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

B-Tier
Journal: Journal of Economic Behavior and Organization
Year: 2024
Volume: 225
Issue: C
Pages: 192-227

Score contribution per author:

2.018 = (α=2.02 / 1 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

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.

Technical Details

RePEc Handle
repec:eee:jeborg:v:225:y:2024:i:c:p:192-227
Journal Field
Theory
Author Count
1
Added to Database
2026-01-29