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A common practice in empirical macroeconomics is to examine alternative recursive orderings of the variables in structural vector autogressive (VAR) models. When the implied impulse responses look similar, the estimates are considered trustworthy. When they do not, the estimates are used to bound the true response without directly addressing the identification challenge. A leading example of this practice is the literature on the effects of uncertainty shocks on economic activity. We prove by counterexample that this practice is invalid in general, whether the data generating process is a structural VAR model or a dynamic stochastic general equilibrium model.
Um eine grüne Transformation der Volkswirtschaft zu erreichen, werden Finanzmärkte und die mit ihnen verbundenen Banken eine wichtige Rolle einnehmen müssen. Aber allein vermögen Banken und Kapitalmärkte wenig, wenn sie nicht im Kontext einer klugen, politischen Rahmensetzung und einer transparenten Erfassung der verursachten Schäden auf Unternehmensebene gesehen werden. Diese drei Pfeiler stellen bildlich den tragenden Unterbau für eine Brücke hin zu einer klimaneutralen Wirt-schaftsverfassung dar. Ihr Zusammenwirken ist eine Voraussetzung dafür, dass die Finanzwirtschaft die benötigten Finanzmittel für die grüne Transformation bereitstellen kann.
A key technology driving the digital transformation of the economy is artificial intelligence (AI). It has gained a high degree of public attention with the initial release of the chatbot ChatGPT, which demonstrates the potential of generative AI (GAI) as a relatively new segment within AI. It is widely expected that GAI will shape the future of many industries and society in the coming years. This article provides a brief overview of the foundations of generative AI (“GAI”) including machine learning and what distinguishes it from other fields of AI. Furthermore, we look at important players in this emerging market, possible use cases and the expected economic potential as of today. It is apparent that, once again, a few US-based Big Tech firms are about to dominate this emerging technology and that the European tech sector is falling further behind. Finally, we conclude that the recently adopted Digital Markets Act (DMA) and the Digital Service Act (DSA) as well as the upcoming AI Act should be reviewed to ensure that the regulatory framework of European digital markets keeps up with the accelerated development of AI.
Homeownership rates differ widely across European countries. We document that part of this variation is driven by differences in the fraction of adults co-residing with their par-ents. Comparing Germany and Italy, we show that in contrast to homeownership rates per household, homeownership rates per individual are very similar during the first part of the life cycle. To understand these patterns, we build an overlapping-generations model where individuals face uninsurable income risk and make consumption-saving and housing tenure decisions. We embed an explicit intergenerational link between children and parents to cap-ture the three-way trade-off between owning, renting, and co-residing. Calibrating the model to Germany we explore the role of income profiles, housing policies, and the taste for inde-pendence and show that a combination of these factors goes a long way in explaining the differential life-cycle patterns of living arrangements between the two countries.
We develop a quantity-driven general equilibrium model that integrates the term structure of interest rates with the repurchase agreements (repo) market to shed light on the com-bined effects of quantitative easing (QE) on the bond and money markets. We characterize in closed form the endogenous dynamic interaction between bond prices and repo rates, and show (i) that repo specialness dampens the impact of any given quantity of asset pur-chases due to QE on the slope of the term structure and (ii) that bond scarcity resulting from QE increases repo specialness, thus strengthening the local supply channel of QE.
Recent regulatory measures such as the European Union’s AI Act re-quire artificial intelligence (AI) systems to be explainable. As such, under-standing how explainability impacts human-AI interaction and pinpoint-ing the specific circumstances and groups affected, is imperative. In this study, we devise a formal framework and conduct an empirical investiga-tion involving real estate agents to explore the complex interplay between explainability of and delegation to AI systems. On an aggregate level, our findings indicate that real estate agents display a higher propensity to delegate apartment evaluations to an AI system when its workings are explainable, thereby surrendering control to the machine. However, at an individual level, we detect considerable heterogeneity. Agents possess-ing extensive domain knowledge are generally more inclined to delegate decisions to AI and minimize their effort when provided with explana-tions. Conversely, agents with limited domain knowledge only exhibit this behavior when explanations correspond with their preconceived no-tions regarding the relationship between apartment features and listing prices. Our results illustrate that the introduction of explainability in AI systems may transfer the decision-making control from humans to AI under the veil of transparency, which has notable implications for policy makers and practitioners that we discuss.
We provide evidence on the extent to which survey items in the Preference Survey Module and the resulting Global Preference Survey measuring social preferences − trust, altruism, positive and negative reciprocity − predict behavior in corresponding experimental games outside the original participant sample of Falk et al. (2022). Our results, which are based on a replication study with university students in Tehran, Iran, are mixed. While quantitative items considering hypothetical versions of the experimental games correlate significantly and economically meaningfully with individual behavior, none of the qualitative items show significant correlations. The only exception is altruism where results correspond more closely to the original findings.
In the euro area, monetary policy is conducted by a single central bank for 20 member countries. However, countries are heterogeneous in their economic development, including their inflation rates. This paper combines a New Keynesian model and a neural network to assess whether the European Central Bank (ECB) conducted monetary policy between 2002 and 2022 according to the weighted average of the inflation rates within the European Monetary Union (EMU) or reacted more strongly to the inflation rate developments of certain EMU countries.
The New Keynesian model first generates data which is used to train and evaluate several machine learning algorithms. They authors find that a neural network performs best out-of-sample. They use this algorithm to generally classify historical EMU data, and to determine the exact weight on the inflation rate of EMU members in each quarter of the past two decades. Their findings suggest disproportional emphasis of the ECB on the inflation rates of EMU members that exhibited high inflation rate volatility for the vast majority of the time frame considered (80%), with a median inflation weight of 67% on these countries. They show that these results stem from a tendency of the ECB to react more strongly to countries whose inflation rates exhibit greater deviations from their long-term trend.
Climate change has become one of the most prominent concerns globally. In this paper, the authors study the transition risk of greenhouse gas emission reduction in structural environmental-macroeconomic DSGE models. First, they analyze the uncertainty in model prediction on the effect of unanticipated and pre-announced carbon price increases. Second, they conduct optimal model-robust policy in different settings. They find that reducing emissions by 40% causes 0.7% to 4% output loss with 2% on average. Pre-announcement of carbon prices affects the inflation dynamics significantly. The central bank should react slightly less to inflation and output growth during the transition risk. With optimal carbon price designs, it should react even less to inflation, and more to output growth.
We analyze the repercussions of different kinds of uncertainty on cash demand, including uncertainty of the digital infrastructures, confidence crises of the financial system, natural disasters, political uncertainties, and inflationary crises. Based on a comprehensive literature survey, theoretical considerations and complemented by case studies, we derive a classification scheme how cash holdings typically evolve in each of these types of uncertainty by separating between demand for domestic and international cash as well as between transaction and store of value balances. Hereby, we focus on the stabilizing macroeconomic properties of cash and recommend guidelines for cash supply by central banks and the banking system. Finally, we exemplify our analysis with five case studies from the developing world, namely Venezuela, Zimbabwe, Afghanistan, Iraq, and Libya.
Trotz der von der EZB eingeleiteten Zinswende in der zweiten Jahreshälfte 2022 als späte Reaktion auf die deutlich unterschätzte Persistenz hoher Inflationsraten im Euroraum sind die Realzinsen sowohl in der Ex-post-Betrachtung als auch in der Ex-ante-Betrachtung keineswegs als restriktiv einzuschätzen. Die Banken haben allerdings recht rasch strengere Vergaberichtlinien beschlossen, und die Nachfrage im Wohnungsbau und bei den Hypothekarkrediten ist stark eingebrochen.
Die Autoren thematisieren die Bedeutung von Zahlungsstromeffekten bei Annuitätenkrediten und analysiert hier vor allem den sogenannten Front-Loading-Effekt. Danach führen höhere Nominalzinsen selbst bei vollständig antizipierten Inflationsraten und unveränderten Realzinsen zu starken finanziellen Zusatzbelastungen in den ersten Phasen der typischerweise langen Kreditlaufzeit. Derartige Liquiditätseffekte können die Zahlungsfähigkeit bzw. die Zahlungsbereitschaft der privaten Investoren empfindlich verringern. Dies gilt vor allem bei Darlehen in Form der Prozentannuität, da hier zusätzlich ein Laufzeitenverkürzungseffekt auftritt. Solche Darlehen sind in Deutschland recht populär.
Mit Blick auf die Zukunft sehen die Autoren auch eine reale Gefahr für den Bestand an Wohnungsbaukrediten, wenn es zu einer Refinanzierung des großen Bestands an billigen Wohnungsbaukrediten kommt, ein Risiko, das auch Auswirkungen auf die makroökonomische und finanzielle Stabilität hat.
Data is considered the new oil of the economy, but privacy concerns limit their use, leading to a widespread sense that data analytics and privacy are contradictory. Yet such a view is too narrow, because firms can implement a wide range of methods that satisfy different degrees of privacy and still enable them to leverage varied data analytics methods. Therefore, the current study specifies different functions related to data analytics and privacy (i.e., data collection, storage, verification, analytics, and dissemination of insights), compares how these functions might be performed at different levels (consumer, intermediary, and firm), outlines how well different analytics methods address consumer privacy, and draws several conclusions, along with future research directions.
This paper studies the impact of banks’ dividend restrictions on the behavior of their institutional investors. Using an identification strategy that relies on the within investor variation and a difference in difference setup, I find that funds permanently decrease their ownership shares at treated banks during the 2020 dividend restrictions in the Eurozone and even exit treated banks’ stocks. Using data before the intro- duction of the ban reveals a positive relationship between fund ownership and banks’ dividend yield, highlighting again the importance of dividends for European banks’ fund investors. This reaction also has pricing implications since there is a negative relationship between the dividend restriction announcement day cumulative abnormal returns and the percentage of fund owners per bank.
This literature survey explores the potential avenues for the design of a green auto asset-backed security by focusing on the European auto securitization market. In this context, we examine the entire value chain of the securitization process to understand the incentives and interests involved at various stages of the transaction. We review recent regulatory developments, feasibility concerns, and potential designs of a sustainable securitization framework. Our study suggests that a Green Auto ABS should be based on both a green use of proceeds and a green collateral-based methodology.
Climate risk has become a major concern for financial institutions and financial markets. Yet, climate policy is still in its infancy and contributes to increased uncertainty. For example, the lack of a sufficiently high carbon price and the variety of definitions for green activities lower the value of existing and new capital, and complicate risk management. This column argues that it would be welfare-enhancing if policy changes were to follow a predictable longer-term path. Accordingly, the authors suggest a role for financial regulation in the transition.
We document the structure of firm-bank relationships across the eleven largest euro area countries and present new stylised facts using novel data from the recent credit registry of the Eurosystem - AnaCredit. We look at the number of banking relationships, reliance on the main bank, credit instruments, loan maturity and interest rates. The granularity of the data allows us to account for cross country differences in firm characteristics. Firms in Southern European countries borrow from a larger number of banks and obtain a lower share of credit from the main bank compared to those in Northern European countries. They also tend to borrow more on short term, more expensive instruments and to obtain loans with shorter maturity. This is consistent with the hypothesis that Southern European countries rely less on relationship banking and obtain credit less conducive to firm growth, in line with the smaller average size of Southern European firms. Instead, no clear pattern emerges in terms of interest rates, consistent with the idea that banks appropriate part of the surplus generated by relationship lending through higher rates.
This research article examines the dual impact of protests on COVID-19 spread, a challenge for policymakers balancing public health and the right to assemble. Using a game theoretical model, it shows that protests can shift infection risks between counties, creating a dilemma for regulators. The empirical study analyzes two German protests in November 2020 using proprietary data from a bus-shuttle service, finding evidence to support the assumption that protests can shift infection risks. The article concludes by discussing the implications of these findings for policymakers, highlighting that regulators’ individually rational strategic decisions may lead to inefficient outcomes.
Retained earnings and foreign portfolio ownership: implications for the current account debate
(2023)
In some countries, a sizable fraction of savings is derived from corporate savings. Although larger, traded corporations are often co-owned by foreign portfolio investors, current international accounting standards allocate all corporate savings to the host country. This paper suggests a framework to correct for this misleading attribution and applies this concept to Germany. For the years 2012 to 2020, our corrections retrospectively reduce German savings and consequently the German current account surplus by, on average, €11.5bn annually. This amounts to approximately five percent of Germany’s average official current account surplus (€226.6bn) across these years.
We find that high macroeconomic uncertainty is associated with greater accumulation of physical capital, despite a reduction in investment and valuations. To reconcile this puzzling evidence, we show that uncertainty predicts lower depreciation and utilization of existing capital, which dominates the investment slowdown. Motivated by these dynamics, we develop a quantitative production-based model in which firms implement precautionary savings through reducing utilization rather than raising invest-ment. Through this novel intensive-margin mechanism, uncertainty shocks command a quarter of the equity premium in general equilibrium, while flexibility in utilization adjustments helps explain uncertainty risk exposures in the cross-section of industry returns.
We assemble a data set of more than eight million German Twitter posts related to the war in Ukraine. Based on state-of-the-art methods of text analysis, we construct a daily index of uncertainty about the war as perceived by German Twitter. The approach also allows us to separate this index into uncertainty about sanctions against Russia, energy policy and other dimensions. We then estimate a VAR model with daily financial and macroeconomic data and identify an exogenous uncertainty shock. The increase in uncertainty has strong effects on financial markets and causes a significant decline in economic activity as well as an increase in expected inflation. We find the effects of uncertainty to be particularly strong in the first months of the war.
In order to reach climate neutrality by 2050, the European Union is taking action in the form of extensive sustainability regulations with the aim to push the private sector towards sustainable economic activities. In this context, a new instrument to finance a company’s sustainability transition has been developed: the sustainability-linked bond (SLB). This paper analyzes the SLB market’s efficiency in attracting those companies that are most crucial for a successful sustainability transition, namely carbon-intensive companies and companies that are lagging behind in their sustainability transition, defined as ESG laggards. By developing a conceptual framework for the SLB market and running a probit and logit regression estimation, this paper shows that the SLB market efficiently attracts carbon-intensive companies, but fails to attract ESG laggards. Moreover, the paper identifies four success factors for the SLB market to improve its future accessibility and credibility.
The European low-carbon transition began in the last few decades and is accelerating to achieve net-zero emissions by 2050. This paper examines how climate-related transition indicators of a large European corporate firm relate to its CDS-implied credit risk across various time horizons. Findings show that firms with higher GHG emissions have higher CDS spreads at all tenors, including the 30-year horizon, particularly after the 2015 Paris Agreement, and in prominent industries such as Electricity, Gas, and Mining. Results suggest that the European CDS market is currently pricing, to some extent, albeit small, the exposure to transition risk for a firm across different time horizons. However, it fails to account for a company’s efforts to manage transition risks and its exposure to the EU Emissions Trading Scheme. CDS market participants seem to find challenging to risk-differentiate ETS-participating firms from other firms.
An unfamiliar term in the not-too-distant past, “net zero” has become a headline-maker in the business and financial world with the growing importance of climate change. Succumbing to increasing pressure, companies and financial institutions around the world have come to adopt net-zero transition plans and targets, pledging to hit certain emission-reduction targets in a long-term period. Moreover, regulators around the world have started to require the disclosure or adoption of net-zero transition plans and targets.
However, an unintended consequence of net-zero transition commitments has been the increased popularity of divestments. That is, many firms seeking to fulfill a net-zero plan are passing on carbon-intensive assets (i.e., oil, gas, and coal assets) to other firms that are likely to be non-committal to environmental goals or that operate under less pressure from investors, stakeholders, and regulators. Such divestments, technically mergers and acquisitions (M&A) transactions, present an ideal opportunity to improve a divesting firm’s environmental record and reach ambitious net-zero goals, creating the impression that an emission reduction has occurred. However, the key is how acquiring firms handle these assets. If they continue operating as before, there will not be an overall improvement for the global climate. Worse, such assets can be operated by new owners in a way that causes more emissions. In any case, such divestments undermine the credibility and value of net-zero ambitions by allowing firms to reach targets by simply divesting assets.
This article explores the reasons and motivations for divestments or, more broadly M&As of carbon-intensive assets and explains why the increased role of net-zero commitments can be undermined by those transactions. We provide some evidence to illustrate the landscape of such transactions and the concerns they give rise to. Lastly, we explore several policy options to address the problem.
There is much discussion today about a possible digital euro (PDE). Is this attention exaggerated? Are “central bank digital currencies” (CBDCs) “a solution in search of a problem”, as some have argued? This article summarizes the main facts about the PDE and concludes that, if the decision on adoption had to be taken today, the arguments against would outweigh those in favor. However, there may be future circumstances in which having a CBDC ready for use can indeed be useful. Therefore, preparing is a good thing, even if the odds of its usefulness in normal conditions are slim.
Es geht um Werbung, Betrug oder die Optimierung von Geschäftsmodellen: Verbraucherdaten sind ein kostbares Gut, das Kreditgeber und Versicherer genauso interessiert wie Händler und Kriminelle. Kai Rannenberg, Professor für Mobile Business & Multilateral Security an der Goethe-Universität, forscht zur Cybersicherheit. Dirk Frank hat mit dem Wirtschaftsinformatiker über Datenschutz, Hackerangriffe und das Auto als »Handy auf Rädern« gesprochen.
Unconventional green
(2023)
We analyze the effects of the PEPP (Pandemic Emergency Purchase Programme), the temporary quantitative easing implemented by the ECB immediately after the burst of the Covid-19 pandemic. We show that the differences in aim, size and flexibility with respect to the traditional Corporate Sector Purchase Programme (CSPP) were able to significantly involve, in addition to the directly targeted bonds, also the green bond segment. Via a standard difference- in-differences model we estimate that the yield on green bonds declined by more than 20 basis points after the PEPP. In order to take into account also the differences attributable to the eligibility to the programme, we employ a triple difference estimator. Bonds that at the same time were green and eligible benefitted of an additional premium of 39 basis points.
Digital platforms have become an important part of the digital economy by facilitating transactions between large numbers of users and by fostering innovation on collaborative platforms. In combination with technical platform services, some platform operators have managed to create powerful ecosystems that create network externalities and benefit from economies of scale and economies of scope. It is striking that, due to the specific economic drivers of the digital infrastructure, platform-based or platform-related services are dominated by a select number of global players. Most of the global platform operators are headquartered in the US, including Alphabet, Amazon, Apple, Meta and Microsoft, also known as the “Big 5”. Some are located in Asia (e.g. Alibaba, Tencent). In Europe there are only a limited number of platform operators with a small market share.
Much research has been conducted on the emergence and characteristics of platforms, network externalities and platform competition. However, there has been very little research on whether or not one can idķentify common features that might explain the success of Big Tech. The following article focuses on an analysis of the Big 5 based on their strategies and development paths. The comparison reveals certain commonalities, from which several conclusions can be drawn regarding the success factors of the Big 5. These insights could be helpful for business decision-makers when shaping digital strategies. But also policy makers, especially in Europe, could benefit from these lessons learned to improve the European technology ecosystem.
I have assessed changes in the monetary policy stance in the euro area since its inception by applying a Bayesian time-varying parameter framework in conjunction with the Hamiltonian Monte Carlo algorithm. I find that the estimated policy response has varied considerably over time. Most of the results suggest that the response weakened after the onset of the financial crisis and while quantitative measures were still in place, although there are also indications that the weakening of the response to the expected inflation gap may have been less pronounced. I also find that the policy response has become more forceful over the course of the recent sharp rise in inflation. Furthermore, it is essential to model the stochastic volatility relating to deviations from the policy rule as it materially influences the results.
This paper presents and compares Bernoulli iterative approaches for solving linear DSGE models. The methods are compared using nearly 100 different models from the Macroeconomic Model Data Base (MMB) and different parameterizations of the monetary policy rule in the medium-scale New Keynesian model of Smets and Wouters (2007) iteratively. I find that Bernoulli methods compare favorably in solving DSGE models to the QZ, providing similar accuracy as measured by the forward error of the solution at a comparable computation burden. The method can guarantee convergence to a particular, e.g., unique stable, solution and can be combined with other iterative methods, such as the Newton method, lending themselves especially to refining solutions.
Can right‐wing terrorism increase support for far‐right populist parties and if so, why? Exploiting quasi‐random variation between successful and failed attacks across German municipalities, we find that successful attacks lead to significant increases in the vote share for the right‐wing, populist Alternative für Deutschland (AfD) party in state elections. Investigating channels, we find that successful attacks lead to differential increases in turnout which are mainly captured by the AfD. Using the German SOEP, a longitudinal panel of individuals, we investigate terror’s impact on individual political attitudes. We first document that people residing in municipalities that experience successful or failed attacks are indistinguishable. We then show that successful terror leads individuals to prefer the AfD, adopt more populist attitudes and report significantly greater political participation at the local level. Terror also leads voters to migrate away from (some) mainstream parties to the AfD. We also find differential media reporting: successful attacks receive more media coverage among local and regional publishers, coverage which makes significantly more use of words related to Islam and terror. Our results hold despite the fact that most attacks are motivated by right‐wing causes and targeted against migrants. Moreover, successful attacks that receive the most media coverage have nearly double the effect on the AfD vote share in state elections and they also increase the AfD vote share in Federal elections, highlighting media salience as a driver of our overall results.
Fabo, Janˇcokov ́a, Kempf, and P ́astor (2021) show that papers written by central bank researchers find quantitative easing (QE) to be more effective than papers written by academics. Weale and Wieladek (2022) show that a subset of these results lose statistical significance when OLS regressions are replaced by regressions that downweight outliers. We examine those outliers and find no reason to downweight them. Most of them represent estimates from influential central bank papers published in respectable academic journals. For example, among the five papers finding the largest peak effect of QE on output, all five are published in high-quality journals (Journal of Monetary Economics, Journal of Money, Credit and Banking, and Applied Economics Letters), and their average number of citations is well over 200. Moreover, we show that these papers have supported policy communication by the world’s leading central banks and shaped the public perception of the effectiveness of QE. New evidence based on quantile regressions further supports the results in Fabo et al. (2021).
The SVB case is a wake-up call for Europe’s regulators as it demonstrates the destructive power of a bank-run: it undermines the role of loss absorbing capital, elbowing governments to bailout affected banks. Many types of bank management weaknesses, like excessive duration risk, may raise concerns of bank losses – but to serve as a run-trigger, there needs to be a large enough group of bank depositors that fails to be fully covered by a deposit insurance scheme. Latent run-risk is the root cause of inefficient liquidations, and we argue that a run on SVB assets could have been avoided altogether by a more thoughtful deposit insurance scheme, sharply distinguishing between loss absorbing capital (equity plus bail-in debt) and other liabilities which are deemed not to be bail-inable, namely demand deposits. These evidence-based insights have direct implications for Europe’s banking regulation, suggesting a minimum and a maximum for a banks’ loss absorption capacity.
Flows of funds run by banks or by firms that belong to the same financial group as a bank are less volatile and less sensitive to bad past performance. This enables bank-affiliated funds to better weather distress and to hold lower precautionary cash buffers in comparison with their unaffiliated peers. Banks provide liquidity support to distressed affiliated funds by buying shares of those funds that are experiencing large outflows. This, in turn, diminishes the severity of strategic complementarities in investors’ redemptions. Liquidity support and other benefits of bank affiliation are conditional on the financial health of the parent company. Distress in the banking system spills over to the mutual fund sector via ownership links. Our research high-lights substantial dependencies between the banking system and the asset management industry, and identifies an important channel via which financial stability risks depend on the organisational structure of the financial sector.
We contribute to the debate about the future of capital markets and corporate finance, which has ensued against the background of a significant boom in private markets and a corresponding decline in the number of firms and the amount of capital raised in public markets in the US and Europe.
Our research sheds light on the fluctuating significance of public and private markets for corporate finance over time, and challenges the conventional view of a linear progression from one market to the other. We argue instead that a more complex pattern of interaction between public and private markets emerges, after taking a long-term perspective and examining historical developments more closely.
We claim that there is a dynamic divide between these markets, and identify certain factors that determine the degree to which investors, capital, and companies gravitate more towards one market than the other. However, in response to the status quo, other factors will gain momentum and favor the respective other market, leading to a new (unstable) equilibrium. Hence, we observe the oscillating domains of public and private markets over time. While these oscillations imply ‘competition’ between these markets, we unravel the complementarities between them, which also militate against a secular trend towards one market. Finally, we examine the role of regulation in this dynamic divide as well as some policy implications arising from our findings.