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Institute
- Center for Financial Studies (CFS) (87) (remove)
The authors study the impact of dissent in the ECB‘s Governing Council on uncertainty surrounding households‘ inflation expectations. They conduct a randomized controlled trial using the Bundesbank Online Panel Households. Participants are provided with alternative information treatments concerning the vote in the Council, e.g. unanimity and dissent, and are asked to submit probabilistic inflation expectations. The results show that the vote is informative.
Households revise their subjective inflation forecast after receiving information about the vote. Dissenting votes cause a wider individual distribution of future inflation. Hence, dissent increases households‘ uncertainty about inflation. This effect is statistically significant once the authors allow for the interaction between the treatments and individual characteristics of respondents.
The results are robust with respect to alternative measures of forecast uncertainty and hold for different model specifications. The findings suggest that providing information about dissenting votes without additional information about the nature of dissent is detrimental to coordinating household expectations.
In the communication of the European Central Bank (ECB), the statement that „we act within our mandate“ is often referred to. Also among practitioners of the Eurosystem the term „mandate“ has become popular. In his Working Paper, Helmut Siekmann analyzes the legal foundation of the tasks and objectives of the Eurosysstem and price stability as a legal term. He finds that the primary law of the EU only very sparsely employs the term „mandate“. It is never used in the context of monetary policy and its institutions. Moreover, he comes to the conclusion that inflation targeting as a task, competence, or objective of the Eurosystem is legally highly questionable according to the common standards of interpretation.
Central banks have faced a succession of crises over the past years as well as a number of structural factors such as a transition to a greener economy, demographic developments, digitalisation and possibly increased onshoring. These suggest that the future inflation environment will be different from the one we know. Thus uncertainty about important macroeconomic variables and, in particular, inflation dynamics will likely remain high.
Veronika Grimm, Lukas Nöh, and Volker Wieland assess the possible development of government interest expenditures as a share of GDP for Germany, France, Italy and Spain. Until 2021, these and other member states could anticipate a further reduction of interest expenditure in the future. This outlook has changed considerably with the recent surge in inflation and government bond rates. Nevertheless, under reasonable assumptions current yield curves still imply that interest expenditure relative to GDP can be stabilized at the current level. The authors also review the implications of a further upward shift in the yield curves of 1 or 2 percentage points. These implications suggest significant medium-term risks for highly indebted member states with interest expenditure approaching or exceeding levels last observed on the eve of the euro area debt crisis. In light of these risks, governments of euro area member states should take substantive action to achieve a sustained decline in debt-to-GDP ratios towards safer levels. They bear the responsibility for making sure that government finances can weather the higher interest rates which are required to achieve price stability in the euro area.
Gegen den Landeshaushalt 2022 des Freistaats Thüringen bestehen nach Einschätzung von Helmut Siekmann erhebliche verfassungsrechtliche Bedenken. In einem Gutachten kommt Siekmann zu dem Schluss, dass sich die festgestellten globalen Minderausgaben im Vergleich zum gesamten Haushaltsvolumen nicht rechtfertigen lassen. Der verfassungsrechtlich gebotene Haushaltsausgleich sei nur dadurch erzielt worden, dass die eigentlich gebotenen Einzelkürzungen nicht vom Parlament entschieden, sondern der Exekutive überlassen worden seien. Durch Globale Minderausgaben soll der Ausgleich von Einnahmen und Ausgaben erreicht werden, ohne dafür erforderliche und politisch oft schwer durchsetzbare Kürzungen bei Einzeltiteln vornehmen zu müssen.
In Thüringen fehlen der Minderheitskoalition aus Linke, SPD und Grünen im Parlament vier Stimmen für eine eigene Mehrheit. Sie muss damit bei allen Entscheidungen eine Unterstützung der oppositionellen CDU aushandeln. Siekmann weist in seinem Gutachten darauf hin, dass die Veranschlagung von globalen Minderausgaben gleich welcher Art in keinem Fall die Exekutive ermächtigt, bestehende Verpflichtungen nicht zu erfüllen.
The authors propose a new method to forecast macroeconomic variables that combines two existing approaches to mixed-frequency data in DSGE models. The first existing approach estimates the DSGE model in a quarterly frequency and uses higher frequency auxiliary data only for forecasting. The second method transforms a quarterly state space into a monthly frequency. Their algorithm combines the advantages of these two existing approaches.They compare the new method with the existing methods using simulated data and real-world data. With simulated data, the new method outperforms all other methods, including forecasts from the standard quarterly model. With real world data, incorporating auxiliary variables as in their method substantially decreases forecasting errors for recessions, but casting the model in a monthly frequency delivers better forecasts in normal times.
The authors present and compare Newton-based methods from the applied mathematics literature for solving the matrix quadratic that underlies the recursive solution of linear DSGE models. The methods are compared using nearly 100 different models from the Macroeconomic Model Data Base (MMB) and different parameterizations of the monetary policy rule in the medium-scale New Keynesian model of Smets and Wouters (2007) iteratively. They find that Newton-based methods compare favorably in solving DSGE models, providing higher accuracy as measured by the forward error of the solution at a comparable computation burden. The methods, however, suffer from their inability to guarantee convergence to a particular, e.g. unique stable, solution, but their iterative procedures lend themselves to refining solutions either from different methods or parameterizations.
Global consensus is growing on the contribution that corporations and finance must make towards the net-zero transition in line with the Paris Agreement goals. However, most efforts in legislative instruments as well as shareholder or stakeholder initiatives have ultimately focused on public companies.
This article argues that such a focus falls short of providing a comprehensive approach to the problem of climate change. In doing so, it examines the contribution of private companies to climate change, the relevance of climate risks for them, as well as the phenomenon of brown-spinning (ie, the practice of public companies selling their highly polluting assets to private companies). We show that one cannot afford to ignore private companies in the net-zero transition and climate change adaptation. Yet, private companies lack several disciplining mechanisms that are available to public companies, such as institutional investor engagement, certain corporate governance arrangements, and transparency through regular disclosure obligations. At this stage, only some generic regulatory instruments such as carbon pricing and environmental regulation apply to them.
The article closes with a discussion of the main policy implications. Primarily, we discuss and evaluate the recent push to extend climate-related disclosure requirements to private companies. These disclosures would not only help investors by addressing information asymmetry, but also serve a wide group of stakeholders and thus aim at promoting a transition to a greener economy.
To ensure the credibility of market discipline induced by bail-in, neither retail investors nor peer banks should appear prominently among the investor base of banks’ loss absorbing capital. Empirical evidence on bank-level data provided by the German Federal Financial Supervisory Authority raises a few red flags. Our list of policy recommendations encompasses disclosure policy, data sharing among supervisors, information transparency on holdings of bail-inable debt for all stakeholders, threshold values, and a well-defined upper limit for any bail-in activity. This document was provided by the Economic Governance Support Unit at the request of the ECON Committee.
Prospective welfare analysis - extending willingness-to-pay assessment to embrace sustainability
(2022)
In this paper we outline how a future change in consumers’ willingness-to-pay can be accounted for in a consumer welfare effects analysis in antitrust. Key to our solution is the prediction of preferences of new consumers and changing preferences of existing consumers in the future. The dimension of time is inextricably linked with that of sustainability. Taking into account the welfare of future cohorts of consumers, concerns for sustainability can therefore be integrated into the consumer welfare paradigm to a greater extent. As we argue in this paper, it is expedient to consider changes in consumers’ willingness-to-pay, in particular if society undergoes profound changes in such preferences, e.g., caused by an increase in generally available information on environmental effects of consumption, and a rising societal awareness about how consumption can have irreversible impacts on the environment. We offer suggestions on how to conceptionalize and operationalize the projection of such consumers’ changing preferences in a “prospective welfare analysis”. This increases the scope of the consumer welfare paradigm and can help to solve conceptual issues regarding the integration of sustainability into antitrust enforcement while keeping consumer surplus as a quantitative gauge.
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.
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.
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.
European banks have substantial investments in assets that are
measured without directly observable market prices (mark-to-
model). Financial disclosures of these value estimates lack
standardization and are hard to compare across banks. These
comparability concerns are concentrated in large European
banks that extensively rely on level 3 estimates with the most
unobservable inputs. Although the relevant balance sheet
positions only represent a small fraction of these large banks’
total assets (2.9%), their value equals a significant fraction of core
equity tier 1 (48.9%). Incorrect valuations thus have a potential to
impact financial stability. 85% of these bank assets are under
direct ECB supervision. Prudential regulation requires value
adjustments that are apt to shield capital against valuation risk.
Yet, stringent enforcement is critical for achieving this objective.
This document was provided by the Economic Governance
Support Unit at the request of the ECON Committee.
The great financial crisis and the euro area crisis led to a substantial reform of financial safety nets across Europe and – critically – to the introduction of supranational elements. Specifically, a supranational supervisor was established for the euro area, with discrete arrangements for supervisory competences and tasks depending on the systemic relevance of supervised credit institutions. A resolution mechanism was created to allow the frictionless resolution of large financial institutions. This resolution mechanism has been now complemented with a funding instrument.
While much more progress has been achieved than most observers could imagine 12 years ago, the banking union remains unfinished with important gaps and deficiencies. The experience over the past years, especially in the area of crisis management and resolution, has provided impetus for reform discussions, as reflected most lately in the Eurogroup statement of 16 June 2022.
This Policy Insight looks primarily at the current and the desired state of the banking union project. The key underlying question, and the focus here, is the level of ambition and how it is matched with effective legal and regulatory tools. Specifically, two questions will structure the discussions:
What would be a reasonable definition and rationale for a ‘complete’ banking union? And what legal reforms would be required to achieve it?
Banking union is a case of a new remit of EU-level policy that so far has been established on the basis of long pre-existing treaty stipulations, namely, Article 127(6) TFEU (for banking supervision) and Article 114 TFEU (for crisis management and deposit insurance). Could its completion be similarly carried out through secondary law? Or would a more comprehensive overhaul of the legal architecture be required to ensure legal certainty and legitimacy?
This article compares the three initial safety nets spanned by the European Union in response to the Covid-19 crisis: SURE, the Pandemic Crisis Support, and the European Guarantee Fund. It compares their design regarding scope, generosity, target groups, implementation, the types of solidarity and conditionality, and asks how they reflect on core-periphery relations in the EU. The article finds that the most important factor in all three instruments is risk-sharing between member states, even though SURE and the EGF display elements of fiscal solidarity. Finally, the article shows that Euro crisis countries from the South are the main recipients of financial aid, while Central and East European countries receive significantly less assistance and core countries in the North and West have no need for them.
Die notwendige ökologische Transformation aber auch darüberhinausgehend die zunehmenden Erwartungen, die Gesellschaft und Politik an die Wirtschaft stellen, erfordern eine Prüfung des Wettbewerbsrechts und seiner Durchsetzung, insbesondere auch der dabei verwendeten (ökonomischen) Konzepte und Methoden, dahingehend, ob die aktuelle Praxis nicht einer stärkeren Berücksichtigung von Nachhaltigkeitszielen in unbegründeter Weise im Wege steht. Auf europäischer Ebene hat der Diskurs darüber im Jahr 2021 erheblich an Fahrt gewonnen. Wir stellen wesentliche Initiativen dar. Dabei zeigt sich unseres Erachtens allerdings auch, dass für eine konstruktive Weiterentwicklung noch die nötigen konzeptionellen und methodischen Grundlagen fehlen.
Linear rational-expectations models (LREMs) are conventionally "forwardly" estimated as follows. Structural coefficients are restricted by economic restrictions in terms of deep parameters. For given deep parameters, structural equations are solved for "rational-expectations solution" (RES) equations that determine endogenous variables. For given vector autoregressive (VAR) equations that determine exogenous variables, RES equations reduce to reduced-form VAR equations for endogenous variables with exogenous variables (VARX). The combined endogenous-VARX and exogenous-VAR equations comprise the reduced-form overall VAR (OVAR) equations of all variables in a LREM. The sequence of specified, solved, and combined equations defines a mapping from deep parameters to OVAR coefficients that is used to forwardly estimate a LREM in terms of deep parameters. Forwardly-estimated deep parameters determine forwardly-estimated RES equations that Lucas (1976) advocated for making policy predictions in his critique of policy predictions made with reduced-form equations.
Sims (1980) called economic identifying restrictions on deep parameters of forwardly-estimated LREMs "incredible", because he considered in-sample fits of forwardly-estimated OVAR equations inadequate and out-of-sample policy predictions of forwardly-estimated RES equations inaccurate. Sims (1980, 1986) instead advocated directly estimating OVAR equations restricted by statistical shrinkage restrictions and directly using the directly-estimated OVAR equations to make policy predictions. However, if assumed or predicted out-of-sample policy variables in directly-made policy predictions differ significantly from in-sample values, then, the out-of-sample policy predictions won't satisfy Lucas's critique.
If directly-estimated OVAR equations are reduced-form equations of underlying RES and LREM-structural equations, then, identification 2 derived in the paper can linearly "inversely" estimate the underlying RES equations from the directly-estimated OVAR equations and the inversely-estimated RES equations can be used to make policy predictions that satisfy Lucas's critique. If Sims considered directly-estimated OVAR equations to fit in-sample data adequately (credibly) and their inversely-estimated RES equations to make accurate (credible) out-of-sample policy predictions, then, he should consider the inversely-estimated RES equations to be credible. Thus, inversely-estimated RES equations by identification 2 can reconcile Lucas's advocacy for making policy predictions with RES equations and Sims's advocacy for directly estimating OVAR equations.
The paper also derives identification 1 of structural coefficients from RES coefficients that contributes mainly by showing that directly estimated reduced-form OVAR equations can have underlying LREM-structural equations.
In more and more situations, artificially intelligent algorithms have to model humans’ (social) preferences on whose behalf they increasingly make decisions. They can learn these preferences through the repeated observation of human behavior in social encounters. In such a context, do individuals adjust the selfishness or prosociality of their behavior when it is common knowledge that their actions produce various externalities through the training of an algorithm? In an online experiment, we let participants’ choices in dictator games train an algorithm. Thereby, they create an externality on future decision making of an intelligent system that affects future participants. We show that individuals who are aware of the consequences of their training on the pay- offs of a future generation behave more prosocially, but only when they bear the risk of being harmed themselves by future algorithmic choices. In that case, the externality of artificially intelligence training induces a significantly higher share of egalitarian decisions in the present.
Using granular supervisory data from Germany, we investigate the impact of unconventional monetary policies via central banks’ purchase of corporate bonds. While this policy results in a loosening of credit market conditions as intended by policy makers, we document two unintended side effects. First, banks that are more exposed to borrowers benefiting from the bond purchases now lend more to high-risk firms with no access to bond markets. Since more loan write-offs arise from these firms and banks are not compensated for this risk by higher interest rates, we document a drop in bank profitability. Second, the policy impacts the allocation of loans among industries. Affected banks reallocate loans from investment grade firms active on bond markets to mainly real estate firms without investment grade rating. Overall, our findings suggest that central banks’ quantitative easing via the corporate bond markets has the potential to contribute to both banking sector instability and real estate bubbles.
Financial literacy affects wealth accumulation, and pension planning plays a key role in this relationship. In a large field experiment, we employ a digital pension aggregation tool to confront a treatment group with a simplified overview of their current pension claims across all pillars of the pension system. We combine survey and administrative bank data to measure the effects on actual saving behavior. Access to the tool decreases pension uncertainty for treated individuals. Average savings increase - especially for the financially less literate. We conclude that simplification of pension information can potentially reduce disparities in pension planning and savings behavior.
The financial sector plays an important role in financing the green transformation of the European economy. A critical assessment of the current regulatory framework for sustainable finance in Europe leads to ambiguous results. Although the level of transparency on ESG aspects of financial products has been significantly improved, it is questionable whether the complex, mainly disclosure-oriented architecture is sufficient to mobilise more private capital into sustainable investments. It should be discussed whether a minimum Taxonomy ratio or Green Asset Ratio has to be fulfilled to market a financial product as “green”. Furthermore, because of the high complexity of the regulation, it could be helpful for the understanding of private investors to establish a simplified green rating, based on the Taxonomy ratio, to facilitate the selection of green financial products.
This policy note summarizes our assessment of financial sanctions against Russia. We see an increase in sanctions severity starting from (1) the widely discussed SWIFT exclusions, followed by (2) blocking of correspondent banking relationships with Russian banks, including the Central Bank, alongside secondary sanctions, and (3) a full blacklisting of the ‘real’ export-import flows underlying the financial transactions. We assess option (1) as being less impactful than often believed yet sending a strong signal of EU unity; option (2) as an effective way to isolate the Russian banking system, particularly if secondary sanctions are in place, to avoid workarounds. Option (3) represents possibly the most effective way to apply economic and financial pressure, interrupting trade relationships.
In the aftermath of the Wirecard scandal the German lead stock market index DAX has undergone a series of reforms, including the introduction of a profitability criterion based on EBITDA for new DAX members and enhanced financial reporting requirements with specified sanctions for non-compliance. Furthermore, DAX members need to adhere to certain provisions in the German Corporate Governance Code relating to audit committees. The final step of the reform was implemented in September 2021: the extension of the DAX from 30 to 40 constituents, with the ranking based solely on the free float market capitalisation. After one year of experience with the new design of the DAX, this paper concludes that the reform has strengthened the DAX in terms of diversification, quality and adaptability. However, there is still room for further improvement by introducing a minimum ESG score for DAX companies and thus making sustainability a relevant factor in the selection process. In addition, full compliance with the recommendations of the German Corporate Governance Code should be a condition for DAX companies. Furthermore, the profitability criterion should be applied on a continuous basis to ensure that loss-making companies can be excluded from the DAX after a grace period.
For the academic audience, this paper presents the outcome of a well-identified, large change in the monetary policy rule from the lens of a standard New Keynesian model and asks whether the model properly captures the effects. For policymakers, it presents a cautionary tale of the dismal effects of ignoring basic macroeconomics. The Turkish monetary policy experiment of the past decade, stemming from a belief of the government that higher interest rates cause higher inflation, provides an unfortunately clean exogenous variance in the policy rule. The mandate to keep rates low, and the frequent policymaker turnover orchestrated by the government to enforce this, led to the Taylor principle not being satisfied and eventually a negative coeffcient on inflation in the policy rule. In such an environment, was the exchange rate still a random walk? Was inflation anchored? Does the “standard model”” suffice to explain the broad contours of macroeconomic outcomes in an emerging economy with large identifying variance in the policy rule? There are no surprises for students of open-economy macroeconomics; the answers are no, no, and yes.
Despite the impressive success of deep neural networks in many application areas, neural network models have so far not been widely adopted in the context of volatility forecasting. In this work, we aim to bridge the conceptual gap between established time series approaches, such as the Heterogeneous Autoregressive (HAR) model (Corsi, 2009), and state-of-the-art deep neural network models. The newly introduced HARNet is based on a hierarchy of dilated convolutional layers, which facilitates an exponential growth of the receptive field of the model in the number of model parameters. HARNets allow for an explicit initialization scheme such that before optimization, a HARNet yields identical predictions as the respective baseline HAR model. Particularly when considering the QLIKE error as a loss function, we find that this approach significantly stabilizes the optimization of HARNets. We evaluate the performance of HARNets with respect to three different stock market indexes. Based on this evaluation, we formulate clear guidelines for the optimization of HARNets and show that HARNets can substantially improve upon the forecasting accuracy of their respective HAR baseline models. In a qualitative analysis of the filter weights learnt by a HARNet, we report clear patterns regarding the predictive power of past information. Among information from the previous week, yesterday and the day before, yesterday's volatility makes by far the most contribution to today's realized volatility forecast. Moroever, within the previous month, the importance of single weeks diminishes almost linearly when moving further into the past.
In a parsimonious regime switching model, we find strong evidence that expected consumption growth varies over time. Adding inflation as a second variable, we uncover two states in which expected consumption growth is low, one with high and one with negative expected inflation. Embedded in a general equilibrium asset pricing model with learning, these dynamics replicate the observed time variation in stock return volatilities and stock- bond return correlations. They also provide an alternative derivation for a measure of time-varying disaster risk suggested by Wachter (2013), implying that both the disaster and the long-run risk paradigm can be extended towards explaining movements in the stock-bond correlation.
This paper examines optimal enviromental policy when external financing is costly for firms. We introduce emission externalities and industry equilibrium in the Holmström and Tirole (1997) model of corporate finance. While a cap-and- trading system optimally governs both firms` abatement activities (internal emission margin) and industry size (external emission margin) when firms have sufficient internal funds, external financing constraints introduce a wedge between these two objectives. When a sector is financially constrained in the aggregate, the optimal cap is strictly above the Pigouvian benchmark and emission allowances should be allocated below market prices. When a sector is not financially constrained in the aggregate, a cap that is below the Pigiouvian benchmark optimally shifts market share to less polluting firms and, moreover, there should be no "grandfathering" of emission allowances. With financial constraints and heterogeneity across firms or sectors, a uniform policy, such as a single cap-and-trade system, is typically not optimal.
There have been numerous attempts to reform the Economic and Monetary Union (EMU) after the Great Recession, however the reform success varies greatly among sub-fields. Additionally, the political science research community has engaged a diverse set of theory- driven explanations, causal mechanisms, and variables to explain respective reform success. This article takes stock of reform policies in the EMU from two angles. First, it outlines distinct theoretical approaches that seek to explain success and failure of reform proposals and second, it surveys how they explain policy output and policy outcome in four policy subfields: financial stabilization, economic governance, financial solidarity, and cooperative dissolution. Finally, the article develops a set of explanatory factors from the existing literature that will be used for a Qualitative Comparative Analysis (QCA).
The sixth sanction package of the European Union in the context of the aggression against Ukraine excludes Sberbank, the largest Russian bank, from the SWIFT network. The increasing use of SWIFT as a tool for sanctions stimulates the rollout of alternative payment information systems by the governments of Russia and China. This policy white paper informs about the alternatives at hand, as well as their advantages and disadvantages. Careful reflection about these issues is particularly important, given the call for an “Economic Article 5” tabled for the next NATO meeting. Finally, the white paper highlights the need for institutional reforms, if policymakers decide to return SWIFT to the status of a global public good after the war.
With Big Data, decisions made by machine learning algorithms depend on training data generated by many individuals. In an experiment, we identify the effect of varying individual responsibility for the moral choices of an artificially intelligent algorithm. Across treatments, we manipulated the sources of training data and thus the impact of each individual’s decisions on the algorithm. Diffusing such individual pivotality for algorithmic choices increased the share of selfish decisions and weakened revealed prosocial preferences. This does not result from a change in the structure of incentives. Rather, our results show that Big Data offers an excuse for selfish behavior through lower responsibility for one’s and others’ fate.
Peer effects can lead to better financial outcomes or help propagate financial mistakes across social networks. Using unique data on peer relationships and portfolio composition, we show considerable overlap in investment portfolios when an investor recommends their brokerage to a peer. We argue that this is strong evidence of peer effects and show that peer effects lead to better portfolio quality. Peers become more likely to invest in funds when their recommenders also invest, improving portfolio diversification compared to the average investor and various placebo counterfactuals. Our evidence suggests that social networks can provide good advice in settings where individuals are personally connected.
Are we in a new “Polanyian moment”? If we are, it is essential to examine how “spontaneous” and punctual expressions of discontent at the individual level may give rise to collective discourses driving social and political change. It is also important to examine whether and how the framing of these discourses may vary across political economies. This paper contributes to this endeavor with the analysis of anti-finance discourses on Twitter in France, Germany, Italy, Spain and the UK between 2019 and 2020. This paper presents three main findings. First, the analysis shows that, more than ten years after the financial crisis, finance is still a strong catalyzer of political discontent. Second, it shows that there are important variations in the dominant framing of public anti-finance discourses on social media across European political economies. If the antagonistic “us versus them” is prominent in all the cases, the identification of who “us” and “them” are, vary significantly. Third, it shows that the presence of far-right tropes in the critique of finance varies greatly from virtually inexistent to a solid minority of statements.
While the COVID-19 pandemic had a large and asymmetric impact on firms, many countries quickly enacted massive business rescue programs which are specifically targeted to smaller firms. Little is known about the effects of such policies on business entry and exit, factor reallocation, and macroeconomic outcomes. This paper builds a general equilibrium model with heterogeneous and financially constrained firms in order to evaluate the short- and long-term consequences of small firm rescue programs in a pandemic recession. We calibrate the stationary equilibrium and the pandemic shock to the U.S. economy, taking into account the factual Paycheck Protection Program (PPP) as a specific grant policy. We find that the policy has only a small impact on aggregate employment because (i) jobs are saved predominately in less productive firms that account for a small share of employment and (ii) the grant induces a reallocation of resources away from larger and less impacted firms. Much of this reallocation happens in the aftermath of the pandemic episode. While a universal grant reduces the firm exit rate substantially, a targeted policy is not only more cost-effective, it also largely prevents the creation of “zombie firms" whose survival is socially inefficient.
We collect data on the size distribution of all U.S. corporate businesses for 100 years. We document that corporate concentration (e.g., asset share or sales share of the top 1%) has increased persistently over the past century. Rising concentration was stronger in manufacturing and mining before the 1970s, and stronger in services, retail, and wholesale after the 1970s. Furthermore, rising concentration in an industry aligns closely with investment intensity in research and development and information technology. Industries with higher increases in concentration also exhibit higher output growth. The long-run trends of rising corporate concentration indicate increasingly stronger economies of scale.
In times of increased political polarization, the continuing existence of a deliberative arena where people with antagonistic views may engage with each other in non-violent ways is critical for democracy to live on. Social media are usually not conceived as such arenas. On the contrary, there has been widespread worry about their role in increasing polarization and political violence. This paper suggests a more positive impact of social media on democracy. Our analysis focuses on the subreddit “r/WallStreetBets” (r/WSB) - a finance-related forum that came under the spotlight when its users coordinated a financial attack on hedge funds during the Gamestop saga in early 2021. Based on an original method attributing partisanship scores to users, we present a network analysis of interactions between users at the opposite sides of the political spectrum on r/WSB. We then develop a content analysis of politically relevant threads in which polarized users participate. Our analyses show that r/WSB provides a rare space where users with antagonistic political leanings engage with each other, debate, and even cooperate.
Identifying the cause of discrimination is crucial to design effective policies and to understand discrimination dynamics. Building on traditional models, this paper introduces a new explanation for discrimination: discrimination based on motivated reasoning. By systematically acquiring and processing information, individuals form motivated beliefs and consequentially discriminate based on these beliefs. Through a series of experiments, I show the existence of discrimination based on motivated reasoning and demonstrate important differences to statistical discrimination and taste-based discrimination. Finally, I demonstrate how this form of discrimination can be alleviated by limiting individuals’ scope to interpret information.
Der Koalitionsvertrag 2021 sieht eine generationengerechte Absicherung des Rentenniveaus durch eine teilweise aus Haushaltsmitteln finanzierte Kapitaldeckung vor. Um dieses Ziel zu verwirklichen, wird hier die Einführung einer Generationenrente ab Geburt vorgeschlagen. Dabei wird aus Haushaltsmitteln ein Betrag von € 5.000 für jedes Neugeborene nach Grundsätzen des professionellen Anlagemanagements am globalen Kapitalmarkt angelegt. Konzeptionell soll sich diese Generationenrente am Modell der Basisrente(§10 Abs. 1 Nr. 2 b EStG) orientieren, d.h. die akkumulierten Gelder sind weder beleihbar, vererbbar noch übertragbar und können frühestens ab Alter 63 zugunsten einer lebenslangen Monatsrente verwendet werden. Unsere Berechnungen zeigen, dass durch die hier vorgeschlagene Generationenrente unabhängig vom Verlauf der individuellen Erwerbsbiographie, Altersarmut für die vom demographischen Wandel besonders betroffenen zukünftigen Generationen vermieden wird.
Spillovers of PE investments
(2022)
In this paper, we investigate a primary potential impact of leveraged buyout (LBOs) transactions: the effects of LBOs on the peers of the LBO target in the same industry. Using a data sample based on US LBO transactions between 1985 and 2016, we investigate the impact of the peer firms in the aftermath of the transaction, relative to non-peer firms. To account for potential endogeneity concerns, we employ a network-based instrumental variable approach. Based on this analysis, we find support for the proposition that LBOs do indeed matter for peer firms’ performance and corporate strategy relative to non-peer firms. Our study supports a learning factor hypothesis: peers gain by learning from the LBO target to improve their operational performance. Conversely, we find no evidence to support the conjecture that peers lose due to the increased competitiveness of the LBO target firm.
The reuse of collateral can support the efficient allocation of safe assets in the financial system. Exploiting a novel dataset, we show that banks substantially increase their reuse of sovereign bonds in response to scarcity induced by Eurosystem asset purchases. While repo rates react little to purchase-induced scarcity when reuse is low, they become increasingly sensitive at high levels of reuse. An elevated reuse rate is also associated with more failures to deliver and a higher volatility of repo rates in the cross-section of bonds. Our results highlight the trade-off between shock absorption and shock amplification effects of collateral reuse.
We investigate whether the bank crisis management framework of the European banking union can effectively bar the detrimental influence of national interests in cross-border bank failures. We find that both the internal governance structure and decision making procedure of the Single Resolution Board (SRB) and the interplay between the SRB and national resolution authorities in the implementation of supranationally devised resolution schemes provide inroads that allow opposing national interests to obstruct supranational resolution. We also show that the Single Resolution Fund (SRG), even after the ratification of the reform of the European Stability Mechanism (ESM) and the introduction of the SRF backstop facility, is inapt to overcome these frictions. We propose a full supranationalization of resolution decision making. This would allow European authorities in charge of bank crisis management to operate autonomously and achieve socially optimal outcomes beyond national borders.
Agencies around the world are in the process of developing taxonomies and standards for sustainable (or ESG) investment products. A key assumption in our model is that of non-consequentialist private investors (households) who derive a "warm glow" decisional utility when purchasing an investment product that is labelled as sustainable. We ask when such labelling is socially beneficial even when the socialplanner can impose a minimum standard on investment and production. In a model of financial constraints (Holmström and Tirole 1997), which we close to include consumer surplus, we also determine the optimal labelling threshold and show how its stringency is affected by determinants such as the prevalence of warm-glow investor preferences, the presence of social network effects, or the relevance of financial constraints at the industry level.
Joint Institutional Frameworks in bilateral relations are circumscribed in policy scope, can lack adequate instruments for dynamic adaptation and provide limited access to decision-making processes internal to the contracting parties. Informal governance, the involvement of private actors as well as rules such as equivalence provide avenues to remedy these limits in bilateral relations in sectoral governance. Through bilateral agreements, the scope of territorially bound political authority is expanded. The formalised and institutionalised frameworks and bodies established are, however, frequently accompanied by mechanisms of informal cooperation and special rules either to cover policy fields where no contractual relation exists, to provide for flexible solutions where needed, or to involve both public and private actors that otherwise do not have access to formal decision-making bodies. This SAFE working paper conceptualises formal and informal modes of cooperation and varying actor constellations. It discusses their relevance for the case of bilateral relations between the European Union (EU) and Switzerland in sectoral governance. More specifically, it draws lessons from EU-Swiss sectoral governance of financial and electricity markets for the future relations of the EU with the United Kingdom (UK). The findings suggest that there are distinct governance arrangements across sectors, while the patterns of sectoral governance are expected to look very much alike in the United Kingdom and Switzerland in the years to come. The general takeaway is that Brexit will have repercussions for the EU’s external relations with other third countries, putting ever more emphasis on formal and rule-based approaches, while leaving a need for sector-specific cross border co-operation.
Why bank money creation?
(2022)
We provide a rationale for bank money creation in our current monetary system by investigating its merits over a system with banks as intermediaries of loanable funds. The latter system could result when CBDCs are introduced. In the loanable funds system, households limit banks’ leverage ratios when providing deposits to make sure they have enough “skin in the game” to opt for loan monitoring. When there is unobservable heterogeneity among banks with regard to their (opportunity) costs from monitoring, aggregate lending to bank-dependent firms is inefficiently low. A monetary system with bank money creation alleviates this problem, as banks can initiate lending by creating bank deposits without relying on household funding. With a suitable regulatory leverage constraint, the gains from higher lending by banks with a high repayment pledgeability outweigh losses from banks which are less diligent in monitoring. Bank-risk assessments, combined with appropriate risk-sensitive capital requirements, can reduce or even eliminate such losses.
Search costs for lenders when evaluating potential borrowers are driven by the quality of the underwriting model and by access to data. Both have undergone radical change over the last years, due to the advent of big data and machine learning. For some, this holds the promise of inclusion and better access to finance. Invisible prime applicants perform better under AI than under traditional metrics. Broader data and more refined models help to detect them without triggering prohibitive costs. However, not all applicants profit to the same extent. Historic training data shape algorithms, biases distort results, and data as well as model quality are not always assured. Against this background, an intense debate over algorithmic discrimination has developed. This paper takes a first step towards developing principles of fair lending in the age of AI. It submits that there are fundamental difficulties in fitting algorithmic discrimination into the traditional regime of anti-discrimination laws. Received doctrine with its focus on causation is in many cases ill-equipped to deal with algorithmic decision-making under both, disparate treatment, and disparate impact doctrine. The paper concludes with a suggestion to reorient the discussion and with the attempt to outline contours of fair lending law in the age of AI.
With open banking, consumers take greater control over their own financial data and share it at their discretion. Using a rich set of loan application data from the largest German FinTech lender in consumer credit, this paper studies what characterizes borrowers who share data and assesses its impact on loan application outcomes. I show that riskier borrowers share data more readily, which subsequently leads to an increase in the probability of loan approval and a reduction in interest rates. The effects hold across all credit risk profiles but are the most pronounced for borrowers with lower credit scores (a higher increase in loan approval rate) and higher credit scores (a larger reduction in interest rate). I also find that standard variables used in credit scoring explain substantially less variation in loan application outcomes when customers share data. Overall, these findings suggest that open banking improves financial inclusion, and also provide policy implications for regulators engaged in the adoption or extension of open banking policies.
With free delivery of products virtually being a standard in E-commerce, product returns pose a major challenge for online retailers and society. For retailers, product returns involve significant transportation, labor, disposal, and administrative costs. From a societal perspective, product returns contribute to greenhouse gas emissions and packaging disposal and are often a waste of natural resources. Therefore, reducing product returns has become a key challenge. This paper develops and validates a novel smart green nudging approach to tackle the problem of product returns during customers’ online shopping processes. We combine a green nudge with a novel data enrichment strategy and a modern causal machine learning method. We first run a large-scale randomized field experiment in the online shop of a German fashion retailer to test the efficacy of a novel green nudge. Subsequently, we fuse the data from about 50,000 customers with publicly-available aggregate data to create what we call enriched digital footprints and train a causal machine learning system capable of optimizing the administration of the green nudge. We report two main findings: First, our field study shows that the large-scale deployment of a simple, low-cost green nudge can significantly reduce product returns while increasing retailer profits. Second, we show how a causal machine learning system trained on the enriched digital footprint can amplify the effectiveness of the green nudge by “smartly” administering it only to certain types of customers. Overall, this paper demonstrates how combining a low-cost marketing instrument, a privacy-preserving data enrichment strategy, and a causal machine learning method can create a win-win situation from both an environmental and economic perspective by simultaneously reducing product returns and increasing retailers’ profits.
Short sale bans may improve market quality during crises: new evidence from the 2020 Covid crash
(2022)
In theory, banning short selling stabilizes stock prices but undermines pricing efficiency and has ambiguous impacts on market liquidity. Empirical studies find mixed and conflicting results. This paper leverages cross-country policy variation during the 2020 Covid crisis to assess differential impacts of bans on stock liquidity, prices, and volatility. Results suggest that bans improved liquidity and stabilized prices for illiquid stocks but temporarily diminished liquidity for highly liquid stocks.The findings support theories in which short sale bans may improve liquidity by selectively filtering out informed— potentially predatory—traders. Thus, policies that target the most illiquid stocks may deliver better overall market quality than uniform short sale bans imposed on all stocks.
We propose a new instrument for estimating the price elasticity of gasoline demand that exploits systematic differences across U.S. states in the pass-through of oil price shocks to retail gasoline prices. These differences, which are primarily driven by variation in the cost of producing and distributing gasoline, create cross-sectional dispersion in gasoline price growth in response to an aggregate oil price shock. We find that the elasticity was stable near -0.3 until the end of 2014, but subsequently rose to about -0.2. Our estimates inform the recent debate about gasoline-tax holidays and policies to reduce carbon emissions.
Consumers purchase energy in many forms. Sometimes energy goods are consumed directly, for instance, in the form of gasoline used to operate a vehicle, electricity to light a home, or natural gas to heat a home. At other times, the cost of energy is embodied in the prices of goods and services that consumers buy, say when purchasing an airline ticket or when buying online garden furniture made from plastic to be delivered by mail. Previous research has focused on quantifying the pass-through of the price of crude oil or the price of motor gasoline to U.S. inflation. Neither approach accounts for the fact that percent changes in refined product prices need not be proportionate to the percent change in the price of oil, that not all energy is derived from oil, and that the correlation of price shocks across energy markets is far from one. This paper develops a vector autoregressive model that quantifies the joint impact of shocks to several energy prices on headline and core CPI inflation. Our analysis confirms that focusing on gasoline price shocks alone will underestimate the inflationary pressures emanating from the energy sector, but not enough to overturn the conclusion that much of the observed increase in headline inflation in 2021 and 2022 reflected non-energy price shocks.