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Household Life Insurance Demand

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  • Edward Frees
  • Yunjie (Winnie) Sun

Abstract

What types of households own life insurance? Who owns term life and who owns whole life insurance? These are questions of great interest to insurers that operate in a highly competitive market. To answer these questions, we jointly examine household demand of two types of insurance, term and whole life, using data from the Survey of Consumer Finances, a probability sample of the U.S. population. We model both the frequency and the severity of demand for insurance, building on the work of Lin and Grace by using explanatory variables that they developed. For the frequency portion, the household decisions about whether to own term and whole life insurance are modeled simultaneously with a bivariate probit regression model. Given ownership of life insurance by a household, the amounts of insurance are analyzed using generalized linear models with a normal copula. The copula permits the bivariate modeling of insurance amounts for households who own both term and whole life insurance, about 20% of our sample. These models allow analysts to predict who owns life insurance and how much they own, an important input to the marketing process.Moreover, our findings suggest that household demand for term and whole life insurance is jointly determined. After controlling for explanatory variables, there exists a negative relationship for a household’s decision to own both whole and term life insurance (the frequency part) and a positive relationship for the amount of insurance purchased (the severity part). This indicates that the greater the probability of holding one type, the smaller the probability of holding the other type of life insurance. However, higher demand for both types of insurance exists when a household decides to own both. This mixed effect extends prior work that established a negative relationship, suggesting that term life insurance and whole life insurance are substitutes for one another. In contrast, our findings reveal that the ownership decision involves substitution, but, for households owning both types of insurance, amounts are positively related. Therefore, term and whole life insurance are substitutes in the frequency yet complements in the severity.

Suggested Citation

  • Edward Frees & Yunjie (Winnie) Sun, 2010. "Household Life Insurance Demand," North American Actuarial Journal, Taylor & Francis Journals, vol. 14(3), pages 338-354.
  • Handle: RePEc:taf:uaajxx:v:14:y:2010:i:3:p:338-354
    DOI: 10.1080/10920277.2010.10597595
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    Citations

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    Cited by:

    1. Jiang Cheng & Lu Yu, 2019. "Life and health insurance consumption in China: demographic and environmental risks," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 44(1), pages 67-101, January.
    2. Barry Mulholland & Michael Finke & Sandra Huston, 2016. "Understanding the Shift in Demand for Cash Value Life Insurance," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 19(1), pages 7-36, March.
    3. Hwang, In Do, 2024. "Behavioral aspects of household portfolio choice: Effects of loss aversion on life insurance uptake and savings," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1029-1053.
    4. Tan Andrew K. G. & Yen Steven T. & Hasan Abdul Rahman & Muhamed Kamarudin, 2014. "Demand for Life Insurance in Malaysia: An Ethnic Comparison Using Household Expenditure Survey Data," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 8(2), pages 179-204, July.
    5. Edward W. Frees & Gee Lee & Lu Yang, 2016. "Multivariate Frequency-Severity Regression Models in Insurance," Risks, MDPI, vol. 4(1), pages 1-36, February.
    6. Chu-Shiu Li & Gene C. Lai & Saruultuya Tsendsuren & Richard J. Butler & Chwen-Chi Liu, 2023. "Cognitive abilities and life insurance holdings: evidence from 16 European countries," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 48(1), pages 110-166, March.
    7. Yulia Hristova, 2022. "Life Insurance Penetration Drivers in Bulgaria," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 6, pages 98-119.
    8. Côté, Marie-Pier & Genest, Christian & Omelka, Marek, 2019. "Rank-based inference tools for copula regression, with property and casualty insurance applications," Insurance: Mathematics and Economics, Elsevier, vol. 89(C), pages 1-15.
    9. Cassandra R. Cole & Stephen G. Fier, 2021. "An examination of life insurance policy surrender and loan activity," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(2), pages 483-516, June.

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