Estimating the Critical Parameter in Almost Stochastic Dominance from Insurance Deductibles

Yi-Chieh Huang (), Kamhon Kan (), Larry Y. Tzeng () and Kili C. Wang ()
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Yi-Chieh Huang: Department of Business Administration, National Central University, Taoyuan City 320317, Taiwan
Kamhon Kan: Institute of Economics, Academia Sinica, Taipei City 115201, Taiwan
Larry Y. Tzeng: Department of Finance, National Taiwan University, Taipei City 106319, Taiwan; Center for Research in Econometric Theory and Applications, National Taiwan University, Taipei City 106319, Taiwan; Risk and Insurance Research Center, National Chengchi University, Taipei City 116011, Taiwan
Kili C. Wang: Risk and Insurance Research Center, National Chengchi University, Taipei City 116011, Taiwan; Department of Risk Management and Insurance, Tamkang University, New Taipei City 251301, Taiwan

Management Science, 2021, vol. 67, issue 8, 4742-4755

Abstract: 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.

Keywords: almost stochastic dominance; generalized almost second-degree stochastic dominance; preference parameter; automobile theft insurance; deductible (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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