2026-10-08Antonio Penta(UPF) What’s in a u?. Room: E5.07, 12:00. We revisit the long-lasting debate about the meaning of the utility function used in Expected Utility (EU). Contrary to the common view that EU inherently links risk aversion to diminishing marginal utility, we demonstrate that these two concepts need not coincide. Marginal utility of money is an input into risk attitude, but it is not its sole determinant. An independent ‘pure risk’ attitude is also a contributing factor. We discuss some theoretical implications of this result for the following topics: non-neutral
risk attitudes for profit maximizing firms; risk, time and psychological distance; convex time budget decisions; the equity premium puzzle. We also discuss matters of identification: for firms; via proxies; via MLE methods under parametric restrictions; in intertemporal choice problems; and cross-domain elicitation in multi-dimensional settings, and its relationship with the methods and results from psychology.
2026-10-15Nicola Lacetera(Bologna) Trading Off Openness: Economic Information and Immigration Policy Preferences. Room: E5.22, 12:00. We conducted a survey experiment with over 8,000 participants in Germany, Hungary and Italy to examine how information about the economic impact of immigration affects the support for more open immigration policies. Respondents who received projections showing higher future incomes under more open immigration policies reported greater support for these policies. The treatment also partly changed how prior attitudes affected policy preferences. Structural estimates suggest that majority support for immigration above current levels would require annual per-capita income gains of about 1.2% in Italy and 1.7% in Germany, and greater or unattainable gains in Hungary. These large figures suggest that economic benefits alone are unlikely to generate substantial support for more open immigration policies.
2026-10-22Friederike Mengel(Essex) Perceptions of Social Influence in Networks. Room: E5.22, 12:00. In a series of laboratory and online experiments, we investigate the perceived and actual influence, direct and indirect, that early movers have over later movers in a sequential-move collective action game played on a network. Each human subject is assigned to a particular node in a specified 5 or 10 node network, and chooses “In” or “Out” knowing how many neighbors have previously chosen “In”. First-mover influence is measured as the proportion of network members who choose “In” following a first mover’s “In” versus “Out” choice. Influence is quite heterogeneous across nodes. Human subjects are aware of the influence their network position conveys and act on it, but tend to overestimate influence at poorly connected nodes. A simple adaptive learning model explains entry and perceptions of influence reasonably well, especially at well connected nodes.
2026-10-29Melis Kartal(WU Vienna) TBA. Room: E5.22, 12:00. No abstract available.
2026-11-10Tim Cason(Purdue) TBA. Room: E5.22, 12:00. No abstract available.
2026-11-19Rustamdjam Hakimov(University of Lausanne) TBA. Room: tba, 12:00. No abstract available.
2026-11-26Yiming Liu(WZB) Model-Directed Attention and the Persistence of Wrong Mental Models: Evidence from Firm Pricing. Room: E5.07, 12:00. We document a mechanism through which wrong mental models survive in data-rich environments: by remaining silent about the patterns they deem irrelevant, wrong models direct attention away from the patterns that refute them. We examine this in firm pricing under consumer intertemporal substitution (IS), where shifts in purchase timing add to the sales spike on the discount day and produce dips before and after. A simple model in which lower prices lead to higher sales is silent about the dips and attributes the spike entirely to new demand. In survey and administrative data from 13,000 gas station managers, over 40 percent neglect or underestimate IS, and those holding the simple model perceive demand as more elastic, set lower prices, and earn lower profits. Online experiments provide causal evidence. Holding the data fixed, subjects assigned the simple model are less likely to recall the dips and more likely to neglect IS than those assigned a model that explains the dips. Two interventions further support this mechanism: prompting attention to the dips lowers IS-neglect, and encountering an alternative model that is also wrong, but explains the dips, dislodges the simple model.
2026-12-03Agata Farina(University of Chicago) TBA. Room: E5.07, 12:00. No abstract available.
2026-12-10Nils Köbis(Duisburg-Essen) TBA. Room: E5.22, 12:00. No abstract available.
2026-12-14Sevgi Yuksel(NYU) TBA. Room: E5.07, 12:00. No abstract available.
