Generative AI (GenAI) shifts data disclosure from a one-off act into an iterative co-creation process, where users repeatedly decide whether, what, and how much information to reveal and how it should be processed through prompts. We propose prompt literacy—the ability to strategically craft, interpret, and refine prompts—as a core dimension of AI literacy that determines how individuals navigate this process. Prompt literacy not only enhances perceived benefits by enabling more tailored and valuable outcomes, but also encourages deeper and more frequent disclosure, thereby heightening perceived risks. This dual effect creates an inherent tension in GenAI interactions. Our findings show that prompt literacy fosters self-investment in the disclosure process, which in turn shapes privacy value perceptions (i.e., the cumulative effect of benefits and risks). Through this self-investment, individuals perceive greater ownership of the outcomes, ultimately leading to more positive privacy value assessments. Notably, this positive effect is especially salient in data-rich contexts. By integrating insights from privacy, co-creation, and AI literatures, this research investigates key factors in privacy value formation and offers implications for the design of GenAI tools and literacy interventions. Johanna Zimmermann*, Jan H. Schumann, Yakov Bar, Koen Pauwels (*presenting author)

We consider a model of price and quality competition in which consumers perfectly observe prices but can distinguish qualities only if their differences are large enough. Assuming that producers can vary prices and quantities much faster than quality we show for the duopoly case (Betram or Cournot competition while quality is fixed) that – depending on their discount rates – producers will either stay with socially optimal quality or enter a regular sawtooth wave of fluctuating quality and prices. In particular, this wave is characterized by consecutive reductions of quality and price interrupted by sudden and substantial upswings of quality to a level at, or larger than, the social optimum and a corresponding larger price. Average quality and social welfare during the sawtooth wave are less than in social optimum. Quality regulation may interrupt the sawtooth wave, but if it is too weak, it will further reduce average quality and social welfare.

Natural disasters are growing in frequency globally. Understanding how vulnerable populations respond to these disasters is essential for effective policy response. This paper explores the short- and long-run consequences of the 1906 San Francisco Fire, one of the largest urban fires in American history. Using linked Census records, I follow residents of San Francisco and their children from 1900 to 1940. Historical records suggest that exogenous factors such as wind and the availability of water determined where the fire stopped. I implement a spatial regression discontinuity design across the boundary of the razed area to identify the effect of the fire on those who lost their home to it. I find that in the short run, the fire displaced affected residents, forced them into lower paying occupations and out of entrepreneurship. Experiencing the disaster disrupted children’s school attendance and led to an average loss of six months of education. While some effects attenuated over time, the negative effect on occupational earnings and business ownership persist even in 1940, 34 years after the fire. Therefore, my findings reject the hope for a “reversal of fortune” for the victims, in contrast to what is found for more recent natural disasters such as hurricane Katrina.

We examine whether risk-taking for others varies with the number of people affected. In a series of online experiments, agents made investment decisions for groups of different sizes (1, 5, 10, 25, 50, and 100 principals) under two incentive conditions. In the FLAT condition, agents had no skin in the game and received no payoff. The CONVEX condition created an asymmetric setting that privatized gains and socialized losses: successful investments paid both principals and agents, while failed investments affected only the principals. Across three studies, participants made sequential and simultaneous decisions in a within-subject design, as well as a single decision in a between-subjects design. The results are inconclusive, as strong order effects dominated the outcomes. We discuss implications. (Sascha Füllbrunn and Wolfgang Luhan)

Economic narratives are pervasive in the public discourse and can shape individual behavior. But so far we know very little about whether house- holds actually demand and value narratives as information. We combine a large-scale expert survey with a nationally representative household sample in the U.S. to examine the demand for economic narratives in a high-stakes environment of an unprecedentedly high recession probability. We document a substantial willingness to pay for economic narratives of more than 4 USD, which is even higher than for numerical forecast information. The WTP systematically varies across demographics, being higher for women, younger, high-income, and high-education respondents. The dominant motives for acquiring narratives are intrinsic, but a smaller share also lists instrumental motives. Economic narratives shape respondents’ expectations about future economic conditions, their understanding of recession drivers, and their spending beliefs. Our findings underscore the potential of narratives as a tool to im- prove economic understanding and to foster more informed decision-making.