Measuring Probabilistic Risk Attitudes

• 成果类型: Article; Early Access
• 署名作者: Nascimento, Arnaldo; Ng, Che Tat; Gonzalez, Richard
• 署名单位: University of Waterloo; University of Michigan System; University of Michigan
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2024.04870
• 发表日期: 2025
• 关键词: PROBABILITY WEIGHTING FUNCTIONS; Measures; probabilistic risk attitude

摘要

We introduce formal measures for two psychological factors of probabilistic risk attitudes: attractiveness (motivational factor) and discriminability (cognitive factor). Unlike previous approaches that relied on heuristic proxies, our measures precisely capture these two fundamental factors. Our measures are mathematically tractable, robust to discontinuities, such as in the NEO-additive case, and flexible to be applied to any weighting function, as well as to both small and large probabilities. Additionally, through detailed numerical analysis, we examine to what extent existing weighting function parameters capture the two factors: attractiveness and discriminability. Finally, using these new measures, we provide a formal understanding of the independence between motivational and cognitive factors.