Life Insurance Purchasing to Maximize Utility of Household Consumption

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  • This article was downloaded by: [University of North Carolina]On: 07 October 2014, At: 14:00Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK

    North American Actuarial JournalPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/uaaj20

    Life Insurance Purchasing to Maximize Utility ofHousehold ConsumptionErhan Bayraktar a & Virginia R. Young aa Department of Mathematics , University of Michigan , Ann Arbor , MichiganPublished online: 11 Jul 2013.

    To cite this article: Erhan Bayraktar & Virginia R. Young (2013) Life Insurance Purchasing to Maximize Utility of HouseholdConsumption, North American Actuarial Journal, 17:2, 114-135, DOI: 10.1080/10920277.2013.793159

    To link to this article: http://dx.doi.org/10.1080/10920277.2013.793159

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  • North American Actuarial Journal, 17(2), 114135, 2013Copyright C Society of ActuariesISSN: 1092-0277 print / 2325-0453 onlineDOI: 10.1080/10920277.2013.793159

    Life Insurance Purchasing to Maximize Utilityof Household Consumption

    Erhan Bayraktar and Virginia R. YoungDepartment of Mathematics, University of Michigan, Ann Arbor, Michigan

    We determine the optimal amount of life insurance for a household of two wage earners. We consider the simple case of exponentialutility, thereby removing wealth as a factor in buying life insurance, while retaining the relationship among life insurance, income, andthe probability of dying and thus losing that income. For insurance purchased via a single premium or premium payable continuously,we explicitly determine the optimal death benefit. We show that if the premium is determined to target a specific probability of loss perpolicy, then the rates of consumption are identical under single premium or continuously payable premium. Thus, not only is equivalenceof consumption achieved for the households under the two premium schemes, it is also obtained for the insurance company in the senseof equivalence of loss probabilities.

    1. INTRODUCTIONThe problem of finding the optimal strategy for purchasing life insurance has not been studied nearly as much as the corre-

    sponding problem for life annuities; see Milevsky and Young (2007) and the many references therein for research dealing with lifeannuities. Notable exceptions are the seminal papers of Richard (1975) and Campbell (1980) and the more recent papers of Pliskaand Ye (2007), Huang and Milevsky (2008), Kraft and Steffensen (2008), Nielsen and Steffensen (2008), Wang et al. (2010),Kwak et al. (2011), Bruhn and Steffensen (2011), and Egami and Iwaki (2011). We highlight the last two articles because thatwork is closely related to the work in this article. Bruhn and Steffensen (2011) find the optimal insurance purchasing strategy tomaximize the utility of consumption for a household, in which utility of consumption is a power function. Thus, the optimal deathbenefit is related to the wealth of the household. Similarly, Egami and Iwaki (2011) maximize household utility of consumptionand terminal wealth at a fixed time and find that the optimal death benefit is a function of wealth because of the nature of theirutility function.

    In this article we focus on the idea that, when maximizing the utility of household consumption, life insurance serves as incomereplacement; therefore, the amount purchased should be independent of the households wealth. Indeed, when a wage earner dies,the wealth of the household remains, but the income of that wage earner is lost; life insurance can replace that lost income. Granted,life insurance is often awarded to the beneficiary in a single payment, but the beneficiary can use that payment to buy an annuity,which more clearly replaces lost income.

    To obtain an optimal amount of life insurance that is independent of the wealth of the household, we assume that utility ofconsumption is exponential. The resulting optimal death benefit is a function of the rates of mortality and rates of income of thehousehold but not of its wealth. An added bonus of using exponential utility is that the optimization problem greatly simplifies,and we explicitly express the optimal death benefit, the optimal rates of consumption (both before and after the death of a wageearner), and the optimal investment in the risky asset.

    The rest of the article is organized as follows: In Section 2 we model the household as two wage earners; the household wishesto maximize its (exponential) utility of consumption until the second death, with the possibility of purchasing life insurance thatpays at the first death. Additionally, we allow the household to invest in a risky and a riskless asset. In Sections 3 and 4 we solve the

    We thank the Committee for Knowledge Extension and Research of the Society of Actuaries for financially supporting this work. Additionally,research of Erhan Bayraktar is supported in part by the National Science Foundation under grants DMS-0955463, DMS-0906257, and the SusanM. Smith Professorship of Actuarial Mathematics. Research of Virginia R. Young is supported in part by the Cecil J. and Ethel M. NesbittProfessorship of Actuarial Mathematics.

    Address correspondence to Virginia R. Young, Department of Mathematics, University of Michigan, 530 Church Street, Ann Arbor, MI48109. E-mail: vryoung@umich.edu

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  • LIFE INSURANCE PURCHASING AND HOUSEHOLD CONSUMPTION 115

    optimization problem in the case of premium paid with a single premium or payable continuously until the first death, respectively.We find explicit expressions for the optimal amount of death benefit for the household, and we determine how that death benefitvaries with the underlying parameters. In Section 5 we compare the optimal rates of consumption from Sections 3 and 4 and showthat they are identical if premium is determined by targeting a specific probability of loss per policy.

    For those readers who wish to skip the mathematical content of the article, Section 6 provides a numerical example to illustrateour results, and Section 7 concludes the article with a detailed summary of those results. We also have available an Excel spreadsheetat http://www.math.lsa.umich.edu/erhan/OptimalLifeInsurance.xlsx that the interested reader can use to calculate the optimalamount of life insurance for his or her household.

    2. FINANCIAL BACKGROUND, STATEMENT OF PROBLEM, VERIFICATION LEMMAIn this section we present the financial and insurance market for the household. Then we state the optimization problem that

    this household faces. Finally, we present a verification lemma that we use to solve the optimization problem.

    2.1. Financial MarketThe household invests in a Black-Scholes financial market with one riskless asset earning at the rate r 0 and one risky asset

    whose price process S = {St }t0 follows geometric Brownian motion:

    dSt = St dt + St dBt ,

    in which B = {Bt }t0 is a standard Brownian motion on a filtered probability space (,F ,F = {Ft }t0,P), with > r and > 0. (In courses on the theory of interest, actuaries call r the force of interest.)

    Let Wt denote the wealth of the household at time t 0. Let t denote the dollar amount invested in the risky asset at timet 0. Finally, let ct denote the continuous rate of consumption of the household at time t 0.

    A consumption policy c = {ct }t0 is admissible if it is an F-progressively measurable process satisfying t

    0 |cs | ds < almostsurely, for all t 0. An investment policy = {t }t0 is admissible if it is an F-progressively measurable process satisfying t

    0 2s ds < almost surely, for all t 0. Furthermore, we require that the policies are such that Wt > for all t 0 with

    probability 1. For example, this restriction prohibits the household from borrowing an infinite amount of wealth and consuming itall instantly.

    The household receives income from two sources: While family member (x) is alive, the household receives income at theconti

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