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A simple non-parametric method for eliciting prospect theory's value function and measuring loss aversion under risk and ambiguity
Theory and Decision ( IF 0.802 ) Pub Date : 2021-04-09 , DOI: 10.1007/s11238-021-09811-6
Pavlo Blavatskyy

Prospect theory emerged as one of the leading descriptive decision theories that can rationalize a large body of behavioral regularities. The methods for eliciting prospect theory parameters, such as its value function and probability weighting, are invaluable tools in decision analysis. This paper presents a new simple method for eliciting prospect theory’s value function without any auxiliary/simplifying parametric assumptions. The method is applicable both to choice under ambiguity (Knightian uncertainty) and risk (when events are characterized by objective probabilities). Our new elicitation method is implemented in a simple paper-and-pencil experiment (via an iterative multiple price list format). This is one of the first experiments that elicits non-parametric prospect theory’s value function with salient rewards. The collected data generally confirm findings in the existing literature: the value function is S-shaped (concave in the gain domain and convex in the loss domain) though there is a weaker loss aversion on the aggregate level and a substantial heterogeneity in loss aversion on the individual level (41% loss averse, 6% loss neutral and 53% gain seeking).



中文翻译:

一种简单的非参数方法,用于得出前景理论的价值函数并度量风险和歧义下的损失厌恶

前景理论作为主要的描述性决策理论之一而出现,可以使大量的行为规律合理化。得出前景理论参数(例如其价值函数和概率加权)的方法是决策分析中的宝贵工具。本文提出了一种在没有任何辅助/简化参数假设的情况下得出前景理论价值函数的简单方法。该方法适用于歧义下的选择(Knightian不确定性)和风险下的选择(当事件以客观概率为特征时)。我们的新启发方法是通过简单的纸笔实验(通过迭代的多个价目表格式)实现的。这是引发具有非凡前景的非参数前景理论的价值函数的首批实验之一。

更新日期:2021-04-09
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