Research talks with Jana Schuetz and Jiaoying Pei

Meeting time: Tuesday, May 19, at 5pm CET. The session lasts about 90 minutes. The Zoom-link will be available here one day before the session.

At this session we will have two 30 min presentations from junior researchers, Jana Schuetz and Jiaoying Pei. Each presentation will be followed by about a 10 min discussion. All are welcome to attend. 

Jana Schuetz (Jönköping International Business School): Financial literacy is an important prerequisite for making informed financial decisions, but it remains low, especially among women and older people. Internalized stereotypes can undermine confidence and subsequently affect behavior in financial matters, leading to suboptimal decisions. This paper investigates how stereotype salience affects confidence in financial literacy. In an information provision experiment, we inform respondents about age or gender differences in numeracy to examine the impact on financial literacy, confidence, hypothetical investment and saving decisions, and demand for information and education. We find that being informed about age differences has no significant effect. In contrast, being informed about gender differences increases the confidence of male respondents through a stereotype boost, while leaving female respondents largely unaffected.

Jiaoying Pei (University of Cambridge): We amend adaptive expectations (AE) to make it robust in the face of nonstationarities such as those emerging in self-referential forecasting systems. We borrow insights from robust control in engineering and propose that the learning rate α in adaptive expectations is to be modulated in a way to minimize surprise relative to a reference model. As reference, we suggest the Kalman filter model recently used in a study examining how professional forecasters predict economic outcomes. We show how this prescribes changing α in the direction of autocovariance of prediction errors. We refer to the resulting forecasting model as Robust Expectations Adaptation REA. Ours contrasts with the traditional prescription in reinforcement learning, which is to change α in the direction of the change in the size of the prediction error, the Pearce-Hall model, recently imported in the economics literature. Using 40,000+ forecasts from experiments on self-referential economic markets, we discover that participants change α as in REA, but generally only if surprise is above the median experienced by the individual. The Pearce-Hall model almost never fits the data.