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In the insurance market, each life insurance policy is purchased on one household member’s life, so it is important to consider individual life insurance demand at the policy level even when viewing household economy as a whole. Given the fact that the majority of married couples have two wage earners nowadays in the US, it becomes more essential to study the division of life insurance demand between the working couples and further understand the risk sharing effect within a household. In literature, the effect of one’s earnings on the spouse’s life insurance demand remains a subject of debate. This paper aims to discuss this subject and contributes to look in particular at the joint decision of life insurance holdings between working couples and further discuss the determinants of life insurance demand in different types of households. The focus is to study the life insurance demand by examining individual life insurance holdings in a household through a heterogeneous-agent life cycle model with the rationale of household lifetime utility maximization. In the model, the household’s optimal life cycle decisions of consumption, savings, labor supply, and life insurance purchases are obtained. The model results indicate that, if the wife’s working ability increases, the household will expand the life insurance demand on the wife while the change of the husband’s life insurance is ambiguous. In the benchmark economy with independent income assumption, one’s positive wage shock can increase the one’s life insurance yet decrease the spouse’s. But the two experimental economies with dependent income assumption suggest that one’s growing earnings may increase the spouse’s life insurance demand when the one’s future earnings are related to the spouse’s mortality risk and income. The model results also show that life insurance in the single-parent household peaks earlier than the couple household, and suggest that one’s life insurance demand is positively associated with the one’s income and the number of children, while is ambiguously related to household wealth. The analysis of the model economy implies that the life insurance demand of a household is dominantly determined by financial vulnerability at its early ages with low income and small wealth, and by financial supports needed and premiums at its old ages with large wealth, small number of children and high mortality risk.


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19 Jul 2022
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  • Subject
    • Business

  • Date submitted

    19 July 2022

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    • Author Biography:

      Dr. Ning Wang is currently an Assistant Professor of Finance in the Mike Cottrell College of Business at the University of North Georgia. She served as an Assistant Professor of Finance at Valdosta State University from 2013 to 2017 and received her Ph.D. degree in risk management and insurance at Georgia State University in 2013. Dr. Wang’s research interests include applications of dynamic modeling in financial economics, insurance markets, dynamic modeling, personal financial planning, and catastrophic risk management. Dr. Wang teaches the courses of principles of finance, investment management, and financial policy at the undergraduate level at the University of North Georgia and expects to teach the MBA finance course in future. She mainly taught healthcare financial management, financial management, advanced corporate finance, computer applications in financial management, risk management and insurance, and personal finance at either undergraduate or MBA levels when she worked at Valdosta State University. Dr. Wang has published four papers about financial and insurance markets in academic peer-reviewed journals. She has also presented several working papers in prestigious academic conferences in the areas of finance and insurance, such as the annual meetings of American Risk and Insurance Association, Financial Management Association, Western/Southern Risk and Insurance Association, and Academy of Financial Services, and she also holds the membership of these associations. This paper is based on Dr. Wang’s dissertation which was awarded the Dissertation Grant at Georgia State University in 2013.