Financial student aid leads to better educational and economic outcomes, yet a persistent gap exists between take-up and eligibility. Using a survey among 22,222 university students across Germany, I elicit perceived individual eligibility and general perceptions about student aid through hypothetical case scenarios. 63% of the non-receivers of student aid systematically underestimate its financial value and 87% of eligible students misperceive their eligibility status. In an experiment with 6,225 non-receivers, I show that concise information about student aid and individual entitlement causally reduces misperceptions, and increases take-up rates for student aid by 1.1 pp (47%). Students from low socioeconomic status react more strongly to the intervention. Using the intervention as instrument shows that correcting misperceptions causes an increase in the likelihood for take-up by ~50 pp. Take-up of student aid increases students’ total income while reducing financial strain on parents. The findings imply that providing information can help tackle social inequality by correcting misperceptions and triggering disadvantaged students to take up.

Manuscript in preparation.

Social benefits programs aim to tackle social inequality, but across the world, take-up is often less than half of eligibility rates. Using survey data from 22,222 students in Germany, we identify students who are eligible but do not take up student aid, and analyze how misperceptions about personal eligibility and about the program itself drive non-take-up. We find that 78.6% of eligible students who do not receive aid mistakenly believe to be ineligible, and that misperceptions about the eligibility criteria determine their non-take-up. Additionally, having a close friend or family member who receives aid significantly increases the likelihood of take-up, indicating that sharing experiences and knowledge plays a crucial role. The results suggest that informing individuals about their entitlement and the program, in combination with providing clear instructions on how to claim aid, can increase take-up and help reduce social inequality.

Manuscript in preparation.

We argue that many interventions fail to shift behavior in the intended direction because they do not address the underlying problem. We develop a parsimonious, and generalizable anamnesis questionnaire to identify the underlying problem. The questionnaire classifies the underlying problem along three archetypical diagnoses: awareness, intention, and implementation problems.  This allows us to predict the effectiveness of interventions across different contexts. We test our conceptual framework in an online experiment with 7,500 subjects. Across three different settings, our diagnosis predicts when interventions such as reminders, monetary incentives, and simplifications succeed or fail. On average, a 1% increase in predicted effectiveness corresponds to an 1.2% increase in actual effectiveness. Choosing an intervention based on a diagnosis increases the treatment effect size by around 70% compared to randomly choosing one of the tested interventions.

Manuscript in preparation.

We design a comprehensive experimental setup to study (i) intrinsic preferences for gradual information revelation (ii) with different skewness (positive, negative, or symmetric) (iii) in two information environments. In a “compound lottery” environment, symmetric information revelation is preferred, while in an otherwise equivalent “information structure” environment, positively skewed information revelation is preferred. In both environments, early resolution is preferred over late resolution, with the three types of gradual resolution positioned in between. Our study integrates the three dimensions (timing, skewness, environment) of intrinsic preferences only studied separately to date, relates the findings to behavioral theories, and shows that careful consideration of the information environment is necessary when investigating preferences for gradual information revelation.

Revised manuscript in preparation.

We study utility-based intensity measures of higher-order risk preferences and their relation to field behavior in a representative German sample of 2970 adults. Using a new method based on the elicitation of certainty equivalents and a machine learning approach, we find that 85%, 77%, and 62% express risk-averse, prudent, and temperate behavior, respectively. Interestingly, also among risk seekers, more than 70% behave prudentially, which extends to the intensive margin and documents mixed risk aversion and mixed risk-seeking behavior. Age, gender, education, and religion are significantly related to risk aversion, prudence, and temperance. Our intensity measures of risk preferences are significantly related to financial decision-making, job choice, and addictive behaviors. Importantly, field behavior that according to economic theory is insufficiently explained by risk aversion alone is significantly predicted by prudence, where risk aversion mostly remains insignificant.

Manuscript in preparation.