A Laboratory Study of Bayesian Updating in Small Feedback-Based Decision Problems
- 1 School of Economics and Finance, University of Western Sydney, Australia
- 2 Faculty of Economics, Kyoto Sangyo University, Japan
Abstract
This study explores small feedback-based decision problems experimentally. Conducted were the experiments in which the decision-maker’s payoff distribution was limited to either favorable distribution or unfavorable distribution. The first remarkable observation revealed complexity/loss aversion in the experiment. The second observation included the law of small numbers. Deviations from maximization were also observed. Finally, we investigated the imperfect Bayesian decision-makers observed in the experiment by exploring to what extent the decision-makers could update subjective Bayesian probability and rely on it in making decisions.
DOI: https://doi.org/10.3844/ajassp.2005.1129.1133
Copyright: © 2005 Takemi Fujikawa and Sobei H. Oda. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- 3,052 Views
- 2,189 Downloads
- 1 Citations
Download
Keywords
- Sequential search
- Bayesian updating
- small feedback-based decision problems
- experiment
- JEL Classification: C91
- D81
- D83