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Speculative news on corporate takeovers may hurt productivity because uncertainty and threat of job loss cause anxiety, distraction, and reduced collaboration and morale among employees and managers. Using a panel of OECD-headquartered firms, we show that firm productivity temporarily declines upon announcements of speculative takeover rumors that do not materialize. This productivity dip is more pronounced for targets and for firms in countries with weaker employee rights and less long-term orientation. Abnormal stock returns mirror these results. The evidence fosters our understanding of potential real effects of speculative financial news and the costs of takeover threats.
This paper examines the performance of 538 sovereign wealth fund (SWF) investments into venture capital, private equity, and real asset funds (“alternative asset funds”) from 52 countries around the world over the years 1995-2020. The data indicate SWFs are significantly slower to fully liquidate and earn lower returns from their investments, particularly from their investments in venture capital funds. The longer duration and lower performance of SWFs is more pronounced for strategic SWFs than savings SWFs. We show that venture capital fund investments are more likely to be in countries with lower quality disclosure indices. SWFs are more often in buyout funds, and in larger funds with a greater number of limited partners. SWF performance is enhanced by having different types of institutional investors in the same limited partnership. Overall, the data indicate sovereign wealth funds make large investments in alternative asset funds with a longer-term view and earn a lower financial return consistent with strategic and political SWF investment motives.
This paper examines the causes and consequences of hedge fund investments in exchange traded funds (ETFs) using U.S. data from 1998 to 2018. The data indicate that transient hedge funds and quasi-indexer hedge funds are substantially more likely to invest in ETFs. Unexpected hedge fund inflows cause a rise in ETF investments, and the economic significance of unexpected flow is more than twice as large for transient than quasi-indexer hedge funds. ETF investment is in general associated with lower hedge fund performance. But when ETF investment is accompanied by an increase in total flow and unexpected flow, the negative impact of ETF holdings on performance is mitigated. The data are consistent with the view that hedge fund ETF investment unrelated to unexpected flow is an agency cost of delegated portfolio management.
Highly interconnected global supply chains make countries vulnerable to supply chain disruptions. The authors estimate the macroeconomic effects of global supply chain shocks for the euro area. Their empirical model combines business cycle variables with data from international container trade.
Using a novel identification scheme, they augment conventional sign restrictions on the impulse responses by narrative information about three episodes: the Tohoku earthquake in 2011, the Suez Canal obstruction in 2021, and the Shanghai backlog in 2022. They show that a global supply chain shock causes a drop in euro area real economic activity and a strong increase in consumer prices. Over a horizon of one year, the global supply chain shock explains about 30% of inflation dynamics. They also use regional data on supply chain pressure to isolate shocks originating in China.
Their results show that supply chain disruptions originating in China are an important driver for unexpected movements in industrial production, while disruptions originating outside China are an especially important driver for the dynamics of consumer prices.
A novel spatial autoregressive model for panel data is introduced, which incor-porates multilayer networks and accounts for time-varying relationships. Moreover, the proposed approach allows the structural variance to evolve smoothly over time and enables the analysis of shock propagation in terms of time-varying spillover effects.
The framework is applied to analyse the dynamics of international relationships among the G7 economies and their impact on stock market returns and volatilities. The findings underscore the substantial impact of cooperative interactions and highlight discernible disparities in network exposure across G7 nations, along with nuanced patterns in direct and indirect spillover effects.
In his speech at the conference „The SNB and its Watchers“, Otmar Issing, member of the ECB Governing Council from its start in 1998 until 2006, takes a look back at more than twenty years of the conference series „The ECB and Its Watchers“. In June 1999, Issing established this format together with Axel Weber, then Director of the Center for Financial Studies, to discuss the monetary policy strategy of the newly founded central bank with a broad circle of participants, that is academics, bank economists and members of the media on a „neutral ground“. At the annual conference, the ECB and its representatives would play an active role and engage in a lively exchange of view with the other participants. Over the years, Volker Wieland took over as organizer of the conference series, which also was adopted by other central banks. In his contribution at the second conference „The SNB and its Watchers“, Issing summarizes the experience gained from over twenty years of the ECB Watchers Conference.
Der Beitrag führt in das sozialpsychologische Phänomen des Gruppendenkens ein. Kennzeichen und Gegenstrategien werden anhand von Zeugenaussagen vor dem Wirecard-Untersuchungsausschuss am Beispiel des Aufsichtsrats illustriert. Normative Implikationen de lege ferenda schließen sich an. Sie betreffen unabhängige Mitglieder (auch auf der Arbeitnehmerbank), Direktinformationsrechte im Unternehmen (unter Einschluss von Hinweisgebern) und den Investorendialog (auch mit Leerverkäufern).
Industry classification groups firms into finer partitions to help investments and empirical analysis. To overcome the well-documented limitations of existing industry definitions, like their stale nature and coarse categories for firms with multiple operations, we employ a clustering approach on 69 firm characteristics and allocate companies to novel economic sectors maximizing the within-group explained variation. Such sectors are dynamic yet stable, and represent a superior investment set compared to standard classification schemes for portfolio optimization and for trading strategies based on within-industry mean-reversion, which give rise to a latent risk factor significantly priced in the cross-section. We provide a new metric to quantify feature importance for clustering methods, finding that size drives differences across classical industries while book-to-market and financial liquidity variables matter for clustering-based sectors.
Dynamics of life course family transitions in Germany: exploring patterns, process and relationships
(2023)
This paper explores dynamics of family life events in Germany using discrete time event history analysis based on SOEP data. We find that higher educational attainment, better income level, and marriage emerge as salient protective factors mitigating the risk of mortality; better education also reduces the likelihood of first marriage whereas, lower educational attainment, protracted period, and presence of children act as protective factors against divorce. Our key finding shows that disparity in mean life expectancies between individuals from low- and high-income brackets is observed to be 9 years among males and 6 years among females, thereby illustrating the mortality inequality attributed to income disparities. Our estimates show that West Germans have low risk of death, less likelihood of first marriage, and they have a high risk of divorce and remarriage compared to East Germans.
We present determinacy bounds on monetary policy in the sticky information model. We find that these bounds are more conservative here when the long run Phillips curve is vertical than in the standard Calvo sticky price New Keynesian model. Specifically, the Taylor principle is now necessary directly - no amount of output targeting can substitute for the monetary authority’s concern for inflation. These determinacy bounds are obtained by appealing to frequency domain techniques that themselves provide novel interpretations of the Phillips curve.
We study the redistributive effects of inflation combining administrative bank data with an information provision experiment during an episode of historic inflation. On average, households are well-informed about prevailing inflation and are concerned about its impact on their wealth; yet, while many households know about inflation eroding nominal assets, most are unaware of nominal-debt erosion. Once they receive information on the debt-erosion channel, households update upwards their beliefs about nominal debt and their own real net wealth. These changes in beliefs causally affect actual consumption and hypothetical debt decisions. Our findings suggest that real wealth mediates the sensitivity of consumption to inflation once households are aware of the wealth effects of inflation.
In current discussions on large language models (LLMs) such as GPT, understanding their ability to emulate facets of human intelligence stands central. Using behavioral economic paradigms and structural models, we investigate GPT’s cooperativeness in human interactions and assess its rational goal-oriented behavior. We discover that GPT cooperates more than humans and has overly optimistic expectations about human cooperation. Intriguingly, additional analyses reveal that GPT’s behavior isn’t random; it displays a level of goal-oriented rationality surpassing human counterparts. Our findings suggest that GPT hyper-rationally aims to maximize social welfare, coupled with a strive of self-preservation. Methodologically, our esearch highlights how structural models, typically employed to decipher human behavior, can illuminate the rationality and goal-orientation of LLMs. This opens a compelling path for future research into the intricate rationality of sophisticated, yet enigmatic artificial agents.
A key solution for public good provision is the voluntary formation of institutions that commit players to cooperate. Such institutions generate inequality if some players decide not to participate but cannot be excluded from cooperation benefits. Prior research with small groups emphasizes the role of fairness concerns with positive effects on cooperation. We show that effects do not generalize to larger groups: if group size increases, groups are less willing to form institutions generating inequality. In contrast to smaller groups, however, this does not increase the number of participating players, thereby limiting the positive impact of institution formation on cooperation.
This paper investigates retirees’ optimal purchases of fixed and variable longevity income annuities using their defined contribution (DC) plan assets and given their expected Social Security benefits. As an alternative, we also evaluate using plan assets to boost Social Security benefits through delayed claiming. We determine that including deferred income annuities in DC accounts is welfare enhancing for all sex/education groups examined. We also show that providing access to well-designed variable deferred annuities with some equity exposure further enhances retiree wellbeing, compared to having access only to fixed annuities. Nevertheless, for the least educated, delaying claiming Social Security is preferred, whereas the most educated benefit more from using accumulated DC plan assets to purchase deferred annuities.
This paper studies the macro-financial implications of using carbon prices to achieve ambitious greenhouse gas (GHG) emission reduction targets. My empirical evidence shows a 0.6% output loss and a rise of 0.3% in inflation in response to a 1% shock on carbon policy. Furthermore, I also observe financial instability and allocation effects between the clean and highly polluted energy sectors. To have a better prediction of medium and long-term impact, using a medium-large macro-financial DSGE model with environmental aspects, I show the recessionary effect of an ambitious carbon price implementation to achieve climate targets, a 40% reduction in GHG emission causes a 0.7% output loss while reaching a zero-emission economy in 30 years causes a 2.6% output loss. I document an amplified effect of the banking sector during the transition path. The paper also uncovers the beneficial role of pre-announcements of carbon policies in mitigating inflation volatility by 0.2% at its peak, and our results suggest well-communicated carbon policies from authorities and investing to expand the green sector. My findings also stress the use of optimal green monetary and financial policies in mitigating the effects of transition risk and assisting the transition to a zero-emission world. Utilizing a heterogeneous approach with macroprudential tools, I find that optimal macroprudential tools can mitigate the output loss by 0.1% and investment loss by 1%. Importantly, my work highlights the use of capital flow management in the green transition when a global cooperative solution is challenging.
Measuring and reducing energy consumption constitutes a crucial concern in public policies aimed at mitigating global warming. The real estate sector faces the challenge of enhancing building efficiency, where insights from experts play a pivotal role in the evaluation process. This research employs a machine learning approach to analyze expert opinions, seeking to extract the key determinants influencing potential residential building efficiency and establishing an efficient prediction framework. The study leverages open Energy Performance Certificate databases from two countries with distinct latitudes, namely the UK and Italy, to investigate whether enhancing energy efficiency necessitates different intervention approaches. The findings reveal the existence of non-linear relationships between efficiency and building characteristics, which cannot be captured by conventional linear modeling frameworks. By offering insights into the determinants of residential building efficiency, this study provides guidance to policymakers and stakeholders in formulating effective and sustainable strategies for energy efficiency improvement.
The forward guidance trap
(2023)
This paper examines the policy experience of the Fed, ECB and BOJ during and after the Covid-19 pandemic and draws lessons for monetary policy strategy and ist communication. All three central banks provided appropriate accommodation during the pandemic but two failed to unwind this accommodation in a timely manner. The Fed and ECB guided real interest rates to inappropriately negative levels as the economy recovered from the pandemic, fueling high inflation. The policy error can be traced to decisions regarding forward guidance on policy rates that delayed lift-off while the two central banks continued to expand their balance sheets. The Fed and the ECB fell into the forward guidance trap. This could have been avoided if policy were guided by a forward- looking rule that properly adjusted the nominal interest rate with the evolution of the inflation outlook.
This paper develops and implements a backward and forward error analysis of and condition numbers for the numerical stability of the solutions of linear dynamic stochastic general equilibrium (DSGE) models. Comparing seven different solution methods from the literature, I demonstrate an economically significant loss of accuracy specifically in standard, generalized Schur (or QZ) decomposition based solutions methods resulting from large backward errors in solving the associated matrix quadratic problem. This is illustrated in the monetary macro model of Smets and Wouters (2007) and two production-based asset pricing models, a simple model of external habits with a readily available symbolic solution and the model of Jermann (1998) that lacks such a symbolic solution - QZ-based numerical solutions miss the equity premium by up to several annualized percentage points for parameterizations that either match the chosen calibration targets or are nearby to the parameterization in the literature. While the numerical solution methods from the literature failed to give any indication of these potential errors, easily implementable backward-error metrics and condition numbers are shown to successfully warn of such potential inaccuracies. The analysis is then performed for a database of roughly 100 DSGE models from the literature and a large set of draws from the model of Smets and Wouters (2007). While economically relevant errors do not appear pervasive from these latter applications, accuracies that differ by several orders of magnitude persist.
This study looks at potential windfall profits for the four banking acquisitions in 2023. Based on accounting figures, an FT article states that a total of USD 44bn was left on the table. We see accounting figures as a misleading analysis. By estimating marked-based cumulative abnormal returns (CAR), we find positive abnormal returns in all four cases which when made quantifiable, are around half of the FT’s accounting figures. Furthermore, we argue that transparent auctions with enough bidders should be preferred to negotiated bank sales.
This document was provided/prepared by the Economic Governance and EMU Scrutiny Unit at the request of the ECON Committee.
The recent COVID-19 pandemic represents an unprecedented worldwide event to study the influence of related news on the financial markets, especially during the early stage of the pandemic when information on the new threat came rapidly and was complex for investors to process. In this paper, we investigate whether the flow of news on COVID-19 had an impact on forming market expectations. We analyze 203,886 online articles dealing with COVID-19 and published on three news platforms (MarketWatch.com, NYTimes.com, and Reuters.com) in the period from January to June 2020. Using machine learning techniques, we extract the news sentiment through a financial market-adapted BERT model that enables recognizing the context of each word in a given item. Our results show that there is a statistically significant and positive relationship between sentiment scores and S&P 500 market. Furthermore, we provide evidence that sentiment components and news categories on NYTimes.com were differently related to market returns.
This paper proposes tests for out-of-sample comparisons of interval forecasts based on parametric conditional quantile models. The tests rank the distance between actual and nominal conditional coverage with respect to the set of conditioning variables from all models, for a given loss function. We propose a pairwise test to compare two models for a single predictive interval. The set-up is then extended to a comparison across multiple models and/or intervals. The limiting distribution varies depending on whether models are strictly non-nested or overlapping. In the latter case, degeneracy may occur. We establish the asymptotic validity of wild bootstrap based critical values across all cases. An empirical application to Growth-at-Risk (GaR) uncovers situations in which a richer set of financial indicators are found to outperform a commonly-used benchmark model when predicting downside risk to economic activity.
The financial sector plays an important role in financing the green transformation. Various regulatory initiatives in the EU aim to improve transparency in relation to the sustainability of financial products and the sustainability of economic activities of non-financial and financial undertakings. For credit institutions, the Green Asset Ratio (GAR) has been established by the European regulatory authorities as a KPI for measuring the proportion of Taxonomy-aligned on-balance-sheet exposure in relation to the total assets. The breakdown of the total GAR by type of counterparty, environmental objective and type of asset provides in-depth information about the sustainability profile of a credit institution. This information, which has not been available to date, may also initiate discussions between management and shareholders or other stakeholders regarding the future sustainability strategy of credit institutions. This paper provides an overview of the regulatory background and the method of calculating the GAR along different dimensions. Finally, the potential benefits and limitations of the GAR are discussed.
A safe core mandate
(2023)
Central banks have vastly expanded their footprint on capital markets. At a time of extraordinary pressure by many sides, a simple benchmark for the scale and scope of their core mandate of price and financial stability may be useful.
We make a case for a narrow mandate to maintain and safeguard the border between safe and quasi safe assets. This ex-ante definition minimizes ambiguity and discourages risk creation and limit panic runs, primarily by separating market demand for reliable liquidity from risk-intolerant, price-insensitive demand for a safe store of value. The central bank may be occasionally forced to intervene beyond the safe core but should not be bound by any such ex-ante mandate, unless directed to specific goals set by legislation with explicit fiscal support.
We review distinct features of liquidity and safety demand, seeking a definition of the safety border, and discuss LOLR support for borderline safe assets such as MMF or uninsured deposits.
A safe core formulation is close to the historical focus on regulated entities, collateralized lending and attention to the public debt market, but its specific framing offers some context on controversial issues such as the extent of LOLR responsibilities. It also justifies a persistently large scale for central bank liabilities (Greenwood, Hansom and Stein 2016), as safety demand is related to financial wealth rather than GDP. Finally, it is consistent with an active central bank role in supporting liquidity in government debt markets trading and clearing (Duffie 2020, 2021).
We study the interplay of capital and liquidity regulation in a general equilibrium setting by focusing on future funding risks. The model consists of a banking sector with long-term illiquid investment opportunities that need to be financed by shortterm debt and by issuing equity. Reliance on refinancing long-term investment in the middle of the life-time is risky, since the next generation of potential short-term debt holders may not be willing to provide funding when the return prospects on the long-term investment turn out to be bad. For moderate return risk, equilibria with and without bank default coexist, and bank default is a self-fulfilling prophecy. Capital and liquidity regulation can prevent bank default and may implement the first-best. Yet the former is more powerful in ruling out undesirable equilibria and thus dominates liquidity regulation. Adding liquidity regulation to optimal capital regulation is redundant.
Can consumption-based mechanisms generate positive and time-varying real term premia as we see in the data? I show that only models with time-varying risk aversion or models with high consumption risk can independently produce these patterns. The latter explanation has not been analysed before with respect to real term premia, and it relies on a small group of investors exposed to high consumption risk. Additionally, it can give rise to a “consumption-based arbitrageur” story of term premia. In relation to preferences, I consider models with both time-separable and recursive utility functions. Specifically for recursive utility, I introduce a novel perturbation solution method in terms of the intertemporal elasticity of substitution. This approach has not been used before in such models, it is easy to implement, and it allows a wide range of values for the parameter of intertemporal elasticity of substitution.
Many consumers care about climate change and other externalities associated with their purchases. We analyze the behavior and market effects of such “socially responsible consumers” in three parts. First, we develop a flexible theoretical framework to study competitive equilibria with rational consequentialist consumers. In violation of price taking, equilibrium feedback non-trivially dampens a consumer’s mitigation efforts, undermining responsible behavior. This leads to a new type of market failure, where even consumers who fully “internalize the externality” overconsume externality-generating goods. At the same time, socially responsible consumers change the relative effectiveness of taxes, caps, and other policies in lowering the externality. Second, since consumer beliefs about and preferences over dampening play a crucial role in our framework, we investigate them empirically via a tailored survey. Consistent with our model, consumers are predominantly consequentialist, and on average believe in dampening. Inconsistent with our model, however, many consumers fail to anticipate dampening. Third, therefore, we analyze how such “naive” consumers modify our theoretical conclusions. Naive consumers behave more responsibly than rational consumers in a single-good economy, but may behave less responsibly in a multi-good economy with cross-market spillovers. A mix of naive and rational consumers may yield the worst outcomes.
We investigate how unconventional monetary policy, via central banks’ purchases of corporate bonds, unfolds in credit-saturated markets. While this policy results in a loosening of credit market conditions as intended by policymakers, we report two unintended side effects. First, the policy impacts the allocation of credit among industries. Affected banks reallocate loans from investment-grade firms active on bond markets almost entirely to real estate asset managers. Other industries do not obtain more loans, particularly real estate developers and construction firms. We document an increase in real estate prices due to this policy, which fuels real estate overvaluation. Second, more loan write-offs arise from lending to these firms, and banks are not compensated for this risk by higher interest rates. We document a drop in bank profitability and, at the same time, a higher reliance on real estate collateral. Our findings suggest that central banks’ quantitative easing has substantial adverse effects in credit-saturated economies.
We conduct a field experiment with clients of a German universal bank to explore the impact of peer information on sustainable retail investments. Our results show that infor-mation about peers’ inclination towards sustainable investing raises the amount allocated to stock funds labeled sustainable, when communicated during a buying decision. This effect is primarily driven by participants initially underestimating peers’ propensity to invest sustainably. Further, treated individuals indicate an increased interest in addi-tional information on sustainable investments, primarily on risk and return expectations. However, when analyzing account-level portfolio holding data over time, we detect no spillover effects of peer information on later sustainable investment decisions.
The complexities of geopolitical events, financial and fiscal crises, and the ebb and flow of personal life circumstances can weigh heavily on individuals’ minds as they make critical economic decisions. To investigate the impact of cognitive load on such decisions, the authors conducted an incentivized online experiment involving a representative sample of 2,000 French households. The results revealed that exposure to a taxing and persistent cognitive load significantly reduced consumption, particularly for individuals under the threat of furlough, while simultaneously increasing their account balances, particularly for those not facing such employment uncertainty. These effects were not driven by supply constraints or a worsening of credit constraints. Instead, cognitive load primarily affected the optimality of the chosen policy rules and impaired the ability of the standard economic model to accurately predict consumption patterns, although this effect was less pronounced among college-educated subjects
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.
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.
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.
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.
This Policy Letter presents two event studies based on the pre-war data that foreshadows the remarkable way in which Russian economy was able to withstand the pressure from unprecedented package of international sanctions. First, it shows that a sudden stop of one of the two domestic producers of zinc in 2018 did not lead to a slowdown in the steel industry, which heavily relied on this input. Second, it demonstrates that a huge increase in cost of fuel called mazut in 2020 had virtually no impact on firms that used it, even in the regions where it was hard to substitute it for alternative fuels. This Policy Letter argues that such stability in production can be explained by the fact that Russian economy is heavily oriented toward commodities. It is much easier to replace a commodity supplier than a supplier of manufacturing goods, and many commodity producers operate at high profit margins that allow them to continue to operate even after big increases in their costs. Thus, sanctions had a much smaller impact on Russia than they would have on an economy with larger manufacturing sector, where inputs are less substitutable and profit margins are smaller.
This paper investigates stock market reaction to greenwashing by analyzing a new channel whereby companies change their names to green-related ones (i.e., names that evoke green and sustainable sentiments) to persuade the public that their activities are green. The findings reveal a striking positive stock price reaction to the announcement of corporate name changes to green-related names only for companies not involved in green activities at the time of the announcement. However, over an extended period of time, companies unrelated to green activities experience substantial negative abnormal returns if they fail to align their operational focus with the new name after the change.
We propose a model with mean-variance foreign investors who exhibit a convex disutility associated to brown bond holdings. The model predicts that bond green premia should be smaller in economies with a closer financial account and highly volatile exchange rates. This happens because foreign intermediaries invest relatively less in such economies, and this lowers the marginal disutility of investing in polluting activities. We find strong empirical evidence in favor of this hypothesis using a global bond market dataset. Exchange rate volatility and financial account openness are thus able to explain the higher financing costs of green projects in emerging markets relative to advanced economies, especially when green bonds are denominated in local currency: a disadvantage that we can call the "green sin" of emerging economies.
How does group identity affect belief formation? To address this question, we conduct a series of online experiments with a representative sample of individuals in the US. Using the setting of the 2020 US presidential election, we find evidence of intergroup preference across three distinct components of the belief formation cycle: a biased prior belief, avoid-ance of outgroup information sources, and a belief-updating process that places greater (less) weight on prior (new) information. We further find that an intervention reducing the salience of information sources decreases outgroup information avoidance by 50%. In a social learn-ing context in wave 2, we find participants place 33% more weight on ingroup than outgroup guesses. Through two waves of interventions, we identify source utility as the mechanism driving group effects in belief formation. Our analyses indicate that our observed effects are driven by groupy participants who exhibit stable and consistent intergroup preferences in both allocation decisions and belief formation across all three waves. These results suggest that policymakers could reduce the salience of group and partisan identity associated with a policy to decrease outgroup information avoidance and increase policy uptake.
Standard applications of the consumption-based asset pricing model assume that goods and services within the nondurable consumption bundle are substitutes. We estimate substitution elasticities between different consumption bundles and show that households cannot substitute energy consumption by consumption of other nondurables. As a consequence, energy consumption affects the pricing function as a separate factor. Variation in energy consumption betas explains a large part of the premia related to value, investment, and operating profitability. For example, value stocks are typically more energy-intensive than growth stocks and thus riskier, since they suffer more from the oil supply shocks that also affect households.
Whatever it takes to understand a central banker : embedding their words using neural networks
(2023)
Dictionary approaches are at the forefront of current techniques for quantifying central bank communication. In this paper, the author propose a novel language model that is able to capture subtleties of messages such as one of the most famous sentences in central bank communications when ECB President Mario Draghi stated that "within [its] mandate, the ECB is ready to do whatever it takes to preserve the euro".
The authors utilize a text corpus that is unparalleled in size and diversity in the central bank communication literature, as well as introduce a novel approach to text quantication from computational linguistics. This allows them to provide high-quality central bank-specific textual representations and demonstrate their applicability by developing an index that tracks deviations in the Fed's communication towards inflation targeting. Their findings indicate that these deviations in communication significantly impact monetary policy actions, substantially reducing the reaction towards inflation deviation in the US.
This paper applies structure preserving doubling methods to solve the matrix quadratic underlying the recursive solution of linear DSGE models. We present and compare two Structure-Preserving Doubling Algorithms ( SDAs) to other competing methods – the QZ method, a Newton algorithm, and an iterative Bernoulli approach – as well as the related cyclic and logarithmic reduction algorithms. Our comparison is completed 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. We find that both SDAs perform very favorably relative to QZ, with generally more accurate solutions computed in less time. While we collect theoretical convergence results that promise quadratic convergence rates to a unique stable solution, the algorithms may fail to converge when there is a breakdown due to singularity of the coefficient matrices in the recursion. One of the proposed algorithms can overcome this problem by an appropriate (re)initialization. This SDA also performs particular well in refining solutions of different methods or from nearby parameterizations.
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.
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.
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.
The pricing of digital art
(2023)
The intersection of recent advancements in generative artificial intelligence and blockchain technology has propelled digital art into the spotlight. Digital art pricing recognizes that owners derive utility beyond the artwork’s inherent value. We incorporate the consumption utility associated with digital art and model the stochastic discount factor and risk premiums. Furthermore, we conduct a calibration analysis to analyze the effects of shifts in the real and digital economy. Higher returns are required in a digital market upswing due to increased exposure to systematic risk and digital art prices are especially responsive to fluctuations in business cycles within digital markets.
The Eurosystem and the Deutsche Bundesbank will incur substantial losses in 2023 that are likely to persist for several years. Due to the massive purchases of securities in the last 10 years, especially of government bonds, the banks' excess reserves have risen sharply. The resulting high interest payments to the banks since the turnaround in monetary policy, with little income for the large-scale securities holdings, led to massive criticism. The banks were said to be making "unfair" profits as a result, while the fiscal authorities had to forego the previously customary transfers of central bank profits. Populist demands to limit bank profits by, for example, drastically increasing the minimum reserve ratios in the Eurosystem to reduce excess reserves are creating new severe problems and are neither justified nor helpful. Ultimately, the EU member states have benefited for a very long time from historically low interest rates because of the Eurosystem's extraordinary loose monetary policy and must now bear the flip side consequences of the massive expansion of central bank balance sheets during the necessary period of monetary policy normalisation.