Sustainable Architecture for Finance in Europe (SAFE)
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We show that financial advisors recommend more costly products to female clients, based on minutes from about 27,000 real-world advisory meetings and client portfolio data. Funds recommended to women have higher expense ratios controlling for risk, and women less often receive rebates on upfront fees for any given fund. We develop a model relating these findings to client stereotyping, and empirically verify an additional prediction: Women (but not men) with higher financial aptitude reject recommendations more frequently. Women state a preference for delegating financial decisions, but appear unaware of associated higher costs. Evidence of stereotyping is stronger for male advisors.
The recently observed disconnect between inflation and economic activity can be explained by the interplay between the zero lower bound (ZLB) and the costs of external financing. In normal times, credit spreads and the nominal interest rate balance out; factor costs dominate firms' marginal costs. When nominal rates are constrained, larger spreads can more than offset the effect of lower factor costs and induce only moderate inflation responses. The Phillips curve is hence flat at the ZLB, but features a positive slope in normal times and thus a hockey stick shape. Via this mechanism, forward guidance may induce deflationary effects.
We conducted a large-scale household survey in November 2020 to study how altering the time frame of a message (temporal framing) regarding an imminent positive income shock affects consumption plans. The income shock derives from the abolishment of the German solidarity surcharge on personal income taxes, effective in January 2021. We randomize across survey participants whether their extra disposable income is presented in Euros per month, Euros per year, or Euros per ten year-period. Our main findings are as follows: In General, we find our respondents’ intended Marginal Propensity to Consume (MPC) is 28.2%. Across all three treatments, the MPC is a positive function of age and being female while it is a negative function of the income increase’s size, self- control, and being unemployed. Temporal framing effects are statistically and economically highly significant as we find the monthly treatment groups’ average MPC 5.6 and 8.7 percentage points higher compared to the yearly and 10-yearly treatment groups. We will be able to analyze the real consumption behavior of households throughout 2021 based on re-surveying the participants as well as by using transaction-based bank data.
The authors examine the effectiveness of labor cost reductions as a means to stimulate economic activity and assesses the differences which may occur with the prevailing exchange rate regime. They develop a medium-scale three-region DSGE model and show that the impact of a cut in the employers’ social security contributions rate does not vary significantly under different exchange rate regimes. They find that both the interest rate and the exchange rate channel matters. Furthermore, the measure appears to be effective even if it comes along with a consumption tax increase to preserve long-term fiscal sustainability.
Finally, they assess whether obtained theoretical results hold up empirically by applying the local projection method. Regression results suggest that changes in employers’ social security contributions rates have statistically significant real effects – a one percentage point reduction leads to an average cumulative rise in output of around 1.3 percent in the medium term. Moreover, the outcome does not differ significantly across the different exchange rate regimes.
How people form beliefs is crucial for understanding decision-making un- der uncertainty. This is particularly true in a situation such as a pandemic, where beliefs will affect behaviors that impact public health as well as the aggregate economy. We conduct two survey experiments to shed light on potential biases in belief formation, focusing in particular on the tone of information people choose to consume and how they incorporate this information into their beliefs. In the first experiment, people express their preferences over pandemic-related articles with optimistic and pessimistic headlines, and are then randomly shown one of the articles. We find that respondents with more pessimistic prior beliefs about the pandemic are substantially more likely to prefer pessimistic articles, which we interpret as evidence of confirmation bias. In line with this, respondents assigned to the less preferred article rate it as less reliable and informative (relative to those who prefer it); they also discount information from the article when it is less preferred. We further find that these motivated beliefs end up impacting incentivized behavior. In a second experiment, we study how partisan views interact with information selection and processing. We find strong evidence of source dependence: revealing the news source further distorts information acquisition and processing, eliminating the role of prior beliefs in article choice.
This paper studies the behavior of competing firms in a duopoly with rational inattentive consumers. Firms play a sequential game in which they decide to obfuscate their individual prices before competing on price. Probabilistic demand functions are endogenously determined by the consumers’ optimal information strategy, which depends on the firms’ obfuscation choice and the consumers’ unrestricted prior beliefs. We show that the game may result in an obfuscation equilibrium with high prices where both firms obfuscate and a transparency equilibrium with low prices and no obfuscation, providing an argument for market regulation. Lower information costs and asymmetric prior beliefs about prices reduce the probability of an obfuscation equilibrium. Using data on Sweden, we document a decrease in price complexity and corresponding prices in the market for mobile phone subscriptions in the last two decades. Our model rationalizes these changes and explains why complexity and high prices persist in some but not all digitalized markets.
The disposition effect is implicitly assumed to be constant over time. However, drivers of the disposition effect (preferences and beliefs) are rather countercyclical. We use individual investor trading data covering several boom and bust periods (2001-2015). We show that the disposition effect is countercyclical, i.e. is higher in bust than in boom periods. Our findings are driven by individuals being 25% more likely to realize gains in bust than in boom periods. These changes in investors’ selling behavior can be linked to changes in investors’ risk aversion and in their beliefs across financial market cycles.
The centrality of the United States in the global financial system is taken for granted, but its response to recent political and epidemiological events has suggested that China now holds a comparable position. Using minute-by-minute data from 2012 to 2020 on the financial performance of twelve country-specific exchange-traded funds, we construct daily snapshots of the global financial network and analyze them for the centrality and connectedness of each country in our sample. We find evidence that the U.S. was central to the global financial system into 2018, but that the U.S.-China trade war of 2018–2019 diminished its centrality, and the Covid-19 outbreak of 2019–2020 increased the centrality of China. These indicators may be the first signals that the global financial system is moving from a unipolar to a bipolar world.
Smart(phone) investing? A within investor-time analysis of new technologies and trading behavior
(2021)
Using transaction-level data from two German banks, we study the effects of smartphones on investor behavior. Comparing trades by the same investor in the same month across different platforms, we find that smartphones increase purchasing of riskier and lottery-type assets and chasing past returns. After the adoption of smartphones, investors do not substitute trades across platforms and buy also riskier, lottery-type, and hot investments on other platforms. Using smartphones to trade specific assets or during specific hours contributes to explain our results. Digital nudges and the device screen size do not mechanically drive our results. Smartphone effects are not transitory.
The FOMC risk shift
(2021)
We identify a component of monetary policy news that is extracted from high-frequency changes in risky asset prices. These surprises, which we call “risk shifts”, are uncorrelated, and therefore complementary, to risk-free rate surprises. We show that (i) risk shifts capture the lion’s share of stock price movements around FOMC announcements; (ii) that they are accompanied by significant investor fund flows, suggesting that investors react heterogeneously to monetary policy news; and (iii) that price pressure amplifies the stock market response to monetary policy news. Our results imply that central bank information effects are overshadowed by short-term dynamics stemming from investor rebalancing activities and are likely to be more difficult to identify than previously thought.
Broad, long-term financial and economic datasets are a scarce resource, in particular in the European context. In this paper, we present an approach for an extensible, i.e. adaptable to future changes in technologies and sources, data model that may constitute a basis for digitized and structured long- term, historical datasets. The data model covers specific peculiarities of historical financial and economic data and is flexible enough to reach out for data of different types (quantitative as well as qualitative) from different historical sources, hence achieving extensibility. Furthermore, based on historical German company and stock market data, we discuss a relational implementation of this approach.
The so-called Troika, consisting of the EU-Commission, the European Central Bank (ECB) and the International Monetary Fund (IMF), was supposed to support the member states of the euro area which had been hit hard by a sovereign debt crisis. For that purpose, economic adjustment programs were drafted and monitored in order to prevent the break-up of the euro area and sovereign defaults. The cooperation of these institutions, which was born out of necessity, has been partly successful, but has also created persistent problems. With the further increase of public debt, especially in France and Italy, the danger of a renewed crisis in the euro area was growing. The European Stability Mechanism (ESM) together with the European Commission will replace the Troika in the future, following decisions of the EU Summit of December 2018. It shall play the role of a European Monetary Fund in the event of a crisis. The IMF, on the other side, will no longer play an active role in solving sovereign debt crises in the euro area. The current course is, however, inadequate to tackle the core problems of the euro zone and to avoid future crises, which are mainly structural in nature and due to escalating public debt and lack of international competitiveness of some member countries. The current Corona crisis will aggravate the institutional problems. It has led to a common European fiscal response ("Next Generation EU"). This rescue and recovery program will not be financed by ESM resources and will not be monitored by the ESM. One important novelty of this package is that it involves the issuance of substantial common European debt.
Der Einsatz von Künstliche Intelligenz (KI) – Technologien eröffnet viele Chancen, birgt aber auch viele Risiken – insbesondere in der Finanzbranche. Dieses Whitepaper gibt einen Überblick über den aktuellen Stand der Anwendung und Regulierung von KI-Technologien in der Finanzbranche, und diskutiert Chancen und Risiken von KI. KI findet in der Finanzbranche zahlreiche Anwendungsgebiete. Dazu gehören Chatbots, intelligente Assistenten für Kunden, automatischer Hochfrequenzhandel, automatisierte Betrugserkennung, Überwachung der Compliance, Gesichtserkennungssoftware zur Kundenidentifikation u. v. m. Auch Finanzaufsichtsbehörden setzen zunehmend KI-Anwendungen ein, um große und komplexe Datenmengen (Big Data) automatisiert und skalierbar auf Muster zu untersuchen und ihren Aufsichtspflichten nachzukommen.
Die Regulierung von KI in der Finanzbranche ist ein Balanceakt. Auf der einen Seite gibt es eine Notwendigkeit Flexibilität zu gewährleisten, um Innovationen nicht einzudämmen und im internationalen Wettbewerb nicht abgehängt zu werden. Strenge Auflagen können in diesem Zusammenhang als Barriere für die erfolgreiche Weiter-)Entwicklung von KI-Applikationen in der Finanzbranche wirken. Auf der anderen Seite müssen Persönlichkeitsrechte geschützt und Entscheidungsprozesse nachvollziehbar bleiben. Die fehlende Erklärbarkeit und Interpretierbarkeit von KI-Modellen entsteht in erster Linie durch Intransparenz bei einem Großteil heutiger KI-Anwendungen, bei welchen zwar die Natur der Ein- und Ausgaben beobachtbar und verständlich ist, nicht jedoch die genauen Verarbeitungsschritte dazwischen (Blackbox Prinzip).
Dieses Spannungsfeld zeigt sich auch im aktuellen regulatorischen Ansatz verschiedener Behörden. So werden einerseits die positiven Seiten von KI betont, wie Effizienz- und Effektivitätsgewinne sowie Rentabilitäts- und Qualitätssteigerungen (Bundesregierung, 2019) oder neue Methoden der Gefahrenanalyse in der Finanzmarktregulierung (BaFin, 2018a). Andererseits, wird darauf verwiesen, dass durch KI getroffene Entscheidungen immer von Menschen verantwortet werden müssen (EU Art. 22 DSGVO) und demokratische Rahmenbedingungen des Rechtsstaats zu wahren seien (FinTechRat, 2017).
Für die Zukunft sehen wir die Notwendigkeit internationale Regularien prinzipienbasiert, vereinheitlicht und technologieneutral weiterzuentwickeln, ohne dabei die Entwicklung neuer KIbasierter Geschäftsmodelle zu bremsen. Im globalen Wettstreit sollte Europa bei der Regulierung des KI-Einsatzes eine Vorreiterrolle einnehmen und damit seine demokratischen Werte der digitalen Freiheit, Selbstbestimmung und das Recht auf Information weltweit exportieren. Förderprogramme sollten einen stärkeren Fokus auf die Entwicklung nachhaltiger und verantwortungsvoller KI in Banken legen. Dazu zählt insbesondere die (Weiter-)Entwicklung breit einsetzbarer Methoden, die es erlauben, menschen-interpretierbare Erklärungen für erzeugte Ausgaben bereitzustellen und Problemen wie dem Blackbox Prinzip entgegenzuwirken.
Aus Sicht der Unternehmen in der Finanzbranche könnte eine Kooperation mit BigTech-Unternehmen sinnvoll sein, um gemeinsam das Potential der Technologie bestmöglich ausschöpfen zu können. Nützlich wäre auch ein gemeinsames semantisches Metadatenmodell zur Beschreibung der in der Finanzbranche anfallenden Daten. In Zukunft könnten künstliche Intelligenzen Daten aus sozialen Netzwerken berücksichtigen oder Smart Contracts aushandeln. Eine der größten Herausforderungen der Zukunft wird das Anwerben geeigneten Personals darstellen.
Despite the increasing use of cashless payment instruments, the notion that cash loses importance over time can be unambiguously refuted. In contrast, the authors show that cash demand increased steeply over the past 30 years. This is not only true on a global scale, but also for the most important currencies in advanced countries (USD, EUR, CHF, GBP and JPY). In this paper, they focus especially on the role of different crises (technological crises, financial market crises, natural disasters) and analyse the demand for small and large banknote denominations since the 1990s in an international perspective. It is evident that cash demand always increases in times of crises, independent of the nature of the crisis itself. However, largely unaffected from crises we observe a trend increase in global cash aligned with a shift from transaction balances towards more hoarding, especially in the form of large denomination banknotes.
Although the elderly are more vulnerable to COVID-19, the empirical evidence suggests that they do not behave more cautiously in the pandemic than younger individuals. This theoretical model argues that some individuals might not comply with the COVID-19 measures to reassure themselves that they are not vulnerable, and that the incentives for such self-signaling can be stronger for the elderly. The results suggest that communication strategies emphasizing the dangers of COVID-19 could backfire and reduce compliance among the elderly.
We study risk taking in a panel of subjects in Wuhan, China - before, during the COVID-19 crisis, and after the country reopened. Subjects in our sample traveled for semester break in January, generating variation in exposure to the virus and quarantine in Wuhan. Higher exposure leads subjects to reduce planned risk taking, risky investments, and optimism. Our findings help unify existing studies by showing that aggregate shocks affect general preferences for risk and economic expectations, while heterogeneity in experience further affect risk taking through beliefs about individuals’ own outcomes such as luck and sense of control.
JEL Classification: G50, G51, G11, D14, G41
The authors embed human capital-based endogenous growth into a New-Keynesian model with search and matching frictions in the labor market and skill obsolescence from long-term unemployment. The model can account for key features of the Great Recession: a decline in productivity growth, the relative stability of inflation despite a pronounced fall in output (the "missing disinflation puzzle"), and a permanent gap between output and the pre-crisis trend output.
In the model, lower aggregate demand raises unemployment and the training costs associated with skill obsolescence. Lower employment hinders learning-by-doing, which slows down human capital accumulation, feeding back into even fewer vacancies than justified by the demand shock alone. These feedback channels mitigate the disinflationary effect of the demand shock while amplifying its contractionary effect on output. The temporary growth slowdown translates into output hysteresis (permanently lower output and labor productivity).
Occasionally binding constraints have become an important part of economic modelling, especially since western central banks see themselves (again) constraint by the so-called zero lower bound (ZLB) of the nominal interest rate. A binding ZLB constraint poses a major problem for a quantitative-structural analysis: Linear solution methods do no work in the presence of a non-linearity such as the ZLB and existing alternatives tend to be computationally demanding. The urge to study macroeconomic questions related to the Great Recession and the Covid-19 crisis in a quantitative-structural framework requires algorithms that are not only accurate, but that are also robust, fast, and computationally efficient.
A particularly important application where efficient and fast methods for occasionally binding constraints (OBCs) are needed is the Bayesian estimation of macroeconomic models. This paper shows that a linear dynamic rational expectations system with OBCs, depending on the expected duration of the constraint, can be represented in closed form. Combined with a set of simple equilibrium conditions, this can be exploited to avoid matrix inversions and simulations at runtime for signifcant gains in computational speed.
Central banks sometimes evaluate their own policies. To assess the inherent conflict of interest, the authors compare the research findings of central bank researchers and academic economists regarding the macroeconomic effects of quantitative easing (QE). They find that central bank papers report larger effects of QE on output and inflation. Central bankers are also more likely to report significant effects of QE on output and to use more positive language in the abstract. Central bankers who report larger QE effects on output experience more favorable career outcomes. A survey of central banks reveals substantial involvement of bank management in research production.
Empirical estimates of equilibrium real interest rates are so far mostly limited to advanced economies, since no statistical procedure suitable for a large set of countries is available. This is surprising, as equilibrium rates have strong policy implications in emerging markets and developing economies as well; current estimates of the global equilibrium rate rely on only a few countries; and estimates for a more diverse set of countries can improve understanding of the drivers. The authors propose a model and estimation strategy that decompose ex ante real interest rates into a permanent and transitory component even with short samples and high volatility. This is done with an unobserved component local level stochastic volatility model, which is used to estimate equilibrium rates for 50 countries with Bayesian methods.
Equilibrium rates were lower in emerging markets and developing economies than in advanced economies in the 1980s, similar in the 1990s, and have been higher since 2000. In line with economic integration and rising global capital markets, synchronization has been rising over time and is higher among advanced economies. Equilibrium rates of countries with stronger trade linkages and similar demographic and economic trends are more synchronized.
With the second wave of the Covid-19 pandemic in full swing, banks face a challenging environment. They will need to address disappointing results and adverse balance sheet restatements, the intensity of which depends on the evolution of the euro area economies. At the same time, vulnerable banks reinforce real economy deficiencies. The contribution of this paper is to provide a comparative assessment of the various policy responses to address a looming banking crisis. Such a crisis will fully materialize when non-performing assets drag down banks simultaneously, raising the specter of a full-blown systemic crisis. The policy responses available range from forbearance, recapitalization (with public or private resources), asset separation (bad banks, at national or EU level), to debt conversion schemes. We evaluate these responses according to a set of five criteria that define the efficacy of each. These responses are not mutually exclusive, in practice, as they have never been. They may also go hand in hand with other restructuring initiatives, including potential consolidation in the banking sector. Although we do not make a specific recommendation, we provide a framework for policymakers to guide them in their decision making.
Following the financial crash and the subsequent recession, European policymakers have undertaken major reforms regarding the European Economic and Monetary Union (EMU). Yet, the success rate is mixed. Several reform proposals have either completely failed due to opposition forces or are still pending, sometimes for years. This article provides an overview of reforms in four major policy fields: financial stabilisation, economic governance, fiscal solidarity, and cooperative dissolution. Building on the conceptual foundation of policy analysis, it distinguishes between policy outputs and outcomes. Policy output refers to legislation being adopted or agreement on treaty changes, while policy outcomes depict the result from the implementation process.
This policy white paper shows, using data on European Commission (EC) lobby meetings, that financial institutions and finance trade associations have substantial access to EC policymakers. While lobbying could transfer policy-relevant information and expertise to policymakers, it could also result in the capture of policymakers by the industry, which could harm consumers and taxpayers. How could policymakers prevent regulatory capture, but retain the benefits of the sector expertise in policy decisions? Awareness of regulatory capture by policymakers is one of the most important remedies. This paper provides an overview of the origins of the regulatory capture theory and recent academic evidence. The paper shows that regulatory capture could emerge in a variety of institutions and policy areas but is not ubiquitous and depends on the incentives of policymakers and the policy environment. Subsequently, the paper discusses various measures to prevent regulatory capture, such as more transparency, diverse expert groups, and cooling-off periods.
Fiscal policies and household consumption during the COVID-19 pandemic: a review of early evidence
(2020)
We review early evidence on how household consumption behavior has evolved over the pandemic and how different groups of households have responded to fiscal stimulus programs. Due to the scarcity of evidence for Europe, our review focuses on evidence from the US. Notwithstanding the institutional and demographic differences, we highlight generalizable findings and challenges to the design of stimulus policies from the pandemic. In conclusion, we identify several open issues for dis cussion.
OTC discount
(2020)
We document a sizable OTC discount in the interdealer market for German sovereign bonds where exchange and over-the-counter trading coexist: the vastmajority of OTC prices are favorable with respect to exchange quotes. This is a challenge for theories of OTC markets centered around search frictions but consistent with models of hybrid markets based on information frictions. We show empiricallythat proxies for both frictions determine variation in the discount, which is largely passed on to customers. Dealers trade on the exchange for immediacy and via brokers for opacity and anonymity, highlighting the complementary roles played by the di↵erent protocols.
We relate time-varying aggregate ambiguity (V-VSTOXX) to individual investor trading. We use the trading records of more than 100,000 individual investors from a large German online brokerage from March 2010 to December 2015. We find that an increase in ambiguity is associated with increased investor activity. It also leads to a reduction in risk-taking which does not reverse over the following days. When ambiguity is high, the effect of sentiment looms larger. Survey evidence reveals that ambiguity averse investors are more prone to ambiguity shocks. Our results are robust to alternative survey-, newspaper- or market-based ambiguity measures.
Supranational rules, national discretion: increasing versus inflating regulatory bank capital?
(2020)
We study how higher capital requirements introduced at the supranational level affect the regulatory capital of banks across countries. Using the 2011 EBA capital exercise as a quasi-natural experiment, we find that treated banks exploit discretion in the calculation of regulatory capital to inflate their capital ratios without a commensurate increase in their book equity and without a reduction in bank risk. Regulatory capital inflation is more pronounced in countries where credit supply is expected to tighten, suggesting that national authorities forbear their domestic banks to meet supranational requirements, with a focus on short-term economic considerations.
In diesem Beitrag wird ein Vorschlag vorgestellt, wie es trotz langfristiger Niedrigzinsen möglich ist, die vor 18 Jahren eingeführte Riester-Rente so umzugestalten, dass alle Beteiligten davon profitieren. Wird die Mindestauszahlung am Ende der Vertragslaufzeit nur für die Eigenbeiträge, nicht aber für die staatlichen Zulagen garantiert, können deutlich höhere Renditen erzielt werden. Unter dem Strich haben dann nicht nur Privatleute mehr Geld aus ihrer Altersvorsorge, sondern der Staat wird mehr Steuern einnehmen und die Anbieter haben mehr Spielraum für bedarfsgerechte Produktgestaltung.
The paper discusses the policy implications of the Wirecard scandal. The study finds that all lines of defense against corporate fraud, including internal control systems, external audits, the oversight bodies for financial reporting and auditing and the market supervisor, contributed to the scandal and are in need of reform. To ensure market integrity and investor protection in the future, the authors make eight suggestions for the market and institutional oversight architecture in Germany and in Europe.
Banks are not immune from COVID-19. The economic downturn may drive some banks to the point of non-viability (PONV). If so, is the resolution regime in the Euro-area ready to respond? No, for banks may not have the right amount of the right kind of liabilities to make bail-in work. That could lead to a banking crisis. The Euro area can avoid this risk, by arranging now for a recap later. This would plug the gap between what the failing bank has and what it would need to make bail-in work. To do so, banks would pay – possibly via the contributions they make to the Single Resolution Fund – a commitment fee to a European backstop authority for a mandatory, system-wide note issuance facility. This would compel each bank, as it approached or reached the PONV, to issue to the backstop, and the backstop to purchase from the bank, the obligations the failing bank needs in order to make bail-in work. Such obligations would take the form of “senior-most” non-preferred debt, and bail-in would stop with such debt. That would allow the SRB to use the bail-in tool to resolve the failed bank, reopen it and run it under a solvent wind-down strategy. That protects counterparties and customers and ensures the continuity of critical economic functions. It also keeps investors at risk and promotes market discipline. Above all, it preserves financial stability.
Inflation ist ein Konstrukt. Sie wird von unterschiedlichen Akteur*innen unterschiedlich wahrgenommen. Zum Teil passiert dies, weil Warenkörbe differieren, zum Teil weil Erwartungen unterschiedlich gebildet werden. Dieser Beitrag diskutiert die Heterogenität der Infl ation und ihrer Wahrnehmung und was dies für die Zielgröße der Zentralbankpolitik bedeutet.
Inflation ist ein Konstrukt. Sie wird von unterschiedlichen Akteuren unterschiedlich wahrgenommen. Zum Teil passiert dies, weil Warenkörbe differieren, zum Teil weil Erwartungen unterschiedlich gebildet werden. Dieser Beitrag diskutiert die Heterogenität der Inflation und ihrer Wahrnehmung und was dies für die Zielgröße der Zentralbankpolitik bedeutet.
The paper compares provision of public infrastructure via public-private partnerships (PPPs) with provision under government management. Due to soft budget constraints of government management, PPPs exert more effort and therefore have a cost advantage in building infrastructure. At the same time, hard budget constraints for PPPs introduce a bankruptcy risk and bankruptcy costs. Consequently, if bankruptcy costs are high, PPPs may be less efficient than public management, although this does not result from PPPs’ higher interest costs.
We develop a novel empirical approach to identify the effectiveness of policies against a pandemic. The essence of our approach is the insight that epidemic dynamics are best tracked over stages, rather than over time. We use a normalization procedure that makes the pre-policy paths of the epidemic identical across regions. The procedure uncovers regional variation in the stage of the epidemic at the time of policy implementation. This variation delivers clean identification of the policy effect based on the epidemic path of a leading region that serves as a counterfactual for other regions. We apply our method to evaluate the effectiveness of the nationwide stay-home policy enacted in Spain against the Covid-19 pandemic. We find that the policy saved 15.9% of lives relative to the number of deaths that would have occurred had it not been for the policy intervention. Its effectiveness evolves with the epidemic and is larger when implemented at earlier stages.
This paper studies a household’s optimal demand for a reverse mortgage. These contracts allow homeowners to tap their home equity to finance consumption needs. In stylized frameworks, we show that the decision to enter a reverse mortgage is mainly driven by the dierential between the aggregate appreciation of the house price and principal limiting factor on the one hand and the funding costs of a household on the other hand. We also study a rich life-cycle model that can explain the low demand for reverse mortgages as observed in US data. In this model, we analyze the optimal response of a household that is confronted with a health shock or financial disaster. If an agent suers from an unexpected health shock, she reduces the risky portfolio share and is more likely to enter a reverse mortgage. On the other hand, if there is a large drop in the stock market, she keeps the risky portfolio share almost constant by buying additional shares of stock. Besides, the probability to take out a reverse mortgage is hardly aected.
The ruling of the German Federal Constitutional Court and its call for conducting and communicating proportionality assessments regarding monetary policy have been the subject of some controversy. However, it can also be understood as a way to strengthen the de-facto independence of the European Central Bank. The authors shows how a regular proportionality check could be integrated in the ECB’s strategy that is currently undergoing a systematic review. In particular, they propose to include quantitative benchmarks for policy rates and the central bank balance sheet. Deviations from such benchmarks can have benefits in terms of the intended path for inflation while involving costs in terms of risks and side effects that need to be balanced. Practical applications to the euro area are provided
In this paper we adapt the Hamiltonian Monte Carlo (HMC) estimator to DSGE models, a method presently used in various fields due to its superior sampling and diagnostic properties. We implement it into a state-of-theart, freely available high-performance software package, STAN. We estimate a small scale textbook New-Keynesian model and the Smets-Wouters model using US data. Our results and sampling diagnostics confirm the parameter estimates available in existing literature. In addition, we find bimodality in the Smets-Wouters model even if we estimate the model using the original tight priors. Finally, we combine the HMC framework with the Sequential Monte Carlo (SMC) algorithm to create a powerful tool which permits the estimation of DSGE models with ill-behaved posterior densities.
This paper studies the link between bank recapitalization and welfare in a dynamic production economy. The model features financial frictions because banks benefit of a cost advantage at monitoring firms and face costly equity issuance. The competitive equilibrium outcome is inefficient because agents do not internalize the effects banks’ capitalization over the allocation of capital, its price and, in turn, firms investments. It follows, individual recapitalizations are sub-optimal and bailout policies may benefit social welfare in the long-run. Bailouts improve capital allocation in states where aggregate banks are poorly capitalized, therefore enhancing their market valuation, fostering investments, and stabilizing the economy recovery path.
Market fragmentation and technological advances increasing the speed of trading altered the functioning and stability of global equity limit order markets. Taking market resiliency as an indicator of market quality, we investigate how resilient are trading venues in a high-frequency environment with cross-venue fragmented order flow. Employing a Hawkes process methodology on high-frequency data for FTSE 100 stocks on LSE, a traditional exchange, and on Chi-X, an alternative venue, we find that when liquidity becomes scarce Chi-X is a less resilient venue than LSE with variations existing across stocks and time. In comparison with LSE, Chi-X has more, longer, and severer liquidity shocks. Whereas the vast majority of liquidity droughts on both venues disappear within less than one minute, the recovery is not lasting, as liquidity shocks spiral over the time dimension. Over half of the shocks on both venues are caused by spiralling. Liquidity shocks tend to spiral more on Chi-X than on LSE for large stocks suggesting that the liquidity supply on Chi-X is thinner than on LSE. Finally, a significant amount of liquidity shocks spill over cross-venue providing supporting evidence for the competition for order flow between LSE and Chi-X.
Using a structural life-cycle model, we quantify the long-term impact of school closures during the Corona crisis on children affected at different ages and coming from households with different parental characteristics. In the model, public investment through schooling is combined with parental time and resource investments in the production of child human capital at different stages in the children's development process. We quantitatively characterize both the long-term earnings consequences on children from a Covid-19 induced loss of schooling, as well as the associated welfare losses. Due to self-productivity in the human capital production function, skill attainment at a younger stage of the life cycle raises skill attainment at later stages, and thus younger children are hurt more by the school closures than older children. We find that parental reactions reduce the negative impact of the school closures, but do not fully offset it. The negative impact of the crisis on children's welfare is especially severe for those with parents with low educational attainment and low assets. The school closures themselves are primarily responsible for the negative impact of the Covid-19 shock on the long-run welfare of the children, with the pandemic-induced income shock to parents playing a secondary role.
Predictability and the cross-section of expected returns: a challenge for asset pricing models
(2020)
Many modern macro finance models imply that excess returns on arbitrary assets are predictable via the price-dividend ratio and the variance risk premium of the aggregate stock market. We propose a simple empirical test for the ability of such a model to explain the cross-section of expected returns by sorting stocks based on the sensitivity of expected returns to these quantities. Models with only one uncertainty-related state variable, like the habit model or the long-run risks model, cannot pass this test. However, even extensions with more state variables mostly fail. We derive criteria models have to satisfy to produce expected return patterns in line with the data and discuss various examples.
The possibility to investigate the impact of news on stock prices has observed a strong evolution thanks to the recent use of natural language processing (NLP) in finance and economics. In this paper, we investigate COVID-19 news, elaborated with the ”Natural Language Toolkit” that uses machine learning models to extract the news’ sentiment. We consider the period from January till June 2020 and analyze 203,886 online articles that deal with the pandemic and that were published on three platforms: MarketWatch.com, Reuters.com and NYtimes.com. Our findings show that there is a significant and positive relationship between sentiment score and market returns. This result indicates that an increase (decrease) in the sentiment score implies a rise in positive (negative) news and corresponds to positive (negative) market returns. We also find that the variance of the sentiments and the volume of the news sources for Reuters and MarketWatch, respectively, are negatively associated to market returns indicating that an increase of the uncertainty of the sentiment and an increase in the arrival of news have an adverse impact on the stock market.
Using experimental data from a comprehensive field study, we explore the causal effects of algorithmic discrimination on economic efficiency and social welfare. We harness economic, game-theoretic, and state-of-the-art machine learning concepts allowing us to overcome the central challenge of missing counterfactuals, which generally impedes assessing economic downstream consequences of algorithmic discrimination. This way, we are able to precisely quantify downstream efficiency and welfare ramifications, which provides us a unique opportunity to assess whether the introduction of an AI system is actually desirable. Our results highlight that AI systems’ capabilities in enhancing welfare critically depends on the degree of inherent algorithmic biases. While an unbiased system in our setting outperforms humans and creates substantial welfare gains, the positive impact steadily decreases and ultimately reverses the more biased an AI system becomes. We show that this relation is particularly concerning in selective-labels environments, i.e., settings where outcomes are only observed if decision-makers take a particular action so that the data is selectively labeled, because commonly used technical performance metrics like the precision measure are prone to be deceptive. Finally, our results depict that continued learning, by creating feedback loops, can remedy algorithmic discrimination and associated negative effects over time.
In this paper we adopt the Hamiltonian Monte Carlo (HMC) estimator for DSGE models by implementing it into a state-of-the-art, freely available high-performance software package. We estimate a small scale textbook New-Keynesian model and the Smets-Wouters model on US data. Our results and sampling diagnostics confirm the parameter estimates available in existing literature. In addition we combine the HMC framework with the Sequential Monte Carlo (SMC) algorithm which permits the estimation of DSGE models with ill-behaved posterior densities.
Incentivized experiments in which individuals receive monetary rewards according to the outcomes of their decisions are regarded as the gold standard for preference elicitation in experimental economics. These task-related real payments are considered necessary to reveal subjects' "true preferences". Using a systematic, large-sample approach with three subject pools of private investors, professional investors, and students, we test the effect of task-related monetary incentives on risk preferences elicited in four standard experimental tasks. We find no systematic differences in behavior between subjects in the incentivized and non-incentivized regimes. We discuss implications for academic research and for applications in the field.
Discussions regarding the planned European Deposit Insurance Scheme (EDIS), the missing third pillar of the European Banking Union, have been ongoing since the Commission published its initial legisla-tive proposal in 2015. A breakthrough in negotiations has yet to be achieved. The gridlock on EDIS is most commonly attributed to moral hazard concerns over insufficient risk reduction harboured on the side of northern member states, particularly Germany, due to the weak state of some other member states’ banking sectors. While moral hazard based on uneven risk reduction is helpful for explaining divergent member-state preferences on the scope of necessary risk reduction, this does not explain preferences on the institutional design of EDIS. In this paper, we argue that contrary to persistent differences on necessary risk reduction, preferences regarding the institutional design of EDIS have become more closely aligned. We analyse how preferences on EDIS developed in the key member states of Germany, France, and Italy. In all sampled countries, we find path-dependent benefits con-nected to the current design of national Deposit Guarantee Schemes (DGS) that shifted preferences of the banking sector or significant subsectors in favour of retaining national DGSs. Overall, given that a compromise on risk-reduction can be accomplished, we argue that current preferences in these key member states provide an opportunity to implement EDIS in the form of a reinsurance system that maintains national DGSs in combination with a supranational fund.
We employ a representative sample of 80,972 Italian firms to forecast the drop in profits and the equity shortfall triggered by the COVID-19 lockdown. A 3-month lockdown generates an aggregate yearly drop in profits of about 10% of GDP, and 17% of sample firms, which employ 8.8% of the sample’s employees, become financially distressed. Distress is more frequent for small and medium-sized enterprises, for firms with high pre-COVID-19 leverage, and for firms belonging to the Manufacturing and Wholesale Trading sectors. Listed companies are less likely to enter distress, whereas the correlation between distress rates and family firm ownership is unclear.
(JEL G01, G32, G33)
We analyze the ESG rating criteria used by prominent agencies and show that there is a lack of a commonality in the definition of ESG (i) characteristics, (ii) attributes and (iii) standards in defining E, S and G components. We provide evidence that heterogeneity in rating criteria can lead agencies to have opposite opinions on the same evaluated companies and that agreement across those providers is substantially low. Those alternative definitions of ESG also a↵ect sustainable investments leading to the identification of di↵erent investment universes and consequently to the creation of di↵erent benchmarks. This implies that in the asset management industry it is extremely dicult to measure the ability of a fund manager if financial performances are strongly conditioned by the chosen ESG benchmark. Finally, we find that the disagreement in the scores provided by the rating agencies disperses the e↵ect of preferences of ESG investors on asset prices, to the point that even when there is agreement, it has no impact on financial performances.
Die durch das Zweite Corona-Steuerhilfegesetz erfolgte Ausweitung des Verlustrücktrags ist dem Grunde nach ein hochgradig geeignetes und insbesondere breitenwirksames Mittel zur Stützung der Konjunktur. Das vorliegende Policy White Paper legt dar, dass allerdings Art und Umfang der gewählten Ausweitung unzureichend sind. Hierzu analysieren die Verfasser, wie sich die Ausweitung auf Unternehmen unterschiedlicher Größe und Rechtsform auswirkt. Auf Basis dieser Analyse zei-gen sie sodann, dass gemessen an den verfolgten konjunkturpolitischen Zielen es geboten gewesen wäre und weiterhin geboten ist, den Verlustrücktrag auf die Gewerbesteuer zu erstrecken.