Whole Life Insurance in a Lifetime Financial Plan: The Case Study

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For these comparisons, I create a case study for a forty-year-old married couple with two children who are currently developing a lifetime financial plan. Jerry and Beth decided it was time to get serious about retirement and life insurance planning. Jerry is an employee and Beth is a housewife. These gender roles could be reversed, but since life insurance is cheaper for women due to their increased longevity, having the man as the worker is the more conservative case to consider. Jerry requests an additional life insurance death benefit amount equal to $500,000. This, together with his other life insurance, will be enough to support his family in the event of his death before the age of sixty-five.

Jerry currently has $60,000 saved in a 401(k) plan with his employer, which is invested with an equity evolution strategy representative of a typical target date fund: 80% equity until age forty-five, 65 percent stock forty-five through fifty-four, 50 percent stock fifty-five through sixty-four, 40 percent stock sixty-five through seventy-four, and 30 percent inventory thereafter. He would like to plan his retirement at sixty-five. I will investigate a portion of his assets to be saved in the future that equals 401(k) employee contribution limits in 2019 with assumed inflation adjustments: $19,000 can be saved each year until age fifty, then $25,000 thereafter until age sixty. five to take account of catch-up contributions allowed at these ages.

These contribution limits are adjusted for inflation so that the actual savings remain the same, but the nominal amounts increase. Since life insurance premiums are set without adjusting for inflation, the percentage of savings spent on insurance declines over time in real terms. Jerry expects to be in a combined marginal tax bracket of 25% (22% for federal taxes and 3% for state taxes) in his pre-retirement and post-retirement years.

For investment returns, I follow the approach explained in Exhibit 3.11 in Chapter 3. Equity returns are simulated with a random risk premium above the fixed bond return of 3%. This risk premium has an average value of 6% with a volatility of 20%. Inflation is set at 2% per year. This implies a real interest rate of 1%. Interest rate risk is eliminated from the analysis, as there is no possibility that fluctuating interest rates will create capital gains or losses for the underlying bond portfolio. The risky asset is based on large cap stocks in the United States. Overall, this represents an arithmetic average of 9% for stocks (7% in real terms). The compound real growth rate of stocks is 5%. The investment portfolio is modeled using 10,000 Monte Carlo simulations for investment returns based on these capital market expectations. I assume investors get these returns net of any investment or advisory fees. As the investments are held in tax-deferred accounts, there is no further tax burden to worry about. Investors earn gross returns and portfolio distributions are taxed as income.

Life insurance is priced using the 3% interest rate and the Social Security Administration 1980 cohort mortality tables for mortality. Pricing for term and whole life insurance policies is shown in Exhibits 7.1 and 7.2. Income annuities are similarly priced using Society of Actuaries mortality data, as explained in Chapter 4, assuming a 2% annual cost-of-living adjustment to match payments to the rate. assumed inflation. In Chapter 4, income annuity was priced for women. It offered a payout rate of 4.56%.

In this case study, we are using income annuities for men and couples, and we must also take into account that the annuity will not be purchased for twenty-five years. The corresponding payout rates for men and couples with annuities purchased today are 4.83% and 3.93%, respectively. However, with the longevity improvements assumed by the Society of Actuaries over the next twenty-five years, the male and joint pension payout rates at that time are 4.47% and 3.75%, respectively. These last numbers are the ones I use. It makes sense to use different mortality tables to price life insurance and annuities based on the different populations that use these financial products. Annuity holders will tend to live longer.

To better understand the impacts of upside and downside investment volatility, Monte Carlo simulations are used to create a distribution of results. The coins report the 10th percentile, median, and 90th percentile of this distribution. We can interpret the 10th percentile result as a case of bad luck with low returns on investment. It’s possible that the results at retirement are even worse, but in general, Jerry and Beth could expect better results at retirement than those seen at the 10th percentile. The median reflects more typical results. This is the midpoint of the distribution, with a 50% chance of getting worse results and a 50% chance of getting better results. These are reasonable results that Jerry and Beth can expect. The 90th percentile is a chance outcome in which investments perform very well, supporting larger expenses and larger account balances.

Note that these results are presented in terms of nominal dollars to avoid reader confusion as to why inflation-adjusted dollars are lower than nominal dollars. This decision does not affect comparisons of relative results between scenarios. However, readers should understand that the purchasing power of a given amount of income or wealth will be less in the future. For today’s forty-somethings, the real purchasing power of money will be about 60 percent of what it is today at sixty-five, and about 30 percent of what today it is 100 years, assuming 2% inflation.

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*This is an excerpt from Wade Pfau’s book, Safety-First Retirement Planning: An Integrated Approach for a Worry-Free Retirement. (Retirement Researcher’s Guide Series), available now on Amazon

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