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Global consensus is growing on the contribution that corporations and finance must make towards the net-zero transition in line with the Paris Agreement goals. However, most efforts in legislative instruments as well as shareholder or stakeholder initiatives have ultimately focused on public companies: for example, most disclosure obligations result from the given company’s status of being listed on a stock exchange.
This article argues that such a focus falls short of providing a comprehensive approach to the problem of climate change. In doing so, it examines the contribution of private companies to climate change, the relevance of climate risks for them, as well as the phenomenon of brown-spinning. We show that one cannot afford to ignore private companies in the net-zero transition and climate change adaptation. Yet, private companies lack several disciplining mechanisms available to public companies such as institutional investor engagement, certain corporate governance arrangements, and transparency through regular disclosure obligations. At this stage, only some generic regulatory instruments such as carbon pricing and environmental regulation apply to them. The article closes with a discussion of the main policy implications. Primarily, we propose extending sustainability disclosure requirements to private companies.
Sustainability disclosures aim at promoting a transition to a greener economy, rather than (only) protecting investors by addressing information asymmetry. Therefore, these disclosures should encompass private companies that are of relevance for the net-zero transition. Such disclosures can be a powerful tool in shedding light on the polluting private companies that have so far been in the dark as well as serving as a disciplining mechanism.
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.
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.
The present paper proposes an overview of the existing literature covering several aspects related to environmental, social, and governance (ESG) factors. Specifically, we consider studies describing and evaluating ESG methodologies and those studying the impact of ESG on credit risk, debt and equity costs, or sovereign bonds. We further expand the topic of ESG research by including the strand of the literature focusing on the impact of climate change on financial stability, thus allowing us to also consider the most recent research on the impact of climate change on portfolio management.
The reuse of collateral can support the efficient allocation of safe assets in the financial system. Exploiting a novel dataset, we show that banks substantially increase their reuse of sovereign bonds in response to scarcity induced by Eurosystem asset purchases. While repo rates react little to purchase-induced scarcity when reuse is low, they become increasingly sensitive at high levels of reuse. An elevated reuse rate is also associated with more failures to deliver and a higher volatility of repo rates in the cross-section of bonds. Our results highlight the trade-off between shock absorption and shock amplification effects of collateral reuse.
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.
Agencies around the world are in the process of developing taxonomies and standards for sustainable (or ESG) investment products. A key assumption in our model is that of non-consequentialist private investors (households) who derive a "warm glow" decisional utility when purchasing an investment product that is labelled as sustainable. We ask when such labelling is socially beneficial even when the socialplanner can impose a minimum standard on investment and production. In a model of financial constraints (Holmström and Tirole 1997), which we close to include consumer surplus, we also determine the optimal labelling threshold and show how its stringency is affected by determinants such as the prevalence of warm-glow investor preferences, the presence of social network effects, or the relevance of financial constraints at the industry level.
Joint Institutional Frameworks in bilateral relations are circumscribed in policy scope, can lack adequate instruments for dynamic adaptation and provide limited access to decision-making processes internal to the contracting parties. Informal governance, the involvement of private actors as well as rules such as equivalence provide avenues to remedy these limits in bilateral relations in sectoral governance. Through bilateral agreements, the scope of territorially bound political authority is expanded. The formalised and institutionalised frameworks and bodies established are, however, frequently accompanied by mechanisms of informal cooperation and special rules either to cover policy fields where no contractual relation exists, to provide for flexible solutions where needed, or to involve both public and private actors that otherwise do not have access to formal decision-making bodies. This SAFE working paper conceptualises formal and informal modes of cooperation and varying actor constellations. It discusses their relevance for the case of bilateral relations between the European Union (EU) and Switzerland in sectoral governance. More specifically, it draws lessons from EU-Swiss sectoral governance of financial and electricity markets for the future relations of the EU with the United Kingdom (UK). The findings suggest that there are distinct governance arrangements across sectors, while the patterns of sectoral governance are expected to look very much alike in the United Kingdom and Switzerland in the years to come. The general takeaway is that Brexit will have repercussions for the EU’s external relations with other third countries, putting ever more emphasis on formal and rule-based approaches, while leaving a need for sector-specific cross border co-operation.
Debt levels in the eurozone have reached new record highs. The member countries have tried to cushion the economic consequences of the corona pandemic with a massive increase in government spending. End of 2021 public debt in relation to GDP will approach 100% on average. There are various calls to abolish or soften the Maastricht rules of limiting sovereign debt. We see the risk of a new sovereign debt crisis in this decade if it is not possible to bring public debt down to an acceptable level. Our new fiscal rule would be suitable and appropriate for this purpose, because obviously the Maastricht criteria have failed. In contrast to the rigid 3% Maastricht-criterion, our rule is flexible and it addresses the main problem: excessively high public debt ratios. And it lowers the existing incentives for highly indebted governments to exert expansionary pressure on monetary policy. If obeyed strictly, our rule reinforces the snowball effect and reduces the excessively high debt ratios within a manageable period, even if nominal growth is weak. This is confirmed by simulations with different scenarios as well as with the hypothetical application of the new fiscal rule to eurozone economies from 2022 to 2026. Finally, we take up the recent proposal by ESM economists to increase the permissible debt ratio from 60 to 100% of GDP in the eurozone.
Why bank money creation?
(2022)
We provide a rationale for bank money creation in our current monetary system by investigating its merits over a system with banks as intermediaries of loanable funds. The latter system could result when CBDCs are introduced. In the loanable funds system, households limit banks’ leverage ratios when providing deposits to make sure they have enough “skin in the game” to opt for loan monitoring. When there is unobservable heterogeneity among banks with regard to their (opportunity) costs from monitoring, aggregate lending to bank-dependent firms is inefficiently low. A monetary system with bank money creation alleviates this problem, as banks can initiate lending by creating bank deposits without relying on household funding. With a suitable regulatory leverage constraint, the gains from higher lending by banks with a high repayment pledgeability outweigh losses from banks which are less diligent in monitoring. Bank-risk assessments, combined with appropriate risk-sensitive capital requirements, can reduce or even eliminate such losses.
Im Herbst 2020 wurden im Rahmen des vom Land Hessen geförderten LOEWE-Schwerpunktes „Infrastruktur – Design – Gesellschaft“ zwei Haushaltsbefragungen durchgeführt mit dem Ziel, die Akzeptanz und Wirkung verkehrspolitischer Maßnahmen zur Neuaufteilung öffentlicher Räume in Frankfurt am Main zu untersuchen. In der ersten (postalischen) Befragung (N = 853) wurden in den vier Befragungsgebieten Altstadt/Sachsenhausen-Nord, Nordend, Eschersheim und Bonames/Nieder-Eschbach mithilfe des Random-Route-Verfahrens Fragebögen verteilt. In der parallel dazu stattfindenden reinen Onlinebefragung (N = 1.422) wurden alle Frankfurter Stadtteile angesprochen.
Ziel des Berichts ist es, die methodische Vorgehensweise der Erstellung, Durchführung und Auswertung der Erhebung zu beschreiben. Dazu werden die thematischen Schwerpunkte und Zielsetzungen der beiden Befragungen erläutert, die Vorgehensweise bei der Verteilung und Verbreitung der Befragungen und des Pretests sowie die Aufbereitung der Datensätze. Weiterhin werden der Rücklauf und die Repräsentativität der Stichproben analysiert und zuletzt potentielle Fehlerquellen thematisiert.
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.
In this publication, researchers from the social and economic sciences and medicine as well as practitioners from the media and politics reflect on the influence of scientific expertise in times of crisis. Differences and similarities between the Covid-19 pandemic, the financial and economic crisis, the refugee crisis and the climate crisis are elaborated. The interviews were conducted in November/December 2021.
In der Publikation reflektieren Forschenden aus den Sozial- und Wirtschaftswissenschaft und Medizin sowie Praktiker aus Medien und Politik den Einfluss wissenschaftlicher Expertise in Krisenzeiten. Dabei werden Unterschiede und Gemeinsamkeiten zwischen der Covid-19-Pandemie, der Finanz- und Wirtschaftskrise, der Flüchtlingskrise und der Klimakrise herausgearbeitet. Die Gespräche wurden im November/Dezember 2021 geführt.
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.
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.
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.
Short sale bans may improve market quality during crises: new evidence from the 2020 Covid crash
(2022)
In theory, banning short selling stabilizes stock prices but undermines pricing efficiency and has ambiguous impacts on market liquidity. Empirical studies find mixed and conflicting results. This paper leverages cross-country policy variation during the 2020 Covid crisis to assess differential impacts of bans on stock liquidity, prices, and volatility. Results suggest that bans improved liquidity and stabilized prices for illiquid stocks but temporarily diminished liquidity for highly liquid stocks.The findings support theories in which short sale bans may improve liquidity by selectively filtering out informed— potentially predatory—traders. Thus, policies that target the most illiquid stocks may deliver better overall market quality than uniform short sale bans imposed on all stocks.
This paper challenges widespread assumptions in trust research according to which trust and conflict are opposing terms or where trust is generally seen as a value. Rather, it argues that trust is only valuable if properly justified, and it places such justifications in contexts of social and political conflict. For these purposes, the paper suggests a distinction between a general concept and various conceptions of trust, and it defines the concept as a four-place one. With regard to the justification of trust, a distinction between internal and full justification is introduced, and the justification of trust is linked to relations of justification between trusters and trusted. Finally, trust in conflict(s) emerges were such relations exist among the parties of a conflict, often by way of institutional mediation.
We propose a new instrument for estimating the price elasticity of gasoline demand that exploits systematic differences across U.S. states in the pass-through of oil price shocks to retail gasoline prices. These differences, which are primarily driven by variation in the cost of producing and distributing gasoline, create cross-sectional dispersion in gasoline price growth in response to an aggregate oil price shock. We find that the elasticity was stable near -0.3 until the end of 2014, but subsequently rose to about -0.2. Our estimates inform the recent debate about gasoline-tax holidays and policies to reduce carbon emissions.
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 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.
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.
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).
We analyze efficient risk-sharing arrangements when the value from deviating is determined endogenously by another risk sharing arrangement. Coalitions form to insure against idiosyncratic income risk. Self-enforcing contracts for both the original coalition and any coalition formed (joined) after deviations rely on a belief in future cooperation which we term "trust". We treat the contracting conditions of original and deviation coalitions symmetrically and show that higher trust tightens incentive constraints since it facilitates the formation of deviating coalitions. As a consequence, although trust facilitates the initial formation of coalitions, the extent of risk sharing in successfully formed coalitions is declining in the extent of trust and efficient allocations might feature resource burning or utility burning: trust is indeed a double-edged sword.
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 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.
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.
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.
We investigate the impact of uneven transparency regulation across countries and industries on the location of economic activity. Using two distinct sources of regulatory variation—the varying extent of financial-reporting requirements and the staggered introduction of electronic business registers in Europe—, we consistently document that direct exposure to transparency regulation is negatively associated with the focal industry’s economic activity in terms of inputs (e.g., employment) and outputs (e.g., production). By contrast, we find that indirect exposure to supplier and customer industries’ transparency regulation is positively associated with the focal industry’s economic activity. Our evidence suggests uneven transparency regulation can reallocate economic activity from regulated toward unregulated countries and industries, distorting the location of economic activity.
Cryptocurrencies provide a unique opportunity to identify how derivatives impact spot markets. They are fully fungible, trade across multiple spot exchanges at different prices, and futures contracts were selectively introduced on bitcoin (BTC) exchange rates against the USD in December 2017. Following the futures introduction, we find a significantly greater increase in cross-exchange price synchronicity for BTC--USD relative to other exchange rate pairs, as demonstrated by an increase in price correlations and a reduction in arbitrage opportunities and volatility. We also find support for an increase in price efficiency, market quality, and liquidity. The evidence suggests that futures contracts allowed investors to circumvent trading frictions associated with short sale constraints, arbitrage risk associated with block confirmation time, and market segmentation. Overall, our analysis supports the view that the introduction of BTC--USD futures was beneficial to the bitcoin spot market by making the underlying prices more informative.
Using the negotiation process of the Basel Committee on Banking Supervision (BCBS), this paper studies the way regulators form their positions on regulatory issues in the process of international standard-setting and the consequences on the resultant harmonized framework. Leveraging on leaked voting records and corroborating them using machine learning techniques on publicly available speeches, we construct a unique dataset containing the positions of banks and national regulators on the regulatory initiatives of Basel II and III. We document that the probability of a regulator opposing a specific initiative increases by 30% if their domestic national champion opposes the new rule, particularly when the proposed rule disproportionately affects them. We find the effect is driven by regulators who had prior experience of working in large banks – lending support to the private-interest theories of regulation. Meanwhile smaller banks, even when they collectively have a higher share in the domestic market, do not have any impact on regulators’ stand – providing little support to public-interest theories of regulation. Finally, we show this decision-making process manifests into significant watering down of proposed rules, thereby limiting the potential gains from harmonization of international financial regulation.
Resolving financial distress where property rights are not clearly defined: the case of China
(2022)
We use data on financially distressed Chinese companies in order to study a debt market where property rights are crudely defined and poorly enforced. To help with identification we use an event where a business-friendly province published new guidelines regarding the administration and enforcement of assets pledged as collateral. Although by no means a comprehensive reform of bankruptcy law or property rights, by instructing courts to enforce existing, albeit rudimentary, contractual rights the new guidelines virtually eliminated creditors runs and produced a sharp increase in the survival rate of financially-distressed companies. These changes illustrate how piecemeal reforms of property rights and their enforcement may have a significant impact on economic outcomes. Our analysis and results challenge the view that a fully fledged system of private property is a precondition for economic development.
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.
Supranational supervision
(2022)
We exploit the establishment of a supranational supervisor in Europe (the Single Supervisory Mechanism) to learn how the organizational design of supervisory institutions impacts the enforcement of financial regulation. Banks under supranational supervision are required to increase regulatory capital for exposures to the same firm compared to banks under the local supervisor. Local supervisors provide preferential treatment to larger institutes. The central supervisor removes such biases, which results in an overall standardized behavior. While the central supervisor treats banks more equally, we document a loss in information in banks’ risk models associated with central supervision. The tighter supervision of larger banks results in a shift of particularly risky lending activities to smaller banks. We document lower sales and employment for firms receiving most of their funding from banks that receive a tighter supervisory treatment. Overall, the central supervisor treats banks more equally but has less information about them than the local supervisor.
The loan impairment rules recently introduced by IFRS 9 require banks to estimate their future credit losses by using forward-looking information. We use supervisory loan-level data from Germany to investigate how banks apply their reporting discretion and adjust their lending upon the announcement of the new rules. Our identification strategy exploits a cut-off for the level of provisions at the investment grade threshold based on banks’ internal rating of a borrower. We find that banks required to adopt the new rules assign better internal ratings to exactly the same borrowers compared to banks that do not apply IFRS 9 around this cut-off. This pattern is consistent with a strategic use of the increased reporting discretion that is inherent to rules requiring forward-looking loss estimation. At the same time, banks also reduce their lending exposure to exactly those borrowers at the highest risk of experiencing a rating downgrade below the cutoff. These loans would be associated with additional provisions in future periods, both in the intensive and extensive margin. The lending change thus mitigates some of the negative effects of increased reporting opportunism on banks’ crisis resilience. However, when these firms with internal ratings around the investment grade cut-off obtain less external funding through banks, the introduction of IFRS 9 will likely also be associated with real economic effects
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.
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.
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.
The authors estimate perceptions about the Fed's monetary policy rule from panel data on professional forecasts of interest rates and macroeconomic conditions. The perceived dependence of the federal funds rate on economic conditions is time-varying and cyclical: high during tightening episodes but low during easings. Forecasters update their perceptions about the policy rule in response to monetary policy actions, measured by high-frequency interest rate surprises, suggesting that forecasters have imperfect information about the rule. The perceived rule impacts asset prices crucial for monetary policy transmission, driving how interest rates respond to macroeconomic news and explaining term premia in long-term interest rates.
When the COVID-19 crisis struck, banks using internal-rating based (IRB) models quickly recognized the increase in risk and reduced lending more than banks using a standardized approach. This effect is not driven by borrowers’ quality or by banks in countries with credit booms before the pandemic. The higher risk sensitivity of IRB models does not always result in lower credit provision when risk intensifies. Certain features of the IRB models – the use of a downturn Loss Given Default parameter – can increase banks’ resilience and preserve their intermediation capacity also during downturns. Affected borrowers were not able to fully insulate and decreased corporate investments.
Many nations incentivize retirement saving by letting workers defer taxes on pension contributions, imposing them when retirees withdraw their funds. Using a dynamic life cycle model, we show how ‘Rothification’ – that is, taxing 401(k) contributions rather than payouts – alters saving, investment, consumption, and Social Security claiming patterns. We find that taxing pension contributions instead of withdrawals leads to delayed retirement, somewhat lower lifetime tax payments, and relatively small reductions in consumption. Indeed, the two tax regimes generate quite similar relative inequality metrics: the relative consumption inequality ratio under TEE is only four percent higher than in the EET case. Moreover, results indicate that the Gini measures are also strikingly similar under the EET and the TEE regimes for lifetime consumption, cash on hand, and 401(k) assets, differing by only 1-4 percent. While tax payments are higher early in life under the TEE regime, they are slightly lower in the long run. Moreover, higher EET tax payments are also accompanied by higher volatility. We therefore find few reasons for policymakers to favor either tax approach on egalitarian or revenue-enhancing grounds.
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.
Advances in Machine Learning (ML) led organizations to increasingly implement predictive decision aids intended to improve employees’ decision-making performance. While such systems improve organizational efficiency in many contexts, they might be a double-edged sword when there is the danger of a system discontinuance. Following cognitive theories, the provision of ML-based predictions can adversely affect the development of decision-making skills that come to light when people lose access to the system. The purpose of this study is to put this assertion to the test. Using a novel experiment specifically tailored to deal with organizational obstacles and endogeneity concerns, we show that the initial provision of ML decision aids can latently prevent the development of decision-making skills which later becomes apparent when the system gets discontinued. We also find that the degree to which individuals 'blindly' trust observed predictions determines the ultimate performance drop in the post-discontinuance phase. Our results suggest that making it clear to people that ML decision aids are imperfect can have its benefits especially if there is a reasonable danger of (temporary) system discontinuances.
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.
The leading premium
(2022)
In this paper, we consider conditional measures of lead-lag relationships between aggregate growth and industry-level cash-flow growth in the US. Our results show that firms in leading industries pay an average annualized return 3.6\% higher than that of firms in lagging industries. Using both time series and cross sectional tests, we estimate an annual pure timing premium ranging from 1.2% to 1.7%. This finding can be rationalized in a model in which (a) agents price growth news shocks, and (b) leading industries provide valuable resolution of uncertainty about the growth prospects of lagging industries.
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.
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.
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.
This study analyzes information production and trading behavior of banks with lending relationships. We combine trade-by-trade supervisory data and credit-registry data to examine banks' proprietary trading in borrower stocks around a large number of corporate events. We find that relationship banks build up positive (negative) trading positions in the two weeks before events with positive (negative) news, even when these events are unscheduled, and unwind positions shortly after the event. This trading pattern is more pronounced in situations when banks are likely to possess private information about their borrowers, and cannot be explained by specialized expertise in certain industries or certain firms. The results suggest that banks' lending relationships inform their trading and underscore the potential for conflicts of interest in universal banking, which have been a prominent concern in the regulatory debate for a long time. Our analysis illustrates how combining large data sets can uncover unusual trading patterns and enhance the supervision of financial institutions.