Center for Cognitive and Decision Sciences, Department of Psychology, University of Basel.
German Institute for Economic Research.
J Pers Soc Psychol. 2021 Feb;120(2):538-557. doi: 10.1037/pspp0000287. Epub 2020 Mar 2.
People's risk preferences are thought to be central to many consequential real-life decisions, making it important to identify robust correlates of this construct. Various psychological theories have put forth a series of candidate correlates, yet the strength and robustness of their associations remain unclear because of disparate operationalizations of risk preference and analytic limitations in past research. We addressed these issues with a study involving several operationalizations of risk preference (all collected from each participant in a diverse sample of the German population; = 916), and by adopting an exhaustive modeling approach-specification curve analysis. Our analyses of 6 candidate correlates (household income, sex, age, fluid intelligence, crystallized intelligence, years of education) suggest that sex and age have robust and consistent associations with risk preference, whereas the other candidate correlates show weaker and more (domain-) specific associations (except for crystallized intelligence, for which there were no robust associations). The results further demonstrate the important role of construct operationalization when assessing people's risk preferences: Self-reported propensity measures picked up various associations with the proposed correlates, but (incentivized) behavioral measures largely failed to do so. In short, the associations between the 6 candidate correlates and risk preference depend mostly on how risk preference is measured, rather than whether and which control variables are included in the model specifications. The present findings inform several theories that have suggested candidate correlates of risk preference, and illustrate how personality research may profit from exhaustive modeling techniques to improve theory and measurement of essential constructs. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
人们的风险偏好被认为是许多重要现实生活决策的核心，因此确定这一结构的稳健相关因素非常重要。各种心理学理论提出了一系列候选相关因素，但由于风险偏好的不同操作化和过去研究中的分析局限性，它们之间的关联的强度和稳健性仍不清楚。我们通过一项涉及风险偏好的几种操作化（均从德国人口的多样化样本中的每个参与者收集；n = 916）的研究，以及采用详尽的建模方法——规范曲线分析，解决了这些问题。我们对 6 个候选相关因素（家庭收入、性别、年龄、流体智力、晶体智力、受教育年限）的分析表明，性别和年龄与风险偏好之间存在稳健且一致的关联，而其他候选相关因素则显示出较弱且更（领域特定的）关联（晶体智力除外，其没有稳健的关联）。研究结果进一步证明了在评估人们的风险偏好时，结构操作化的重要性：自我报告的倾向度量与所提出的相关因素有各种关联，但（激励）行为度量则没有这样的关联。简而言之，6 个候选相关因素与风险偏好之间的关联主要取决于如何测量风险偏好，而不是模型规格中是否包含以及包含哪些控制变量。本研究结果为提出风险偏好候选相关因素的几种理论提供了信息，并说明了人格研究如何从详尽的建模技术中受益，以改进对重要结构的理论和测量。
