Initial anchors and limited information in learning-to-forecast experiments

• Published in: Journal of economic behavior & organization Vol. 225; pp. 192 - 227
• Main Author: Xiao, Wei
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.09.2024
• Subjects: Anchoring-and-adjustment; Behavioral learning; Bounded rationality; Learning-to-forecast; C53; C63; D84; Learning-to-forecast; Anchoring-and-adjustment; C91; C92; D83; Behavioral learning; Bounded rationality
• DOI: 10.1016/j.jebo.2024.06.038
• ISSN: 0167-2681

In this paper, I introduce two novel treatments into learning-to-forecast experiments: an initial anchor and a limited information treatment. The initial anchor pins down the subjects’ initial expectations and makes cross-session results more comparable. In the limited information treatment, subjects can only observe the most recent market outcome. Surprisingly, price dynamics do not differ between full and limited information sessions. This suggests that when making decisions, subjects disregard most information and rely primarily on a few recent observations. Furthermore, regardless of the market’s feedback system, positive or negative, subjects predominantly use a single heuristic to form expectations. •Two new treatments are introduced into learning-to-forecast experiments.•An initial anchor can successfully pin down subjects’ initial expectations.•In the limited-info treatment, subjects can only observe the most recent outcome.•Surprisingly, having more information does not improve subjects’ predictions.•Subjects use one heuristic to make predictions, regardless of the feedback system.