Numerical Predictions and Decisions

Drawing on established ideas from behavioral economics, this project investigates how people make numerical predictions and decisions, with applications to finance and marketing contexts.

For example, after observing sustained increases in stock prices, what leads people to expect those trends to continue or reverse—reflecting the hot hand fallacy or the gambler's fallacy? In addition to previously identified determinants, what additional factors influence such beliefs?

Similarly, when individuals show increased commitment to a product or service simply because they paid for it—exhibiting the sunk cost bias—what overlooked factors underlie this behavior, and to what extent do those factors account for it?

Together, this project aims to improve our understanding of how people respond to quantitative information and how such responses shape behavior in managerial decision-making contexts.

The undergraduate research assistant's responsibilities will include compiling literature reviews, collecting and analyzing data, and contributing to other aspects of the research process as needed.