Learning in a multilateral bargaining experiment
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多边议价实验中的学习
- 研究问题
- 多数决议价实验中的行为如何随经验演变，以及面板相关和玩家异质性的处理会怎样影响共同学习模型的检验？
- 方法与思路
- 作者建立学习模型，调整标准误以反映面板结构，并提出考虑玩家异质性的有效估计量，比较两种修正规则下的行为。
- 材料陈述的贡献
- 摘要称标准误调整影响推断，共同学习模型在两类估计下得到不同检验结论，且估计信念受到不止最近一次结果的影响。
- 阅读关注点
- 应核对实验规则、学习与信念更新方程、面板相关调整方式，以及异质性估计如何改变跨规则模型限制的检验。
- 阅读边界
- 摘要未说明样本规模、估计量条件和效应数值；拒绝与未拒绝仅是所述检验结果，不能据此确认某种学习机制为真。
原文摘要
This paper analyzes data from an investigation of a majoritarian bargaining experiment. A learning model is proposed to account for the evolution of play in this experiment. It is also suggested that an adjustment must be made to account for the panel structure of the data. Such adjustments have been used in other fields and are known to be important as unadjusted standard errors may be severely biased downward. These results indicate that this adjustment also has an important effect in this application. Furthermore, an efficient estimator that takes into account heterogeneity across players is proposed. A unique learning model to account for the paths of play under two different amendment rules cannot be rejected with the standard estimator with adjusted standard errors, however it can be rejected using the efficient estimator. The data and the estimated learning model suggest that after proposing "fair"Â divisions, subjects adapt and their proposals change rapidly in the treatment where uneven proposals are almost always accepted. Their beliefs in the estimated learning model are influenced by more than just the most recent outcomes.