Modeling Repeated Choice Behaviors of Automobile Insurance Policies for New Car Owners
Lawrence W. Lan
|關鍵字:||汽車保險保單;離散選擇模式;重複選擇行為;成對組合羅吉特;Automobile insurance policies;Discrete choice model;Repeated choice behaviors;Paired combinatorial logit model|
本研究的模式架構分為兩大部分：第一部分為車體損失險保單的選擇；第二部分為非車體保單（例如第三人責任險及其他附加險）的選擇。本研究的重點放在第一部分，探討投保人每年持續選擇車體險種的問題。研究方法採用離散選擇模式，替選方案包含車體險種及持續投保相同險種的年數。離散選擇模式考慮多項羅吉特模式(multinomial logit model)、巢式羅吉特模式(nested logit model)、及成對組合模式(paired combinatorial logit model)。
Car owners purchase appropriate automobile insurance policies (AIP) to provide coverage for property damages and personal injuries incurred by traffic accidents. Physical damage coverage, the most expensive policy, is the major source of incomes for non-life insurance companies in most countries today. However, new car owners are likely to purchase physical damage coverage in the first few years and then downgrade their insurance by purchasing reduced coverage or not buying any physical damage coverage in the subsequent years. As such, premium revenues for non-life insurance companies will be substantially reduced. The study is motivated by the importance of developing a modeling framework to gain insights into the insured’s choice for AIP. The research develops a model system that consists of two components: the first component is the decision to select different types of physical damage coverage; the second component is the choice of non-physical damage coverage involving third party liability as a basic protection with additional coverage. This study focuses on the first component and, particularly, explores repeated choices of different types of physical damage coverage. A discrete choice modeling framework including the choice of physical damage coverage type and the number of consecutive years that the insured has purchased the same type of coverage is further developed. Various discrete choice models including multinomial logit, nested logit, and paired combinatorial logit are attempted. The proposed modeling framework is empirically illustrated using a panel data provided by a non-life insurance company in Taiwan. The results indicate that the repeated choices of AIP are influenced by age of the driver, vehicle make, and engine capacity. The nested logit model statistically rejected the multinomial logit model, which demonstrates the statistical and structural superiority of the nested logit model in analyzing the insured’s repeated choices. Although the paired combinatorial logit model is more flexible than the multinomial logit and nested logit models, estimation of such model becomes very difficult when the number of alternatives gets large. The model framework developed in the study has improved our understanding of the repeated choices of AIP, and the estimation results have provided valuable implications for the insurer to modify existing automobile insurance policies or to develop marketing strategies so as to enhance repurchase intention of the insured.
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