Estimating the Critical Parameter in Almost Stochastic Dominance from Insurance Deductibles

• 成果类型: Article
• 署名作者: Huang, Yi-Chieh; Kan, Kamhon; Tzeng, Larry Y.; Wang, Kili C.
• 署名单位: National Central University; Academia Sinica - Taiwan; National Taiwan University; National Taiwan University; National Chengchi University; Tamkang University
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2020.3768
• 发表日期: 2021
• 页码: 4742-4755
• 关键词: almost stochastic dominance; generalized almost second-degree stochastic dominance; preference parameter; automobile theft insurance; deductible

摘要

Knowing how small a violation of stochastic dominance rules would be accepted by most individuals is a prerequisite to applying almost stochastic dominance criteria. Unlike previous laboratory-experimental studies, this paper estimates an acceptable violation of stochastic dominance rules with 939,690 real world data observations on a choice of deductibles in automobile theft insurance. We find that, for all policyholders in the sample who optimally chose a low deductible, the upper bound estimate of the acceptable violation ratio is 0.0014, which is close to zero. On the other hand, considering that most decision makers, such as 99% (95%) of the policyholders in the sample, optimally chose the low deductible, the upper bound estimate of the acceptable violation ratio is 0.0405 (0.0732). Our results provide reference values for the acceptable violation ratio for applying almost stochastic dominance rules.