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How do environmental factors affect financial decision-making? Using plausibly exogenous variation in exposure to fluctuations in temperature over a sample of individuals between 2004 and 2018 across 28 European countries and Israel, we estimate the causal effect of a marginal change in temperature on financial investments and its interaction with individual personality characteristics. We find that a 10\% increase in temperature is associated with a 0.1 percentage point (pp) rise in the probability that an optimist invests in bonds, a 0.12 pp decline in the probability for stocks, and a 0.11 pp rise in mutual funds. However, among pessimists, we find null effects. We find similar results when we focus on the intensive margin of investment as well. Our results are identified of within-person variation after controlling for all shocks that are common within a country and year, thereby purging variation in time-varying country policies and macroeconomic conditions. These results are unique to optimists versus pessimists, rather than general happiness or interest. Furthermore, the variation in optimism is largely driven by attitudes about risk, rather than attitudes about trust. Our results are consistent with behavioral finance models where expectations moderate the transmission of shocks onto financial decision-making.

How do financial markets switch from states of optimism to pessimism and vice versa? Given that a financial market is currently stable, what is the probability that it will become unstable and crash? We answer those questions in the context of a natural experiment with risk sources of probability judgment error, i.e. source functions, implied by index option prices. Source functions reflect investors (option traders) sentiments about the ranking of index options' attractiveness and the weight they place on each rank. We introduce a novel behavioural process (hereinafter BELLE), constructed from noise in investors probability judgment, that (1) characterizes investor sentiment about tail events in index option prices over time and probability ranks, (2) provides early warning signals of market instability, and (3) crash probability estimates from a closed form expression for the time varying transition probability that a seemingly stable market state will become unstable and crash. The model makes the fatalistic prediction that over time investor sentiment about index option prices characterize market transition from stable to unstable states and crash almost surely.

Evidence from psychology literature confirms the long-held intuition that mood affects judgment. Specifically, individuals who are in a negative mood are more likely to think critically and avoid heuristic processing. This paper uses two proxies for mood, weather and media pessimism, to show that investors make better selling decisions when they are feeling sad. A one-unit increase in cloudiness leads to 1.4% 3-factor alpha improvement at a 12-month horizon. The disposition effect, which decreases in magnitude when investors are in a negative mood, provides an explanation for these results.

We study the effects of SEC oversight, proxied by a firm’s geographic proximity to the nearest SEC regional office, on the firm’s management earnings forecasts. Using exogenous changes in proximity caused by SEC district office elevations to regional status, we find that firms located in closer proximity to SEC regional offices issue management earnings forecasts more frequently. We also show that this relationship strengthens when peer firms experience SEC investigations and are more strictly obligated to clarify previous misleading information. Our results suggest that firms use voluntary disclosures to mitigate SEC oversight. We show further that firms are likely to gain credibility by disclosing more pessimistic forecasts and releasing bad news more frequently and in a timelier way. Investors (analysts) are more likely to adjust their investments (forecasts) according to management earnings forecasts issued by firms that are located near SEC offices. As a result, the SEC is less likely to issue comment letters to nearby firms that issue management earnings forecasts more often.

We decompose total disagreement about macro variables into the disagreement among optimists (i.e., forecasters whose forecast exceeds a certain threshold) and pessimists. Optimistic (pessimistic) forecasters tend to disagree more in good (bad) times. Pessimistic (optimistic) disagreement commands a negative and significant (positive, although often (insignificant) risk premium and total disagreement is often insignificant when included in the same regression. These results are robust across a variety of empirical specifications and sets of test assets. A theoretical model, in which the risk premia of optimistic and pessimistic disagreement depend in a non-trivial way on forecasters’ beliefs and on the joint impact of optimistic and pessimistic disagreement on the price of the assets used to speculate on individual beliefs, rationalizes the empirical findings.

Politicians, scientists and journalists have aired vastly different assessments of the COVID-19 pandemic, ranging from rather optimistic to very pessimistic ones. In this paper we investigate how narratives conveying different assessments of the pandemic impact economic behavior. In a controlled experiment with incentivized economic games we find that subjects behave more risk averse and less patiently when confronted with a pessimistic compared to an optimistic or balanced narrative. Further we find that narratives change subjects’ expectations about the pandemic and the stock market. Hence our experiment provides causal evidence for an impact of narratives on fundamental determinants of household behavior.

Although civil war devastates the environment, we still do not understand the role of environmental policies in post-conflict countries and often have a pessimistic view without empirical evidence. We challenge this view by arguing that the introduction of independent monitoring mechanisms can make environmental regulations effective even in post-conflict countries. We substantiate this claim by exploiting analytical opportunities in the Democratic Republic of the Congo (DRC). In 2011–2013, the government implemented independent monitoring mechanisms to lessen the side effects of mining activities on deforestation. The reform, however, only applied to mining permit zones, which had arbitrary square shapes. By combining a geographic regression discontinuity and difference in differences to what we call a difference-in-geographic-discontinuity (DiGD) design, as well as using satellite-based data available at every 30 meters for over 40 million cells in the DRC, we find that the 2011–2013 reform substantially decreased deforestation rates immediately inside the mining permits. This finding implies that the environmental effects of civil war can crucially depend on post-conflict policies.

The research is devoted to the study of understatement and overstatement as linguocultural categories that reflect the peculiarities of the national British character and play a special role in situations of intercultural communication. The author considers understatement as a communicative non-positivity, which consists in non-directness, subjectivity, pessimism, non-categoricity, indirection, manifested in motivational speech acts, as well as in all communication situations where the interests of the interlocutor are affected. Overstatement is defined as communicative attractiveness, which implies emotivity, hyperbolized evaluativeness, optimism and informality (democracy), which are characteristic of expressive speech acts. The content of these linguocultural categories is a system of ritualized strategies of communicative behavior (verbal and nonverbal) aimed at harmonious, conflict-free communication and compliance with cultural traditions and norms in interactive communication. The generalization of strategies of understatement and overstatement in the speech of an Englishman reveals not only his strategic intentions, but also the subtle mechanism of interpersonal communication in the British linguoculture.

Economic theory predicts that expectations on future house price growth are related to the current price of a house. We test this relationship for the supply side of the secondary housing market using micro data that links individual expectations to a subjective owner estimated value (OEV). We find a strong causal relationship that optimistic expectations indeed imply higher OEVs as compared to neutral or pessimistic expectations. We find qualitatively and quantitatively consistent results for Italy and the US as well as for booming and gloomy years. Our results survive ample robustness checks. Since we use subjective data on house prices, we first show that OEVs are indeed a valid source to study house price dynamics by performing three types of convergent validity tests. We find that price dynamics derived by either combining OEVs and dwelling characteristics, or making use of repeatedly provided OEVs by the same owner over time reproduce objectively measured market trends strikingly well – even over decades. In contrast, OEVs and objective data tend to differ in levels – potentially due to psychological bias. These results hold for a large set of countries. We hence conclude that the "wisdom of the home-owner crowd" is sufficient to study house price dynamics but OEVs are less suited for measuring the level of market prices.

Life span uncertainty (longevity risk) impacts several economic decisions. Individuals can form and revise their survival beliefs making use of behavioural heuristics. We propose a model of sentiment, in which individuals are assumed to switch between optimistic and pessimistic expectations on their health. When optimism is persistent in the face of health shocks, or when individuals are more likely to change their sentiment from pessimistic to optimistic than otherwise, our model predicts survival under-estimation at young ages and over-estimation at old ages. An empirical analysis based on the longitudinal data from the Health and Retirement Study (HRS) validates our model.

We examine whether financial analysts cater to investors’ beliefs, using the market liberalization (Stock Connect) programs in China as a shock to investor beliefs. We find that analysts become less optimistic in their recommendations following the introduction of less optimistic investors through the Stock Connect programs. In addition, catering theory predicts that when investors hold heterogeneous beliefs, analysts tend to segment the market and slant toward extreme positions in order to attract target investors. Consistent with this prediction, we find that analyst dispersion increases in the post period. Moreover, analysts with buy or strong buy (sell or underperform) recommendations of a given firm become more optimistic (pessimistic) in their research report tone. Finally, we show that in updating their earnings forecasts, analysts are more (less) responsive to earnings surprises that are consistent (inconsistent) with their stock recommendations. Overall, this paper presents evidence supporting a catering theory for analyst bias.

The outbreak of the COVID-19 pandemic has threatened socio-economic security on a global scale. Democracy has been put to the test by the spread of COVID-19, with two main arguments having arisen: 1) COVID-19 is contributing to a trend of democratic backsliding; 2) states with illiberal practices are better at handling the outbreak than are states with liberal practices. This paper answers these two arguments. In the first section, using data from various sources, this paper examines three trends to counter the democratic backslide argument: the maintenance of democracy, fallen democracy, and autocracy. The paper shows that COVID-19 has contributed very little to the decline of democracy and, in actuality, democratic backslide that occurred in 2020 happened due to factors that existed even before the outbreak—COVID-19 was merely a reflector or trigger point for states struggling with democracy. In the second section, this paper argues that states with autocratic practices may be able to contain the spread of the pandemic, but in comparison with democratic states, they are unable to manage the pandemic crisis, resulting in a larger death rate and economic decline. As such, the pessimistic belief that the COVID-19 pandemic is bringing about the fall of democracy may be overstated.

Using a probability-based sample of the Norwegian population, we test whether an informational treatment about fewer audits by the Norwegian Tax Administration during the peak of the COVID-19 crisis affects support for an economic relief program designed to save jobs and prevent bankruptcies. The information treatment significantly reduces support for the economic relief program. The underlying mechanisms are lower trust in the tax administration and more pessimism about its ability to detect misuse of the program.

This manuscript introduces the 2021 Survey of American Catholic Priests (SACP), a data- gathering initiative which resulted in a new dataset containing responses to 54 survey questions from 1,036 Catholic priests in the United States. Replicating questions from a 2002 poll of Catholic priests from the Los Angeles Times allowed us to assess changes over time. Here, we present selected findings in eight areas: summary comparisons, morale, moral assessments, relationships to and evaluations of bishops, salvation exclusivism, perceptions of the conservatism or liberalism of younger priests, approval of Pope Francis, and the state of the Catholic Church in America. We find strong empirical confirmation of the nearly ubiquitous perception that younger priests are more orthodox in their beliefs than older priests. Additionally, we find a significant turn toward pessimism regarding the current state and trajectory of the Church. Other patterns and opportunities for further analyses are discussed.

We investigate the effect of how news outlets communicate macroeconomic information to consumers on support for governmental policy in the context of the COVID-19 crisis. In our survey experiment based on a representative sample of 3000 individuals in Germany, respondents are exposed to an expert forecast of GDP growth. Individuals are randomly assigned to either receive no information, the baseline forecast information, or real-world frames of the same information used in newspaper articles on the topic. We find that in contrast to the baseline information, positive framing of forecasted economic growth by news outlets increases support for pandemic policy. This effect is especially pronounced for respondents with more pessimistic macroeconomic expectations. Further evidence suggests that negative economic news are perceived as more credible and hence less surprising in times of recession, not translating into a change in political opinion.

We study firms' hiring decisions in a world in which both managers and investors are prone to expectation errors. We show that high managerial sentiment increases employment growth, especially at firms with worse investment opportunities and low-quality corporate governance, and during times of low investor sentiment. Using data on U.S. publicly traded companies and CEO option holdings, we find evidence consistent with these predictions. The results unveil a new channel through which managerial sentiment affects firms' operations, and suggest that managerial optimism can counter the negative effect of pessimistic investors on labor markets.

Survey data are ubiquitous in the economics literature, ranging from unemployment rate and CPI to surveys of professional forecasts and consumer finances. However, their potential biases are rarely discussed. By randomizing the order of responses to the questions in an economic survey, we document a pervasive response order bias: respondents tend to select answers at or near the top of the lists, leading to a systematic bias in survey results. This bias is smaller when respondents are more certain about their answers and disappears for “objective” questions (e.g., questions on demographics and recent experiences). Our evidence directly shows the bias in the levels of many survey-based variables and indirectly implies a bias in their changes, the latter likely correlated with the uncertainty in the economy. To assess bias magnitude, we examine two salient features at the time of our survey: the COVID pandemic and the approaching 2020 presidential election. We find that respondents’ expectations are shaped by their political leanings and personal experience during the pandemic: when forecasting stock returns, GDP growth, or COVID vaccine development, respondents are more pessimistic if they lean Democratic or personally know someone with COVID, but are more optimistic if they expect their preferred presidential candidate to win. The magnitude of these effects is comparable to the size of the response order bias. The implications of our evidence for financial services, public health policy, and political elections are discussed.

This paper uses a laboratory experiment to study beliefs and their relationship to action and strategy choices in finitely and indefinitely repeated prisoners' dilemma games. We find subjects' beliefs about the other player's action are accurate despite some systematic deviations corresponding to early pessimism in the indefinitely repeated game and late optimism in the finitely repeated game. The data reveals a close link between beliefs and actions that differs between the two games. In particular, the same history of play leads to different beliefs, and the same belief leads to different action choices in each game. Moreover, we find beliefs anticipate the evolution of behavior within a super game, changing in response to the history of play (in both games) and the number of rounds played (in the finitely repeated game). We then use the subjects' beliefs over actions in each round to identify their beliefs over super game strategies played by the other player. We find these beliefs correctly capture the different classes of strategies used in each game. Importantly, subjects using different strategies have different beliefs, and for the most part, strategies are subjectively rational given beliefs. The results also suggest subjects tend to overestimate the likelihood that others use the same strategy as them, while underestimating the likelihood that others use less cooperative strategies.

Errors in survey expectations display waves of pessimism and optimism and significant sluggishness. This paper develops a novel theoretical framework of time-varying beliefs capturing these empirical facts. In our model, the dynamic beliefs arise endogenously due to agents’ attitude toward alternative models. Decision-maker’s distorted beliefs generate countercyclical risk aversion, procyclical portfolio weights, countercyclical equilibrium asset returns, and excess volatility. A calibrated version of our model is shown to match salient features in equity markets.

This study cross-checks the symmetric and asymmetric effects of investor’s optimistic and pessimistic sentiments of Bitcoin on 23 sectoral stock return indices (10 Islamic stock sectoral indices and one composite Islamic market index by Dow Jones Islamic market and 12 industrial indices by Kenneth R French). Results of Autoregressive Distributed Lag (ARDL) and Nonlinear ARDL models are supporting our conjecture that when investors’ are being optimistic (pessimistic) to Bitcoin they move part of their funds from stocks (Bitcoin) to Bitcoin (stocks). Second, we found asymmetric effects of both sentiment indices on the Islamic stock indices and conventional stock indices. Third, we found support for the decoupling hypothesis as Bitcoin sentiments are affecting conventional stock indices more than Islamic stock indices. Fourth, investors’ optimistic sentiments are robust than pessimistic sentiments explaining sectoral stock return indices. Fifth, insignificance of OBSI and PBSI in most of the sectoral stock indices are evidencing the hedging opportunity for Bitcoin investors.

This paper studies whether and how differently projected information about the impact of the Covid-19 pandemic affects individuals' prosocial behavior and expectations on future outcomes. We conducted an online experiment with British participants (N=961) when the UK introduced its first lockdown and the outbreak was on its growing stage. Participants were primed with either the environmental or economic consequences (i.e., negative primes), or the environmental or economic benefits (i.e., positive primes) of the pandemic, or with neutral information. We measured priming effects on an incentivized take-and-give dictator game and on participants' expectations about future environmental quality and economic growth. Our results show that primes affect participants' expectations, but not their prosociality. In particular, participants primed with environmental consequences hold a more pessimistic view on future environmental quality, while those primed with economic benefits are more optimistic about future economic growth. Instead, the positive environmental prime and the negative economic prime do not influence expectations. Our results offer insights into how information affects behavior and expectations during the Covid-19 pandemic.

A regulator who designs a public stress test to avert default of a distressed bank via private investment must account for large investors' private information on the bank's state. We provide conditions for crowding-in (crowding-out) so that the regulator offers more (less) information to better-informed investors. Crowding-in obtains if investors' private information is not too discriminating of the state. We show that the region of the common prior is consequential: if crowding-in occurs for ex-ante optimistic investors then crowding-out follows if they were instead pessimistic. Investors' value from more precise private signals may come from their effect on the public test's precision.

This study examines whether race/ethnicity of financial intermediaries influences the production and dissemination of information in the U.S. capital markets. We find that brokerage diversity influences both the forecasting style and accuracy of analysts. Asian analysts are more likely to issue bold positive forecasts while African American and Hispanic analysts are relatively more pessimistic. Further, White (Asian) analysts are more (less) accurate while African American and Hispanic analysts are as accurate as their peers. These accuracy differences primarily reflect the effects of brokerage diversity. Stock market participants perceive Asian analysts relatively more favorably in spite of their lower accuracy but their career outcomes are adversely affected by increased diversity. In contrast, stock market participants perceive African American and Hispanic analysts relatively less favorably and their career outcomes are minimally affected by brokerage diversity. Taken together, these findings demonstrate that minority analysts do not benefit from increased diversity while White analysts do.

Stockholders are faced with both macroeconomic uncertainty and uncertainty that is generated from fears. We develop a financial stress factor as a proxy for pessimism that operates through stockholders' expectations about the elevated market volatility and shocks the cross-section of stock returns. Due to agent's asymmetric aversion, financial stress affords positive risk prices, and has large effects on stocks with highly subjective valuations and are difficult to arbitrage. Exposure to financial stress risks explains cross-sectional stock return variations in various stock characteristic dimensions.

We revisit the link between the risk of sovereign default and default costs. Contrary to prior literature, we show that higher costs of default may result in higher default probabilities, lower bond prices, and fiscal limits that are not pinned down by economic fundamentals. Government debt sustainability depends on private investment behavior, which is affected by expectations about defaults and capital returns. We argue that this feedback loop gives rise to multiple equilibria. In `bad' equilibria, investors expect default and low capital returns; their low capital investment tightens the governments' fiscal constraints and reduces the probability of debt repayment, validating investor pessimism. In `good' equilibria, optimistic investors choose higher capital investment; this results in higher future fiscal surpluses, raises the probability of debt repayment and validates investor optimism.

This paper explores how heterogeneity in life expectancy, objective (statistical) as well as subjective, affects savings behavior between healthy and unhealthy people. Using data from the Health and Retirement Study, we show that people in poor health not only have shorter actual lifespan, but are also more pessimistic about their remaining time of life. Using a standard overlapping-generations model, we show that differences in life expectancy can explain one third of the differences in accumulated wealth with an important part driven by pessimism among unhealthy people.

By linking sell-side equity analysts to their deed records and LinkedIn profiles, I show that analysts with higher exposure to negative wealth shocks issue more pessimistic and less accurate forecasts. The effects are stronger when analysts have higher leverage in their homes and face career concerns. I also find that stocks recommended by exposed analysts underperform those of non-exposed counterparts, by an amount that is significant and economically large in magnitude. The results remain robust to unobserved skill differences, the potential endogeneity of housing prices, the self-selection of analysts into neighborhoods with certain traits, and placebo tests where housing wealth shocks are randomized across analysts. Collectively, this study provides new evidence on if and how personal wealth shocks impact analysts' work productivity and forecast behavior.

It is uncanny that historically, the large majority of U.S. market crashes have occurred in the month of October. I assert that three key conditions are gathered for this to happen. 1) There is a market-wide or macroeconomic informational ambiguity that has been lingering since before the summer months with high downside risk; 2) that despite this ambiguity, leverage is used to create a bubble and 3) that investors are driven by what I call the “ambiguity-forced-resolution bias.” I apply this reasoning to predict a crash in October 2020. I show that there currently is a bubble in the U.S. using a new indicator. I test that ambiguity/uncertainty was unusually high in months prior October crashes. Finally, I discuss why this upcoming crash is an opportunity for investors to reorder the equity market’s priorities to fund sectors that tackle rising societal and environmental challenges.

An extensive stream of literature investigates how product market competition, by increasing the proprietary costs of disclosure, influences corporate disclosure policy. We hypothesize that the proprietary costs incurred by firms are associated with how a disclosure is framed and structured. We predict and find that the intensity of competition in the product market is associated with more negative and uncertain earnings conference calls. We also find evidence of firms “casting calls” by emphasizing more pessimistic analysts’ questions. Our results are robust to matched analyses on cash flow uncertainty and to examining the casting of analysts, as opposed to their questions, on the earnings call. Finally, we find consistent results using alternative measures of linguistic structure and in an alternative channel of disclosure with an alternative measure of linguistic framing. Our results demonstrate that firms attempt to mitigate proprietary costs by managing discretionary disclosure structure and framing their conference calls.

We examine a sample of analysts who, despite having a bearish stock recommendation for a covered firm, issue an unusually optimistic earnings forecast at the end of the year. For the period 2004 through 2018, among analysts with an unfavorable stock recommendation, we find that about 5% issue a final earnings forecast prior to the earnings announcement that exceeds even the most optimistic earnings forecast issued by any other analyst covering the stock, presumably in an effort to increase the likelihood that the firm misses earnings expectations. More than 11% of all firm-year observations are subject to at least one such forecast at the hands of a bearish analyst. We find that analysts with pessimistic stock recommendations are more likely to issue these “difficult-to-beat” earnings forecasts when they have greater pressure to justify their negative view of the stock and when the earnings forecast has greater potential to revise investor beliefs. Nevertheless, stock returns associated with these optimistic forecast revisions are muted. We also find that although Thomson Reuters often excludes these forecasts from the consensus earnings estimate, the majority remain in the consensus and increase the likelihood that the firm misses the consensus forecast by about 21%. However, the market reaction to a negative earnings surprise is less severe when a bearish analyst has issued a difficult-to-beat forecast for the firm. Our study sheds light on one perverse strategy analysts use to increase the likelihood of an earnings miss.

This study investigates the effect of managerial sentiment on corporate disclosure decisions. Using terrorist attacks in the United States as adverse shocks to managerial sentiment, we find that firms located in the metropolitan areas attacked issue more negatively biased earnings forecasts. The effect is stronger for firms with higher operating uncertainty and firms with younger, inexperienced, or less confident executives, and it is weaker for firms located in states with increasing violent crime rates. A potential alternative explanation is that managers strategically bias earnings forecasts downward and attribute the poor performance to terrorist attacks. To address this issue, we conduct a battery of additional analyses and find results more consistent with managerial sentiment than strategic attribution. In addition, we show that our results are unlikely to be driven by any economic effects of terrorist attacks. Finally, firms in attacked areas exhibit a more pessimistic tone in 10-K/10-Q filings. JEL Classifications: D83; G14; M41.

The authors study investor beliefs—sentiment and disagreement—about stock market returns during the COVID-19 pandemic using a large number of investor messages, about 3.7 million, on a social media investing platform, StockTwits. The rich and multimodal features of StockTwits data allow the authors to explore the evolution of sentiment and disagreement within and across investors, sectors, and even industries. The authors find that sentiment (disagreement) has a sharp decrease (increase) across all investors with any investment philosophy, horizon, and experience between February 19, 2020, and March 23, 2020, when a historical market high was followed by a record drop. Surprisingly, these measures have a sharp reversal toward the end of March. However, the performance of these measures across various sectors is heterogeneous. Financial and healthcare sectors are the most pessimistic and optimistic divisions, respectively. TOPICS:Security Analysis and Valuation, quantitative methods, big data/machine learning, financial crises and financial market history, performance measurement Key Findings ▪ Daily time series of the sentiment and disagreement is not a stationary process. ▪ Sentiment (disagreement) has a sharp decrease (increase) across all investors with any investment philosophy, horizon, and experience between February 19, 2020, and March 23, 2020, when a historical market high was followed by a record drop. ▪ The financial and healthcare sectors are the most pessimistic and optimistic divisions, respectively.

This paper demonstrates how people deceive themselves into thinking of themselves as altruistic. I present a lab experiment in which subjects need to decide whether to behave altruistically or selfishly in an ambiguous environment. Due to the nature of ambiguity in this environment, those who are pessimistic have a legitimate reason to behave selfishly, even if they are inherently altruistic. For people who are inherently selfish but like to think of themselves as altruistic, this environment can serve as a scapegoat for selfish behavior. That is, by falsely claiming to be pessimistic, individuals can behave selfishly without damaging their self-image of being altruistic. Through two seemingly unrelated experimental tasks, I elicit subjects’ adopted beliefs and true beliefs about the same probability. I find that selfish subjects adopt beliefs that are systematically more pessimistic beliefs than their true beliefs, whereas altruistic subjects adopt beliefs that are in alignment with their true beliefs. The most plausible explanation for why only selfish subjects manipulate their beliefs is that selfish behavior damages their self-image and belief manipulation helps them mitigate that damage; altruistic subjects, by contrast, have no such need for belief manipulation because their behavior does not damage their self-image.

This paper aims to compare the pessimistic character of Spasse’s Jon Zaveri and Goethe's Werther. Although the novels were written in different periods, “Why?!” (Albanian: Pse?!) by the Albanian author Sterjo Spasse, in the thirties of the twentieth century, and “The Sorrows of Young Werther” (German: Die Leiden des jungen Werthers), by the German author Johan Wolfgang Goethe, in the seventies of the seventeenth century, they have their similarities and contradictions, which is natural given the fact of the social and economic circumstances of both the Western European and European Balkan areas. Goethe's Werther, although much earlier in time than Spasse’s Jon, lived in an environment that bears no resemblance to the environment in which Jon was born, raised, and formed. Werther, was traditionally rich, educated, and wandered around different places. His social circle was of an intellectual and artistic level. There is talk of ballrooms, pianos, music, novels, drawing, travel, and great writers...while, in Jon's social circle, especially where we deal with family and social conventionalism, it is completely different even though we are almost in the second half of the twentieth century. Jon is the only villager who leaves the village and goes to the city to get educated, while all the villagers are not only in mentality, but also in their clothes they wear still traditional. This is also beautifully portrayed at the time of John's wedding, when his family arrange a marriage getting him married to his wife Aferdita! She is a bride in traditional village style clothes, as described by Jon, just like all the wedding guests, with the exception of Jon, who had changed his dressing style, getting dressed as a citizen. The most obvious commonality in the characters of the novels “Why?!” and “The Sorrows of Young Werther”, is the pessimism of both and the suicide of both. John commits suicide in the lake by disagreeing with the marriage and fails to understand love, while Werther is madly in love, a love that leads him to suicide. So, Jon commits suicide by not finding the WHY of life and young love, which he never managed to understand or experience, while Werther fails to find the WHY of not making true the dream of his love, love which blinds him and takes him to the peak of pessimism, to suicide! Goethe's Werther is influenced as a personality by the world of art, while Spasse’s Jon is influenced by the world of philosophers.

We investigate gender differences across multiple dimensions after 3 months of the first UK lockdown of March 2020, using an online sample of approximately 1,500 Prolific respondents’ residents in the UK. We find that women's mental health was worse than men along the four metrics we collected data on, that women were more concerned about getting and spreading the virus, and that women perceived the virus as more prevalent and lethal than men did. Women were also more likely to expect a new lockdown or virus outbreak by the end of 2020, and were more pessimistic about the contemporaneous and future state of the UK economy, as measured by their forecasted contemporaneous and future unemployment rates. We also show that between earlier in 2020 before the outbreak of the Coronavirus pandemic and June 2020, women had increased childcare and housework more than men. Neither the gender gaps in COVID-19-related health and economic concerns nor the gender gaps in the increase in hours of childcare and housework can be accounted for by a rich set of control variables. Instead, we find that the gender gap in mental health can be partially accounted for by the difference in COVID-19-related health concerns between men and women.

This paper explores the effects of public information (e.g., accounting earnings) in a competitive lending setting where the borrower can engage in risk shifting. If a privately informed "inside" creditor bids against outsider creditors, public information levels the playing field with nontrivial effects on bidding and risk-shifting. A perfect public signal would yield the least efficient outcome: introducing some measurement noise alleviates risk shifting by subjecting the outsider to the winner's curse. However, for pessimistic priors about the borrower, greater precision can alleviate risk shifting, locally. We derive conditions under which greater signal precision lowers the probability of creditor turnover and discuss implications for financial reporting regulations along the business cycle.

This paper characterizes incomplete preferences with optimism and pessimism (IPOP) over Anscombe-Aumann acts, a class of preference orders that may fail axioms that require the decision-maker to think contingently. The main result axiomatizes preferences that compare any pair of distinct acts in such a way that an act is ranked higher than another act if and only if the minimal expected utility from the former is still greater than the maximal expected utility from the latter. This representation has a natural interpretation as conservative attitudes of the decision-maker under contingencies. The representation reduces to the standard SEU preferences when belief sets are minimal, while it encapsulates obvious dominance, the decision criterion proposed by Li (2017), as the polar case of when belief sets are maximal.

This study examines the effect of macroeconomic uncertainty on the accuracy of management earnings forecasts. Focusing on Japanese management earnings forecasts, which are effectively mandated, I find that during periods of high macroeconomic uncertainty, firms tend to report accurate earnings forecasts. I also find that macroeconomic uncertainty lessens optimistic but not pessimistic errors. These findings are consistent with the scenario that managers try to avoid missing their forecasts or revising their forecasts downward because investors place greater weight on bad news when macroeconomic uncertainty is high. Consistent with this scenario, additional analyses reveal that firms experience a larger decrease in stock prices when they miss their forecasts or revise their forecasts downward under high macroeconomic uncertainty. Moreover, these findings are robust after controlling for the effect of earnings management. These results suggest that the usefulness of management forecasts does not decrease even when macroeconomic uncertainty is high.

We show that a firm’s one-year-ahead capital investments and inventory increase (decrease) when peer firms’ MD&A narratives become more optimistic (pessimistic). This finding is driven by firms that access peer firms’ 10-K filings within seven days of filing, and remains after controlling for other determinants of a firm’s investments as well as economic connections between the firm and peer firms. Moreover, a firm’s investment response varies according to content in peer firms’ MD&A narratives. For instance, a firm makes more (less) capital investments when peer firms become more optimistic in their industry/investment-related (competition-related) narratives. Our findings provide broad insights on the information content and proprietary costs of MD&A disclosures.

Using a survey with randomized elements and truth-telling incentives, we document scientists’ beliefs about current and future disruptions to their research and how these beliefs depend on the eventual length of the COVID-19 pandemic. Overall, scientists with more favorable ratings of their institution’s response to the pandemic have more optimistic forecasts, even when controlling for their current level of disruptions. This relationship holds even amongst groups with the most pessimistic forecasts, who should be prioritized as science policy responses continue to develop.

This paper contributes to the policy discussion on COVID-19 by presenting evidence on firms’ perceived shock in the immediate aftermath of the pandemic outbreak, and exploring heterogeneities in the associated disruption of longer-run R&D choices. We take advantage of unique panel data on 7,800 Italian companies between January 2020 –right before the pandemic– and March of the same year –in the midst of lockdown policies. We then exploit the revision in firms’ research plans and expectations within this short-time window to capture the idiosyncratic impact of the epidemic event. Our analysis shows greater fragilities for internationalized companies and firms involved in (cutting-edge) product innovations. Their significantly-more pessimistic expectations in the short-run are also reflected into a sizable disruption of preexisting R&D plans, which will likely have a relevant impact on long-run growth. Beyond the role played by expectations, we show that the very characteristics of the innovative process critically shape firms’ reaction to the general uncertainty induced by the pandemic outbreak. Two main patterns seem to emerge from our analysis. On the one hand, there is a strong degree of persistence in R&D choices for a small set of great innovators, with substantial past expenditure in in-house research activities. On the other, the COVID-19 shock especially jeopardized R&D plans of newly-innovative companies that were transitioning toward more-dynamic ways of doing business. Taken together, our results help the policy maker identifying ideal targets for interventions so to avoid the disruption of key segments of the market. This is of double importance in this stage of the crisis whereby a second pandemic wave may entail some regularities.

The causal nexus between socio-economic insecurity and anti-immigration sentiments remains unclear despite correlational evidence. We exploit the disruption brought about by the Covid-19 outbreak to randomly provide survey respondents with information about the consequences of the epidemic. We find that pessimistic information about both the economic and health consequences causally reinforces the desire to restrict access to health care to native residents. Further, the prospect of dire economic consequences brings about a general adversity to immigration as well as political radicalisation. Both effects are less pronounced in areas with larger immigrant populations. Our theoretical model pins down two possible mechanisms explaining these results: a zero-sum game to split scarce public resources between residents and immigrants on the one hand and, on the other, fear of contagion. These also shape the tradeoff between prioritizing residents and extending vaccination programmes to immigrants to lower contagion risk.

This paper studies a life-cycle model economy in which agents utilize idiosyncratic information to forecast personal income risk. Agents either inherit full information (``dynastic households") or learn to forecast lifetime income using personal employment data given incorrect initial beliefs (``non-dynastic households"). We find that the distribution of initial beliefs regarding the transition probabilities into and out of unemployment greatly impact both aggregate savings and the stationary wealth distribution in a simple model economy. The wealth Gini coefficient in a model economy comprised solely of dynastic agents is 18%-52% lower than in the simulations with both dynastic and non-dynastic households. Optimistic households accumulate less wealth and are more likely to enter states of unemployment with little or no savings and pessimistic households over-accumulate wealth relative to households who inherit correct beliefs. Further, our framework shows how the welfare of rational agents and the value of holding correct beliefs depends on the beliefs of other agents.

The research in this paper explores the aggregate potential impact of the 2020 market crisis as well as assumptions with respect to future employee and employer behavior in response to the current situation and potential decreases in defined contribution eligibility arising from increased unemployment. The combined impact of all intermediate assumptions (including the investment losses already experienced in the first quarter of 2020) certainly appears to be manageable: The $3.68 trillion aggregate deficit for all U.S. households ages 35–64 as of January 1, 2020, only increased 4.5 percent or $166.21 billion. Even the combination of pessimistic assumptions in this analysis only increased the aggregate retirement deficits by 11.2 percent or $412.77 billion. Of course, the crisis could result in unexpectedly worse outcomes — market losses could be even greater, plan terminations more common, etc. Further, this analysis is not meant to minimize the potential impact of the current situation on specific individuals who are most affected. A future EBRI Issue Brief will focus on the latter. Another paper will analyze the impact of the Coronavirus Aid, Relief, and Economic Security (CARES) Act on retirement income adequacy, factoring in the potential ability of affected workers to take much bigger loans and withdrawals than they could even during the 2007–2009 financial crisis.

This paper documents a negative cross-transmission of bank-idiosyncratic credit risk events to the equity value of peers comprising other banks, insurance and real estate firms inter alia. Large jumps in the idiosyncratic component of bank CDS spreads significantly reduce the equity value of peers, particularly on the event day. The negative externality does not hinge on the “information connectedness” between the two entities as proxied by characteristics such as common core line of business, common country or region, and inter-country common legal tradition. The negative externality is stronger in turmoil market conditions when risk-aversion levels are higher and/or investors are subject to pessimism. The more fragile the risk profile of the event bank and peer firm prior to the event the stronger the cross-transmission. The findings lend support to the wake-up call paradigm at micro level, and are insightful towards a better assessment of the vulnerability of the financial system.

Using the gradual lifting of the short-sale ban in the Chinese stock market from 2010 to 2019 as natural experiments, the paper studies mutual funds’ strategies towards short-sales. The difference-in-difference regressions consistently show that mutual funds hold fewer shares when stocks are allowed to sell short, and their shareholding reduction towards short-selling is more intensive in stocks with higher valuation, larger market value, higher profitability, higher investment rate or more media coverage. These results are robust in short-term and long-term sample, annual data and classified funds. Our findings suggest that mutual funds generally dislike short-selling activities, and since short-sellers process negative information to alleviate stocks’ overvaluation, or spread pessimistic beliefs to undervalue high-quality stocks, mutual funds’ dislike towards short-selling reinforces in overvalued or high-quality stocks.

The COVID-19 global pandemic has caused significant global economic and social disruption. In McKibbin and Fernando (2020), we used data from historical pandemics to explore seven plausible scenarios of the economic consequences if COVID-19 were to become a global pandemic. In this paper, we use currently observed epidemiological outcomes across countries and recent data on sectoral shutdowns and economic shocks to estimate the likely impact of COVID-19 pandemic on the global economy in coming years under six new scenarios. The first scenario explores the outcomes if the current course of COVID-19 is successfully controlled, and there is only a mild recurrence in 2021. We then explore scenarios where the opening of economies results in recurrent outbreaks of various magnitudes and countries respond with and without economic shutdowns. We also explore the impact if no vaccine becomes available and the world must adapt to living with COVID-19 in coming decades. The final scenario is the case where a given country is in the most optimistic scenario (scenario 1), but the rest of the world is in the most pessimistic scenario. The scenarios in this paper demonstrate that even a contained outbreak (which is optimistic), will significantly impact the global economy in the coming years. The economic consequences of the COVID-19 pandemic under plausible scenarios are substantial and the ongoing economic adjustment is far from over.

We show that much of the market premium for the year occurs on a handful of days, identifiable well in advance, on which several of the market's most famous, high-media-attention firms simultaneously announce earnings after the market close. Puzzlingly, the market surges occur during the 24 hours prior to the earnings announcements, from close to close. Since there is no overlap between the price increase period and the information revelation, the high returns do not appear to represent a risk premium, and our tests seem to rule out information-leakage explanations. Deepening the puzzle, the market delivers high returns only prior to post-close earnings-announcement clusters, not in advance of clusters that occur in the pre-open period. In addition to being economically large and easily tradeable, the effect is statistically significant, and the results hold consistently throughout our sample. We argue that the best explanation for our findings is that of Miller (1977) as extended by Hong and Stein (2007): when over a short “attention” period difference of opinion combines with short-sale constraints, prices will rise as optimists buy while pessimists cannot sell.

Despite thousands of gun deaths annually, the United States has failed to reach consensus on any means of addressing the public health crisis that is gun violence. The issue has become politically polarized, constitutionalized, and an object of pessimism and despair. We propose a regulatory system in which gun manufacturers would be strictly liable to a federal fund for deaths caused by their guns, paired with a subsidy that will serve to ensure the availability of guns sufficient to meet the rights the Supreme Court has found in the Second Amendment. While strict liability of this kind can indeed serve its traditional purposes of spreading costs and incentivizing better designs and processes, our primary goal is to alter the political economy around the issue of gun violence more generally. If manufacturers bear an increasing share of the costs created by their products, they will endeavor not only to produce products and advertise them in ways likely to reduce those costs but also to advocate for regulations that may do the same. While our proposal may not depolarize the issue entirely, it at least attempts to focus the minds and experience of those who know guns best on effective means of reducing guns’ social costs.

Research in the field of behavioral ethics finds that much unethical behavior is not the result of conscious amorality. Rather, cognitive and motivational biases enable and even encourage people who consider themselves to be pro-social to act badly without ever recognizing the shortcomings of their behavior. This Article, delivered as the annual Chris Beecroft, Jr. Memorial Lecture on Dispute Resolution at the UNLV Boyd School of Law, explores how the findings of behavioral ethics can help to better understand, predict, and potentially combat unethical behavior in legal negotiation. Its admittedly pessimistic conclusion is that legal negotiation is an activity that is likely to be rife with behavior that is unethical, or at least presses hard against ethical boundaries. The Article summarizes the core findings of behavioral ethics research, explains why this research suggests that deceptive behavior will be common in negotiation, argues that the agency role played by lawyers in legal negotiation likely also encourages unethical behavior, and, finally, propose steps that lawmakers or negotiators themselves might take to reduce the amount of deceptive behavior in legal negotiation.