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Vehicle registrations have been shown to strongly react to tax reforms aimed at reducing CO2 emissions from passengers’ cars, but are the effects equally strong for positive and negative tax changes? The literature on asymmetric reactions to price and tax changes has documented asymmetries for everyday goods but has not yet considered durables. We leverage multiple vehicle registration tax (VRT) reforms in Norway and estimate their impact on within car-model substitutions. We estimate stronger effects for cars receiving tax cuts and rebates than for those affected by tax increases. The corresponding estimated elasticity is − 1.99 for VRT decreases and 0.77 for increases. As consumers may also substitute across car models, our estimates represent a lower bound.
The centrality of the United States in the global financial system is taken for granted, but its response to recent political and epidemiological events has suggested that China now holds a comparable position. Using minute-by-minute data from 2012 to 2020 on the financial performance of twelve country-specific exchange-traded funds, we construct daily snapshots of the global financial network and analyze them for the centrality and connectedness of each country in our sample. We find evidence that the U.S. was central to the global financial system into 2018, but that the U.S.-China trade war of 2018–2019 diminished its centrality, and the Covid-19 outbreak of 2019–2020 increased the centrality of China. These indicators may be the first signals that the global financial system is moving from a unipolar to a bipolar world.
This study explores the implications of rising markups for optimal Mirrleesian income and profit taxation. Using a stylized model with two individuals, the main forces shaping welfare-optimal policies are analytically characterized. Although a higher profit tax has redistributive benefits, it adversely affects market competition, leading to a greater equilibrium cost-of-living. Rising markups directly contribute to a decline in optimal marginal taxes on labor income. The optimal policy response to higher markups includes increasingly relying on the profit tax to fund redistribution. Declining optimal marginal income taxes assists the redistributive function of the profit tax by contributing to the expansion of the profit tax base. This response alone considerably increases the equilibrium cost-of-living. Nevertheless, a majority of the individuals become better off with the optimal policy. If it is not possible to tax profits optimally, due, for example, to profit shifting, increasing redistribution via income taxes is not optimal; every individual is worse off relative to the scenario with optimal profit taxation.
Small businesses face major challenges to becoming more innovative. These challenges are particularly prevalent in emerging economies where high uncertainties are a barrier to innovation. We know from previous studies that linkages to universities, on the one hand, and public procurement, on the other, support large and innovative firms in their efforts to become more innovative. However, we do not know whether these positive effects also hold true for small businesses. In this paper, we focus on how policy strategies reducing information, market and financial uncertainties shape small businesses’ innovation in China. Based on a sample of 926 small businesses derived from the World Bank Enterprises Survey in China (2012), we find that university-industry linkages enhance innovation, though only when it comes to minor forms of innovation. In line with the resource-based view of the firm, this effect is stronger for small businesses with higher capabilities. Moreover, we show that bidding for or delivering contracts to public sector clients has a positive effect on innovation, and in particular of major forms of innovation. In the bidding selection process, private firms and firms with higher capabilities are selected. Our findings show that both policy strategies have enhanced innovation, though with different effects on the degree of novelty. We attribute this finding to the different degrees of uncertainties they address.
The disposition effect is implicitly assumed to be constant over time. However, drivers of the disposition effect (preferences and beliefs) are rather countercyclical. We use individual investor trading data covering several boom and bust periods (2001-2015). We show that the disposition effect is countercyclical, i.e. is higher in bust than in boom periods. Our findings are driven by individuals being 25% more likely to realize gains in bust than in boom periods. These changes in investors’ selling behavior can be linked to changes in investors’ risk aversion and in their beliefs across financial market cycles.
Having a gatekeeper position in a collaborative network offers firms great potential to gain competitive advantages. However, it is not well understood what kind of collaborations are associated with such a position. Conceptually grounded in social network theory, this study draws on the resource-based view and the relational factors view to investigate which types of collaboration characterize firms that are in a gatekeeper position, which ultimately could improve firm performance in subsequent periods. The empirical analysis utilizes a unique longitudinal data set to examine dynamic network formation. We used a data crawling approach to reconstruct collaboration networks among the 500 largest companies in Germany over nine years and matched these networks with performance data. The results indicate that firms in gatekeeper positions often engage in medium-intensity collaborations and less likely weak-intensity collaborations. Strong-intensity collaborations are not related to the likelihood of being a gatekeeper. Our study further reveals that a firm's knowledge base is an important moderator and that this knowledge base can increase the benefits of having a gatekeeper position in terms of firm performance.
Smart(phone) investing? A within investor-time analysis of new technologies and trading behavior
(2021)
Using transaction-level data from two German banks, we study the effects of smartphones on investor behavior. Comparing trades by the same investor in the same month across different platforms, we find that smartphones increase purchasing of riskier and lottery-type assets and chasing past returns. After the adoption of smartphones, investors do not substitute trades across platforms and buy also riskier, lottery-type, and hot investments on other platforms. Using smartphones to trade specific assets or during specific hours contributes to explain our results. Digital nudges and the device screen size do not mechanically drive our results. Smartphone effects are not transitory.
Using the pandemic as a laboratory, we show that asset markets assign a time- varying price to firms' disaster risk exposure. In 2020 the cross-section of realized and expected stock returns reflected firms' different exposure to the pandemic, as measured by their vulnerability to social distancing. Realized and expected return differentials initially widened and then narrowed, but disaster exposure still commanded a risk premium in December 2020. When inferred from market outcomes, resilience correlates not only with social distancing, but also with cash and environmental ratings. However, vulnerability to social distancing is the only characteristic that identifies persistently scarred firms.
Expectations about economic variables vary systematically across genders. In the domain of inflation, women have persistently higher expectations than men. We argue that traditional gender roles are a significant factor in generating this gender expectations gap as they expose women and men to different economic signals in their daily lives. Using unique data on the participation of men and women in household grocery chores, their resulting exposure to price signals, and their inflation expectations, we document a tight link between the gender expectations gap and the distribution of grocery shopping duties. Because grocery prices are highly volatile, and consumers focus disproportionally on positive price changes, frequent exposure to grocery prices increases perceptions of current inflation and expectations of future inflation. The gender expectations gap is largest in households whose female heads are solely responsible for grocery shopping, whereas no gap arises in households that split grocery chores equally between men and women. Our results indicate that gender differences in inflation expectations arise due to social conditioning rather than through differences in innate abilities, skills, or preferences.
We assess the effect and the timing of the corporate arm of the ECB quantitative easing (CSPP) on corporate bond issuance. Because of several contemporaneous measures, to isolate the programme effects we rely on one key eligibility feature: the euro denomination of newly issued bonds. We find that the significant increase in bonds issuance by eligible firms is due to the CSPP and that this effect took at least six months to unfold. This result holds even when comparing firms with similar ratings, thus providing evidence that unconventional monetary policy can foster a financing diversification regardless of firms’ risk profile. We also highlight the impact of the programme on the real economic activity. The evidence suggests that while all firms increased investment in capital expenditures and intangible assets, the CSPP induced eligible firms to invest in marketable and equity securities, to repurchase their own stocks, to hold cash and to carry out short-term investment.
The authors present evidence of a new propagation mechanism for wealth inequality, based on differential responses, by education, to greater inequality at the start of economic life. The paper is motivated by a novel positive cross-country relationship between wealth inequality and perceptions of opportunity and fairness, which holds only for the more educated. Using unique administrative micro data and a quasi-field experiment of exogenous allocation of households, the authors find that exposure to a greater top 10% wealth share at the start of economic life in the country leads only the more educated placed in locations with above-median wealth mobility to attain higher wealth levels and position in the cohort-specific wealth distribution later on. Underlying this effect is greater participation in risky financial and real assets and in self-employment, with no evidence for a labor income, unemployment risk, or human capital investment channel. This differential response is robust to controlling for initial exposure to fixed or other time-varying local features, including income inequality, and consistent with self-fulfilling responses of the more educated to perceived opportunities, without evidence of imitation or learning from those at the top.
By focusing on the cost conditions at issuance, I find that not only the Covid-19 pandemic effects were different across bonds and firms at different stages, but also that the market composition was significantly affected, collapsing on investment- grade bonds, a segment in which the share of bonds eligible to the ECB corporate programmes strikingly increased from 15% to 40%. At the same time the high-yield segment shrunk to almost disappear at 4%. In addition to a market segmentation along the bond grade and the eligibility to the ECB programmes, another source of risk detected in the pricing mechanism is the weak resilience to pandemic: the premium requested is around 30 basis points and started to be priced only after the early containment actions taken by the national authorities. On the contrary, I do not find evidence supporting an increased risk for corporations headquartered in countries with a reduced fiscal space, nor the existence of a premium in favour of green bonds, which should be the backbone of a possible “green recovery”.
Relying on a perspective borrowed from monetary policy announcements and introducing an econometric twist in the traditional event study analysis, we document the existence of an .event risk transfer., namely a significant credit risk transmission from the sovereign to the corporate sector after a sovereign rating downgrade. We find that after the delivery of the downgrade, corporate CDS spreads rise by 36% per annum and there is a widespread contagion across countries, in particular among those which were most exposed to the sovereign debt crisis. This effect exists on top of the standard relation between sovereign and corporate credit risk.
India has recorded 142,186 deaths over 36 administrative regions placing India third in the world after the US and Brazil for COVID-19 deaths as of 12 December 2020. Studies indicate that south-west monsoon season plays a role in the dynamics of contagious diseases, which tend to peak post-monsoon season. Recent studies show that vitamin D and its primary source Ultraviolet-B (UVB) radiation may play a protective role in mitigating COVID-19 deaths. However, the combined roles of the monsoon season and UVB radiation in COVID-19 in India remain still unclear. In this observational study, we empirically study the respective roles of monsoon season and UVB radiation, whilst further exploring, whether the monsoon season negatively impacts the protective role of UVB radiation in COVID-19 deaths in India. We use a log-linear Mundlak model to a panel dataset of 36 administrative regions in India from 14 March 2020–19 November 2020 (n = 6751). We use the cumulative COVID-19 deaths as the dependent variable. We isolate the association of monsoon season and UVB radiation as measured by Ultraviolet Index (UVI) from other confounding time-constant and time-varying region-specific factors. After controlling for various confounding factors, we observe that a unit increase in UVI and the monsoon season are separately associated with 1.2 percentage points and 7.5 percentage points decline in growth rates of COVID-19 deaths in the long run. These associations translate into substantial relative changes. For example, a permanent unit increase of UVI is associated with a decrease of growth rates of COVID-19 deaths by 33% (= − 1.2 percentage points) However, the monsoon season, mitigates the protective role of UVI by 77% (0.92 percentage points). Our results indicate a protective role of UVB radiation in mitigating COVID-19 deaths in India. Furthermore, we find evidence that the monsoon season is associated with a significant reduction in the protective role of UVB radiation. Our study outlines the roles of the monsoon season and UVB radiation in COVID-19 in India and supports health-related policy decision making in India.
Nations are imposing unprecedented measures at a large scale to contain the spread of the COVID-19 pandemic. While recent studies show that non-pharmaceutical intervention measures such as lockdowns may have mitigated the spread of COVID-19, those measures also lead to substantial economic and social costs, and might limit exposure to ultraviolet-B radiation (UVB). Emerging observational evidence indicates the protective role of UVB and vitamin D in reducing the severity and mortality of COVID-19 deaths. This observational study empirically outlines the protective roles of lockdown and UVB exposure as measured by the ultraviolet index (UVI). Specifically, we examine whether the severity of lockdown is associated with a reduction in the protective role of UVB exposure. We use a log-linear fixed-effects model on a panel dataset of secondary data of 155 countries from 22 January 2020 until 7 October 2020 (n = 29,327). We use the cumulative number of COVID-19 deaths as the dependent variable and isolate the mitigating influence of lockdown severity on the association between UVI and growth rates of COVID-19 deaths from time-constant country-specific and time-varying country-specific potentially confounding factors. After controlling for time-constant and time-varying factors, we find that a unit increase in UVI and lockdown severity are independently associated with − 0.85 percentage points (p.p) and − 4.7 p.p decline in COVID-19 deaths growth rate, indicating their respective protective roles. The change of UVI over time is typically large (e.g., on average, UVI in New York City increases up to 6 units between January until June), indicating that the protective role of UVI might be substantial. However, the widely utilized and least severe lockdown (governmental recommendation to not leave the house) is associated with the mitigation of the protective role of UVI by 81% (0.76 p.p), which indicates a downside risk associated with its widespread use. We find that lockdown severity and UVI are independently associated with a slowdown in the daily growth rates of cumulative COVID-19 deaths. However, we find evidence that an increase in lockdown severity is associated with significant mitigation in the protective role of UVI in reducing COVID-19 deaths. Our results suggest that lockdowns in conjunction with adequate exposure to UVB radiation might have even reduced the number of COVID-19 deaths more strongly than lockdowns alone. For example, we estimate that there would be 11% fewer deaths on average with sufficient UVB exposure during the period people were recommended not to leave their house. Therefore, our study outlines the importance of considering UVB exposure, especially while implementing lockdowns, and could inspire further clinical studies that may support policy decision-making in countries imposing such measures.
Digital wealth and its necessary regulation have gained prominence in recent years. The European Commission has published several documents and policy proposals relating, directly or indirectly, to the data economy. A data economy can be defined as an ecosystem of different types of market players collaborating to ensure that data is accessible and usable in order to extract value from data through, for example, creating a variety of applications with great potential to improve daily life. The value of data can increase from EUR 257 billion (1.85 of EU Gross Domestic Product (GDP)) to EUR 643 billion by 2020 (3.17% of EU GDP), according to the EU Commission. The legal implications of the increasing value of the data economy are clear; hence the need to address the challenges presented by its legal regulation.
This paper explores entrepreneurs’ initially intended exit strategies and compares them to their final exit paths using an inductive approach that builds on the grounded theory methodology. Our data shows that initially intended and final exit strategies differ among entrepreneurs. Two groups of entrepreneurs emerged from our data. The first group comprises entrepreneurs who financed their firms through equity investors. The second group is made up of entrepreneurs who financed their businesses solely with their own equities. Our data shows that the first group originally intended a financial harvest exit strategy and settled with this harvest exit strategy. The second group initially intended a stewardship exit strategy but did not succeed. We used the theory of planned behavior and the behavioral agency model to analyze our data. By examining our results from these two theoretical perspectives, our study explains how entrepreneurs’ exit intentions lead to their actual exit strategies.
Ownership of databases: personal data protection and intellectual property rights on databases
(2021)
When we think on initiatives on access to and reuse of data, we must consider both the European Intellectual Property Law and the General Data Protection Regulation (GDPR). The first one provides a special intellectual property (IP) right – the sui generis right – for those makers that made a substantial investment when creating the database, whether it contains personal or non-personal data. That substantial investment can be made by just one person, but, in many cases, it is the result of the activities of many people and/or some undertakings processing and aggregating data. In the modern digital economy, data are being dubbed the ‘new oil’ and the sui generis right might be con- sidered a right to control any access to the database, thus having an undeniable relevance. Besides, there are still important inconsistences between IP Law and the GDPR, which must be removed by the European legislator. The genuine and free consent of the data subject for the use of his/her data must remain the first step of the legal analysis.
Commercialization of consumers’ personal data in the digital economy poses serious, both conceptual and practical, challenges to the traditional approach of European Union (EU) Consumer Law. This article argues that mass-spread, automated, algorithmic decision-making casts doubt on the foundational paradigm of EU consumer law: consent and autonomy. Moreover, it poses threats of discrimination and under- mining of consumer privacy. It is argued that the recent legislative reaction by the EU Commission, in the form of the ‘New Deal for Consumers’, was a step in the right direction, but fell short due to its continued reliance on consent, autonomy and failure to adequately protect consumers from indirect discrimination. It is posited that a focus on creating a contracting landscape where the consumer may be properly informed in material respects is required, which in turn necessitates blending the approaches of competition, consumer protection and data protection laws.
The quality of life: protecting non-personal interests and non-personal data in the age of big data
(2021)
Under the current legal paradigm, the rights to privacy and data protection provide natural persons with subjective rights to protect their private interests, such as related to human dignity, individual autonomy and personal freedom. In principle, when data processing is based on non-personal or aggregated data or when such data pro- cesses have an impact on societal, rather than individual interests, citizens cannot rely on these rights. Although this legal paradigm has worked well for decades, it is increasingly put under pressure because Big Data processes are typically based indis- criminate rather than targeted data collection, because the high volumes of data are processed on an aggregated rather than a personal level and because the policies and decisions based on the statistical correlations found through algorithmic analytics are mostly addressed at large groups or society as a whole rather than specific individuals. This means that large parts of the data-driven environment are currently left unregu- lated and that individuals are often unable to rely on their fundamental rights when addressing the more systemic effects of Big Data processes. This article will discuss how this tension might be relieved by turning to the notion ‘quality of life’, which has the potential of becoming the new standard for the European Court of Human Rights (ECtHR) when dealing with privacy related cases.
The health and genetic data of deceased people are a particularly important asset in the field of biomedical research. However, in practice, using them is compli- cated, as the legal framework that should regulate their use has not been fully developed yet. The General Data Protection Regulation (GDPR) is not applicable to such data and the Member States have not been able to agree on an alternative regulation. Recently, normative models have been proposed in an attempt to face this issue. The most well- known of these is posthumous medical data donation (PMDD). This proposal supports an opt-in donation system of health data for research purposes. In this article, we argue that PMDD is not a useful model for addressing the issue at hand, as it does not consider that some of these data (the genetic data) may be the personal data of the living relatives of the deceased. Furthermore, we find the reasons supporting an opt-in model less convincing than those that vouch for alternative systems. Indeed, we propose a normative framework that is based on the opt-out system for non-personal data combined with the application of the GDPR to the relatives’ personal data.
Tail-correlation matrices are an important tool for aggregating risk measurements across risk categories, asset classes and/or business segments. This paper demonstrates that traditional tail-correlation matrices—which are conventionally assumed to have ones on the diagonal—can lead to substantial biases of the aggregate risk measurement’s sensitivities with respect to risk exposures. Due to these biases, decision-makers receive an odd view of the effects of portfolio changes and may be unable to identify the optimal portfolio from a risk-return perspective. To overcome these issues, we introduce the “sensitivity-implied tail-correlation matrix”. The proposed tail-correlation matrix allows for a simple deterministic risk aggregation approach which reasonably approximates the true aggregate risk measurement according to the complete multivariate risk distribution. Numerical examples demonstrate that our approach is a better basis for portfolio optimization than the Value-at-Risk implied tail-correlation matrix, especially if the calibration portfolio (or current portfolio) deviates from the optimal portfolio.
Nowadays, digitalization has an immense impact on the landscape of jobs. This technological revolution creates new industries and professions, promises greater efficiency and improves the quality of working life. However, emerging technologies such as robotics and artificial intelligence (AI) are reducing human intervention, thus advancing automation and eliminating thousands of jobs and whole occupational images. To prepare employees for the changing demands of work, adequate and timely training of the workforce and real-time support of workers in new positions is necessary. Therefore, it is investigated whether user-oriented technologies, such as augmented reality (AR) and virtual reality (VR) can be applied “on-the-job” for such training and support—also known as intelligence augmentation (IA). To address this problem, this work synthesizes results of a systematic literature review as well as a practically oriented search on augmented reality and virtual reality use cases within the IA context. A total of 150 papers and use cases are analyzed to identify suitable areas of application in which it is possible to enhance employees' capabilities. The results of both, theoretical and practical work, show that VR is primarily used to train employees without prior knowledge, whereas AR is used to expand the scope of competence of individuals in their field of expertise while on the job. Based on these results, a framework is derived which provides practitioners with guidelines as to how AR or VR can support workers at their job so that they can keep up with anticipated skill demands. Furthermore, it shows for which application areas AR or VR can provide workers with sufficient training to learn new job tasks. By that, this research provides practical recommendations in order to accompany the imminent distortions caused by AI and similar technologies and to alleviate associated negative effects on the German labor market.
The so-called Troika, consisting of the EU-Commission, the European Central Bank (ECB) and the International Monetary Fund (IMF), was supposed to support the member states of the euro area which had been hit hard by a sovereign debt crisis. For that purpose, economic adjustment programs were drafted and monitored in order to prevent the break-up of the euro area and sovereign defaults. The cooperation of these institutions, which was born out of necessity, has been partly successful, but has also created persistent problems. With the further increase of public debt, especially in France and Italy, the danger of a renewed crisis in the euro area was growing. The European Stability Mechanism (ESM) together with the European Commission will replace the Troika in the future, following decisions of the EU Summit of December 2018. It shall play the role of a European Monetary Fund in the event of a crisis. The IMF, on the other side, will no longer play an active role in solving sovereign debt crises in the euro area. The current course is, however, inadequate to tackle the core problems of the euro zone and to avoid future crises, which are mainly structural in nature and due to escalating public debt and lack of international competitiveness of some member countries. The current Corona crisis will aggravate the institutional problems. It has led to a common European fiscal response ("Next Generation EU"). This rescue and recovery program will not be financed by ESM resources and will not be monitored by the ESM. One important novelty of this package is that it involves the issuance of substantial common European debt.
Broad, long-term financial and economic datasets are a scarce resource, in particular in the European context. In this paper, we present an approach for an extensible, i.e. adaptable to future changes in technologies and sources, data model that may constitute a basis for digitized and structured long- term, historical datasets. The data model covers specific peculiarities of historical financial and economic data and is flexible enough to reach out for data of different types (quantitative as well as qualitative) from different historical sources, hence achieving extensibility. Furthermore, based on historical German company and stock market data, we discuss a relational implementation of this approach.
We focus on the role of social media as a high-frequency, unfiltered mass information transmission channel and how its use for government communication affects the aggregate stock markets. To measure this effect, we concentrate on one of the most prominent Twitter users, the 45th President of the United States, Donald J. Trump. We analyze around 1,400 of his tweets related to the US economy and classify them by topic and textual sentiment using machine learning algorithms. We investigate whether the tweets contain relevant information for financial markets, i.e. whether they affect market returns, volatility, and trading volumes. Using high-frequency data, we find that Trump’s tweets are most often a reaction to pre-existing market trends and therefore do not provide material new information that would influence prices or trading. We show that past market information can help predict Trump’s decision to tweet about the economy.
WiWi news [1/2021]
(2021)
Using loan-level data from Germany, we investigate how the introduction of model-based capital regulation affected banks’ ability to absorb shocks. The objective of this regulation was to enhance financial stability by making capital requirements responsive to asset risk. Our evidence suggests that banks ‘optimized’ model-based regulation to lower their capital requirements. Banks systematically underreported risk, with under reporting being more pronounced for banks with higher gains from it. Moreover, large banks benefitted from the regulation at the expense of smaller banks. Overall, our results suggest that sophisticated rules may have undesired effects if strategic misbehavior is difficult to detect.
This paper aims at an improved understanding of the relationship between monetary policy and racial inequality. We investigate the distributional effects of monetary policy in a unified framework, linking monetary policy shocks both to earnings and wealth differentials between black and white households. Specifically, we show that, although a more accommodative monetary policy increases employment of black households more than white households, the overall effects are small. At the same time, an accommodative monetary policy shock exacerbates the wealth difference between black and white households, because black households own less financial assets that appreciate in value. Over multi-year time horizons, the employment effects are substantially smaller than the countervailing portfolio effects. We conclude that there is little reason to think that accommodative monetary policy plays a significant role in reducing racial inequities in the way often discussed. On the contrary, it may well accentuate inequalities for extended periods.
The FOMC risk shift
(2021)
We identify a component of monetary policy news that is extracted from high-frequency changes in risky asset prices. These surprises, which we call “risk shifts”, are uncorrelated, and therefore complementary, to risk-free rate surprises. We show that (i) risk shifts capture the lion’s share of stock price movements around FOMC announcements; (ii) that they are accompanied by significant investor fund flows, suggesting that investors react heterogeneously to monetary policy news; and (iii) that price pressure amplifies the stock market response to monetary policy news. Our results imply that central bank information effects are overshadowed by short-term dynamics stemming from investor rebalancing activities and are likely to be more difficult to identify than previously thought.
“Right to Buy” (RTB), a large-scale natural experiment by which incumbent tenants in public housing could buy properties at heavily-subsidised prices, increased the UK homeownership rate by over 10 percentage points between 1980 and the late 1990s. This paper studies its impact on crime, showing that RTB generated significant reductions in property and violent crime that persist up to today. The behavioural changes of incumbent tenants and the renovation of public properties were the main drivers of the crime reduction. This is evidence of a novel means by which subsidised homeownership and housing policy may contribute to reduce criminality.
Although the elderly are more vulnerable to COVID-19, the empirical evidence suggests that they do not behave more cautiously in the pandemic than younger individuals. This theoretical model argues that some individuals might not comply with the COVID-19 measures to reassure themselves that they are not vulnerable, and that the incentives for such self-signaling can be stronger for the elderly. The results suggest that communication strategies emphasizing the dangers of COVID-19 could backfire and reduce compliance among the elderly.
How people form beliefs is crucial for understanding decision-making un- der uncertainty. This is particularly true in a situation such as a pandemic, where beliefs will affect behaviors that impact public health as well as the aggregate economy. We conduct two survey experiments to shed light on potential biases in belief formation, focusing in particular on the tone of information people choose to consume and how they incorporate this information into their beliefs. In the first experiment, people express their preferences over pandemic-related articles with optimistic and pessimistic headlines, and are then randomly shown one of the articles. We find that respondents with more pessimistic prior beliefs about the pandemic are substantially more likely to prefer pessimistic articles, which we interpret as evidence of confirmation bias. In line with this, respondents assigned to the less preferred article rate it as less reliable and informative (relative to those who prefer it); they also discount information from the article when it is less preferred. We further find that these motivated beliefs end up impacting incentivized behavior. In a second experiment, we study how partisan views interact with information selection and processing. We find strong evidence of source dependence: revealing the news source further distorts information acquisition and processing, eliminating the role of prior beliefs in article choice.
Several recent studies have expressed concern that the Haar prior typically imposed in estimating sign-identi.ed VAR models may be unintentionally informative about the implied prior for the structural impulse responses. This question is indeed important, but we show that the tools that have been used in the literature to illustrate this potential problem are invalid. Speci.cally, we show that it does not make sense from a Bayesian point of view to characterize the impulse response prior based on the distribution of the impulse responses conditional on the maximum likelihood estimator of the reduced-form parameters, since the the prior does not, in general, depend on the data. We illustrate that this approach tends to produce highly misleading estimates of the impulse response priors. We formally derive the correct impulse response prior distribution and show that there is no evidence that typical sign-identi.ed VAR models estimated using conventional priors tend to imply unintentionally informative priors for the impulse response vector or that the corre- sponding posterior is dominated by the prior. Our evidence suggests that concerns about the Haar prior for the rotation matrix have been greatly overstated and that alternative estimation methods are not required in typical applications. Finally, we demonstrate that the alternative Bayesian approach to estimating sign-identi.ed VAR models proposed by Baumeister and Hamilton (2015) su¤ers from exactly the same conceptual shortcoming as the conventional approach. We illustrate that this alternative approach may imply highly economically implausible impulse response priors.
Since the 1970s, exports and imports of manufactured goods have been the engine of international trade and much of that trade relies on container shipping. This paper introduces a new monthly index of the volume of container trade to and from North America. Incorporating this index into a structural macroeconomic VAR model facilitates the identification of shocks to domestic U.S. demand as well as foreign demand for U.S. manufactured goods. We show that, unlike in the Great Recession, the primary determinant of the U.S. economic contraction in early 2020 was a sharp drop in domestic demand. Although detrended data for personal consumption expenditures and manufacturing output suggest that the U.S. economy has recovered to near 90% of pre-pandemic levels as of March 2021, our structural VAR model shows that the component of manufacturing output driven by domestic demand had only recovered to 59% of pre-pandemic levels and that of real personal consumption only to 76%. The difference is mainly accounted for by unexpected reductions in frictions in the container shipping market.
We raise some critical points against a naïve interpretation of “green finance” products and strategies. These critical insights are the background against which we take a closer look at instruments and policies that might allow green finance to become more impactful. In particular, we focus on the role of a taxonomy and investor activism. We also describe the interaction of government policies with green finance practice – an aspect, which has been mostly neglected in policy debates but needs to be taken into account. Finally, the special case of green government bonds is discussed.
The authors embed human capital-based endogenous growth into a New-Keynesian model with search and matching frictions in the labor market and skill obsolescence from long-term unemployment. The model can account for key features of the Great Recession: a decline in productivity growth, the relative stability of inflation despite a pronounced fall in output (the "missing disinflation puzzle"), and a permanent gap between output and the pre-crisis trend output.
In the model, lower aggregate demand raises unemployment and the training costs associated with skill obsolescence. Lower employment hinders learning-by-doing, which slows down human capital accumulation, feeding back into even fewer vacancies than justified by the demand shock alone. These feedback channels mitigate the disinflationary effect of the demand shock while amplifying its contractionary effect on output. The temporary growth slowdown translates into output hysteresis (permanently lower output and labor productivity).
Central banks sometimes evaluate their own policies. To assess the inherent conflict of interest, the authors compare the research findings of central bank researchers and academic economists regarding the macroeconomic effects of quantitative easing (QE). They find that central bank papers report larger effects of QE on output and inflation. Central bankers are also more likely to report significant effects of QE on output and to use more positive language in the abstract. Central bankers who report larger QE effects on output experience more favorable career outcomes. A survey of central banks reveals substantial involvement of bank management in research production.
Despite the increasing use of cashless payment instruments, the notion that cash loses importance over time can be unambiguously refuted. In contrast, the authors show that cash demand increased steeply over the past 30 years. This is not only true on a global scale, but also for the most important currencies in advanced countries (USD, EUR, CHF, GBP and JPY). In this paper, they focus especially on the role of different crises (technological crises, financial market crises, natural disasters) and analyse the demand for small and large banknote denominations since the 1990s in an international perspective. It is evident that cash demand always increases in times of crises, independent of the nature of the crisis itself. However, largely unaffected from crises we observe a trend increase in global cash aligned with a shift from transaction balances towards more hoarding, especially in the form of large denomination banknotes.
Occasionally binding constraints have become an important part of economic modelling, especially since western central banks see themselves (again) constraint by the so-called zero lower bound (ZLB) of the nominal interest rate. A binding ZLB constraint poses a major problem for a quantitative-structural analysis: Linear solution methods do no work in the presence of a non-linearity such as the ZLB and existing alternatives tend to be computationally demanding. The urge to study macroeconomic questions related to the Great Recession and the Covid-19 crisis in a quantitative-structural framework requires algorithms that are not only accurate, but that are also robust, fast, and computationally efficient.
A particularly important application where efficient and fast methods for occasionally binding constraints (OBCs) are needed is the Bayesian estimation of macroeconomic models. This paper shows that a linear dynamic rational expectations system with OBCs, depending on the expected duration of the constraint, can be represented in closed form. Combined with a set of simple equilibrium conditions, this can be exploited to avoid matrix inversions and simulations at runtime for signifcant gains in computational speed.
High-frequency changes in interest rates around FOMC announcements are a standard method of measuring monetary policy shocks. However, some recent studies have documented puzzling effects of these shocks on private-sector forecasts of GDP, unemployment, or inflation that are opposite in sign to what standard macroeconomic models would predict. This evidence has been viewed as supportive of a „Fed information effect“ channel of monetary policy, whereby an FOMC tightening (easing) communicates that the economy is stronger (weaker) than the public had expected.
The authors show that these empirical results are also consistent with a „Fed response to news“ channel, in which incoming, publicly available economic news causes both the Fed to change monetary policy and the private sector to revise its forecasts. They provide substantial new evidence that distinguishes between these two channels and strongly favors the latter; for example, regressions that include the previously omitted public macroeconomic news, high-frequency stock market responses to Fed announcements, and a new survey that they conduct of individual Blue Chip forecasters all indicate that the Fed and private sector are simply responding to the same public news, and that there is little if any role for a „Fed information effect“.
The authors examine the effectiveness of labor cost reductions as a means to stimulate economic activity and assesses the differences which may occur with the prevailing exchange rate regime. They develop a medium-scale three-region DSGE model and show that the impact of a cut in the employers’ social security contributions rate does not vary significantly under different exchange rate regimes. They find that both the interest rate and the exchange rate channel matters. Furthermore, the measure appears to be effective even if it comes along with a consumption tax increase to preserve long-term fiscal sustainability.
Finally, they assess whether obtained theoretical results hold up empirically by applying the local projection method. Regression results suggest that changes in employers’ social security contributions rates have statistically significant real effects – a one percentage point reduction leads to an average cumulative rise in output of around 1.3 percent in the medium term. Moreover, the outcome does not differ significantly across the different exchange rate regimes.
The recently observed disconnect between inflation and economic activity can be explained by the interplay between the zero lower bound (ZLB) and the costs of external financing. In normal times, credit spreads and the nominal interest rate balance out; factor costs dominate firms' marginal costs. When nominal rates are constrained, larger spreads can more than offset the effect of lower factor costs and induce only moderate inflation responses. The Phillips curve is hence flat at the ZLB, but features a positive slope in normal times and thus a hockey stick shape. Via this mechanism, forward guidance may induce deflationary effects.
Can boundedly rational agents survive competition with fully rational agents? The authors develop a highly nonlinear heterogeneous agents model with rational forward looking versus boundedly rational backward looking agents and evolving market shares depending on their relative performance. Their novel numerical solution method detects equilibrium paths characterized by complex bubble and crash dynamics. Boundedly rational trend-extrapolators amplify small deviations from fundamentals, while rational agents anticipate market crashes after large bubbles and drive prices back close to fundamental value. Overall rational and non-rational beliefs co-evolve over time, with time-varying impact, and their interaction produces complex endogenous bubble and crashes, without any exogenous shocks.
On the accuracy of linear DSGE solution methods and the consequences for log-normal asset pricing
(2021)
This paper demonstrates a failure of standard, generalized Schur (or QZ) decomposition based solutions methods for linear dynamic stochastic general equilibrium (DSGE) models when there is insufficient eigenvalue separation about the unit circle. The significance of this is demonstrated in a simple production-based asset pricing model with external habit formation. While the exact solution afforded by the simplicity of the model matches post-war US consumption growth and the equity premium, QZ-based numerical solutions miss the later by many annualized percentage points.
Macroeconomic stabilisation and monetary policy effectiveness in a low-interest-rate environment
(2021)
The secular decline in the equilibrium real interest rate observed over the past decades has materially limited the room for policy-rate reductions in recessions, and has led to a marked increase in the incidence of episodes where policy rates are likely to be at, or near, the effective lower bound on nominal interest rates. Using the ECB's New Area-Wide Model, we show that, if unaddressed, the effective lower bound can cause substantial costs in terms of worsened macroeconomic performance, as rejected in negative biases in inflation and economic activity, as well as heightened macroeconomic volatility. These costs can be mitigated by the use of nonstandard instruments, notably the joint use of interest-rate forward guidance and large-scale asset purchases. When considering alternatives to inflation targeting, we find that make-up strategies such as price-level targeting and average-inflation targeting can, if they are well-understood by the private sector, largely undo the negative biases and heightened volatility induced by the effective lower bound.
Using the exact wording of the ECB’s definition of price-stability, we started a representative online survey of German citizens in January 2019 that is designed to measure long-term inflation expectations and the credibility of the inflation target. Our results indicate that credibility has decreased in our sample period, particularly in the course of the deep recession implied by the COVID-19 pandemic. Interestingly, even though inflation rates in Germany have been clearly below 2% for several years, credibility has declined mainly because Germans increasingly expect that inflation will be much higher than 2% over the medium term. We investigate how inflation expectations and the impact of the pandemic depend on personal characteristics including age, gender, education, income, and political attitude.
The “European Green Deal” stipulates that the EU will become climate-neutral by 2050. This transformation requires enormous investments in all major sectors including energy, mobility, industrial manufacturing, real estate and farming. Although the EU Commission has announced that a total of EUR 1 trillion will be invested into the green transformation of the European economy over the next ten years, the majority of the investments must be financed by the private sector. Alongside many factors affecting a successful implementation of the Green Deal, a regulatory framework for the financial industry has to be established to facilitate the financing of sustainable investments. To that end, the European Sustainable Finance Strategy lays the foundation for a complex set of different measures that have been launched in recent years. This article provides a comprehensive overview of key regulatory initiatives such as the taxonomy regulation, the disclosure frameworks for both corporates and financial institutions and other aspects of financial market regulation that have already significantly improved the regulatory framework for sustainable finance. Nevertheless, some additional instruments could be considered, such as a reform of top management remuneration or the provision of tax incentives for green investments in the real economy, and these are briefly discussed.
The crisis management and deposit insurance (CMDI) framework in the euro area requires a reset. Although its policy objectives remain valid, the means of achieving them do not. As the euro area comes the end of the long transition period taken to implement the BRRD/SRMR, it should take the opportunity to reset expectations about resolution.
Above all, resolution should be for the many, not just the few. There should be a single presumptive path for dealing with failed banks: the use of bail-in to facilitate orderly liquidation under a solvent-wind down strategy. This will protect deposits and set the stage – together with the backstop that the European Stability Mechanism provides to the Single Resolution Fund (SRF) -- for the transformation of the SRF into the Single Deposit Guarantee Scheme (SDGS). To avoid forbearance, responsibility for emergency liquidity assistance (ELA) should rest, not with national central banks, but with the ECB as a single lender of last resort. Finally, national deposit guarantee schemes should function as institutional protection schemes and become investors of last resort in their member banks. Together, these measures would complete Banking Union, promote market discipline, avoid imposing additional burdens on taxpayers, help untie the doom loop between weak banks and weak governments, strengthen the euro and enhance financial stability.
This in-depth analysis provides evidence on differences in the practice of supervising large banks in the UK and in the euro area. It identifies the diverging institutional architecture (partially supranationalised vs. national oversight) as a pivotal determinant for a higher effectiveness of supervisory decision making in the UK. The ECB is likely to take a more stringent stance in prudential supervision than UK authorities. The setting of risk weights and the design of macroprudential stress test scenarios document this hypothesis. This document was provided by the Economic Governance Support Unit at the request of the ECON Committee.
This document was requested by the European Parliament's Committee on Economic and Monetary Affairs. It was originally published on the European Parliament’s webpage: www.europarl.europa.eu/RegData/etudes/IDAN/2021/689443/IPOL_IDA(2021)689443_EN.pdf
This in-depth analysis proposes ways to retract from supervisory COVID-19 support measures without perils for financial stability. It simulates the likely impact of the corona crisis on euro area banks’ capital and predicts a significant capital shortfall. We recommend to end accounting practices that conceal loan losses and sustain capital relief measures. Our in-depth analysis also proposes how to address the impending capital shortfall in resolution/liquidation and a supranational recapitalisation.
Rising temperatures, falling ratings: the effect of climate change on sovereign creditworthiness
(2021)
How will a changing climate impact the creditworthiness of governments over the very long term? Financial markets need credible, digestible information on how climate change translates into material risks. To bridge the gap between climate science and real-world financial indicators, the authors simulate the effect of climate change on sovereign credit ratings for 108 countries, creating the world’s first climate-adjusted sovereign credit rating. The study offers a first methodological approach to extend the long-term rating to an ultra-long-term reality, aiming at long-term investors, but also regulators and rating agencies.
Central banks normally accept debt of their own governments as collateral in liquidity operations without reservations. This gives rise to a valuable liquidity premium that reduces the cost of government finance. The ECB is an interesting exception in this respect. It relies on external assessments of the creditworthiness of its member states, such as credit ratings, to determine eligibility and the haircut it imposes on such debt. The authors show how such features in a central bank’s collateral framework can give rise to cliff effects and multiple equilibria in bond yields and increase the vulnerability of governments to external shocks. This can potentially induce sovereign debt crises and defaults that would not otherwise arise.
Die Distributed Ledger- bzw. Blockchain-Technologie führt zu einer zunehmenden Dezentralisierung von Finanzdienstleistungen („Decentralised Finance“), die weitgehend ohne die Einschaltung von Finanzintermediären angeboten werden können. Dazu trägt wesentlich die sog. „Tokenisierung“ von Vermögensgegenständen, Zahlungsmitteln und Rechten bei, die verschlüsselt als „Kryptowerte“ in verteilten Transaktionsregistern digital abgebildet werden können. Der vorliegende Beitrag erläutert die Grundlagen und Anwendungsfelder dezentraler Finanzdienstleistungen mit Kryptowerten, die mittelfristig die gesamte Architektur des Finanzsektors verändern könnten. Dieser Trend betrifft längst nicht nur die kontrovers diskutierten Zahlungsverkehrssysteme mit Kryptowährungen wie dem Bitcoin, sondern Handelsplattformen, Kapitalmärkte oder Unternehmensfinanzierungen. Es bildet sich ein rasch wachsendes Ökosystem aus Startups, Technologieunternehmen und etablierten Finanzdienstleistern, für das jedoch noch ein verlässlicher regulatorischer Rahmen fehlt. Die derzeit auf europäischer Ebene diskutierte Initiative „MiCA (Markets in Crypto Assets)“ geht in die richtige Richtung, sollte aber im Interesse der Wettbewerbsfähigkeit des europäischen Finanzsektors zeitnah umgesetzt werden.
We raise some critical points against a naïve interpretation of “green finance” products and strategies. These critical insights are the background against which we take a closer look at instruments and policies that might allow green finance to become more impactful. In particular, we focus on the role of a taxonomy and investor activism. We also describe the interaction of government policies with green finance practice – an aspect, which has been mostly neglected in policy debates but needs to be taken into account. Finally, the special case of green government bonds is discussed.
We show that financial advisors recommend more costly products to female clients, based on minutes from about 27,000 real-world advisory meetings and client portfolio data. Funds recommended to women have higher expense ratios controlling for risk, and women less often receive rebates on upfront fees for any given fund. We develop a model relating these findings to client stereotyping, and empirically verify an additional prediction: Women (but not men) with higher financial aptitude reject recommendations more frequently. Women state a preference for delegating financial decisions, but appear unaware of associated higher costs. Evidence of stereotyping is stronger for male advisors.
The pricing of an ambiguous asset, whose cash flow stream is uncertain, may be affected by three factors: the belief regarding the realization likelihood of cash flows, the subjective attitude towards risk, and the attitude towards ambiguity. While previous literature looks at the total price discount under ambiguity, this paper investigates with laboratory experiments how much effect each factor can induce. We apply both non-parametric and parametric methods to cleanly separate the belief effects, the risk premiums, and the ambiguity premiums from each other. Both methods lead to similar results: Overall, subjects have substantial ambiguity aversion, and ambiguity premiums account for the largest price deviation component when the degree of ambiguity is high. As information accumulates, ambiguity premiums decrease. We also find that beliefs do influence prices under ambiguity. This is not because beliefs are biased towards either good or bad scenarios per se, but because subjects display sticky belief updating as new information becomes available. The clear separation performed in this paper between belief and attitude also enables a more accurate estimation of the parameter of ambiguity aversion compared to previous studies, since the effect of beliefs is partialled out. Overall, we find empirically that both factors, belief and attitude towards ambiguity, are important factors in pricing under ambiguity.
The salience of ESG ratings for stock pricing: evidence from (potentially) confused investors
(2021)
We exploit the a modification to Sustainanlytics’ environmental, social, and governance (ESG) rating methodology, which is subsequently adopted by Morningstar, to study whether ESG ratings are salient for stock pricing. We show that the inversion of the rating scale but not new information leads some investors to make incorrect assessments about the meaning of the change in ESG ratings. They buy (sell) stocks they misconceive as ESG upgraded (downgraded) even when the opposite is true. This trading behavior exerts transitory price pressure on affected stocks. Our paper highlights the importance of ESG ratings for investors and consequently for asset prices.
We conducted a large-scale household survey in November 2020 to study how altering the time frame of a message (temporal framing) regarding an imminent positive income shock affects consumption plans. The income shock derives from the abolishment of the German solidarity surcharge on personal income taxes, effective in January 2021. We randomize across survey participants whether their extra disposable income is presented in Euros per month, Euros per year, or Euros per ten year-period. Our main findings are as follows: In General, we find our respondents’ intended Marginal Propensity to Consume (MPC) is 28.2%. Across all three treatments, the MPC is a positive function of age and being female while it is a negative function of the income increase’s size, self- control, and being unemployed. Temporal framing effects are statistically and economically highly significant as we find the monthly treatment groups’ average MPC 5.6 and 8.7 percentage points higher compared to the yearly and 10-yearly treatment groups. We will be able to analyze the real consumption behavior of households throughout 2021 based on re-surveying the participants as well as by using transaction-based bank data.
Nach der Bundestagswahl am 26. September 2021 wird sich die künftige Bundesregierung mit einer Reihe drängender Herausforderungen befassen müssen. Aus Sicht des Leibniz-Instituts für Finanzmarktforschung SAFE haben die folgenden, miteinander verbundenen Einzelpunkte dabei Priorität:
1. Schaffung eines ordnungspolitischen Pakets zur Sicherung globaler Gemeinschaftsgüter, wie etwa des Klimas
2. Initiative zum Aufbau notwendiger Datensätze und Standards für eine zielgenaue Nachhaltigkeitsgestaltung an den Finanzmärkten
3. regulatorischer Fahrplan zur Erfassung, Ermöglichung und Einhegung einer digitalen Transformation des Finanzsystems
4. Vollendung der Bankenunion, insbesondere durch einen „europäischen Schlussstein“: der Schaffung einer einheitlichen Aufsicht und Letztabsicherung
5. Durchbrechung des „Doom-Loop“ zwischen Staaten und Banken in Europa, insbesondere durch Begrenzung des Umfangs, in dem eigene Staatsanleihen im Portfolio von Banken liegen dürfen
6. ernsthafter Versuch zur Schaffung eines einheitlichen und integren europäischen Kapitalmarkts mit einer Aufsicht nach US-Vorbild
7. Banken- und Kapitalmarktunion als wesentliche Bausteine für eine grundlegende Reform der Altersversorgung mit mehr Teilhabe aller Bürger:innen an der Leistungsentwicklung der Volkswirtschaft
This policy white paper shows, using data on European Commission (EC) lobby meetings, that financial institutions and finance trade associations have substantial access to EC policymakers. While lobbying could transfer policy-relevant information and expertise to policymakers, it could also result in the capture of policymakers by the industry, which could harm consumers and taxpayers. How could policymakers prevent regulatory capture, but retain the benefits of the sector expertise in policy decisions? Awareness of regulatory capture by policymakers is one of the most important remedies. This paper provides an overview of the origins of the regulatory capture theory and recent academic evidence. The paper shows that regulatory capture could emerge in a variety of institutions and policy areas but is not ubiquitous and depends on the incentives of policymakers and the policy environment. Subsequently, the paper discusses various measures to prevent regulatory capture, such as more transparency, diverse expert groups, and cooling-off periods.
With the second wave of the Covid-19 pandemic in full swing, banks face a challenging environment. They will need to address disappointing results and adverse balance sheet restatements, the intensity of which depends on the evolution of the euro area economies. At the same time, vulnerable banks reinforce real economy deficiencies. The contribution of this paper is to provide a comparative assessment of the various policy responses to address a looming banking crisis. Such a crisis will fully materialize when non-performing assets drag down banks simultaneously, raising the specter of a full-blown systemic crisis. The policy responses available range from forbearance, recapitalization (with public or private resources), asset separation (bad banks, at national or EU level), to debt conversion schemes. We evaluate these responses according to a set of five criteria that define the efficacy of each. These responses are not mutually exclusive, in practice, as they have never been. They may also go hand in hand with other restructuring initiatives, including potential consolidation in the banking sector. Although we do not make a specific recommendation, we provide a framework for policymakers to guide them in their decision making.
We study risk taking in a panel of subjects in Wuhan, China - before, during the COVID-19 crisis, and after the country reopened. Subjects in our sample traveled for semester break in January, generating variation in exposure to the virus and quarantine in Wuhan. Higher exposure leads subjects to reduce planned risk taking, risky investments, and optimism. Our findings help unify existing studies by showing that aggregate shocks affect general preferences for risk and economic expectations, while heterogeneity in experience further affect risk taking through beliefs about individuals’ own outcomes such as luck and sense of control.
JEL Classification: G50, G51, G11, D14, G41
In this paper we put forward a legal argument in favour of granting more independence to BaFin, the German securities market supervisor. Following the Wirecard scandal, our reform proposal aims at strengthening the impartiality and credibility of the German supervisor and, as a consequence, at restoring capital market integrity. In order to achieve the necessary degree of democratic legitimacy for giving BaFin more independence and disassociating it from the Ministry of Finance, the paper sets out the necessary steps for a legal reform that creates accountability of BaFin vis-à-vis the Parliament, subjecting it to strict disclosure and reporting obligations.
Managed portfolios that exploit positive first-order autocorrelation in monthly excess returns of equity factor portfolios produce large alphas and gains in Sharpe ratios. We document this finding for factor portfolios formed on the broad market, size, value, momentum, investment, prof- itability, and volatility. The value-added induced by factor management via short-term momentum is a robust empirical phenomenon that survives transaction costs and carries over to multi-factor portfolios. The novel strategy established in this work compares favorably to well-known timing strategies that employ e.g. factor volatility or factor valuation. For the majority of factors, our strategies appear successful especially in recessions and times of crisis.
Climate change is one of the highest-ranking issues on the political and social agenda. Vulnerabilities of the world ecosystem laid bare by the COVID-19 pandemic and the potential damage for the human and business life made the need for urgent action clear once again. Corporations are one of the main actors that will play a major role in the decarbonisation of the economy. They need to put forward a net zero strategy and targets, transitioning to net-zero by 2050. Yet, an important but rather overlooked stakeholder group in the sustainability debates can pose a significant stumbling block in this transition: employees. Although climate action has huge benefits by ameliorating adverse environmental events and is expected to have overall positive impact on employment, net zero transition in companies, especially in certain sectors and regions, will cause substantial adverse employment effects for the workforce. This has the potential to slow down or even derail the necessary climate action in companies. In this regard, just transition is a promising concept, which calls for a swift and decisive climate action in corporations while taking account of and mitigating adverse effects for their workforce. If well implemented, it can accelerate net zero transition in companies. This potential clash of environmental (E) and social (S) aspects of ESG agenda, materialised in the companies’ net zero transition, and its potential remedy, just transition, have important implications for corporate governance and finance, especially for directors’ duties & executive remuneration, sustainability disclosures, institutional investors’ engagement and green finance.
This paper examines how the transmission of government portfolio risk arising from maturity operations depends on the stance of monetary/fiscal policy. Accounting for risk premia in the fiscal theory allows the government portfolio to affect the expected inflation, even in a frictionless economy. The effects of maturity rebalancing on expected inflation in the fiscal theory directly depend on the conditional nominal term premium, giving rise to an optimal debt maturity policy that is state dependent. In a calibrated macro-finance model, we demonstrate that maturity operations have sizable effects on expected inflation and output through our novel risk transmission mechanism.
This paper sets up an experimental asset market in the laboratory to investigate the effects of ambiguity on price formation and trading behavior in financial markets. The obtained trading data is used to analyze the effect of ambiguity on various market outcomes (the price level, volatility, trading activity, market liquidity, and the degree of speculative trading) and to test the quality of popular empirical market-based measures for the degree of ambiguity. We find that ambiguity decreases market prices and trading activity; ambiguity leads to lower market liquidity through wider bid-ask spreads; and ambiguity leads to less speculative trading. We also find that popular market-based measures of ambiguity used in the empirical literature do not seem to correctly capture the true degree of ambiguity.
Analysing causality among oil prices and, in general, among financial and economic variables is of central relevance in applied economics studies. The recent contribution of Lu et al. (2014) proposes a novel test for causality— the DCC-MGARCH Hong test. We show that the critical values of the test statistic must be evaluated through simulations, thereby challenging the evidence in papers adopting the DCC-MGARCH Hong test. We also note that rolling Hong tests represent a more viable solution in the presence of short-lived causality periods.
We show that the COVID-19 pandemic triggered a surge in the elasticity of non-financial corporate to sovereign credit default swaps in core EU countries, characterized by strong fiscal capacity. For peripheral countries with lower budgetary slackness, the pandemic had essentially no impact on such elasticity. This evidence is consistent with the disaster-induced repricing of government support, which we model through a rare-disaster asset pricing framework with bailout guarantees and defaultable public debt. The model implies that risk-adjusted guarantees in the core were 2.6 times those in the periphery, suggesting that fiscal capacity buffers provide relief to firms’ financing costs.
This paper studies the consumption response to an increase in the domestic value of foreign currency household debt during a large depreciation. We use detailed consumption survey data that follows households for four years around Hungary’s 2008 currency crisis. We find that, relative to similar local currency debtors, foreign currency debtors reduce consumption approximately one-for-one with increased debt service, suggesting a role for liquidity constraints. We document a variety of margins of adjustment to the shock. Foreign currency debtors reduce both the quantity and quality of expenditures, consistent with nonhomothetic preferences and “flight from quality.” We find no effect on overall household labor supply, consistent with a weak wealth effect on labor supply. However, a small subset of households adjusts labor supply toward foreign income streams. Affected households also boost home pro- duction, suggesting a shift in consumption from money-intensive to time-intensive goods.
We analyze the impact of decreases in available lending resources on quantitative and qualita- tive dimensions of firms’ patenting activities. We thereby make use of the European Banking Authority?s capital exercise to carve out the causal effect of bank lending on firm innovation. In order to do so we combine various datasets to derive information on firms’ financials, their patenting behaviors, as well as their relationships with their lenders. Building on this self- generated dataset, we provide support for the “less finance, less innovation” view. At the same time, we show that lower available financial resources for firms lead to improvement in the qualitative dimensions of their patents. Hence, we carve out a “less finance, less but better innovation” pattern.
We define a sentiment indicator that exploits two contrasting views of return predictability, and study its properties. The indicator, which is based on option prices, valuation ratios and interest rates, was unusually high during the late 1990s, reflecting dividend growth expectations that in our view were unreasonably optimistic. We interpret it as helping to reveal irrational beliefs about fundamentals. We show that our measure is a leading indicator of detrended volume, and of various other measures associated with financial fragility. We also make two methodological contributions. First, we derive a new valuation-ratio decomposition that is related to the Campbell and Shiller (1988) loglinearization, but which resembles the traditional Gordon growth model more closely and has certain other advantages for our purposes. Second, we introduce a volatility index that provides a lower bound on the market's expected log return.
This paper explores the interplay of feature-based explainable AI (XAI) tech- niques, information processing, and human beliefs. Using a novel experimental protocol, we study the impact of providing users with explanations about how an AI system weighs inputted information to produce individual predictions (LIME) on users’ weighting of information and beliefs about the task-relevance of information. On the one hand, we find that feature-based explanations cause users to alter their mental weighting of available information according to observed explanations. On the other hand, explanations lead to asymmetric belief adjustments that we inter- pret as a manifestation of the confirmation bias. Trust in the prediction accuracy plays an important moderating role for XAI-enabled belief adjustments. Our results show that feature-based XAI does not only superficially influence decisions but re- ally change internal cognitive processes, bearing the potential to manipulate human beliefs and reinforce stereotypes. Hence, the current regulatory efforts that aim at enhancing algorithmic transparency may benefit from going hand in hand with measures ensuring the exclusion of sensitive personal information in XAI systems. Overall, our findings put assertions that XAI is the silver bullet solving all of AI systems’ (black box) problems into perspective.
Many equity markets combine continuous trading and call auctions. Oftentimes designated market makers (DMMs) supply additional liquidity. Whereas prior research has focused on their role in continuous trading, we provide a detailed analysis of their activity in call auctions. Using data from Germany’s Xetra system, we find that DMMs are most active when they can provide the greatest benefits to the market, i.e., in relatively illiquid stocks and at times of elevated volatility. Their trades stabilize prices and they trade profitably.
Incentives, self-selection, and coordination of motivated agents for the production of social goods
(2021)
We study, theoretically and empirically, the effects of incentives on the self-selection and coordination of motivated agents to produce a social good. Agents join teams where they allocate effort to either generate individual monetary rewards (selfish effort) or contribute to the production of a social good with positive effort complementarities (social effort). Agents differ in their motivation to exert social effort. Our model predicts that lowering incentives for selfish effort in one team increases social good production by selectively attracting and coordinating motivated agents. We test this prediction in a lab experiment allowing us to cleanly separate the selection effect from other effects of low incentives. Results show that social good production more than doubles in the low- incentive team, but only if self-selection is possible. Our analysis highlights the important role of incentives in the matching of motivated agents engaged in social good production.
We investigate the differential effect of the COVID-19 shock to the stock market shock on the share prices of firms with different levels of ESG (Environmental, Social and Governance) scores. Thereby, we analyse whether and to what extent better ESG ratings provided insurance for investors in the stocks of those firms during this shock. We focus our analysis on the European market in which ESG investment plays a particularly important role. Using a broad sample of listed firms we provide mixed evidence. On the one hand, we show that immediately after the start of the shock firms with a higher ESG score outperformed their peers. On the other hand, this effect faded less than six weeks later. Given the quick recovery of the market our finding supports the idea that ESG stocks provide limited insurance in severe crises.
By computing a volatility index (CVX) from cryptocurrency option prices, we analyze this market’s expectation of future volatility. Our method addresses the challenging liquidity environment of this young asset class and allows us to extract stable market implied volatilities. Two alternative methods are considered to compute volatilities from granular intra-day cryptocurrency options data, which spans over the COVID-19 pandemic period. CVX data therefore capture ‘normal’ market dynamics as well as distress and recovery periods. The methods yield two cointegrated index series, where the corresponding error correction model can be used as an indicator for market implied tail-risk. Comparing our CVX to existing volatility benchmarks for traditional asset classes, such as VIX (equity) or GVX (gold), confirms that cryptocurrency volatility dynamics are often disconnected from traditional markets, yet, share common shocks.
Artificial Intelligence (AI) and Machine Learning (ML) are currently hot topics in industry and business practice, while management-oriented research disciplines seem reluctant to adopt these sophisticated data analytics methods as research instruments. Even the Information Systems (IS) discipline with its close connections to Computer Science seems to be conservative when conducting empirical research endeavors. To assess the magnitude of the problem and to understand its causes, we conducted a bibliographic review on publications in high-level IS journals. We reviewed 1,838 articles that matched corresponding keyword-queries in journals from the AIS senior scholar basket, Electronic Markets and Decision Support Systems (Ranked B). In addition, we conducted a survey among IS researchers (N = 110). Based on the findings from our sample we evaluate different potential causes that could explain why ML methods are rather underrepresented in top-tier journals and discuss how the IS discipline could successfully incorporate ML methods in research undertakings.
This paper analyzes the scope of the private market for pandemic insurance. We develop a framework that explains theoretically how the equilibrium price of pandemic insurance depends on accumulation risk, covariance between pandemic claims and other claims, and covariance between pandemic claims and the stock market performance. Using the natural catastrophe (NatCat) insurance market as a laboratory, we estimate the relationship between the insurance price markup and the tail characteristics of the loss distribution. Then, by using the high-frequency data tracking the economic impact of the COVID-19 pandemic in the United States, we calibrate the loss distribution of a hypothetical insurance contract designed to alleviate the impact of the pandemic on small businesses. The pandemic insurance contract price markup corresponds to the top 20% markup observed in the NatCat insurance market. Then we analyze an intertemporal risk-sharing scheme that can reduce the expected shortfall of the loss distribution by 50%.
When requesting a web-based service, users often fail in setting the website’s privacy settings according to their self privacy preferences. Being overwhelmed by the choice of preferences, a lack of knowledge of related technologies or unawareness of the own privacy preferences are just some reasons why users tend to struggle. To address all these problems, privacy setting prediction tools are particularly well-suited. Such tools aim to lower the burden to set privacy preferences according to owners’ privacy preferences. To be in line with the increased demand for explainability and interpretability by regulatory obligations – such as the General Data Protection Regulation (GDPR) in Europe – in this paper an explainable model for default privacy setting prediction is introduced. Compared to the previous work we present an improved feature selection, increased interpretability of each step in model design and enhanced evaluation metrics to better identify weaknesses in the model’s design before it goes into production. As a result, we aim to provide an explainable and transparent tool for default privacy setting prediction which users easily understand and are therefore more likely to use.
Market risks account for an integral part of life insurers' risk profiles. This paper explores the market risk sensitivities of insurers in two large life insurance markets, namely the U.S. and Europe. Based on panel regression models and daily market data from 2012 to 2018, we analyze the reaction of insurers' stock returns to changes in interest rates and CDS spreads of sovereign counterparties. We find that the influence of interest rate movements on stock returns is more than 50% larger for U.S. than for European life insurers. Falling interest rates reduce stock returns in particular for less solvent firms, insurers with a high share of life insurance reserves and unit-linked insurers. Moreover, life insurers' sensitivity to interest rate changes is seven times larger than their sensitivity towards CDS spreads. Only European insurers significantly suffer from rising CDS spreads, whereas U.S. insurers are immunized against increasing sovereign default probabilities.
We characterize the optimal linear tax on capital in an Overlapping Generations model with two period lived households facing uninsurable idiosyncratic labor income risk. The Ramsey government internalizes the general equilibrium effects of private precautionary saving on factor prices and taxes capital unless the weight on future generations in the social welfare function is sufficiently high. For logarithmic utility a complete analytical solution of the Ramsey problem exhibits an optimal aggregate saving rate that is independent of income risk, whereas the optimal time-invariant tax on capital implementing this saving rate is increasing in income risk. The optimal saving rate is constant along the transition and its sign depends on the magnitude of risk and on the Pareto weight of future generations. If the Ramsey tax rate that maximizes steady state utility is positive, then implementing this tax rate permanently induces a Pareto-improving transition even if the initial equilibrium capital stock is below the golden rule.
This paper documents that the bond investments of insurance companies transmit shocks from insurance markets to the real economy. Liquidity windfalls from household insurance purchases increase insurers’ demand for corporate bonds. Exploiting the fact that insurers persistently invest in a small subset of firms for identification, I show that these increases in bond demand raise bond prices and lower firms’ funding costs. In response, firms issue more bonds, especially when their bond underwriters are well connected with investors. Firms use the proceeds to raise investment rather than equity payouts. The results emphasize the significant impact of investor demand on firms’ financing and investment activities.
Using a structural life-cycle model, we quantify the heterogeneous impact of school closures during the Corona crisis on children affected at different ages and coming from households with different parental characteristics. In the model, public investment through schooling is combined with parental time and resource investments in the production of child human capital at different stages in the children’s development process. We quantitatively characterize the long-term consequences from a Covid-19 induced loss of schooling, and find average losses in the present discounted value of lifetime earnings of the affected children of close to 1%, as well as welfare losses equivalent to about 0.6% of permanent consumption. Due to self-productivity in the human capital production function, skill attainment at a younger stage of the life cycle raises skill attainment at later stages, and thus younger children are hurt more by the school closures than older children. We find that parental reactions reduce the negative impact of the school closures, but do not fully offset it. The negative impact of the crisis on children’s welfare is especially severe for those with parents with low educational attainment and low assets. The school closures themselves are primarily responsible for the negative impact of the Covid-19 shock on the long-run welfare of the children, with the pandemic-induced income shock to parents playing a secondary role.
We extend the canonical income process with persistent and transitory risk to cyclical shock distributions with left-skewness and excess kurtosis. We estimate our income process by GMM for US household data. We find countercyclical variance and procyclical skewness of persistent shocks. All shock distributions are highly leptokurtic. The tax and transfer system reduces dispersion and left-skewness. We then show that in a standard incomplete-markets life-cycle model, first, higherorder risk has sizable welfare implications, which depend on risk attitudes; second, it matters quantitatively for the welfare costs of cyclical idiosyncratic risk; third, it has non-trivial implications for self-insurance against shocks.
Historical evidence like the global financial crisis from 2007-09 highlights that sector concentration risk can play an important role for the solvency of insurers. However, current microprudential frameworks like the US RBC framework and Solvency II consider only name concentration risk explicitly in their solvency capital requirements for asset concentration risk and neglect sector concentration risk. We show by means of US insurers’ asset holdings from 2009 to 2018 that substantial sectoral asset concentrations exist in the financial, public and real estate sector, and find indicative evidence for a sectoral search for yield behavior. Based on a theoretical solvency capital allocation scheme, we demonstrate that the current regulatory approaches can lead to inappropriate and biased levels of solvency capital for asset concentration risk, and should be revised. Our findings have also important implications on the ongoing discussion of asset concentration risk in the context of macroprudential insurance regulation.
We consider an additively time-separable life-cycle model for the family of power period utility functions u such that u0(c) = c−θ for resistance to inter-temporal substitution of θ > 0. The utility maximization problem over life-time consumption is dynamically inconsistent for almost all specifications of effective discount factors. Pollak (1968) shows that the savings behavior of a sophisticated agent and her naive counterpart is always identical for a logarithmic utility function (i.e., for θ = 1). As an extension of Pollak’s result we show that the sophisticated agent saves a greater (smaller) fraction of her wealth in every period than her naive counterpart whenever θ > 1 (θ < 1) irrespective of the specification of discount factors. We further show that this finding extends to an environment with risky returns and dynamically inconsistent Epstein-Zin-Weil preferences.
Using a structural life-cycle model and data on school visits from Safegraph and school closures from Burbio, we quantify the heterogeneous impact of school closures during the Corona crisis on children affected at different ages and coming from households with different parental characteristics. Our data suggests that secondary schools were closed for in-person learning for longer periods than elementary schools (implying that younger children experienced less school closures than older children), and that private schools experienced shorter closures than public schools, and schools in poorer U.S. counties experienced shorter school closures. We then extend the structural life cycle model of private and public schooling investments studied in Fuchs-Schündeln, Krueger, Ludwig, and Popova (2021) to include the choice of parents whether to send their children to private schools, empirically discipline it with data on parental investments from the PSID, and then feed into the model the school closure measures from our empirical analysis to quantify the long-run consequences of the Covid-19 school closures on the cohorts of children currently in school. Future earnings- and welfare losses are largest for children that started public secondary schools at the onset of the Covid-19 crisis. Comparing children from the topto children from the bottom quartile of the income distribution, welfare losses are ca. 0.8 percentage points larger for the poorer children if school closures were unrelated to income. Accounting for the longer school closures in richer counties reduces this gap by about 1/3. A policy intervention that extends schools by 3 months (6 weeks in the next two summers) generates significant welfare gains for the children and raises future tax revenues approximately sufficient to pay for the cost of this schooling expansion.