A Laboratory Study of Bayesian Updating in Small Feedback-Based Decision Problems | Science Publications

American Journal of Applied Sciences

Takemi Fujikawa¹  Sobei H. Oda¹ 

关键词: Sequential search;    Bayesian updating;    small feedback-based decision problems;    experiment;    JEL Classification: C91;    D81;    D83;   

DOI  :  10.3844/ajassp.2005.1129.1133

学科分类：自然科学（综合）

来源: Science Publications

【 摘 要 】

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.

【 授权许可】

Unknown