Research Seminars

In the burgeoning realm of cryptocurrency, social media platforms like Twitter have become pivotal in influencing market trends and investor sentiments. In our study, we leverage GPT-4 and a fine-tuned transformer-based BERT model for a multimodal sentiment analysis, focusing on the impact of emoji sentiment on cryptocurrency markets. By translating emojis into quantifiable sentiment data, we correlate these insights with key market indicators like BTC Price and the VCRIX index. This approach informs the development of trading strategies aimed at utilizing social media sentiment to forecast market trends. Crucially, our findings suggest that strategies based on emoji sentiment can facilitate the avoidance of significant market downturns and contribute to the stabilization of returns. This research underscores the practical benefits of integrating advanced AI-driven analyses into financial strategies, offering a nuanced perspective on the interplay between digital communication and market dynamics in an academic context.

Paper available at SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4722627

Uncertainty shocks cause economic activity to contract and more so, if an effective lower bound on interest rates constrains monetary policy. In this paper, we investigate whether countries within currency unions are also particularly prone to suffer from the adverse effects of heightened uncertainty because they lack monetary independence. First, we estimate a Bayesian VAR on quarterly panel data for 16 Euro Area countries. We find that country-specific uncertainty shocks impact economic activity adversely. Second, we calibrate a DSGE model of a small open economy and show that it can account for the evidence. Finally, we show that currency union membership strongly reduces the effects of uncertainty shocks because it anchors long-run expectations of the price level and thus alleviates precautionary price setting in the face of increased uncertainty.

We investigate how information regarding production externalities (e.g. ecolabels) can be presented to create market pressure on firms to reduce said externalitites. Specifically, we ask whether integrating information regarding externalities and consumer product ratings into one rating, can result in pressure to reduce externalities from all consumers, not just ‘green/activist’ consumers. Theoretically we show that an equilibrium exists where producers invest in both high product quality and low production externality. However, we show that with separate ratings, this equilibrium requires a high share of ’green’ consumers who only wish to purchase products with low production externalities, whereas with combined ratings it does not. Experimentally we confirm the prediction that both separate and combined ratings help overcome the product quality asymmetric information problem, and find investments in externality reduction were substantially higher in the combined rating treatment.

We investigate Italy's teacher assignment system, where teachers can rank geographical regions (municipalities, districts, or provinces), leading to ties in their rank order lists (ROLs). The geographical structure significantly influences teachers' priority rights at different schools as well. Analyzing administrative data, we identify systematic violations of teachers' priority rights, resulting from the way ties in teachers' ROLs are resolved—a mechanism initially introduced to mitigate efficiency losses from random tie-breaking. To address these issues, we propose a new assignment mechanism that completely respects priority rights and Pareto improves over random tie-breaking. Additionally, our mechanism is strategy-proof for the teachers, unlike the current mechanism. Using administrative data, we quantitatively evaluate the potential improvements in fairness and welfare that could arise from implementing our proposed mechanism.

We analyze the impact of individual attitudes on market dynamics in a laboratory experiment with 320 participants under risk and imprecision, where imprecision is modelled in either probabilities, outcome realizations, or a combination of both. In two stages, we first elicit individual reservation prices for risky and imprecise lotteries and then analyze price dynamics in a continuous double auction environment with risky and imprecise fundamentals. Our results underpin the importance of whether imprecision is modelled in probabilities or outcomes on the individual level: On average, we find imprecision-in-outcomes seeking, but neutrality towards imprecision in probabilities, the combination of probabilities and outcomes, and risk. In markets, however, individual attitudes are overridden by market dynamics as past price developments are the main predictor for current realized prices. We find no significant differences between treatments with respect to market variables such as trading volume, volatility, and the dispersion of final asset holdings. Yet, at the market closing, we observe significant overpricing in the risk condition, as well as underpricing in conditions with imprecision in probabilities (supporting ambiguity aversion) and the combination of imprecise probabilities and outcomes, respectively.

This study examines how children spend their time differently across four categories of activities: chores, care, learning, and leisure. In particular, I am interested in the difference that between the decision to perform the activities and the hours they dedicate among boys and girls. The data used in this study is taken from the Tanzanian Integrated Labor Force (ILFS) survey, specifically the Time-Use module. The choice of country in particular is an attempt to describe the dynamic of time-use within a household in one of the developing countries, specifically from Sub-Saharan Africa. To estimate the probability of performing the role and time spent on each category, I use Cragg’s double hurdle model to handle the zero-inflated nature of the dependent variable. This study contributes to the understanding of gender gap issues in time use among children.

Do investors benefit when managers have a long-term perspective? The conventional narrative suggests that they do. This paper exploits the characteristics of language used in annual reports and offers a nuanced answer. Motivated by real option theory, our results indicate that long-term orientation tilts investment policy towards intangible assets that increase the firm’s valuable real options that are associated with greater idiosyncratic volatility, is associated with higher equity and debt value, and generally increases firm value when uncertain sentiment is high. These associations either disappear, or change sign, when uncertain sentiment is low. Overall, consistent with the implications of real option theory, our findings suggest that corporate long-termism is value-enhancing only when accompanied by high uncertainty.

This paper investigates the role of education as a possible barrier to the utilization of social protection programs. We focus on a large-scale free health insurance innovation in the province of Khyber Pakhtunkhwa, Pakistan. We are able to combine household panel data including detailed health information as well as household census data with administrative data on insurance enrollment and utilization. We show descriptively as well as controlling for temporal and spatial differences in the enrolment campaign, that education positively correlates with the utilization of the scheme, and that this correlation exists for both male and female education. Moreover, we exploit data on public school construction and use the establishment of girl schools as an instrument for local female education for causal inference. We find that female education significantly increases health insurance utilization on the individual as well as household level. The results suggest that this pro-poor social health protection program entails implicit barriers, making it less egalitarian than possibly intended.

The application of Agent-Based Modelling to Game Theory allows us to benefit from the strengths of both approaches, and to enrich the study of games when solutions are difficult to elicit analytically. Using an agent-based approach to sequential games, however, poses some issues that result in a few applications of this type. We contribute to this aspect by applying the agent-based approach to a lobbying game involving environmental regulation and firms’ choice of abatement. We simulate this game and test the robustness of its game-theoretical prediction against the results obtained. We find that while theoretical predictions are generally consistent with the simulated results, this novel approach highlights a few differences. First, the market converges to a green state for a larger number of cases with respect to theoretical predictions. Second, simulations show that it is possible for this market to converge to a polluting state in the very long run. This result is not envisaged by theoretical predictions. Sensitivity experiments on the main model parameters confirm the robustness of our findings.

Reducing out-of-pocket costs of medication has been shown to lead to higher use initiation rates in childhood. Less is known, however, about the potentially asymmetric effects of increases in such costs, resulting from a loss in insurance coverage. This paper looks at the expiration of prescription drug copay waivers for children in Slovakia to investigate changes in pharmaceutical use resulting from increasing out-of-pocket costs. Leveraging age thresholds for copay waivers, this paper uses event study analyses to show that increases in out-of-pocket costs reduce prescription drug use, as well as average spending. Using a dataset capturing the universe of prescriptions filled between 2016–2018, we are further able to understand these effects among both chronic and non-chronic users. We trace the effects of these changes in prescription drug use to down-stream health consequences for children, as measured by GP visits and hospitalizations. Linking these data to social security records, we are further able to understand spillovers onto parental health and employment.

Under social-genetic assortative mating (SGAM), socio-economic status (SES) and genetically inherited traits are both assets in marriage markets, become associated in spouse pairs, and are passed together to future generations. This gives a new explanation for persistent intergenerational inequality and observed genetic differences between rich and poor. We model SGAM and test for it in large surveys in two countries. Spouses of earlier-born siblings have genetics predicting more education. This effect is mediated by individuals' own education and income. Thus, shocks to SES are reflected in the DNA of subsequent generations. Under SGAM, genetic variation is endogenous to economic institutions.

We study the effect of a CZK 80,000 (36%) increase in parental allowance, a universal basic income-type benefit, on the labor supply of parents of young children in the Czech Republic. Drawing a parental allowance does not preclude labor market activity, which allows us to study the income effect. The reform led to a 6 percentage point (15%) decrease in labor market participation of mothers of young children. The effect is particularly strong among mothers with only one child (10 p.p., 28%) and among university-educated mothers (16 p.p., 36%). We observe a virtually identical reduction in hours worked. We found no effect on the labor supply of fathers of young children.

Luckman et al. (2018) experimentally tested the conjecture that a single model of risky intertemporal choice can account for both risky and intertemporal choices, and under the conditions of their experiment, found evidence supporting it. Given the existing literature, that is a remarkable result which warrants (conceptual) replication. A key reason to be sceptical about the result is that Luckman et al. (2018), following a well-established tradition in psychology, had first-year psychology students participate that were rewarded with non-monetary course credits (see also Luckman et al. 2020), casting shadows of doubt on whether their participants were properly incentivised. Proper incentivization is a long-standing bone of contention among experimentally working economists and psychologists and it is widely accepted among economists that the elicitation of risk preferences and time preferences is very much a function of the way that experimenters incentivize choices. Another reason to be sceptical is that the experiment was not properly powered up; hence the no-difference results reported by the authors might be spurious. In our conceptual replication, we find significant differences between the risky and intertemporal choices at both the group and individual level. We find further that there is no significant difference between choices made by participants that are paid a flat incentive and participants that are paid under the random incentive scheme, at the group level. We find that order effects matter for intertemporal choices, but not for risky choices. At the individual level, we find evidence in favour of the model that assumes a common value function, but separate choice functions. This result is robust across the incentive systems, and order of presentation, but sensitive to different prior distributions. Other semi-nested models are sensitive to the different orders of presentation as well as incentive systems.

We consider settings such as innovation-oriented R&D where agents must explore across different projects with varying but uncertain payoffs. How does providing partial data on project payoffs affect individual performance and social welfare? While data can typically reduce uncertainty and improve welfare, we present a simple theoretical framework where data provision can decrease group and individual payoffs. In particular, we predict that when data shines a light on sufficiently attractive (but not optimal) projects, it can crowd-out exploration activity, lowering individual and group payoffs as compared to the case where no data is provided. We test our theory in an online lab experiment where we show that data provision on the true value of one project can hurt individual payoffs by 12% and reduce the group's likelihood of discovering the optimal outcome by 48%. Our results provide a theoretical and empirical foundation outlining the conditions under which the streetlight effect emerges, where data leads agents to look under the lamppost rather than engage in individually and socially beneficial exploration.

Women are underrepresented in business, academic, and political decision-making bodies across the world. To investigate the causal effect of gender representation on multilateral negotiations, we experimentally manipulate the composition of triads in a majoritarian, divide-the-dollar game. We document a robust gender gap in earnings, driven largely by the exclusion of women from alliances rather than differential shares within alliances. Experiments with different subject pools show that distinct bargaining dynamics can underlie the same inequitable outcomes: While gender-biased outcomes can be caused by outright discrimination, they can also be driven by more complex dynamics related to differences in bargaining strategies. We identify two fundamental gender differences in bargaining dynamics. First, men are more likely to make opening offers and enjoy a payoff advantage for doing so, yet women that propose first do not and may even suffer backlash. Second, mixed-gender alliances are less stable when the excluded party is male rather than female. These findings show that there is no “one-size-fits-all” solution to the gender gap we uncovered and highlight the importance of studying bargaining dynamics in detail.

We provide causal evidence that mandatory portfolio disclosure helps investors evaluate and select hedge fund managers. Using a staggered difference-in-differences analysis, we demonstrate that investor capital flows better predict fund performance among funds that publicly disclose their portfolio holdings. Additional cross-sectional analyses suggest that this gain in selection ability varies with the informational value of disclosure. Furthermore, examining investor-level allocations, we find that institutional investors earn higher returns on their allocations to disclosing funds. Overall, these results help contribute to the cost-benefit analysis of mandatory portfolio disclosure.