Miracle-dz/UniFAR-FTUs huggingface dataset:
Socially Interdependent Investment

We report the results of an economic experiment on how social preferences and behavioral imitation lead to the social clustering of investment decisions, even if the expected return of the underlying asset is known. During the experiment, subjects are asked how much of their endowment they wish to allocate in an asset to which there is a 50% chance the amount they invest will be tripled and a 50% chance their investment will be lost. To study the social interdependence of investment decisions we use a 2 x 2 factorial design varying: (i) whether the subjects initially observed high or low investment social anchors, (ii) whether information about the investment decisions of other subjects in their social group is provided. Overall, we find strong evidence that individuals' investment decisions are malleable to the investment decisions of their peers, which in turn leads to the social clustering of investment decisions. Furthermore, social anchors shape initial investment levels, leading to mean investment rates that are double in size in the high anchor treatment relative to the low anchor treatment.
The influence of personality traits on university performance: Evidence from Italian freshmen students

Despite several attempts to provide a definite pattern regarding the effects of personality traits on performance in higher education, the debate over the nature of the relationship is far from being conclusive. The use of different subject pools and sample sizes, as well as the use of identification strategies that either do not adequately account for selection bias or are unable to establish causality between measures of academic performance and noncognitive skills, are possible sources of heterogeneity. This paper investigates the impact of the Big Five traits, as measured before the beginning of the academic year, on the grade point average achieved in the first year after the enrolment, taking advantage of a unique and large dataset from a cohort of Italian students in all undergraduate programs containing detailed information on student and parental characteristics. Relying on a robust strategy to credibly satisfy the conditional independence assumption, we find that higher levels of conscientiousness and openness to experience positively affect student score.
Outside Options Drive Wage Inequalities in Continuing Jobs: Evidence From a Natural Experiment

The literature on wage bargaining so far mainly argues that unemployment benefits are relevant outside options for employees. This paper demonstrates that also a change in outside wage options drives wages in continuing jobs. We use the natural experiment of a crafts reform that reduces outside wage options for a clearly defined treatment group of employees in deregulated crafts occupations in comparison to employees in crafts occupations that have not been reformed. Five years after the reform,the wages of employees in deregulated crafts increased by five percent less than wages of employees in the other group. Reform effects are concentrated in employers with high increases in their median wage level after the reform. Wage differences therefore seem to be the result of wage renegotiations initiated by employees,rather than renegotiations initiated by employers.Works councils or collective bargaining, firm size, firm profits or regional unemployment have no impact on wage differentiation after taking wage increases into account. We show for the first time that changes in outside options induce wage differentiation at the employer level even in the tightly regulated German labour market. We use entropy matching on the basis of a large representative administrative linked employer-employee panel data set to guarantee homogeneous treatment and control groups before the reform.We isolate the outside wage option effect from other wage determinants by restricting our sample to employers not affected by the crafts reform.
Beta Uncertainty

A stock's exposure to systematic risk factors is surrounded by substantial uncertainty. This beta uncertainty is both economically and statistically significantly priced in the cross-section of stock returns. Stocks with high beta uncertainty substantially under-perform those with low beta uncertainty: a two-standard-deviation increase in the measure decreases average annual returns by 9.7%. These results cannot be explained by previously discovered determinants of cross-sectional stock returns. Aggregate beta uncertainty negatively predicts market excess returns in the short and medium term. We find supporting evidence for a mis-pricing explanation of the beta uncertainty premium.
Slipping on Stereotypes – Gender Effects in the Erosion of Ethical Behavior

Ethical outcomes in organizations can strongly be influenced by gender constellations and related stereotypical ascriptions in the workplace. In this paper, we investigate experimentally how people’s gender affects ethical outcomes in repeated same- or mixed-gender interactions. In our first study (N = 681), we apply a slippery slope auditing setting (Gino and Bazerman, 2009) in which an auditor takes an approval decision on the unethical behavior of an “estimator” (the audited firm) that emerges either suddenly – in an “abrupt treatment”, or gradually – in a “slip- pery slope” treatment. We find that in same-gender estimator-auditor constellations, there are no significant differences in auditors’ approvals of overestimated amounts between the abrupt and the slippery slope treatment. Strikingly, in mixed-gender constellations, we find significant opposite effects: when male estimators are audited by females, we observe a significant slippery slope effect, caused by a high approval frequency of overestimations in the slippery slope treat- ment. Contrarily, when female estimators are audited by a males, approval frequencies spike in the abrupt treatment. To better understand these findings, in a second study (N = 90), we asked participants which level of competence or honesty they ascribe to male and female esti- mators in the estimation task. Responses indicate that the detected slippery slope effect when male estimators are audited by females may be driven by female auditors ascribing more com- petence to male estimators, what becomes particularly relevant in the slippery slope treatment where unethical behavior is difficult to perceive. Further, our finding that male auditors are especially prone to approve overestimated amounts by females in the abrupt treatment, where unethical behavior becomes salient, might root in a more ethical evaluation of female estimates. Implications for organizations are discussed.
Do stock markets play a role in determining COVID‐19 economic stimulus? A cross‐country analysis

Abstract This paper makes an innovative contribution to the extant literature by analysing the determinants of economic stimulus packages implemented by governments in response to the COVID‐19 pandemic. In particular, we explore whether stock market declines observed in many countries can predict the size of COVID‐19 stimulus packages. Moreover, we explore whether a country's level of income can augment the underlying relationship between stock market declines and stimulus packages. The findings reveal that a larger stock market decline results in a larger stimulus package; however, this effect is only observed in countries that have an income level greater than the mean and/or median per capita gross domestic product (GDP). Moreover, our results show that monetary policy is more responsive to a stock market decline than fiscal policy. Thus, our results underscore the importance of international donor agencies such as the World Bank and International Monetary Fund (IMF) in supporting less affluent countries in coping with the adverse impacts of the COVID‐19 pandemic on their economies.
Stock Market Return Predictability Before and After the Dodd-Frank Act

We analyze the stock market return predictability for three different periods. We evaluate the conditional variance (CV) and the variance risk premium (VRP) as predictors of stock market returns for which we are using well-established versions of the heterogeneous auto-regressive (HAR) model and propose two new semi-parametric extensions. Results show that the CV and VRP are predictors of future stock market returns in the period before the global financial crisis (GFC). However, these variables lose predictive power after the Dodd-Frank Act (DFA) and change sign, indicating that investors are willing to pay a risk premium for "good uncertainty".
COVID-19, Recession and Fall in Real Wages in Argentina. Who Will Be Most Affected?

This paper explores the aggregate and systematic income risk of formal workers in Argentina, using an extensive longitudinal database that contains information on approximately half a million formal employees in the private sector throughout the country for a span of twenty years (1996-2015). We estimate pooled quantile regression models to measure the sensitivity of remunerations to the economic cycle along the conditional distribution of salaries, which allow us to capture the heterogeneity of Gross Domestic Product (GDP) impacts on different conditional quantiles. The main result is that estimated income risk decreases monotonically along the conditional distribution of salaries, showing that individuals located at the lower part of the distribution are more exposed to the fortunes of the aggregate economy. One important factor that probably explains this difference in salary elasticity is given by the role of the unions. Although this decreasing pattern on elasticity remains when we separate estimates by economic sector and firm size, we found some specificities, since males that work in Construction sector and small firms are those with higher income risk. These estimates allow us to approximate the magnitude of the impact of the current recession in Argentina, which is deepening due to the COVID-19 pandemic.
Turn-of-the-Year Effect in Asia Pacific Stock Markets: New Evidence

This paper examines a well-known seasonal anomaly - the turn-of-the-year (TOY) effect in fifteen Asia Pacific stock indices by using an updated dataset and forward-looking methods. The analysis utilizes daily dataset that spans from January 2000 to December 2018. Applying the Ordinary Least Square (OLS) regression and EGARCH approach, the results of this paper suggest that the TOY effect becomes detectable again after the GFC in developed stock markets with tax year not ending in December. Oppositely, the magnitude of this anomaly has diminished in the emerging financial markets after the GFC, which is consistent with the EMH. The evidence of the leverage effect in the unconditional volatility is proposed that volatility in negative shocks is considerably higher than that of positive shocks across examined stock indices. This phenomenon is more conspicuous in mature stock indices compared to emerging indices. The positive connection between the leverage effect and stock market volatility is propositioned as diminishing magnitude of this effect during the stable market condition after the GFC. Our findings lend reinforcement to the conclusion that some Asia Pacific stock markets satisfy the weak form of the EMH.
Doing Safe by Doing Good: Non-Financial Reporting and the Risk Effects of Corporate Social Responsibility

Abstract We compare the effects of corporate social responsibility (CSR) on firms' equity risk under two different (non-)financial reporting regimes: the risk-based U.S. and the content-based EU system. We observe a strongly negative CSR-risk relation in the EU, but a much weaker general impact in the U.S. In correspondence with goal-framing theory, we find several moderating effects on this association, depending on the reporting regime: (i) A highly volatile market environment unfolds the risk-reducing effect of CSR in the U.S. system, but has no moderating effect in the EU; (ii) Rising CSR awareness buttresses the risk-reducing effect of CSR in the EU, but has an opposing effect in the U.S.; (iii) Risk reductions are most strongly associated with social and governance rather than environmental activity in the EU regime, while there are no such individual effects in the U.S.
Online Supplement to an Incidental Parameters Free Inference Approach for Panels with Common Shocks

This paper develops a novel Method of Moments approach for panel data models with endogenous regressors and unobserved common factors. The proposed approach does not require estimating explicitly a large number of parameters in either time-series or cross-sectional dimension, T and N respectively. Hence, it is free from the incidental parameter problem. In particular, the proposed approach does not suffer from ``Nickell bias'' of order O(1/T), nor from bias terms that are of order O(1/N). Therefore, it can operate under substantially weaker restrictions compared to existing large T procedures. Two alternative GMM estimators are analysed; one makes use of a fixed number of ``averaged estimating equations'' a la Anderson and Hsiao (1982), whereas the other one makes use of ``stacked estimating equations'', the total number of which increases at the rate of O(T). It is demonstrated that both estimators are consistent and asymptotically mixed-normal as N goes to infinity for any value of T. Low-level conditions that ensure local and global identification in this setup are examined using several examples.
Sustainable News – A Sentiment Analysis of the Effect of ESG Information on Stock Prices

We investigate the effect of Environmental, Social, and Governance (ESG) related news sentiment on the stock market performance of the Dow Jones Industrial Average (DJIA) constituents. Relying on a large data set of news articles that were published online or in print media between the years of 2010 and 2018, we extract each article's sentiment with respect to ESG-related topics using a dictionary approach and calculate a polarity-based sentiment index. Estimating autoregressive distributed lag models reveals significant effects of both temporary and permanent changes in ESG-related news sentiment on idiosyncratic returns for the vast majority of the DJIA constituents. According to the models' results, we can assign the stocks to different groups depending on their investors' apparent predisposition towards ESG-news, which in turn seems to be linked with a stock's financial performance.
Does Social Media Sentiment Matter in the Pricing of U.S. Stocks?

This paper applies a recently developed social media-based sentiment proxy for the construction of a new risk factor for sentiment-augmented asset pricing models on U.S. equities. Accounting for endogeneity, autocorrelation and heteroskedasticity in a GMM framework, we ﬁnd that the inclusion of sentiment signiﬁcantly improves the performance of the ﬁve-factor model from Fama and French (2015, 2017) for di ﬀ erent industry and style portfolios like size, value, proﬁtability, investment. The sentiment risk premium provides the missing component in the behavioral asset pricing theory of Shefrin and Belotti (2008) and (partially) resolves the pricing puzzles of small extreme growth, small extreme investment stocks and small stocks that invest heavily despite low proﬁtability.
The Effect of Endorsement on Nascent Venture Success: When is the royal Seal an Asset for your Start-up?

Nascent ventures struggle to connect to providers of resources that are pivotal for their survival and growth, such as capital and talent. Organizational endorsement helps these ventures to increase their visibility and perception of their value in the eyes of the resource providers and therefore to overcome their liability of newness and improve their legitimacy. In this paper we investigate the e ffect of endorsement on the success of nascent ventures to access the required resources. We demonstrate the effect of endorsement and propose conditions that make this e ffect stronger for some nascent ventures. We leverage a unique dataset of 1,391 nascent ventures that have applied to participate in pitch events hosted by a venture development organization (VDO) founded by the Royal Family in the UK. We confi rm our central hypothesis on the positive impact of endorsement on the success of the selected nascent ventures to acquire investment ex post the pitch event. Moreover, we find that the endorsement signi ficantly benefi ts ventures at their medium level of maturity (i.e. their stage of product or service development) and/or located in environments with low munifi cence (i.e. availability of resource providers). Our fi ndings provide more granular insights into the mechanics of endorsement as a specifi c form of organizational sponsorship.
One Session Options: Playing the Announcement Lottery?

One session options (OSO) are unique financial instruments that perfectly fit the criteria for a lottery-type asset; a low-price (average premium of 1 b.p.) coupled with a relatively small probability of a large payoff. Using intra-day data for over 12.8 million intra-day option contracts on the 3-Year Treasury Bond, we examine trading behaviour in the OSO market over the period 2002-2019. We find that trading volume is higher on days with a major macroeconomic announcement, and concentrated earlier in the trading session, prior to the data release. Trading volume tends to be higher when there is a difference of opinion surrounding the announcement outcome or when the level of economic policy uncertainty is higher. Trading in OSO has some predictive value for the surprise component of the macroeconomic announcement, but this does not translate into economic profits. While there is a positive option payoff on average, the average net profit is negative once premiums are accounted for. Our results are robust to different measures of uncertainty, market activity, and model form. It seems likely that OSO trading behaviour is best explained by ‘differences of opinion’.
Strategic Trading when the Market Maker Has a Monopoly on Short-Lived Information

This paper develops a strategic trading model in which the market maker has a monopoly on short-lived information. Given that modern market makers are high frequency traders, it is assumed that market makers are able to process any short-lived information event faster than other traders. Since the market maker’s information is short-lived, informed traders sequentially learn about it and adjust their strategies accordingly. The correlation structure of the market maker’s short-lived information has significant effects on the dynamic trading equilibrium and can generate new stylized facts like negative trading intensities and non-monotonic news sensitivities.
Adding Value Through Cross-Border M&A: Evidence from the Netherlands

Purpose: The aim of this thesis is to research corporate geographic diversification to determine if cross-border M&amp;A involving Dutch acquirers and a selection of countries are value-enhancing for Dutch acquirers. Moreover we will aim to identify variables which influence value-creation in Dutch cross-border M&amp;A. <br><br>Methodology: This paper applies a deductive approach using theories and previous studies to form hypotheses for the purpose of the study. Event study and multiple linear regression analyses are used to test the hypotheses. <br><br>Empirical Foundation: Cross-Border M&amp;A between Dutch-based acquiring firms with target firms from a selection of countries were empirically studied between 01-01-1980 till 30-04-2014. <br><br>Conclusion: Our findings show that cross-border acquisitions by acquirers from the Netherlands generally create value. Looking at the source of value-creation from a country level perspective, we found evidence that value is mainly created in acquisitions of targets based in Germany, United Kingdom and the United States. Furthermore we found positive value creation for acquisitions of targets based in North America and Western Europe. Our results are in line with an existing study on Dutch cross-border acquisitions which found evidence of value creation in acquisitions of target firms from North America and Western Europe. Determinants found to influence value-creation were relative deal size and the legal status of the target firm (public vs. non-public). We did not find significant evidence for other determinants examined in this study.
Crypto Covered Interest Parity Deviations

Studying deviations from covered interest rate parity (CIP) in the Bitcoin/US-Dollar (BTC/USD) market, we find large CIP deviations of up to 15% until Q1/2018. Afterwards, CIP deviations have been subdued, which we attribute to the market entry of high-frequency traders (HFTs). We argue that these market entries have increased efficiency of cryptocurrency markets with respect to CIP as well as liquidity, volatility, and bid-ask spreads. Remarkably, these efficiency gains are larger for the less liquid cryptocurrency Litecoin. Employing a difference-in-differences design, we show that the launch of the BTC/USD future at the Chicago Mercantile Exchange (CME) did not affect market efficiency. Finally, remaining CIP deviations after Q1/2018 seem mostly related to increased credit risk of certain crypto exchanges.
Herding in Probabilistic Forecasts

Decision makers often ask experts to forecast a future state. Experts, however, can be biased. In the economics and psychology literature, one extensively studied behavioral bias is called herding. Under strong levels of herding, disclosure of public information may lower forecasting accuracy. This result, however, is derived only for point forecasts. In this paper, we consider experts’ probabilistic forecasts under herding, find a closed-form expression for the first two moments of a unique equilibrium forecast, and show that the experts report too similar locations and inflate the variance of their forecasts because of herding. Furthermore, we show that the negative externality of public information no longer holds. In addition to reacting to new information as expected, probabilistic forecasts contain more information about the experts’ full beliefs and interpersonal structure. This facilitates model estimation. To this end, we consider a one-shot setting with one forecast per expert and show that our model is identifiable up to an infinite number of solutions based on point forecasts but up to two solutions based on probabilistic forecasts. We then provide a Bayesian estimation procedure for these two solutions and apply it to economic forecasting data collected by the European Central Bank and the Federal Reserve Bank of Philadelphia. We find that, on average, the experts invest around 19% of their efforts into making similar forecasts. The level of herding shows an increasing trend from 1999 to 2007 but drops sharply during the financial crisis of 2007–2009 and then rises again until 2019. This paper was accepted by Yan Chen, behavioral economics and decision analysis.