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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.
In this study, we analyze the trading behavior of banks with lending relationships. We combine detailed German data on banks’ proprietary trading and market making with lending information from the credit register and then examine how banks trade stocks of their borrowers around important corporate events. We find that banks trade more frequently and also profitably ahead of events when they are the main lender (or relationship bank) for the borrower. Specifically, we show that relationship banks are more likely to build up positive (negative) trading positions in the two weeks before positive (negative) news events, and also that they unwind these positions shortly after the event. This trading pattern is more pronounced for unscheduled earnings events, M&A transactions, and after borrower obtain new bank loans. Our results suggest that lending relationships endow banks with important information, highlighting the potential for conflicts of interest in banking, which has been a prominent concern in the regulatory debate.
Increasing the diversity of policy committees has taken center stage worldwide, but whether and why diverse committees are more effective is still unclear. In a randomized control trial that varies the salience of female and minority representation on the Federal Reserve’s monetary policy committee, the FOMC, we test whether diversity affects how Fed information influences consumers’ subjective beliefs. Women and Black respondents form unemployment expectations more in line with FOMC forecasts and trust the Fed more after this intervention. Women are also more likely to acquire Fed-related information when associated with a female official. White men, who are overrepresented on the FOMC, do not react negatively. Heterogeneous taste for diversity can explain these patterns better than homophily. Our results suggest more diverse policy committees are better able to reach underrepresented groups without inducing negative reactions by others, thereby enhancing the effectiveness of policy communication and public trust in the institution.
We identify strong cross-border institutions as a driver for the globalization of in-novation. Using 67 million patents from over 100 patent offices, we introduce novel measures of innovation diffusion and collaboration. Exploiting staggered bilateral in-vestment treaties as shocks to cross-border property rights and contract enforcement, we show that signatory countries increase technology adoption and sourcing from each other. They also increase R&D collaborations. These interactions result in techno-logical convergence. The effects are particularly strong for process innovation, and for countries that are technological laggards or have weak domestic institutions. Increased inter-firm rather than intra-firm foreign investment is the key channel.
Using hand-collected data on CEO appointments during shareholder activism campaigns, this study examines whether shareholder involvement in CEO recruiting affects frictions in CEO hiring decisions. The results indicate that appointments of CEOs who are recruited with shareholder activist influence are followed by more favorable stock market reactions and stronger profitability improvements than CEO appointments that also occur during activism campaigns but without the influence of activists. I find little evidence that shareholder activists increase hiring frictions by facilitating the recruiting of CEOs who will implement myopic corporate policies. Analyses of recruiting process characteristics reveal that activist influence is associated with more resources being dedicated to the CEO search process and with a higher propensity to recruit CEOs from outside the firm. These findings contribute to the CEO labor market literature, which tends to focus on the decision to remove incumbent CEOs but provides limited insights into CEO recruiting.
This paper argues that the key mechanisms protecting retail investors’ financial stake in their portfolio investments are indirect. They do not rely on actions by the investors or by any private actor directly charged with looking after investors’ interests. Rather, they are provided by the ecosystem that investors (are legally forced to) inhabit, as a byproduct of the mostly self-interested, mutually and legally constrained behavior of third parties without a mandate to help the investors (e.g., speculators, activists). This elucidates key rules, resolves the mandatory vs. enabling tension in corporate/securities law, and exposes passive investing’s fragile reliance on others’ trading.
Do required minimum distribution 401(k) rules matter, and for whom? Insights from a lifecylce model
(2021)
Tax-qualified vehicles helped U.S. private-sector workers accumulate $25Tr in retirement assets. An often-overlooked important institutional feature shaping decumulations from these retirement plans is the “Required Minimum Distribution” (RMD) regulation, requiring retirees to withdraw a minimum fraction from their retirement accounts or pay excise taxes on withdrawal shortfalls. Our calibrated lifecycle model measures the impact of RMD rules on financial behavior of heterogeneous households during their worklives and retirement. We show that proposed reforms to delay or eliminate the RMD rules should have little effects on consumption profiles but more impact on withdrawals and tax payments for households with bequest motives.
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.
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.
Our starting point is the following simple but potentially underappreciated observation: When assessing willingness to pay (WTP) for hedonic features of a product, the results of such measurement are influenced by the context in which the consumer makes her real or hypothetical choice or in which the questions to which she replies are set (such as in a contingent valuation analysis). This observation is of particular relevance when WTP regards sustainability, the “non-use value” of which does not derive from a direct (physical) sensation and where perceived benefits depend heavily on available information and deliberations. The recognition of such context sensitivity paves the way for a broader conception of consumer welfare (CW), and our proposed standard of “reflective WTP” may materially change the scope for private market initiatives with regards to sustainability, while keeping the analytical framework within the realm of the CW paradigm. In terms of practical implications, we argue, for instance, that actual purchasing decisions may prove insufficient to measure consumer appreciation of sustainability, as they may rather echo learnt but unreflected heuristics and may be subject to the specific shopping context, such as heavy price promotions. Also, while it may reflect current social norm, the latter may change considerably over time as more consumers adopt their behavior.
Extant research shows that CEO characteristics affect earnings management. This paper studies how investors infer a specific characteristic of CEOs, namely moral commitment to honesty, from earnings management and how this perception – in conjunction with their own social and moral preferences – shapes their investment choices. We conduct two laboratory experiments simulating investment choices. Our results show that participants perceive a CEO to be more committed to honesty when they infer that the CEO engaged less in earnings management. For investment decisions, a one standard deviation increase in a CEO's perceived commitment to honesty compared to another CEO reduces the relevance of differences in the CEOs’ claimed future returns by 40%. This effect is most prominent among investors with a proself value orientation. To prosocial investors, their own honesty values and those attributed to the CEO matter directly, while returns play a secondary role. Overall, perceived CEO honesty matters to different investors for distinct reasons.
We study the design features of disclosure regulations that seek to trigger the green transition of the global economy and ask whether such regulatory interventions are likely to bring about sufficient market discipline to achieve socially optimal climate targets.
We categorize the transparency obligations stipulated in green finance regulation as either compelling the standardized disclosure of raw data, or providing quality labels that signal desirable green characteristics of investment products based on a uniform methodology. Both categories of transparency requirements can be imposed at activity, issuer, and portfolio level.
Finance theory and empirical evidence suggest that investors may prefer “green” over “dirty” assets for both financial and non-financial reasons and may thus demand higher returns from environmentally-harmful investment opportunities. However, the market discipline that this negative cost of capital effect exerts on “dirty” issuers is potentially attenuated by countervailing investor interests and does not automatically lead to socially optimal outcomes.
Mandatory disclosure obligations and their (public) enforcement can play an important role in green finance strategies. They prevent an underproduction of the standardized high-quality information that investors need in order to allocate capital according to their preferences. However, the rationale behind regulatory intervention is not equally strong for all categories and all levels of “green” disclosure obligations. Corporate governance problems and other agency conflicts in intermediated investment chains do not represent a categorical impediment for green finance strategies.
However, the many forces that may prevent markets from achieving socially optimal equilibria render disclosure-centered green finance legislation a second best to more direct forms of regulatory intervention like global carbon taxation and emissions trading schemes. Inherently transnational market-based green finance concepts can play a supporting role in sustainable transition, which is particularly important as long as first-best solutions remain politically unavailable.
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.
Device-to-device (D2D) communication is an innovative solution for improving wireless network performance to efficiently handle the ever-increasing mobile data traffic. Communication takes place directly between two devices that are in each other’s transmission range. So far, research has focused on the technical challenges of implementing this technology and assumes a user’s general willingness to participate as forwarder in this technology. However, this simplifying assumption is not realistic, as willingness to participate in D2D communication can vary depending on the user. In this work, we consider the scenario that a user can act as a forwarder for a receiver who is not directly or insufficiently reached by the base station and accordingly has no or poor Internet connection. We take a user-centric approach and investigate the willingness to provide an Internet connection as a forwarder. We are the first to investigate user preferences for D2D communication using a choice-based conjoint analysis. Our results, based on a representative sample of potential users (N=181), show that the social relationship between the potential forwarder and the receiver has the greatest impact on the potential forwarder’s decision to provide an Internet connection to the receiver, accepting sacrifices in terms of additional battery consumption and reduced own service performance. In a detailed segment analysis, we observe significant preference differences depending on smartphone usage behavior and user age. Taking the corresponding preferences into account when matching forwarders and receivers can further increase technology adoption.
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.
Conditional yield skewness is an important summary statistic of the state of the economy. It exhibits pronounced variation over the business cycle and with the stance of monetary policy, and a tight relationship with the slope of the yield curve. Most importantly, variation in yield skewness has substantial forecasting power for future bond excess returns, high-frequency interest rate changes around FOMC announcements, and consensus survey forecast errors for the ten-year Treasury yield. The COVID pandemic did not disrupt these relations: historically high skewness correctly anticipated the run-up in long-term Treasury yields starting in late 2020. The connection between skewness, survey forecast errors, excess returns, and departures of yields from normality is consistent with a theoretical framework where one of the agents has biased beliefs.
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.
The authors identify U.S. monetary and fiscal dominance regimes using machine learning techniques. The algorithms are trained and verified by employing simulated data from Markov-switching DSGE models, before they classify regimes from 1968-2017 using actual U.S. data. All machine learning methods outperform a standard logistic regression concerning the simulated data. Among those the Boosted Ensemble Trees classifier yields the best results. The authors find clear evidence of fiscal dominance before Volcker. Monetary dominance is detected between 1984-1988, before a fiscally led regime turns up around the stock market crash lasting until 1994. Until the beginning of the new century, monetary dominance is established, while the more recent evidence following the financial crisis is mixed with a tendency towards fiscal dominance.
This note argues that the European Central Bank should adjust its strategy in order to consider broader measures of inflation in its policy deliberations and communications. In particular, it points out that a broad measure of domestic goods and services price inflation such as the GDP deflator has increased along with the euro area recovery and the expansion of monetary policy since 2013, while HICP inflation has become more variable and, on average, has declined. Similarly, the cost of owner-occupied housing, which is excluded from the HICP, has risen during this period. Furthermore, it shows that optimal monetary policy at the effective lower bound on nominal interest rates aims to return inflation more slowly to the inflation target from below than in normal times because of uncertainty about the effects and potential side effects of quantitative easing.
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.
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.
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“.
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.
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
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 paper discusses policy implications of a potential surge in NPLs due to COVID-19. The study provides an empirical assessment of potential scenarios and draws lessons from previous crises for effective NPL treatment. The paper highlights the importance of early and realistic assessment of loan losses to avoid adverse incentives for banks. Secondary loan markets would help in this process and further facilitate bank resolution as laid down in the BRRD, which should be uphold even in extreme scenarios.
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.
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.
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.
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.
We empirically examine the Capital Purchase Program (CPP) used by the US gov- ernment to bail out distressed banks with equity infusions during the Great Recession. We find strong evidence that a feature of the CPP – the government’s ability to ap- point independent directors on the board of an assisted bank that missed six dividend payments to the Treasury – helped attenuate bailout-related moral hazard. Banks were averse to these appointments – the empirical distribution of missed payments exhibits a sharp discontinuity at five. Director appointments by the Treasury led to improved bank performance, lower CEO pay, and higher stock market valuations.
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.
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.
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.
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.
Dieser Artikel behandelt das Zusammenspiel von staatlich organisierten sozialen Sicherungssystemen und der privaten Eigenvorsorge durch Vermögensbildung als Grundpfeiler der sozialen Marktwirtschaft in Deutschland. Die jährlichen Ausgaben der verschiedenen staatlichen Sicherungssysteme belaufen sich auf rund ein Drittel des erwirtschafteten Bruttosozialprodukts, wobei die umlagefinanzierten Alterssicherungssysteme für die Arbeitsnehmer den größten Anteil ausmachen. Sachvermögen in Form von selbst genutzten Wohnungen sowie Finanzvermögen in Form von Bankeinlagen und Ansprüche gegen private Versicherungen machen den größten Anteil der Eigenversorge aus. Aufgrund des niedrigen Zinsniveaus sowie des demografischen Wandels der Gesellschaft wird die Eigenvorsorge durch Anlagen an den internationalen Wertpapiermärkten sowohl für Selbständige als auch Arbeitsnehmer immer bedeutender.
We analyze the joint dynamics of prices, productivity, and employment across firms, building a dynamic equilibrium model of heterogeneous firms who compete for workers and customers in frictional labor and product markets. Using panel data on prices and output for German manufacturing firms, the model is calibrated to evaluate the quantitative contributions of productivity and demand for the labor market. Product market frictions decisively dampen the firms' employment adjustments to productivity shocks. We further analyze the impact of aggregate shocks to the first and second moments of productivity and demand and relate them to business-cycle features in our data.