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We analyze the repercussions of different kinds of uncertainty on cash demand, including uncertainty of the digital infrastructures, confidence crises of the financial system, natural disasters, political uncertainties, and inflationary crises. Based on a comprehensive literature survey, theoretical considerations and complemented by case studies, we derive a classification scheme how cash holdings typically evolve in each of these types of uncertainty by separating between demand for domestic and international cash as well as between transaction and store of value balances. Hereby, we focus on the stabilizing macroeconomic properties of cash and recommend guidelines for cash supply by central banks and the banking system. Finally, we exemplify our analysis with five case studies from the developing world, namely Venezuela, Zimbabwe, Afghanistan, Iraq, and Libya.
Data is considered the new oil of the economy, but privacy concerns limit their use, leading to a widespread sense that data analytics and privacy are contradictory. Yet such a view is too narrow, because firms can implement a wide range of methods that satisfy different degrees of privacy and still enable them to leverage varied data analytics methods. Therefore, the current study specifies different functions related to data analytics and privacy (i.e., data collection, storage, verification, analytics, and dissemination of insights), compares how these functions might be performed at different levels (consumer, intermediary, and firm), outlines how well different analytics methods address consumer privacy, and draws several conclusions, along with future research directions.
This paper studies the impact of banks’ dividend restrictions on the behavior of their institutional investors. Using an identification strategy that relies on the within investor variation and a difference in difference setup, I find that funds permanently decrease their ownership shares at treated banks during the 2020 dividend restrictions in the Eurozone and even exit treated banks’ stocks. Using data before the intro- duction of the ban reveals a positive relationship between fund ownership and banks’ dividend yield, highlighting again the importance of dividends for European banks’ fund investors. This reaction also has pricing implications since there is a negative relationship between the dividend restriction announcement day cumulative abnormal returns and the percentage of fund owners per bank.
This literature survey explores the potential avenues for the design of a green auto asset-backed security by focusing on the European auto securitization market. In this context, we examine the entire value chain of the securitization process to understand the incentives and interests involved at various stages of the transaction. We review recent regulatory developments, feasibility concerns, and potential designs of a sustainable securitization framework. Our study suggests that a Green Auto ABS should be based on both a green use of proceeds and a green collateral-based methodology.
Climate risk has become a major concern for financial institutions and financial markets. Yet, climate policy is still in its infancy and contributes to increased uncertainty. For example, the lack of a sufficiently high carbon price and the variety of definitions for green activities lower the value of existing and new capital, and complicate risk management. This column argues that it would be welfare-enhancing if policy changes were to follow a predictable longer-term path. Accordingly, the authors suggest a role for financial regulation in the transition.
We document the structure of firm-bank relationships across the eleven largest euro area countries and present new stylised facts using novel data from the recent credit registry of the Eurosystem - AnaCredit. We look at the number of banking relationships, reliance on the main bank, credit instruments, loan maturity and interest rates. The granularity of the data allows us to account for cross country differences in firm characteristics. Firms in Southern European countries borrow from a larger number of banks and obtain a lower share of credit from the main bank compared to those in Northern European countries. They also tend to borrow more on short term, more expensive instruments and to obtain loans with shorter maturity. This is consistent with the hypothesis that Southern European countries rely less on relationship banking and obtain credit less conducive to firm growth, in line with the smaller average size of Southern European firms. Instead, no clear pattern emerges in terms of interest rates, consistent with the idea that banks appropriate part of the surplus generated by relationship lending through higher rates.
WE PRESENT OUR VISION OF OMNISCIENTDB, A NOVEL DATABASE THAT LEVERAGES THE IMPLICITLY STORED KNOWLEDGE IN LARGE LANGUAGE MODELS TO AUGMENT DATA SETS FOR ANALYTICAL QUERIES OR MACHINE LEARNING TASKS. OMNISCIENTDB EMPOWERS USERS TO AUGMENT DATA SETS BY MEANS OF SIMPLE SQL QUERIES AND THUS HAS THE POTENTIAL TO DRAMATICALLY REDUCE THE MANUAL OVERHEAD ASSOCIATED WITH DATA INTEGRATION. IT USES AUTOMATIC PROMPT ENGINEERING TO CONSTRUCT APPROPRIATE PROMPTS FOR GIVEN SQL QUERIES AND PASSES THEM TO A LARGE LANGUAGE MODEL LIKE GPT-3 TO CONTRIBUTE ADDITIONAL DATA, AUGMENTING THE EXPLICITLY STORED DATA. OUR INITIAL EVALUATION DEMONSTRATES THE GENERAL FEASIBILITY OF OUR VISION, EXPLORES DIFFERENT PROMPTING TECHNIQUES IN GREATER DETAIL, AND POINTS TOWARDS FUTURE RESEARCH.
Forging new paths – the Bundesbank’s transformation journey : interview with Karmela Holtgreve
(2023)
Iinterview with Karmela Holtgreve [Director General Strategy and Innovation, Deutsche Bundesbank]
WE STUDY REDISTRIBUTIVE EFFECTS OF INFLATION USING A RANDOMIZED INFORMATION EXPERIMENT ON BANK CLIENTS. ON AVERAGE, INDIVIDUALS ARE WELL INFORMED ABOUT CURRENT INFLATION AND ARE CONCERNED ABOUT ITS IMPACT ON WEALTH. YET, MOST INDIVIDUALS ARE NOT AWARE OF HOW INFLATION ERODES NOMINAL POSITIONS. ONCE THEY RECEIVE INFORMATION ON THIS EROSION CHANNEL, THEY UPDATE PERCEPTIONS AND EXPECTATIONS ABOUT OWN NET NOMINAL POSITIONS. LEARNING ABOUT THE INFLATION-INDUCED EROSION OF NOMINAL POSITIONS CAUSALLY AFFECTS CHOICES IN HYPOTHETICAL REAL-ESTATE TRANSACTIONS AND ACTUAL CONSUMPTION. THE FINDINGS SUGGEST THAT HOUSEHOLD WEALTH MEDIATES THE SENSITIVITY OF CONSUMPTION TO INFLATION ONCE HOUSEHOLDS ARE AWARE OF THE BALANCE-SHEET EFFECTS OF INFLATION.
SAFE Update June 2023
(2023)
PURPOSE: This theoretical study seeks to understand how the development of ‘Transnational Business Feminism’ in response to the 2008 financial crisis, was implemented in 2013 through Japan’s ‘Womenomics’ program. The paper further examines how efficient this said form of neoliberal feminist economic program was in in addressing vulnerabilities in the Japanese financial system during the ongoing Covid-19 pandemic. Finally, it looks at how the pandemic has shifted conversations around the future of gender and finance in Japan through the Environmental, Social and Governance (ESG) framework.
DESIGN/METHOD: Drawing on a variety of sources, this paper uses a case study research methodology as well as statistical data from a variety of sources to draw theoretical conclusions on the specific case of Japan’s economy.
RESULTS/FINDINGS: This paper reveals that the programs implemented by the Japanese government failed to address existing gender inequalities and systemic risk in the Japanese economy, and that women in Japan were hit much harder by the repercussions of the pandemic, in spite of Womenomics policies.
ORIGINALITY/VALUE: This study offers insights into the effectiveness of neoliberal feminist agendas in addressing systemic financial and economic risk, in order to help optimize the potential of ESG.
Retained earnings and foreign portfolio ownership: implications for the current account debate
(2023)
In some countries, a sizable fraction of savings is derived from corporate savings. Although larger, traded corporations are often co-owned by foreign portfolio investors, current international accounting standards allocate all corporate savings to the host country. This paper suggests a framework to correct for this misleading attribution and applies this concept to Germany. For the years 2012 to 2020, our corrections retrospectively reduce German savings and consequently the German current account surplus by, on average, €11.5bn annually. This amounts to approximately five percent of Germany’s average official current account surplus (€226.6bn) across these years.
We find that high macroeconomic uncertainty is associated with greater accumulation of physical capital, despite a reduction in investment and valuations. To reconcile this puzzling evidence, we show that uncertainty predicts lower depreciation and utilization of existing capital, which dominates the investment slowdown. Motivated by these dynamics, we develop a quantitative production-based model in which firms implement precautionary savings through reducing utilization rather than raising invest-ment. Through this novel intensive-margin mechanism, uncertainty shocks command a quarter of the equity premium in general equilibrium, while flexibility in utilization adjustments helps explain uncertainty risk exposures in the cross-section of industry returns.
We assemble a data set of more than eight million German Twitter posts related to the war in Ukraine. Based on state-of-the-art methods of text analysis, we construct a daily index of uncertainty about the war as perceived by German Twitter. The approach also allows us to separate this index into uncertainty about sanctions against Russia, energy policy and other dimensions. We then estimate a VAR model with daily financial and macroeconomic data and identify an exogenous uncertainty shock. The increase in uncertainty has strong effects on financial markets and causes a significant decline in economic activity as well as an increase in expected inflation. We find the effects of uncertainty to be particularly strong in the first months of the war.
The present study investigates the moderating effect of usage intensity of the social networking site (SNS) Instagram (IG) on the influence of advertisement disclosure types on advertising performance. A national sample (N = 566) participated in a randomized online experiment including a real influencer and followers in order to investigate how different advertisement disclosure types affect advertising performance and how usage intensity moderates this effect. We find that disclosing an influencer’s postings with “#ad” increases the trustworthiness of the influencer and the general credibility of the posting for heavy users, but not for light users. Followership of a user has been found to strongly improve all researched variables (attitude toward product placement, trustworthiness of the spokesperson and general credibility of the posting). This study adds to literature the first distinction on heavy and light usage intensity, and on followership of an IG user when regarding the effects of advertisement disclosure types on advertising performance. To conclude, we present a number of recommendations regarding how advertisers, influencers, and SNS providers should develop strategies for monitoring, understanding, and responding to different social media users, e.g., to closely monitor an influencer’s audience to identify heavy users and optimally target them.
In order to reach climate neutrality by 2050, the European Union is taking action in the form of extensive sustainability regulations with the aim to push the private sector towards sustainable economic activities. In this context, a new instrument to finance a company’s sustainability transition has been developed: the sustainability-linked bond (SLB). This paper analyzes the SLB market’s efficiency in attracting those companies that are most crucial for a successful sustainability transition, namely carbon-intensive companies and companies that are lagging behind in their sustainability transition, defined as ESG laggards. By developing a conceptual framework for the SLB market and running a probit and logit regression estimation, this paper shows that the SLB market efficiently attracts carbon-intensive companies, but fails to attract ESG laggards. Moreover, the paper identifies four success factors for the SLB market to improve its future accessibility and credibility.
The European low-carbon transition began in the last few decades and is accelerating to achieve net-zero emissions by 2050. This paper examines how climate-related transition indicators of a large European corporate firm relate to its CDS-implied credit risk across various time horizons. Findings show that firms with higher GHG emissions have higher CDS spreads at all tenors, including the 30-year horizon, particularly after the 2015 Paris Agreement, and in prominent industries such as Electricity, Gas, and Mining. Results suggest that the European CDS market is currently pricing, to some extent, albeit small, the exposure to transition risk for a firm across different time horizons. However, it fails to account for a company’s efforts to manage transition risks and its exposure to the EU Emissions Trading Scheme. CDS market participants seem to find challenging to risk-differentiate ETS-participating firms from other firms.
An unfamiliar term in the not-too-distant past, “net zero” has become a headline-maker in the business and financial world with the growing importance of climate change. Succumbing to increasing pressure, companies and financial institutions around the world have come to adopt net-zero transition plans and targets, pledging to hit certain emission-reduction targets in a long-term period. Moreover, regulators around the world have started to require the disclosure or adoption of net-zero transition plans and targets.
However, an unintended consequence of net-zero transition commitments has been the increased popularity of divestments. That is, many firms seeking to fulfill a net-zero plan are passing on carbon-intensive assets (i.e., oil, gas, and coal assets) to other firms that are likely to be non-committal to environmental goals or that operate under less pressure from investors, stakeholders, and regulators. Such divestments, technically mergers and acquisitions (M&A) transactions, present an ideal opportunity to improve a divesting firm’s environmental record and reach ambitious net-zero goals, creating the impression that an emission reduction has occurred. However, the key is how acquiring firms handle these assets. If they continue operating as before, there will not be an overall improvement for the global climate. Worse, such assets can be operated by new owners in a way that causes more emissions. In any case, such divestments undermine the credibility and value of net-zero ambitions by allowing firms to reach targets by simply divesting assets.
This article explores the reasons and motivations for divestments or, more broadly M&As of carbon-intensive assets and explains why the increased role of net-zero commitments can be undermined by those transactions. We provide some evidence to illustrate the landscape of such transactions and the concerns they give rise to. Lastly, we explore several policy options to address the problem.
There is much discussion today about a possible digital euro (PDE). Is this attention exaggerated? Are “central bank digital currencies” (CBDCs) “a solution in search of a problem”, as some have argued? This article summarizes the main facts about the PDE and concludes that, if the decision on adoption had to be taken today, the arguments against would outweigh those in favor. However, there may be future circumstances in which having a CBDC ready for use can indeed be useful. Therefore, preparing is a good thing, even if the odds of its usefulness in normal conditions are slim.
The current economic landscape is complex and globalized, and it imposes on individuals the responsibility for their own financial security. This situation has been intensified by the COVID-19 crisis, since short-time work and layoffs significantly limit the availability of financial resources for individuals. Due to the long duration of the lockdown, these challenges will have a long-term impact and affect the financial well-being of many citizens. Moreover, it can be assumed that the consequences of this crisis will once again particularly affect groups of people who have already frequently been identified as having low financial literacy. Financial literacy is therefore an important target for educational measures and interventions. However, it cannot be considered in isolation but must take into account the many potential factors that influence financial literacy alone or in combination. These include personality traits and socio-demographic factors as well as the (in)ability to defer gratification. Against this background, individualized support offers can be made. With this in mind, in the first step of this study, we analyze the complex interaction of personality traits, socio-demographic factors, the (in-)ability to delay gratification, and financial literacy. In the second step, we differentiate the identified effects regarding different groups to identify moderating effects, which, in turn, allow conclusions to be drawn about the need for individualized interventions. The results show that gender and educational background moderate the effects occurring between self-reported financial literacy, financial learning opportunities, delay of gratification, and financial literacy.
A person's intelligence level positively influences his or her professional success. Gifted and highly intelligent individuals should therefore be successful in their careers. However, previous findings on the occupational situation of gifted adults are mainly known from popular scientific sources in the fields of coaching and self-help groups and confirm prevailing stereotypes that gifted people have difficulties at work. Reliable studies are scarce. This systematic literature review examines 40 studies with a total of 22 job-related variables. Results are shown in general for (a) the employment situation and more specific for the occupational aspects (b) career, (c) personality and behavior, (d) satisfaction, (e) organization, and (f) influence of giftedness on the profession. Moreover, possible differences between female and male gifted individuals and gifted and non-gifted individuals are analyzed. Based on these findings, implications for practice as well as further research are discussed.
Unconventional green
(2023)
We analyze the effects of the PEPP (Pandemic Emergency Purchase Programme), the temporary quantitative easing implemented by the ECB immediately after the burst of the Covid-19 pandemic. We show that the differences in aim, size and flexibility with respect to the traditional Corporate Sector Purchase Programme (CSPP) were able to significantly involve, in addition to the directly targeted bonds, also the green bond segment. Via a standard difference- in-differences model we estimate that the yield on green bonds declined by more than 20 basis points after the PEPP. In order to take into account also the differences attributable to the eligibility to the programme, we employ a triple difference estimator. Bonds that at the same time were green and eligible benefitted of an additional premium of 39 basis points.
Digital platforms have become an important part of the digital economy by facilitating transactions between large numbers of users and by fostering innovation on collaborative platforms. In combination with technical platform services, some platform operators have managed to create powerful ecosystems that create network externalities and benefit from economies of scale and economies of scope. It is striking that, due to the specific economic drivers of the digital infrastructure, platform-based or platform-related services are dominated by a select number of global players. Most of the global platform operators are headquartered in the US, including Alphabet, Amazon, Apple, Meta and Microsoft, also known as the “Big 5”. Some are located in Asia (e.g. Alibaba, Tencent). In Europe there are only a limited number of platform operators with a small market share.
Much research has been conducted on the emergence and characteristics of platforms, network externalities and platform competition. However, there has been very little research on whether or not one can idķentify common features that might explain the success of Big Tech. The following article focuses on an analysis of the Big 5 based on their strategies and development paths. The comparison reveals certain commonalities, from which several conclusions can be drawn regarding the success factors of the Big 5. These insights could be helpful for business decision-makers when shaping digital strategies. But also policy makers, especially in Europe, could benefit from these lessons learned to improve the European technology ecosystem.
I have assessed changes in the monetary policy stance in the euro area since its inception by applying a Bayesian time-varying parameter framework in conjunction with the Hamiltonian Monte Carlo algorithm. I find that the estimated policy response has varied considerably over time. Most of the results suggest that the response weakened after the onset of the financial crisis and while quantitative measures were still in place, although there are also indications that the weakening of the response to the expected inflation gap may have been less pronounced. I also find that the policy response has become more forceful over the course of the recent sharp rise in inflation. Furthermore, it is essential to model the stochastic volatility relating to deviations from the policy rule as it materially influences the results.
This paper presents and compares Bernoulli iterative approaches for solving linear DSGE models. The methods are compared using nearly 100 different models from the Macroeconomic Model Data Base (MMB) and different parameterizations of the monetary policy rule in the medium-scale New Keynesian model of Smets and Wouters (2007) iteratively. I find that Bernoulli methods compare favorably in solving DSGE models to the QZ, providing similar accuracy as measured by the forward error of the solution at a comparable computation burden. The method can guarantee convergence to a particular, e.g., unique stable, solution and can be combined with other iterative methods, such as the Newton method, lending themselves especially to refining solutions.
The intergroup sensitivity effect in mergers and acquisitions: testing the role of merger motives
(2021)
Research has shown that people are more defensive to criticism when it stems from an outgroup member, compared to an ingroup member (the intergroup sensitivity effect: ISE). We conducted two online vignette experiments to examine the ISE in the context of an organizational merger and the role of merger motives for the ISE. We predicted that the ISE would also emerge in mergers and acquisitions (M&As), but people would respond less negatively to criticism from the outgroup when the motive for the merger is described as achieving synergies rather than growth. In Experiment 1 (N = 452), which did not mention any motives behind the acquisition, a significant ISE emerged. Experiment 2 (N = 587) again showed an ISE regardless of the merger motive. In both experiments, the ISE was mediated by perceptions of the outgroup criticism as less legitimate and constructive. Overall, this research points to the intergroup sensitivity effect as a relevant phenomenon during post-merger integration.
SAFE Update April 2023
(2023)
The importance of agile methods has increased in recent years, not only to manage IT projects but also to establish flexible and adaptive organisational structures, which are essential to deal with disruptive changes and build successful digital business strategies. This paper takes an industry-specific perspective by analysing the dissemination, objectives and relative popularity of agile frameworks in the German banking sector. The data provides insights into expectations and experiences associated with agile methods and indicates possible implementation hurdles and success factors. Our research provides the first comprehensive analysis of agile methods in the German banking sector. The comparison with a selected number of fintechs has revealed some differences between banks and fintechs. We found that almost all banks and fintechs apply agile methods in IT projects. However, fintechs have relatively more experience with agile methods than banks and use them more intensively. Scrum is the most relevant framework used in practice. Scaled agile frameworks are so far negligible in the German banking sector. Acceleration of projects is apparently the most important objective of deploying agile methods. In addition, agile methods can contribute to cost savings and lead to improved quality and innovation performance, though for banks it is evidently more challenging to reach their respective targets than for fintechs. Overall our findings suggest that German banks are still in a maturing process of becoming more agile and that there is room for an accelerated adoption of agile methods in general and scaled agile frameworks in particular.
Fabo, Janˇcokov ́a, Kempf, and P ́astor (2021) show that papers written by central bank researchers find quantitative easing (QE) to be more effective than papers written by academics. Weale and Wieladek (2022) show that a subset of these results lose statistical significance when OLS regressions are replaced by regressions that downweight outliers. We examine those outliers and find no reason to downweight them. Most of them represent estimates from influential central bank papers published in respectable academic journals. For example, among the five papers finding the largest peak effect of QE on output, all five are published in high-quality journals (Journal of Monetary Economics, Journal of Money, Credit and Banking, and Applied Economics Letters), and their average number of citations is well over 200. Moreover, we show that these papers have supported policy communication by the world’s leading central banks and shaped the public perception of the effectiveness of QE. New evidence based on quantile regressions further supports the results in Fabo et al. (2021).
This paper examines rent sharing in private investments in public equity (PIPEs) between newly public firms and private investors. The evidence suggests highly asymmetric rent sharing. Newly public firms earn a negative return of up to −15% in the first post-PIPE year, while investors benefit due to the ability to dictate transaction terms. The results are economically relevant because newly public firms are, at least in recent years, more likely to tap private rather than public markets for follow-on financing shortly after the initial public offering (IPO), and because the results for newly public firms contrast with those for the broad PIPE market in Lim et al. (2021). The study also contributes to the PIPE literature by offering an integrative view of competing theories of the cross-section of post-PIPE stock returns. We simultaneously test proxies for corporate governance, asymmetric information, bargaining power, and managerial entrenchment. While all explanations have univariate predictive power for the post-PIPE performance, only the proxies for corporate governance and asymmetric information are robust in ceteris-paribus tests.
The clinical and economic value of a successful shutdown during the SARS-CoV-2 pandemic in Germany
(2020)
Background and aim A shutdown of businesses enacted during the SARS-CoV-2 pandemic can serve different goals, e.g., preventing the intensive care unit (ICU) capacity from being overwhelmed (‘flattening the curve’) or keeping the reproduction number substantially below one (‘squashing the curve’). The aim of this study was to determine the clinical and economic value of a shutdown that is successful in ‘flattening’ or ‘squashing the curve’ in Germany.
Methods In the base case, the study compared a successful shutdown to a worst-case scenario with no ICU capacity left to treat COVID-19 patients. To this end, a decision model was developed using, e.g., information on age-specific fatality rates, ICU outcomes, and the herd protection threshold. The value of an additional life year was borrowed from new, innovative oncological drugs, as cancer reflects a condition with a similar morbidity and mortality burden in the general population in the short term as COVID-19.
Results A shutdown that is successful in ‘flattening the curve’ is projected to yield an average health gain between 0.02 and 0.08 life years (0.2 to 0.9 months) per capita in the German population. The corresponding economic value ranges between €1543 and €8027 per capita or, extrapolated to the total population, 4% to 19% of the gross domestic product (GDP) in 2019. A shutdown that is successful in ‘squashing the curve’ is expected to yield a minimum health gain of 0.10 life years (1.2 months) per capita, corresponding to 24% of the GDP in 2019. Results are particularly sensitive to mortality data and the prevalence of undetected cases.
Conclusion A successful shutdown is forecasted to yield a considerable gain in life years in the German population. Nevertheless, questions around the affordability and underfunding of other parts of the healthcare system emerge.
We use census data to show that structural transformation reflects a fundamental reallocation of labour from goods to services, instead of a relabelling that occurs when goods-producing firms outsource their in-house service production. The novelty of our approach is that it categorizes labour by occupations, which are invariant to outsourcing. We find that the reallocation of labour from goods-producing to service-producing occupations is a robust feature in censuses from around the world and different time periods. To understand the underlying forces, we propose a tractable model in which uneven occupation-specific technological change generates structural transformation of occupation employment.
Combining market data with a publicly available monthly snapshot of Deutsche Börse’s index ranking list, I create a model that predicts index changes in the DAX, MDAX, SDAX, and TecDAX from 2010 to 2019 before they are officially announced. Even though I empirically show that index changes are predictable, they still earn sizeable post-announcement 1-day abnormal returns up to 1.42% and − 1.54% for promotions and demotions, respectively. While abnormal returns are larger in smaller stocks, I find no evidence that they are related to funding constraints or additional risk for trading on wrong predictions. A trading strategy that trades according to my model yields an annualized Sharpe ratio of 0.83 while being invested for just 4 days a year.
We propose a novel approach to the study of international trade based on a theory of country integration that embodies a broad systemic viewpoint on the relationship between trade and growth. Our model leads to an indicator of country openness that measures a country's level of integration through the full architecture of its connections in the trade network. We apply our methodology to a sample of 204 countries and find a sizable and significant positive relationship between our integration measure and a country's growth rate, while that of the traditional measures of outward orientation is only minor and statistically insignificant.
The SVB case is a wake-up call for Europe’s regulators as it demonstrates the destructive power of a bank-run: it undermines the role of loss absorbing capital, elbowing governments to bailout affected banks. Many types of bank management weaknesses, like excessive duration risk, may raise concerns of bank losses – but to serve as a run-trigger, there needs to be a large enough group of bank depositors that fails to be fully covered by a deposit insurance scheme. Latent run-risk is the root cause of inefficient liquidations, and we argue that a run on SVB assets could have been avoided altogether by a more thoughtful deposit insurance scheme, sharply distinguishing between loss absorbing capital (equity plus bail-in debt) and other liabilities which are deemed not to be bail-inable, namely demand deposits. These evidence-based insights have direct implications for Europe’s banking regulation, suggesting a minimum and a maximum for a banks’ loss absorption capacity.
Flows of funds run by banks or by firms that belong to the same financial group as a bank are less volatile and less sensitive to bad past performance. This enables bank-affiliated funds to better weather distress and to hold lower precautionary cash buffers in comparison with their unaffiliated peers. Banks provide liquidity support to distressed affiliated funds by buying shares of those funds that are experiencing large outflows. This, in turn, diminishes the severity of strategic complementarities in investors’ redemptions. Liquidity support and other benefits of bank affiliation are conditional on the financial health of the parent company. Distress in the banking system spills over to the mutual fund sector via ownership links. Our research high-lights substantial dependencies between the banking system and the asset management industry, and identifies an important channel via which financial stability risks depend on the organisational structure of the financial sector.
The rapid spread of the Coronavirus (COVID-19) confronts policy makers with the problem of measuring the effectiveness of containment strategies, balancing public health considerations with the economic costs of social distancing measures. We introduce a modified epidemic model that we name the controlled-SIR model, in which the disease reproduction rate evolves dynamically in response to political and societal reactions. An analytic solution is presented. The model reproduces official COVID-19 cases counts of a large number of regions and countries that surpassed the first peak of the outbreak. A single unbiased feedback parameter is extracted from field data and used to formulate an index that measures the efficiency of containment strategies (the CEI index). CEI values for a range of countries are given. For two variants of the controlled-SIR model, detailed estimates of the total medical and socio-economic costs are evaluated over the entire course of the epidemic. Costs comprise medical care cost, the economic cost of social distancing, as well as the economic value of lives saved. Under plausible parameters, strict measures fare better than a hands-off policy. Strategies based on current case numbers lead to substantially higher total costs than strategies based on the overall history of the epidemic.
This paper defends The Transformation of Values into Prices on the Basis of Random Systems, published in EIER, by answering to the Comments made in the same journal by Professors Mori, Morioka and Yamazaki. The clarifications mainly concern the justification of the randomness assumptions, the conditions needed to obtain the equality of total profit with total surplus value in the simplified one-industry system and the invariance of the results to changes in the units of measurement.
We contribute to the debate about the future of capital markets and corporate finance, which has ensued against the background of a significant boom in private markets and a corresponding decline in the number of firms and the amount of capital raised in public markets in the US and Europe.
Our research sheds light on the fluctuating significance of public and private markets for corporate finance over time, and challenges the conventional view of a linear progression from one market to the other. We argue instead that a more complex pattern of interaction between public and private markets emerges, after taking a long-term perspective and examining historical developments more closely.
We claim that there is a dynamic divide between these markets, and identify certain factors that determine the degree to which investors, capital, and companies gravitate more towards one market than the other. However, in response to the status quo, other factors will gain momentum and favor the respective other market, leading to a new (unstable) equilibrium. Hence, we observe the oscillating domains of public and private markets over time. While these oscillations imply ‘competition’ between these markets, we unravel the complementarities between them, which also militate against a secular trend towards one market. Finally, we examine the role of regulation in this dynamic divide as well as some policy implications arising from our findings.
Art-related non-fungible tokens (NFTs) took the digital art space by storm in 2021, generating massive amounts of volume and attracting a large number of users to a previously obscure part of blockchain technology. Still, very little is known about the attributes that influence the price of these digital assets. This paper attempts to evaluate the level of speculation associated with art NFTs, comprehend the characteristics that confer value on them and design a profitable trading strategy based on our findings. We analyze 860,067 art NFTs that have been deployed on the Ethereum blockchain and have been involved in 317,950 sales using machine learning methods to forecast the probability of sale, the trade frequency and the average price. We find that NFTs are highly speculative assets and that their price and recurrence of sale are heavily determined by the floor and the last sale prices, independent of any fundamental value.
The discount control mechanisms that closed-end funds often choose to adopt before IPO are supposedly implemented to narrow the difference between share price and net asset value. We find evidence that non-discretionary discount control mechanisms such as mandatory continuation votes serve as costly signals of information to reveal higher fund quality to investors. Rents of the skill signaled through the announcement of such policies accrue to managers rather than investors as differences in skill are revealed through growing assets under management rather than risk- adjusted performance.
We analyze the performance of marketplace lending using loan cash flow data from the largest platform, Lending Club. We find substantial risk-adjusted performance of about 40 basis points per month for the entire loan portfolio. Other loan portfolios grouped by risk category have similar risk-adjusted performance. We show that characteristics of the local bank sector for each loan, such as concentration of deposits and the presence of national banks, are related to the performance of loans. Thus, marketplace lending has the potential to finance a growing share of the consumer credit market in the absence of a competitive response from the traditional incumbents.
Armstrong et al. (2022) review the empirical methods used in the accounting literature to draw causal inferences. They document a growing number of studies using quasi-experimental methods and provide a critical perspective on this trend as well as the use of these methods in the accounting literature. In this discussion, I complement their review by broadening the perspective. I argue for a design-based approach to accounting research that shifts attention from methods to the entire research design. I also discuss why studies that aim to draw causal inferences are important, how these studies fit into the scientific process, and why assessing the strength of the research design is important when evaluating studies and aggregating research findings.
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.
Speculative news on corporate takeovers may hurt productivity because uncertainty and threat of job loss cause anxiety, distraction, and reduced collaboration and morale among employees and managers. Using a panel of OECD-headquartered firms, we show that firm productivity temporarily declines upon announcements of speculative takeover rumors that do not materialize. This productivity dip is more pronounced for targets and for firms in countries with weaker employee rights and less long-term orientation. Abnormal stock returns mirror these results. The evidence fosters our understanding of potential real effects of speculative financial news and the costs of takeover threats.
Sample-based longitudinal discrete choice experiments: preferences for electric vehicles over time
(2021)
Discrete choice experiments have emerged as the state-of-the-art method for measuring preferences, but they are mostly used in cross-sectional studies. In seeking to make them applicable for longitudinal studies, our study addresses two common challenges: working with different respondents and handling altering attributes. We propose a sample-based longitudinal discrete choice experiment in combination with a covariate-extended hierarchical Bayes logit estimator that allows one to test the statistical significance of changes. We showcase this method’s use in studies about preferences for electric vehicles over six years and empirically observe that preferences develop in an unpredictable, non-monotonous way. We also find that inspecting only the absolute differences in preferences between samples may result in misleading inferences. Moreover, surveying a new sample produced similar results as asking the same sample of respondents over time. Finally, we experimentally test how adding or removing an attribute affects preferences for the other attributes.
Venture capital-backed firms, unavoidable value-destroying trade sales, and fair value protections
(2021)
This paper investigates the implications of the fair value protections contemplated by the standard corporate contract (i.e., the standard contract form for which corporate law provides) for the entrepreneur–venture capitalist relationship, focusing, in particular, on unavoidable value-destroying trade sales. First, it demonstrates that the typical entrepreneur–venture capitalist contract does institutionalize the venture capitalist’s liquidity needs, allowing, under some circumstances, for counterintuitive instances of contractually-compliant value destruction. Unavoidable value-destroying trade sales are the most tangible example. Next, it argues that fair value protections can prevent the entrepreneur and venture capitalist from allocating the value that these transactions generate as they would want. Then, it shows that the reality of venture capital-backed firms calls for a process of adaptation of the standard corporate contract that has one major step in the deactivation or re-shaping of fair value protections. Finally, it argues that a standard corporate contract aiming to promote social welfare through venture capital should feature flexible fair value protections.
This paper examines the performance of 538 sovereign wealth fund (SWF) investments into venture capital, private equity, and real asset funds (“alternative asset funds”) from 52 countries around the world over the years 1995-2020. The data indicate SWFs are significantly slower to fully liquidate and earn lower returns from their investments, particularly from their investments in venture capital funds. The longer duration and lower performance of SWFs is more pronounced for strategic SWFs than savings SWFs. We show that venture capital fund investments are more likely to be in countries with lower quality disclosure indices. SWFs are more often in buyout funds, and in larger funds with a greater number of limited partners. SWF performance is enhanced by having different types of institutional investors in the same limited partnership. Overall, the data indicate sovereign wealth funds make large investments in alternative asset funds with a longer-term view and earn a lower financial return consistent with strategic and political SWF investment motives.
This paper examines the causes and consequences of hedge fund investments in exchange traded funds (ETFs) using U.S. data from 1998 to 2018. The data indicate that transient hedge funds and quasi-indexer hedge funds are substantially more likely to invest in ETFs. Unexpected hedge fund inflows cause a rise in ETF investments, and the economic significance of unexpected flow is more than twice as large for transient than quasi-indexer hedge funds. ETF investment is in general associated with lower hedge fund performance. But when ETF investment is accompanied by an increase in total flow and unexpected flow, the negative impact of ETF holdings on performance is mitigated. The data are consistent with the view that hedge fund ETF investment unrelated to unexpected flow is an agency cost of delegated portfolio management.
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.
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.
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.
SAFE Update February 2023
(2023)
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.
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.
Industry concentration and markups in the US have been rising over the last 3-4 decades. However, the causes remain largely unknown. This paper uses machine learning on regulatory documents to construct a novel dataset on compliance costs to examine the effect of regulations on market power. The dataset is comprehensive and consists of all significant regulations at the 6-digit NAICS level from 1970-2018. We find that regulatory costs have increased by $1 trillion during this period. We document that an increase in regulatory costs results in lower (higher) sales, employment, markups, and profitability for small (large) firms. Regulation driven increase in concentration is associated with lower elasticity of entry with respect to Tobin's Q, lower productivity and investment after the late 1990s. We estimate that increased regulations can explain 31-37% of the rise in market power. Finally, we uncover the political economy of rulemaking. While large firms are opposed to regulations in general, they push for the passage of regulations that have an adverse impact on small firms.
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.
This study examines the recent literature on the expectations, beliefs and perceptions of investors who incorporate Environmental, Social, Governance (ESG) considerations in investment decisions with the aim to generate superior performance and also make a societal impact. Through the lens of equilibrium models of agents with heterogeneous tastes for ESG investments, green assets are expected to generate lower returns in the long run than their non- ESG counterparts. However, at the short run, ESG investment can outperform non-ESG investment through various channels. Empirically, results of ESG outperformance are mixed. We find consensus in the literature that some investors have ESG preference and that their actions can generate positive social impact. The shift towards more sustainable policies in firms is motivated by the increased market values and the lower cost of capital of green firms driven by investors’ choices.
This paper 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.
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 examines how the implementation of a new dark order - Midpoint Extended Life Order on NASDAQ - impacts financial markets stability in terms of occurrences of mini-flash crashes in individual securities. We use high-frequency order book data and apply panel regression analysis to estimate the effect of M-ELO trading on market stability and liquidity provision. The results suggest a predominance of a speed bump effect of M-ELO rather than a darkness effect. We find that the introduction of M-ELO increases market stability by reducing the average number of mini-flash crashes, but its impact on market quality is mixed.
The right to ask questions and voice their opinions at annual general meetings (AGMs) represents one of the few avenues for shareholders to communicate directly and publicly with the firm’s management. Examining AGM transcripts of U.S. companies between 2007 and 2021, we find that shareholders actively express their concerns about environmental, social and governance (ESG) issues in accordance with their specific relationship with the company. Further, they are also demonstrably more vocal about ESG issues at AGMs of firms with poor sustainability performance. What is more, we show that this soft engagement translates into a more negative tone which, in turn, results in lower approval rates for management proposals. Shareholders' soft engagement at AGMs is hence an effective way to "walk the talk".
The issuance of sustainability-linked loans (SLLs) has grown exponentially in recent years. Using a scoring methodology, we examine the underlying key performance indicators of a large sample of SLLs and analyze whether their design creates effective incentives for improving corporate sustainability performance. We demonstrate that the majority of loans fails to meet key requirements that would make them credible instruments for generating effective sustainability incentives. These findings call into question the actual sustainability impact that may be achieved through the issuance of ESG-linked debt.
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.
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.
This paper investigates retirees’ optimal purchases of fixed and variable longevity income annuities using their defined contribution (DC) plan assets and given their expected Social Security benefits. As an alternative, we also evaluate using plan assets to boost Social Security benefits through delayed claiming. We determine that including deferred income annuities in DC accounts is welfare enhancing for all sex/education groups examined. We also show that providing access to well-designed variable deferred annuities with some equity exposure further enhances retiree wellbeing, compared to having access only to fixed annuities. Nevertheless, for the least educated, delaying claiming Social Security is preferred, whereas the most educated benefit more from using accumulated DC plan assets to purchase deferred annuities.
We investigate consumption patterns in Europe with supervised machine learning methods and reveal differences in age and wealth impact across countries. Using data from the third wave (2017) of the Eurosystem’s Household Finance and Consumption Survey (HFCS), we assess how age and (liquid) wealth affect the marginal propensity to consume (MPC) in the Netherlands, Germany, France, and Italy. Our regression analysis takes the specification by Christelis et al. (2019) as a starting point. Decision trees are used to suggest alternative variable splits to create categorical variables for customized regression specifications. The results suggest an impact of differing wealth distributions and retirement systems across the studied Eurozone members and are relevant to European policy makers due to joint Eurozone monetary policy and increasing supranational fiscal authority of the EU. The analysis is further substantiated by a supervised machine learning analysis using a random forest and XGBoost algorithm.
Mamma mia! Revealing hidden heterogeneity by PCA-biplot : MPC puzzle for Italy's elderly poor
(2023)
I investigate consumption patterns in Italy and use a PCA-biplot to discover a consumption puzzle for the elderly poor. Data from the third wave (2017) of the Eurosystem’s Household Finance and Consumption Survey (HFCS) indicate that Italian poor old-aged households boast lower levels of the marginal propensity to consume (MPC) than suggested by the dominant consumption models. A customized regression analysis exhibits group differences with richer peers to be only half as large as prescribed by a traditional linear regression model. This analysis has benefited from a visualization technique for high-dimensional matrices related to the unsupervised machine learning literature. I demonstrate that PCA-biplots are a useful tool to reveal hidden relations and to help researchers to formulate simple research questions. The method is presented in detail and suggestions on incorporating it in the econometric modeling pipeline are given.
Fund companies regularly send shareholder letters to their investors. We use textual analysis to investigate whether these letters’ writing style influences fund flows and whether it predicts performance and investment styles. Fund investors react to the tone and content of shareholder letters: A less negative tone leads to higher net flows. Thus, fund companies can use shareholder letters as a tactical instrument to influence flows. However, at the same time, a dishonest communication that is not consistent with the fund’s actual performance decreases flows. A positive writing style predicts higher idiosyncratic risk as well as more style bets, while there is no consistent predictive power for future performance.
Optimal monetary policy studies typically rely on a single structural model and identification of model-specific rules that minimize the unconditional volatilities of inflation and real activity. In their proposed approach, the authors take a large set of structural models and look for the model-robust rules that minimize the volatilities at those frequencies that policymakers are most interested in stabilizing. Compared to the status quo approach, their results suggest that policymakers should be more restrained in their inflation responses when their aim is to stabilize inflation and output growth at specific frequencies. Additional caution is called for due to model uncertainty.
Who should hold bail-inable debt and how can regulators police holding restrictions effectively?
(2023)
This paper analyses the demand-side prerequisites for the efficient application of the bail-in tool in bank resolution, scrutinises whether the European bank crisis management and deposit insurance (CMDI) framework is apt to establish them, and proposes amendments to remedy identified shortcomings.
The first applications of the new European CMDI framework, particularly in Italy, have shown that a bail-in of debt holders is especially problematic if they are households or other types of retail investors. Such debt holders may be unable to bear losses, and the social implications of bailing them in may create incentives for decision makers to refrain from involving them in bank resolution. In turn, however, if investors can expect resolution authorities (RAs) to behave inconsistently over time and bail-out bank capital and debt holders despite earlier vows to involve them in bank rescues, the pricing and monitoring incentives that the crisis management framework seeks to invigorate would vanish. As a result, market discipline would be suboptimal and moral hazard would persist. Therefore, the policy objectives of the CMDI framework will only be achieved if critical bail-in capital is not held by retail investors without sufficient loss-bearing capacity. Currently, neither the CMDI framework nor capital market regulation suffice to assure that this precondition is met. Therefore, some amendments are necessary. In particular, debt instruments that are most likely to absorb losses in resolution should have a high minimum denomination and banks should not be allowed to self-place such securities.
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
Using German and US brokerage data we find that investors are more likely to sell speculative stocks trading at a gain. Investors’ gain realizations are monotonically increasing in a stock’s speculativeness. This translates into a high disposition effect for speculative and a much lower disposition effect for non-speculative stocks. Our findings hold across asset classes (stocks, passive, and active funds) and explain cross-sectional differences in investor selling behavior which previous literature attributed primarily to investor demographics. Our results are robust to rank or attention effects and can be linked to realization utility and rolling mental account.
Recent empirical evidence shows that most international prices are sticky in dollars. This paper studies the policy implications of this fact in the context of an open economy model, allowing for an arbitrary structure of asset markets, general preferences and technologies, time- or state-dependent price setting, and a rich set of shocks. We show that although monetary policy is less efficient and cannot implement the flexible-price allocation, inflation targeting remains robustly optimal in non-U.S. economies. The implementation of this non-cooperative policy results in a "global monetary cycle" with other countries importing the monetary stance of the U.S. The capital controls cannot unilaterally improve the allocation and are useful only when coordinated across countries. Thanks to the dominance of the dollar, the U.S. can extract rents in international goods and asset markets and enjoy a higher welfare than other economies. Although international cooperation benefits other countries by improving global demand for dollar-invoiced goods, it is not in the self-interest of the U.S. and may be hard to sustain.
Output gap revisions can be large even after many years. Real-time reliability tests might therefore be sensitive to the choice of the final output gap vintage that the real-time estimates are compared to. This is the case for the Federal Reserve’s output gap. When accounting for revisions in response to the global financial crisis in the final output gap, the improvement in real-time reliability since the mid-1990s is much smaller than found by Edge and Rudd (Review of Economics and Statistics, 2016, 98(4), 785-791). The negative bias of real-time estimates from the 1980s has disappeared, but the size of revisions continues to be as large as the output gap itself.
The authors systematically analyse how the realtime reliability assessment is affected through varying the final output gap vintage. They find that the largest changes are caused by output gap revisions after recessions. Economists revise their models in response to such events, leading to economically important revisions not only for the most recent years, but reaching back up to two decades. This might improve the understanding of past business cycle dynamics, but decreases the reliability of real-time output gaps ex post.
We have designed and implemented an experimental module in the 2014 Health and Retirement Study to measure older persons' willingness to defer claiming of Social Security benefits. Under the current system’ status quo where delaying claiming boosts eventual benefits, we show that 46% of the respondents would delay claiming and work longer. If respondents were instead offered an actuarially fair lump sum payment instead of higher lifelong benefits, about 56% indicate they would delay claiming. Without a work requirement, the average amount needed to induce delayed claiming is only $60,400, while when part-time work is stipulated, the amount is slightly higher, $66,700. This small difference implies a low utility value of leisure foregone, of under 20% of average household income.
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?
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.
The modern tontine : an innovative instrument for longevity risk management in an aging society
(2020)
We investigate whether a historical pension concept, the tontine, yields enough innovative potential to extend and improve the prevailing privately funded pension solutions in a modern way. The tontine basically generates an age-increasing cash flow, which can help to match the increasing financing needs at old ages. In contrast to traditional pension products, however, the tontine generates volatile cash flows, which means that the insurance character of the tontine cannot be guaranteed in every situation. By employing Multi Cumulative Prospect Theory (MCPT) we answer the question to what extent tontines can be a complement to or a substitute for traditional annuities. We find that it is only optimal to invest in tontines for a certain range of initial wealth. In addition, we investigate in how far the tontine size, the volatility of individual liquidity needs and expected mortality rates contribute to the demand for tontines.
The financial sector plays an important role in financing the green transformation. Various regulatory initiatives in the EU aim to improve transparency in relation to the sustainability of financial products and the sustainability of economic activities of non-financial and financial undertakings. For credit institutions, the Green Asset Ratio (GAR) has been established by the European regulatory authorities as a KPI for measuring the proportion of Taxonomy-aligned on-balance-sheet exposure in relation to the total assets. The breakdown of the total GAR by type of counterparty, environmental objective and type of asset provides in-depth information about the sustainability profile of a credit institution. This information, which has not been available to date, may also initiate discussions between management and shareholders or other stakeholders regarding the future sustainability strategy of credit institutions. This paper provides an overview of the regulatory background and the method of calculating the GAR along different dimensions. Finally, the potential benefits and limitations of the GAR are discussed.
Highly interconnected global supply chains make countries vulnerable to supply chain disruptions. The authors estimate the macroeconomic effects of global supply chain shocks for the euro area. Their empirical model combines business cycle variables with data from international container trade.
Using a novel identification scheme, they augment conventional sign restrictions on the impulse responses by narrative information about three episodes: the Tohoku earthquake in 2011, the Suez Canal obstruction in 2021, and the Shanghai backlog in 2022. They show that a global supply chain shock causes a drop in euro area real economic activity and a strong increase in consumer prices. Over a horizon of one year, the global supply chain shock explains about 30% of inflation dynamics. They also use regional data on supply chain pressure to isolate shocks originating in China.
Their results show that supply chain disruptions originating in China are an important driver for unexpected movements in industrial production, while disruptions originating outside China are an especially important driver for the dynamics of consumer prices.
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 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.
Regulatory impact analysis (RIA) serves to evaluate whether regulatory actions fulfill the desired goals. Although there are different frameworks for conducting RIA, they are only applicable to regulations whose impact can be measured with structured data. Yet, a significant and increasing number of regulations require firms to comply by communicating textual data to consumers and supervisors. Therefore, we develop a methodological framework for RIA in case of unstructured data based on textual analysis and apply it to a recent financial market regulation: MiFID II.
Firms, researchers, and policy makers often want to measure consumption and especially how events, promotions, or policies affect it. Measuring consumption reactions is often hard. Firms lack access to competitors’ sales data and regularly do not share their own with outsiders. Large samples of smartphone location data could solve this problem. This article describes a research project using smartphone location data to estimate consumption reactions to political conflict during the Trump presidency.