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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.
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.
Between 2016 and 2022, life insurers in several European countries experienced negative longterm interest rates, which put pressure on their business models. The aim of this paper is to empirically investigate the impact of negative interest rates on the stock performance of life insurers. To measure the sensitivities, I estimate the level, slope, and curvature of the yield curve using the Nelson-Siegel model and empirical proxies. Panel regressions show that the effect of changes in the level is up to three times greater in a negative interest rate environment than in a positive one. Thus, a 1ppt decline in long-term interest rates reduces the stock returns of European life insurers by up to 10ppt when interest rates are below 0%. I also show that the relationship between the level and the sensitivity to interest rates is convex, and that life insurers benefit from rising interest rates across all maturity types.
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.
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 key performance indicator (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.
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.
Art-related non-fungible tokens (NFTs) took the digital art space by storm in 2021, generating massive amounts of volume and attracting a large number of users to a previously obscure part of blockchain technology. Still, very little is known about the attributes that influence the price of these digital assets. This paper attempts to evaluate the level of speculation associated with art NFTs, comprehend the characteristics that confer value on them and design a profitable trading strategy based on our findings. We analyze 860,067 art NFTs that have been deployed on the Ethereum blockchain and have been involved in 317,950 sales using machine learning methods to forecast the probability of sale, the trade frequency and the average price. We find that NFTs are highly speculative assets and that their price and recurrence of sale are heavily determined by the floor and the last sale prices, independent of any fundamental value.
The 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.
Output gap revisions can be large even after many years. Real-time reliability tests might therefore be sensitive to the choice of the final output gap vintage that the real-time estimates are compared to. This is the case for the Federal Reserve’s output gap. When accounting for revisions in response to the global financial crisis in the final output gap, the improvement in real-time reliability since the mid-1990s is much smaller than found by Edge and Rudd (Review of Economics and Statistics, 2016, 98(4), 785-791). The negative bias of real-time estimates from the 1980s has disappeared, but the size of revisions continues to be as large as the output gap itself.
The authors systematically analyse how the realtime reliability assessment is affected through varying the final output gap vintage. They find that the largest changes are caused by output gap revisions after recessions. Economists revise their models in response to such events, leading to economically important revisions not only for the most recent years, but reaching back up to two decades. This might improve the understanding of past business cycle dynamics, but decreases the reliability of real-time output gaps ex post.
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.
Testing frequency and severity risk under various information regimes and implications in insurance
(2023)
We build on Peter et al. (2017) who examined the benefit of testing frequency risk under various information regimes. We first consider testing only severity risk, and whether the principle of indemnity, i.e. the usual contract term that excludes claims payments above the resulting insured loss, affects the insurance contracts offered and purchased. Under information regimes which are less restrictive (in terms of obtaining and using customer information), it is possible for the insurer to offer different contracts for tested and untested individuals. In the absence of the principle of indemnity, individuals will test their severity risk and a separating equilibrium ensues. With the principle of indemnity, given an actuarially fair pooled contract, individuals will not test for severity under less restrictive information regimes; a pooling equilibrium thus ensues. Under more restrictive information regimes, the insurer offers separating contracts. Individuals will test for severity and purchase appropriate contracts. We also consider testing for both frequency and severity risk. The results here are more varied. The highest gain in efficiency from testing results from one of the more restrictive information regimes. Generally under all information regimes, there is a greater gain in efficiency without the principle of indemnity than with the principle of indemnity.
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.
Using a field study at a German brokerage, we investigate advised individual investors’ behavior and outcomes after self-selecting into a flat-fee scheme (percentage of portfolio value) for mutual funds. In a difference-in-differences setting, we compare 699 switchers to propensity-score-matched advisory clients who remained in the commission-based scheme. Switchers increase their portfolio values, improve portfolio diversification, and increase their portfolio performance. They also demand more financial advice and follow more advisor recommendations. We argue that switchers attribute a higher quality to the unchanged advisory services.
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 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.
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 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.
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.
We estimate the causal effect of shared e-scooter services on traffic accidents by exploiting the variation in the availability of e-scooter services induced by the staggered rollout across 93 cities in six countries. Police-reported accidents involving personal injuries in the average month increased by around 8.2% after shared e-scooters were introduced. Effects are large during summer and insignificant during winter. Further heterogeneity analysis reveals the largest estimated effects for cities with limited cycling infrastructure, while no effects are detectable in cities with high bike-lane density. This difference suggests that public policy can play a crucial role in mitigating accidents related to e-scooters and, more generally, to changes in urban mobility.
Shallow meritocracy
(2023)
Meritocracies aspire to reward hard work and promise not to judge individuals by the circumstances into which they were born. However, circumstances often shape the choice to work hard. I show that people's merit judgments are "shallow" and insensitive to this effect. They hold others responsible for their choices, even if these choices have been shaped by unequal circumstances. In an experiment, US participants judge how much money workers deserve for the effort they exert. Unequal circumstances disadvantage some workers and discourage them from working hard. Nonetheless, participants reward the effort of disadvantaged and advantaged workers identically, regardless of the circumstances under which choices are made. For some participants, this reflects their fundamental view regarding fair rewards. For others, the neglect results from the uncertain counterfactual. They understand that circumstances shape choices but do not correct for this because the counterfactual—what would have happened under equal circumstances—remains uncertain.
Optimal monetary policy studies typically rely on a single structural model and identification of model-specific rules that minimize the unconditional volatilities of inflation and real activity. In their proposed approach, the authors take a large set of structural models and look for the model-robust rules that minimize the volatilities at those frequencies that policymakers are most interested in stabilizing. Compared to the status quo approach, their results suggest that policymakers should be more restrained in their inflation responses when their aim is to stabilize inflation and output growth at specific frequencies. Additional caution is called for due to model uncertainty.
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.
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, investment, 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 policy. We find that the policy has only a modest impact on aggregate output and employment because (i) jobs are saved predominately in the smallest firms that account for a minor share of employment and (ii) the grant reduces the reallocation of resources towards larger and less impacted firms. Much of the reallocation effects occur in the aftermath of the pandemic episode. By preventing inefficient liquidations, the policy dampens the long-term declines of aggregate consumption and of the real wage, thus delivering small welfare gains.
Industry concentration and markups in the US have been rising over the last 3-4 decades. However, the causes remain largely unknown. This paper uses machine learning on regulatory documents to construct a novel dataset on compliance costs to examine the effect of regulations on market power. The dataset is comprehensive and consists of all significant regulations at the 6-digit NAICS level from 1970-2018. We find that regulatory costs have increased by $1 trillion during this period. We document that an increase in regulatory costs results in lower (higher) sales, employment, markups, and profitability for small (large) firms. Regulation driven increase in concentration is associated with lower elasticity of entry with respect to Tobin's Q, lower productivity and investment after the late 1990s. We estimate that increased regulations can explain 31-37% of the rise in market power. Finally, we uncover the political economy of rulemaking. While large firms are opposed to regulations in general, they push for the passage of regulations that have an adverse impact on small firms.
In this article, we examine anti-refugee hate crime in the wake of the large influx of refugees to Germany in 2014 and 2015. By exploiting institutional features of the assignment of refugees to German regions, we estimate the impact of unexpected and sudden large-scale immigration on hate crime against refugees. Results indicate that it is not simply the size of local refugee inflows which drives the increase in hate crime, but rather the combination of refugee arrivals and latent anti-refugee sentiment. We show that ethnically homogeneous areas, areas which experienced hate crimes in the 1990s, and areas with high support for the Nazi party in the Weimar Republic, are more prone to respond to the arrival of refugees with incidents of hate crime against this group. Our results highlight the importance of regional anti-immigration sentiment in the analysis of the incumbent population’s reaction to immigration.
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.
This paper analyzes the current implementation status of sustainability and taxonomy-aligned disclosure under the Sustainable Finance Disclosure Regulation (SFDR) as well as the development of the SFDR categorization of funds offered via banks in Germany. Examining data provided by WM Group, which consists of more than 10,000 investment funds and 2,000 index funds between September 2022 and March 2023, we have observed a significant proportion of Article 9 (dark green) funds transitioning to Article 8 (light green) funds, particularly among index funds. As a consequence of this process, the profile of the SFDR classes has sharpened, which reflects an increased share of sustainable investments in the group of Article 9 funds. When differentiating between environmental and social investments, the share of environmental investments increased, but the share of social investments decreased in the group of Article 9 funds at the beginning of 2023. The share of taxonomy-aligned investments is very low, but slightly increasing for Article 9 funds. However, by March 2023 only around 1,000 funds have reported their sustainability proportions and this picture might change due to legal changes which require all funds in the scope of the SFDR to report these proportions in their annual reports being published after 1 January 2023.
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.
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.
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.
Even as online advertising continues to grow, a central question remains: Who to target? Yet, advertisers know little about how to select from the hundreds of audience segments for targeting (and combinations thereof) for a profitable online advertising campaign. Utilizing insights from a field experiment on Facebook (Study 1), we develop a model that helps advertisers solve the cold-start problem of selecting audience segments for targeting. Our model enables advertisers to calculate the break-even performance of an audience segment to make a targeted ad campaign at least as profitable as an untargeted one. Advertisers can use this novel model to decide whether to test specific audience segments in their campaigns (e.g., in randomized controlled trials). We apply our model to data from the Spotify ad platform to study the profitability of different audience segments (Study 2). Approximately half of those audience segments require the click-through rate to double compared to an untargeted campaign, which is unrealistically high for most ad campaigns. Our model also shows that narrow segments require a lift that is likely not attainable, specifically when the data quality of these segments is poor. We confirm this theoretical finding in an empirical study (Study 3): A decrease in data quality due to Apple’s introduction of the App Tracking Transparency (ATT) framework more negatively affects the click-through rate of narrow (versus broad) audience segments.
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.
Recent empirical evidence shows that most international prices are sticky in dollars. This paper studies the policy implications of this fact in the context of an open economy model, allowing for an arbitrary structure of asset markets, general preferences and technologies, time- or state-dependent price setting, and a rich set of shocks. We show that although monetary policy is less efficient and cannot implement the flexible-price allocation, inflation targeting remains robustly optimal in non-U.S. economies. The implementation of this non-cooperative policy results in a "global monetary cycle" with other countries importing the monetary stance of the U.S. The capital controls cannot unilaterally improve the allocation and are useful only when coordinated across countries. Thanks to the dominance of the dollar, the U.S. can extract rents in international goods and asset markets and enjoy a higher welfare than other economies. Although international cooperation benefits other countries by improving global demand for dollar-invoiced goods, it is not in the self-interest of the U.S. and may be hard to sustain.
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.
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.
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.
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.
Fund companies regularly send shareholder letters to their investors. We use textual analysis to investigate whether these letters’ writing style influences fund flows and whether it predicts performance and investment styles. Fund investors react to the tone and content of shareholder letters: A less negative tone leads to higher net flows. Thus, fund companies can use shareholder letters as a tactical instrument to influence flows. However, at the same time, a dishonest communication that is not consistent with the fund’s actual performance decreases flows. A positive writing style predicts higher idiosyncratic risk as well as more style bets, while there is no consistent predictive power for future performance.
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.
Biodiversity loss poses a significant threat to the global economy and affects ecosystem services on which most large companies rely heavily. The severe financial implications of such a reduced species diversity have attracted the attention of companies and stakeholders, with numerous calls to increase corporate transparency. Using textual analysis, this study thus investigates the current state of voluntary biodiversity reporting of 359 European blue-chip companies and assesses the extent to which it aligns with the upcoming disclosure framework of the Task Force on Nature-related Financial Disclosures (TNFD). The descriptive results suggest a substantial gap between current reporting practices and the proposed TNFD framework, with disclosures largely lacking quantification, details and clear targets. In addition, the disclosures appear to be relatively unstandardized. Companies in sectors or regions exposed to higher nature-related risks as well as larger companies are more likely to report on aspects of biodiversity. This study contributes to the emerging literature on nature-related risks and provides detailed insights on the extent of the reporting gap in light of the upcoming standards.
Investors' return expectations are pivotal in stock markets, but the reasoning behind these expectations remains a black box for economists. This paper sheds light on economic agents' mental models -- their subjective understanding -- of the stock market, drawing on surveys with the US general population, US retail investors, US financial professionals, and academic experts. Respondents make return forecasts in scenarios describing stale news about the future earnings streams of companies, and we collect rich data on respondents' reasoning. We document three main results. First, inference from stale news is rare among academic experts but common among households and financial professionals, who believe that stale good news lead to persistently higher expected returns in the future. Second, while experts refer to the notion of market efficiency to explain their forecasts, households and financial professionals reveal a neglect of equilibrium forces. They naively equate higher future earnings with higher future returns, neglecting the offsetting effect of endogenous price adjustments. Third, a series of experimental interventions demonstrate that these naive forecasts do not result from inattention to trading or price responses but reflect a gap in respondents' mental models -- a fundamental unfamiliarity with the concept of equilibrium.
Mamma mia! Revealing hidden heterogeneity by PCA-biplot : MPC puzzle for Italy's elderly poor
(2023)
I investigate consumption patterns in Italy and use a PCA-biplot to discover a consumption puzzle for the elderly poor. Data from the third wave (2017) of the Eurosystem’s Household Finance and Consumption Survey (HFCS) indicate that Italian poor old-aged households boast lower levels of the marginal propensity to consume (MPC) than suggested by the dominant consumption models. A customized regression analysis exhibits group differences with richer peers to be only half as large as prescribed by a traditional linear regression model. This analysis has benefited from a visualization technique for high-dimensional matrices related to the unsupervised machine learning literature. I demonstrate that PCA-biplots are a useful tool to reveal hidden relations and to help researchers to formulate simple research questions. The method is presented in detail and suggestions on incorporating it in the econometric modeling pipeline are given.
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.
Central clearing counterparties (CCPs) were established to mitigate default losses resulting from counterparty risk in derivatives markets. In a parsimonious model, we show that clearing benefits are distributed unevenly across market participants. Loss sharing rules determine who wins or loses from clearing. Current rules disproportionately benefit market participants with flat portfolios. Instead, those with directional portfolios are relatively worse off, consistent with their reluctance to voluntarily use central clearing. Alternative loss sharing rules can address cross-sectional disparities in clearing benefits. However, we show that CCPs may favor current rules to maximize fee income, with externalities on clearing participation.
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.
Life insurance convexity
(2023)
Life insurers sell savings contracts with surrender options, which allow policyholders to prematurely receive guaranteed surrender values. These surrender options move toward the money when interest rates rise. Hence, higher interest rates raise surrender rates, as we document empirically by exploiting plausibly exogenous variation in monetary policy. Using a calibrated model, we then estimate that surrender options would force insurers to sell up to 2% of their investments during an enduring interest rate rise of 25 bps per year. We show that these fire sales are fueled by surrender value guarantees and insurers’ long-term investments.