Nordend, eine Veränderung in der Wahrnehmung und Verkehrsmittelnutzung der Befragten begünstigen und somit auch wirksam sind. Dabei wurde mitunter ersichtlich, dass es seit der Umwandlung sowohl zu einer gesteigerten Fahrradnutzung als auch zu einer reduzierten Autonutzung entlang der umgewidmeten Strecke gekommen ist.
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.
With Big Data, decisions made by machine learning algorithms depend on training data generated by many individuals. In an experiment, we identify the effect of varying individual responsibility for the moral choices of an artificially intelligent algorithm. Across treatments, we manipulated the sources of training data and thus the impact of each individual’s decisions on the algorithm. Diffusing such individual pivotality for algorithmic choices increased the share of selfish decisions and weakened revealed prosocial preferences. This does not result from a change in the structure of incentives. Rather, our results show that Big Data offers an excuse for selfish behavior through lower responsibility for one’s and others’ fate.
In more and more situations, artificially intelligent algorithms have to model humans’ (social) preferences on whose behalf they increasingly make decisions. They can learn these preferences through the repeated observation of human behavior in social encounters. In such a context, do individuals adjust the selfishness or prosociality of their behavior when it is common knowledge that their actions produce various externalities through the training of an algorithm? In an online experiment, we let participants’ choices in dictator games train an algorithm. Thereby, they create an externality on future decision making of an intelligent system that affects future participants. We show that individuals who are aware of the consequences of their training on the pay- offs of a future generation behave more prosocially, but only when they bear the risk of being harmed themselves by future algorithmic choices. In that case, the externality of artificially intelligence training induces a significantly higher share of egalitarian decisions in the present.
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.
Biased auctioneers
(2022)
We construct a neural network algorithm that generates price predictions for art at auction, relying on both visual and non-visual object characteristics. We find that higher automated valuations relative to auction house pre-sale estimates are associated with substantially higher price-to-estimate ratios and lower buy-in rates, pointing to estimates’ informational inefficiency. The relative contribution of machine learning is higher for artists with less dispersed and lower average prices. Furthermore, we show that auctioneers’ prediction errors are persistent both at the artist and at the auction house level, and hence directly predictable themselves using information on past errors.
Lack of privacy due to surveillance of personal data, which is becoming ubiquitous around the world, induces persistent conformity to the norms prevalent under the surveillance regime. We document this channel in a unique laboratory---the widespread surveillance of private citizens in East Germany. Exploiting localized variation in the intensity of surveillance before the fall of the Berlin Wall, we show that, at the present day, individuals who lived in high-surveillance counties are more likely to recall they were spied upon, display more conformist beliefs about society and individual interactions, and are hesitant about institutional and social change. Social conformity is accompanied by conformist economic choices: individuals in high-surveillance counties save more and are less likely to take out credit, consistent with norms of frugality. The lack of differences in risk aversion and binding financial constraints by exposure to surveillance helps to support a beliefs channel.
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.
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.
We employ a proprietary transaction-level dataset in Germany to examine how capital requirements affect the liquidity of corporate bonds. Using the 2011 European Banking Authority capital exercise that mandated certain banks to increase regulatory capital, we find that affected banks reduce their inventory holdings, pre-arrange more trades, and have smaller average trade size. While non-bank affiliated dealers increase their market-making activity, they are unable to bridge this gap - aggregate liquidity declines. Our results are stronger for banks with a higher capital shortfall, for non-investment grade bonds, and for bonds where the affected banks were the dominant market-maker.
We develop a two-sector incomplete markets integrated assessment model to analyze the effectiveness of green quantitative easing (QE) in complementing fiscal policies for climate change mitigation. We model green QE through an outstanding stock of private assets held by a monetary authority and its portfolio allocation between a clean and a dirty sector of production. Green QE leads to a partial crowding out of private capital in the green sector and to a modest reduction of the global temperature by 0.04 degrees of Celsius until 2100. A moderate global carbon tax of 50 USD per tonne of carbon is 4 times more effective.
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.
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.
The great financial crisis and the euro area crisis led to a substantial reform of financial safety nets across Europe and – critically – to the introduction of supranational elements. Specifically, a supranational supervisor was established for the euro area, with discrete arrangements for supervisory competences and tasks depending on the systemic relevance of supervised credit institutions. A resolution mechanism was created to allow the frictionless resolution of large financial institutions. This resolution mechanism has been now complemented with a funding instrument.
While much more progress has been achieved than most observers could imagine 12 years ago, the banking union remains unfinished with important gaps and deficiencies. The experience over the past years, especially in the area of crisis management and resolution, has provided impetus for reform discussions, as reflected most lately in the Eurogroup statement of 16 June 2022.
This Policy Insight looks primarily at the current and the desired state of the banking union project. The key underlying question, and the focus here, is the level of ambition and how it is matched with effective legal and regulatory tools. Specifically, two questions will structure the discussions:
What would be a reasonable definition and rationale for a ‘complete’ banking union? And what legal reforms would be required to achieve it?
Banking union is a case of a new remit of EU-level policy that so far has been established on the basis of long pre-existing treaty stipulations, namely, Article 127(6) TFEU (for banking supervision) and Article 114 TFEU (for crisis management and deposit insurance). Could its completion be similarly carried out through secondary law? Or would a more comprehensive overhaul of the legal architecture be required to ensure legal certainty and legitimacy?
This paper studies the interactions between corporate law and VC exits by acquisitions, an increasingly common source of VC-related litigation. We find that transactions by VC funds under liquidity pressure are characterized by (i) a substantially lower sale price; (ii) a greater probability of industry outsiders as acquirers; (iii) a positive abnormal return for acquirers. These features indicate the existence of fire sales, which satisfy VCs' liquidation preferences but hurt common shareholders, leaving board members with conflicting fiduciary duties and litigation risks. Exploiting an important court ruling that establishes the board’s fiduciary duties to common shareholders as a priority, we find that after the ruling maturing VCs become less likely to exit by fire sales and they distribute cash to their investors less timely. However, VCs experience more difficult fundraising ex-ante, highlighting the potential cost of a common-favoring regime. Overall the evidence has important implications for optimal fiduciary duty design in VC-backed start-ups.
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.
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.
Energy efficiency represents one of the key planned actions aiming at reducing greenhouse emissions and the consumption of fossil fuel to mitigate the impact of climate change. In this paper, we investigate the relationship between energy efficiency and the borrower’s solvency risk in the Italian market. Specifically, we analyze a residential mortgage portfolio of four financial institutions which includes about 70,000 loans matched with the energy performance certificate of the associated buildings. Our findings show that there is a negative relationship between a building’s energy efficiency and the owner’s probability of default. Findings survive after we account for dwelling, household, mortgage, market control variables, and regional and year fixed effect. Additionally, a ROC analysis shows that there is an improvement in the estimation of the mortgage default probability when the energy efficiency characteristic is included as a risk predictor in the model.
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 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.
This policy note summarizes our assessment of financial sanctions against Russia. We see an increase in sanctions severity starting from (1) the widely discussed SWIFT exclusions, followed by (2) blocking of correspondent banking relationships with Russian banks, including the Central Bank, alongside secondary sanctions, and (3) a full blacklisting of the ‘real’ export-import flows underlying the financial transactions. We assess option (1) as being less impactful than often believed yet sending a strong signal of EU unity; option (2) as an effective way to isolate the Russian banking system, particularly if secondary sanctions are in place, to avoid workarounds. Option (3) represents possibly the most effective way to apply economic and financial pressure, interrupting trade relationships.
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.
Financial literacy affects wealth accumulation, and pension planning plays a key role in this relationship. In a large field experiment, we employ a digital pension aggregation tool to confront a treatment group with a simplified overview of their current pension claims across all pillars of the pension system. We combine survey and administrative bank data to measure the effects on actual saving behavior. Access to the tool decreases pension uncertainty for treated individuals. Average savings increase - especially for the financially less literate. We conclude that simplification of pension information can potentially reduce disparities in pension planning and savings behavior.
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.
Previous studies document a relationship between gambling activity at the aggregate level and investments in securities with lottery-like features. We combine data on individual gambling consumption with portfolio holdings and trading records to examine whether gambling and trading act as substitutes or complements. We find that gamblers are more likely than the average investor to hold lottery stocks, but significantly less likely than active traders who do not gamble. Our results suggest that gambling behavior across domains is less relevant compared to other portfolio characteristics that predict investing in high-risk and high-skew securities, and that gambling on and off the stock market act as substitutes to satisfy the same need, e.g., sensation seeking.
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.
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.
In the aftermath of the Wirecard scandal the German lead stock market index DAX has undergone a series of reforms, including the introduction of a profitability criterion based on EBITDA for new DAX members and enhanced financial reporting requirements with specified sanctions for non-compliance. Furthermore, DAX members need to adhere to certain provisions in the German Corporate Governance Code relating to audit committees. The final step of the reform was implemented in September 2021: the extension of the DAX from 30 to 40 constituents, with the ranking based solely on the free float market capitalisation. After one year of experience with the new design of the DAX, this paper concludes that the reform has strengthened the DAX in terms of diversification, quality and adaptability. However, there is still room for further improvement by introducing a minimum ESG score for DAX companies and thus making sustainability a relevant factor in the selection process. In addition, full compliance with the recommendations of the German Corporate Governance Code should be a condition for DAX companies. Furthermore, the profitability criterion should be applied on a continuous basis to ensure that loss-making companies can be excluded from the DAX after a grace period.
Im Januar 2020 änderte sich für viele Menschen die bis dahin gekannte Normalität durch das Aufkommen des Covid-19-Virus. Dies äußerte sich in einem gravierenden Einfluss auf die physische Mobilität und führte zu einer teilweisen Verlagerung in die virtuelle Mobilität. Angelehnt an die in dieser Arbeit dargestellten Forschungsansätze ist festzustellen, dass ein kausaler Zusammenhang zwischen eingeschränkter Mobilität und sozialer Exklusion von sozialer, politischer, ökonomischer sowie persönlicher Partizipation besteht. Diese Korrelation unter pandemischen Bedingungen wurde zum Zeitpunkt der Analyse kaum untersucht, weshalb es die Zielsetzung dieser Arbeit war, die Thematisierung der Einschränkungen mobilitätsbedingter sozialer Teilhabe durch die Covid-19-Pandemie im medialen Diskurs zu erörtern.
Die quantitative Analyse der drei Zeitungen Frankfurter Allgemeine Zeitung, Süddeutsche Zeitung und Die Zeit ergab, dass die mediale Auseinandersetzung mit dem Untersuchungsgegenstand nur einen marginalen Teil der Artikel prägt und damit eine Randnotiz der Gesellschaft darstellt. Die darauffolgende qualitative Inhaltsanalyse der thematisch passenden Zeitungsartikel lassen auf die Notwendigkeit einer Erweiterung der existierenden theoretischen Exklusionsdimensionen schließen. Grund dafür sind das Auftreten einer Infektionsangst sowie einer neuen Reichweite der Digitalisierung als grundlegende Exklusionsstrukturen während der Pandemie. Insbesondere in der Entscheidung um den Umgang mit dem ÖPNV spiegeln sich vielfältige gesellschaftliche Fragen um Sicherheit und Gesundheitsschutz, aber auch um soziale Teilhabe und Zugang.
The author proposes a Differential-Independence Mixture Ensemble (DIME) sampler for the Bayesian estimation of macroeconomic models.It allows sampling from particularly challenging, high-dimensional black-box posterior distributions which may also be computationally expensive to evaluate. DIME is a “Swiss Army knife”, combining the advantages of a broad class of gradient-free global multi-start optimizers with the properties of a Monte Carlo Markov chain (MCMC). This includes fast burn-in and convergence absent any prior numerical optimization or initial guesses, good performance for multimodal distributions, a large number of chains (the “ensemble”) running in parallel, an endogenous proposal density generated from the state of the full ensemble, which respects the bounds of the prior distribution. The author shows that the number of parallel chains scales well with the number of necessary ensemble iterations.
DIME is used to estimate the medium-scale heterogeneous agent New Keynesian (“HANK”) model with liquid and illiquid assets, thereby for the first time allowing to also include the households’ preference parameters. The results mildly point towards a less accentuated role of household heterogeneity for the empirical macroeconomic dynamics.
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.
For the academic audience, this paper presents the outcome of a well-identified, large change in the monetary policy rule from the lens of a standard New Keynesian model and asks whether the model properly captures the effects. For policymakers, it presents a cautionary tale of the dismal effects of ignoring basic macroeconomics. The Turkish monetary policy experiment of the past decade, stemming from a belief of the government that higher interest rates cause higher inflation, provides an unfortunately clean exogenous variance in the policy rule. The mandate to keep rates low, and the frequent policymaker turnover orchestrated by the government to enforce this, led to the Taylor principle not being satisfied and eventually a negative coeffcient on inflation in the policy rule. In such an environment, was the exchange rate still a random walk? Was inflation anchored? Does the “standard model”” suffice to explain the broad contours of macroeconomic outcomes in an emerging economy with large identifying variance in the policy rule? There are no surprises for students of open-economy macroeconomics; the answers are no, no, and yes.
In a parsimonious regime switching model, we find strong evidence that expected consumption growth varies over time. Adding inflation as a second variable, we uncover two states in which expected consumption growth is low, one with high and one with negative expected inflation. Embedded in a general equilibrium asset pricing model with learning, these dynamics replicate the observed time variation in stock return volatilities and stock- bond return correlations. They also provide an alternative derivation for a measure of time-varying disaster risk suggested by Wachter (2013), implying that both the disaster and the long-run risk paradigm can be extended towards explaining movements in the stock-bond correlation.
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.
The lichenicolous fungus Sarcogyne bicolor H. Magn. was recovered as an Acarospora and is given the replacement name, Acarospora destructans. It is reported new from New Mexico. Two new species of Acarospora are described from New Mexico, Acarospora eganiana and A. worthingtoniana. A form or variety of A. glaucocarpa is treated as a species, Sarcogyne melaniza, an apparently rare taxa in Europe.
We study liquidity provision by competitive high-frequency trading firms (HFTs) in a dynamic trading model with private information. Liquidity providers face adverse selection risk from trading with privately informed investors and from trading with other HFTs that engage in latency arbitrage upon public information. The impact of the two different sources of risk depends on the details of the market design. We determine equilibrium transaction costs in continuous limit order book (CLOB) markets and under frequent batch auctions (FBA). In the absence of informed trading, FBA dominates CLOB just as in Budish et al. (2015). Surprisingly, this result does no longer hold with privately informed investors. We show that FBA allows liquidity providers to charge markups and earn profits – even under risk neutrality and perfect competition. A slight variation of the FBA design removes the inefficiency by allowing traders to submit orders conditional on auction excess demand.
In vielen Städten werden gemeinschaftlicher Wohnprojekte in unterschiedlicher Weise gefördert, weil sie dauerhaft bezahlbares und sicheres Wohnen ermöglichen sowie positiv ins Quartier wirken (sollen). Mitunter kommt dabei die Frage auf, wie ein solcher Mehrwert für das Gemeinwohl bestimmt und wie die Projekte seitens der fördernden Kommune begleitet werden können. Mit diesen Fragen hat sich das Forschungsprojekt 'Gemeinschaftliches Wohnen als kommunales städtebauliches Instrument. Monitoring, Vernetzung und Auswertung gemeinschaftlichen Wohnens in Frankfurt am Main (GeWokosl)' in explorativer Weise befasst. Ziel war es einen Monitoring-Ansatz vorzubereiten, mit dessen Hilfe die Quartiersangebote städtisch geförderter gemeinschaftlicher Wohnprojekten erfasst und unterstützt werden sollen. Dazu wurden Interviews mit zuständigen Verwaltungen in Hamburg, Tübingen, Leipzig und Stuttgart sowie Gruppendiskussion mit sechs gemeinschaftlichen Wohnprojekten in Frankfurt am Main geführt. Ein Monitoring der Wirkungen in das Quartier wird von allen Beteiligten als eine Herausforderung gesehen, da es eine Erfassung der qualitativen projektspezifischen Dynamiken erfordert. Insgesamt zeigen die Interviewergebnisse mit den Stadtverwaltungen ein Spannungsfeld zwischen dem Wunsch, einen die Wohnprojekte unterstützenden Ansatz zu entwickeln und dem Anspruch, die gemeinwohlorientierten Beiträge der Projekte zu kontrollieren und zu steuern. Die Projekte fordern in diesem Kontext eine zuverlässige finanzielle Unterstützung für ihr soziales Engagement und den Ausbau der städtischen sozialen Infrastruktur. Das Forschungsvorhaben wurde als Kooperation zwischen der Stabsstelle Wohnungsmarkt, Mietrecht und innovative Wohnprojekte des Amtes für Wohnungswesen Frankfurt am Main sowie der Professur von Bernd Belina am Institut für Humangeographie der Goethe-Universität im Zeitraum von Mai 2021 bis Februar 2022 durchgeführt.
Peer effects can lead to better financial outcomes or help propagate financial mistakes across social networks. Using unique data on peer relationships and portfolio composition, we show considerable overlap in investment portfolios when an investor recommends their brokerage to a peer. We argue that this is strong evidence of peer effects and show that peer effects lead to better portfolio quality. Peers become more likely to invest in funds when their recommenders also invest, improving portfolio diversification compared to the average investor and various placebo counterfactuals. Our evidence suggests that social networks can provide good advice in settings where individuals are personally connected.
Veronika Grimm, Lukas Nöh, and Volker Wieland assess the possible development of government interest expenditures as a share of GDP for Germany, France, Italy and Spain. Until 2021, these and other member states could anticipate a further reduction of interest expenditure in the future. This outlook has changed considerably with the recent surge in inflation and government bond rates. Nevertheless, under reasonable assumptions current yield curves still imply that interest expenditure relative to GDP can be stabilized at the current level. The authors also review the implications of a further upward shift in the yield curves of 1 or 2 percentage points. These implications suggest significant medium-term risks for highly indebted member states with interest expenditure approaching or exceeding levels last observed on the eve of the euro area debt crisis. In light of these risks, governments of euro area member states should take substantive action to achieve a sustained decline in debt-to-GDP ratios towards safer levels. They bear the responsibility for making sure that government finances can weather the higher interest rates which are required to achieve price stability in the euro area.
The financial sector plays an important role in financing the green transformation of the European economy. A critical assessment of the current regulatory framework for sustainable finance in Europe leads to ambiguous results. Although the level of transparency on ESG aspects of financial products has been significantly improved, it is questionable whether the complex, mainly disclosure-oriented architecture is sufficient to mobilise more private capital into sustainable investments. It should be discussed whether a minimum Taxonomy ratio or Green Asset Ratio has to be fulfilled to market a financial product as “green”. Furthermore, because of the high complexity of the regulation, it could be helpful for the understanding of private investors to establish a simplified green rating, based on the Taxonomy ratio, to facilitate the selection of green financial products.
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.