The results of eliciting risk preferences are highly dependent on the elicitation method used. This raises the question of how risk preferences can be reliably elicited. Using item response theory (IRT), the results of four elicitation methods describing common latent variables identified as risk preferences are combined into a composite score. The responses of 9235 individuals to a dedicated survey indicate that the composite score is a more accurate estimation of latent risk preferences than the results of individual methods, substantially reducing measurement noise and method-specific biases. IRT improves accuracy by allowing variable weighting to be dependent on the most relevant range of each method in estimating latent risk preferences. Therefore, the composite score contains more information about latent risk preferences than the results of either factor-weighted or unweighted methods. Manipulating the specific amounts, order and starting point of the multiple price list method shows that the accuracy of this method is not impervious to framing effects. Combining simpler methods with more advanced methods, which are all framed closely to the relevant situation, yields a more accurate and more robust estimation of latent risk preferences.

中文翻译：

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测量潜在风险偏好：最小化测量偏差

引出风险偏好的结果高度依赖于所使用的引出方法。这就提出了如何可靠地引出风险偏好的问题。使用项目反应理论 (IRT)，将描述被识别为风险偏好的常见潜在变量的四种启发方法的结果组合成一个综合评分。9235 个人对一项专门调查的回应表明，综合评分比单个方法的结果更准确地估计了潜在风险偏好，大大减少了测量噪音和特定于方法的偏差。IRT 通过允许可变权重依赖于估计潜在风险偏好的每种方法的最相关范围来提高准确性。所以，与因子加权或未加权方法的结果相比，综合评分包含更多关于潜在风险偏好的信息。操纵多价目表法的具体数量、顺序和起点表明该方法的准确性不受框架效应的影响。将更简单的方法与更高级的方法相结合，这些方法都与相关情况密切相关，可以对潜在风险偏好进行更准确、更稳健的估计。