Date: October 30, 2025 (12:30 pm – 1:30 pm)

Speaker: Francesca Bastianello

Paper Title: Biases in Belief Updating Within and Across Domains

Paper Authors: Francesca Bastianello and Alex Imas

Abstract: We study variation in over and underreaction both within and across domains. Focusing on the learning domains of forecasting and inference, we develop a framework that nests both problems in the same information environment. By mapping features that are relevant in forecasting (persistence and horizon) to features that are relevant in inference (signal strength), we propose a model of bounded memory and limited attention that explains biases in both domains through a common psychological mechanism. Across-domains, variation in over and underreaction is due to different tasks cueing different initial perceptions (“default frames”) of the information environment. Within-domains, variation is due to limited attention and insufficient adjustment of those frames. Exploiting our multi-feature environment, we transfer inference lessons to forecasting, and develop predictions for multivariate settings. First, more neglected features drive more variation in over and underreaction. Second, interactions among features can turn insensitivity to one into excess sensitivity to another, reversing the classic inference result of underreaction to strong signals and overreaction to weak signals. A series of experimental studies provide support for the model and underlying mechanism.

Bio: Francesca Bastianello’s research interests lie at the intersection of finance, macroeconomics, and behavioral economics. In her research she builds on insights from behavioral economics to develop tractable models of non-rational beliefs, and studies their aggregate financial and macroeconomic implications.

Bastianello earned a Ph.D. in Business Economics from Harvard University, and also holds an M.Phil. in Economic Research and a B.A. in Economics from the University of Cambridge, Trinity College.