Boomers’ life insurance adequacy pre & post the 2008
financial crisis

Janine K. Scott, Ph.D.a,*, John Gilliam, Ph.D., MBA, CFP, ChFC, CLUb

aSchool of Economics & Finance, Massey University, Palmerston North, New Zealand
bDepartment of Personal Financial Planning, Texas Tech University, Box 41210,

Lubbock, TX 79409-1210, USA

Abstract

The baby boomers represent a large percentage of the U.S. population and their preparation for
retirement, or lack thereof, can affect the economy at large. In light of the 2008 financial crisis, boomer
households may be delaying retirement, choosing to work longer. Using the 2004 and 2010 Survey of
Consumer Finance, logistic regression analyses are used to examine life insurance adequacy among
boomers before and after the financial crisis of 2008. We find a significant difference in 2010 between
the baby boomers and the senior generation in life insurance adequacy. Variables related to net worth,
such as income, marital status, and self-insurability, were significant predictors of life insurance
adequacy. Given greater life insurance adequacy among those with higher income, increasing group
term insurance may help mid to low income households. Further implications to practitioners, agents,
and educators are discussed. © 2014 Academy of Financial Services. All rights reserved.

Jel classification: G22

Keywords: Life insurance; Baby boomers; Financial planner; Human capital

1. Introduction

The oldest baby boomers (born between 1946 and 1964), became eligible to draw on
Social Security during the financial crisis of 2008 (Farrell, 2013). As there are a large number
of older Americans, specifically the baby boomers, examining life insurance adequacy

* Corresponding author. Tel.: �64 6 3569099, ext 83844; fax: �64 6 350 5660.
E-mail address: J.K.Scott@massey.ac.nz (J.K. Scott)

Financial Services Review 23 (2014) 287–304

1057-0810/14/$ – see front matter © 2014 Academy of Financial Services. All rights reserved.



among this subgroup of the population is an important recourse. By 2030 the boomer
population is projected to be 61 million (Knickman and Snell, 2002). In the event that baby
boomers do not have sufficient amounts of life insurance, they may sustain financial
hardships that have significant economic consequences.

The impact of a financial crisis can especially reduce the purchasing power of older
households (Kirkpatrick and Tennant, 2002). Because these households are closer to retire-
ment, they are more susceptible to income shocks. Holding inadequate amounts of life
insurance implies that more households may have to rely on social security survivor benefits,
placing additional strain on the economy. Because of the purchasing and consumption
influence boomers possess, depressed spending can weaken an already strained economy
(Beinhocker, Farrell, and Greenberg, 2009).

Older households are interested in insurance not only from a pure death protection
standpoint (i.e., term insurance). They are also interested in its saving component, estate tax
benefits, in addition to bequest motives (Baek and DeVaney, 2005; Ibbotson, Milevsky,
Chen, and Zhu, 2007; Mittra, 1995). This article includes the face amounts of both term and
cash value life insurance. In the absence of sufficient insurance to cover insurable risks (e.g.,
untimely death), households will place too much emphasis on these risks while neglecting
managing uninsurable risks (e.g., investing in the stock market; Mitchell, 2011).

This article seeks to assess life insurance adequacy pre and post the 2008 financial crisis
by investigating if there is a difference in life adequacy between boomers and seniors (those
born before 1946); current life insurance holdings among the boomers in comparison with
other age cohorts pre- and post-financial crisis; and whether having a financial planner
increases the likelihood of boomers having adequate life insurance post-financial crisis.

2. Background

Historically, baby boomer wealth has exceeded their predecessors by more than 100%.
They thrived during a time when saving was not a priority (Beinhocker et al., 2009). A
burgeoning stock market alongside loose lending practices and low borrowing costs weak-
ened the savings motive. Moreover, boomers as a whole did not share the same aversion to
credit that had preoccupied the previous generation, who faced severe economic distress
periods, such as the Depression and World War II.

Boomers may be wealthier than their predecessors, but the same characteristics that define
their generation are creating unique challenges for their future that will have significant
economic implications (Gokhale and Kotlikoff, 2000). They are living longer than earlier
generations and choosing to exist independently from their children. They are spending their
wealth at a faster rate than previous cohorts. Many choose or need to work longer to save
more for retirement. As a result, a larger portion of wealth is annuitized because of the
expansion of programs such as Medicare and Social Security; there are increasing healthcare
costs, and more wealth is tied up in annuities, which results in less bequests.

Boomers also tend to be less risk adverse than younger households. This may be because
of a decreased expected human capital value and a greater level of accumulated assets. For

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older boomers, there may be no more dependents to provide for and there are fewer years to
protect for the surviving spouse (Lin and Grace, 2007). A perception of decreased financial
vulnerability leads some boomers to have inadequate life insurance holdings.

The matter of inadequate life insurance among the baby boomers has been under exam-
ined. Few studies compare how baby boomers utilized life insurance before and after the
financial crisis of 2008; however, there is widespread research that examines how the crisis
impacted the way baby boomers prepared for retirement (Rosnick and Baker, 2010; Tres,
2010). The analysis of retirement preparation before and after the crisis provides a lens
through which we can more broadly understand how baby boomer wealth was affected by
the crisis, allowing us to further examine how life insurance utilization was shaped by the
crisis. For example, Munnell, Golub-Sass, Soto, and Webb (2008) find that in the context of
the housing crash wealth effect, boomers may not have sufficient savings to sustain a desired
standard living in retirement. It may not be surprising to find that boomers may not have
adequate life insurance policies either.

2.1. Life insurance inadequacy

There are various definitions of “inadequacy” when associated with life insurance usage.
Many financial advisors use an individualized capital needs analysis to calculate the amount
of life insurance an individual needs. However, according to the 2010 Life Insurance Study
(LIMRA), the average American has enough life insurance to replace less than four years of
income, with an average amount of $155,000 (LifeJacket, 2011). The 2011 LifeJacket study
reveals that one-third of life insurance policyholders bought their policy a decade ago,
suggesting coverage amounts may not have changed with life circumstances (LifeJacket,
2011).

Inadequate life insurance can have a large impact on retirement preparedness in addition
to significantly reducing living standards for widows (Auerbach and Kotlikoff, 1991; DeV-
aney, 1995). Past studies demonstrate the severe economic impact of inadequate life insur-
ance among older widows, the consequences of which include falling into poverty (Bern-
heim, Forni, Gokhale, and Kotlikoff, 1999).

One of the primary reasons households possess insufficient amounts of insurance coverage
is there is little income to extend beyond household necessities. The 2011 Insurance
Barometer study reveals that 22% of respondents cite inadequate life insurance coverage.
Approximately 28% of respondents who are married would like their spouse or partner to
have life insurance or to add more to their existing coverage. The study also cites that
respondents with life insurance still express concerns about coverage contrasted with those
who own long-term care or medical insurance—perhaps because of insufficient coverage and
high financial risk in the event of a loss. Almost half the respondents who have insufficient
coverage state the price of life insurance as the foremost barrier to purchase, second to having
other financial priorities.

Unawareness of need or risk also results in insufficient amounts of life insurance (Johnson,
1970; Mitchel, 2003), implying that educating households about the inherent necessity of life

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insurance adequacy, and the risks of insufficiency, should result in adequate life insurance.
This produces a simple equation: awareness of need and risk � knowledge � sufficient
financial assets (should) � adequate life insurance. This would not only suggest an oppor-
tunity for financial planners to educate clients, but insinuate that simply delivering the
information, updating clients about the changes in delivery and access to insurance, the wider
use of the Internet as regards life insurance, the use of cell phones for financial transactions,
and so forth, should result in changed behavior. However, we know that the situation is far
more complicated because of behavioral biases and other extenuating factors influencing
household insurance behavior. For example, many households choose to postpone paying all
debts in the event of a spouse’s death. They find alternative ways to fund education for their
children. They may be willing to reduce living standards to adjust after losing a spouse or pin
hopes on remarrying to justify lower amounts of life insurance. All of these reasons would
be sufficient to warrant inadequate coverage of life insurance, but would leave room for
copious “what ifs,” which may cost them future goals. Additionally, the top 10% of life
insurance companies had approximately one-quarter of their assets tied up in mortgage-
backed securities by 2006—assets that were a part of many individual household portfolios.
When many homeowners stopped paying their mortgages, this decreased the underlying
value of these securities, and thus, severely reduced many household portfolios. For many
households “sufficient financial assets” in the simple equation above was more than com-
promised (Baranoff and Sager, 2009).

Calculators are commonly used to determine life insurance adequacy by computing
insurance needs that are based on income and arbitrary numbers, Human Capitalized method,
Capital Needs Analysis, the Multiple Income method, and the Economic Life Cycle method
(Mitchell, 2003). The Human Capitalized model projects income into the future and then
discounts it to the present. The Capital Needs method takes into consideration the reduction
of household income because of the death of a wage earner and the decrease in living
standard suffered by the survivors. This information is then incorporated into insurance
needs. The Multiple Income method uses a predetermined figure and multiplies it by earnings
to derive total life insurance needs. The Economic Life Cycle is based on the life cycle
model—finding an optimal, smooth consumption path over the insured’s lifetime and
determining appropriate life insurance needs. Because these are different methods, incorpo-
rating different household financial information, the amount of life insurance will vary based
on inputs.

Past studies that examine life insurance demand use similar variables to assess adequacy.
Using the 1992 wave of the Health and Retirement Survey (HRS), and the Economic
Security Planner (ESPlanner) financial planning software to compute life insurance needs,
Bernheim et al. (1999) finds underinsurance among single households, non-White house-
holds, younger households, and other groups. Finke, Huston, and Waller (2009) developed
the most recent and extensive model of life insurance adequacy. This model includes current
life insurance, household income, estimated taxes, household economies of scale, and other
key factors to determine adequacy. Finke, Huston, and Waller’s (2009) model for life
insurance adequacy will serve as the framework for this study, discussed later in the article.
Independent variables used in the analyses are discussed below.

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2.2. Independent variables

2.2.1. Age
The effect of age on insurance demand is varied (Chen, Wong, and Lee, 2001; Showers

and Shotick, 1994; Zietz, 2003). As age increases, we would expect life insurance face value
amounts to decrease because the need to replace living expenditures would also be decreas-
ing. Because the value of human capital decreases and the cost of insurance rises, it follows
that there should be a decrease in life insurance coverage (Campbell, 1980). Alternatively,
an increase in mortality risk (and poor health) can necessitate greater insurance holdings,
depending on household preferences (Finke, Huston, and Waller, 2009). For example, older
households, such as the baby boomers may hold life insurance because of bequest motives
or estate planning reasons (Baek and DeVaney, 2005). Given that prior studies find that
households fail to adjust life insurance coverage after initial purchase, we expect no
difference between baby boomers and the senior generation in life insurance adequacy pre
and post the 2008 financial crisis.

2.2.2. Financial professional
The inclusion of a financial planner, accountant, broker, and banker in the descriptive

analysis is pertinent because these professionals may at some point dispense life insurance
advice (Mulholland, Finke, and Huston, 2012). Although the definition of a financial planner
in the Survey of Consumer Finances is not particularly clear, as it does not distinguish
between financial professionals who present themselves as advisors with or without a CFP
designation, it is interesting to see how a financial planner compares with the other previ-
ously listed professionals. Based on the findings of Finke, Huston, and Waller (2009) and
Scott and Finke (2013), we expect a positive relation between the use of a financial planner
(compared with using a non-financial planner professional) on life insurance adequacy.

2.2.3. Education
Education also has varied results from prior studies, demonstrating both positive and

negative associations with life insurance demand (Zietz, 2003). However, stemming from
human capital theory, households with more education should have greater protection
because of a steeper earning capacity (Bryant and Zick, 2006). They should also be better
able to make optimal insurance decisions than those with less education or utilize a financial
service professional to meet insurance needs. Therefore, we expect a positive association
between education and life insurance adequacy.

2.2.4. Marital status
Previous literature reports positive and negative as well as non-significant findings

between marital status and life insurance demand (Zietz, 2003). Because married households
possess the advantage of pooling resources as well as exhibiting greater needs for insurance
than single households, we expect a positive effect on life insurance adequacy.

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2.2.5. Race
Ethnic group differences also play a role in life insurance ownership. Table 1 shows

differences between Blacks, Hispanics, and Whites when compared with each other. These
differences are key in pinpointing specific strategies for each group, considering their
preferences and goals for life insurance. For example, Blacks have an overall preference for
life insurance compared with Hispanics and Whites. They are more likely to consider
burdening family members as a top reason for purchase. Blacks and Whites will use life
insurance to cover funeral expenses more than Hispanics, who will use insurance to fund
education needs (Mitchel, 2011). Though race has been significantly related to the findings
in past studies, we do not expect any differences among racial classes when examining
adequacy.

2.2.6. Risk tolerance
As risk aversion increases, a household should possess greater amounts of life insurance

(Ibbotson et al., 2007). Households who are substantial risk takers display a preference for
risk seeking behavior; the risk tolerance question used in the survey is limited and may not
fully reflect risk tolerance. Therefore, we do not expect a significant relation between risk
tolerance and life insurance adequacy.

2.2.7. Self-employment
Given the volatility of earnings within self-employed households, there should be greater

life insurance coverage than for households who are not self-employed. From a human
capital standpoint, greater life insurance adequacy may be warranted for self-employed
households.

2.2.8. Net worth
Net worth and life insurance demand has been found to be negatively related (Baek and

DeVaney, 2005), as those with greater net worth may be able to self-insure or afford an
unexpected shock to income.

Table 1 Ethnic group difference in life insurance ownership*

Blacks Hispanics Whites

Positive attitude about LI 1 1 1
Feel agents/financial professionals are knowledgeable 1 2 1
Have a greater concern about placing financial burden on others 1 2 2
Seek to understand the product 1 1 1
Prefer to purchase at their workplace 2 2 2
Research on the Internet 1 1 1
Prefer to purchase on the Internet 2 1 2
Prefer to purchase from agent/financial professional 1 2 1

* Adopted from the 2011 Insurance Barometer Study.

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2.2.9. Ability to self-insure
If assets are greater than the present value of human capital, households can afford to

self-insure; thus, having a negative impact on life insurance adequacy. Although net worth
and the ability to self-insure are indeed correlated, the correlation does not interfere with the
analysis evident by correlation tests.

2.2.10. Income
Bernheim et al. (1999) finds more underinsurance at moderate levels of income. As

household income increases, underinsurance increases also. However, past studies also
demonstrate greater affordability of insurance with increased income (Browne and Kim,
1993; Lewis, 1989). As income variation increases, the present value of human capital
decreases, leading to less demand for life insurance (Finke, Huston, and Waller, 2009).

2.2.11. Expectation of income growth
This is one of the variables that aim to capture attitudes related to life insurance adequacy.

Ibbotson et al. (2007) cite that with higher income, a higher discount rate should be used to
value human capital and, thus, would depress life insurance holdings.

2.2.12. Spending greater than income
This variable accounts for liquidity constraints of the household (Bernheim et al., 1999).

Households who spend greater than income will be less likely to have adequate life
insurance.

2.2.13. Social security income
The receipt of social security benefits may depress life insurance holdings (Bernheim,

1991; Fitzgerald, 1987). As with other sources of income, social security benefits should be
included in life insurance demand as it influences survivor benefits (Lewis, 1989).

2.2.14. Health
Related to human capital, greater health should have a positive effect on life insurance

coverage (Baek and DeVaney, 2005). Better health promotes or facilitates better formation
of human capital and it can also translate into more affordable premiums. However, there
may be no effect on adequacy.

2.2.15. Bequest motive
Households with a bequest motive should demand life insurance at a greater rate than

households without a bequest motive. However, having a bequest motive and executing
financial strategies to prepare for the distribution of assets are two separate matters. There-
fore, although we would expect a positive relation between having a bequest motive and
adequate life insurance, it would not be surprising to find insignificant results.

2.2.16. Presence of children
Life insurance demand should be greater for those households with children (Lewis, 1989;

Mulholland, Finke, and Huston, 2012).

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2.2.17. Expectation of having a sizeable estate at death
The inclusion of this variable in the model is similar to including a bequest motive

variable. Again, preferences or expectations may not always lend to financial preparedness.

2.2.18. Homeowner
Based on the findings of other studies, homeownership should have a positive effect on

life insurance coverage (Gandolfi and Miners, 1996). Homeownership can also serve as a
signal for greater life insurance adequacy because of the accumulation of assets within and
beyond the building years of a household’s life cycle stage.

3. Theory

A household seeks to maximize the expected utility of wealth, that is, pursue a level
consumption path over the life cycle. Defined as the present value of expected future market
wages, human capital is a non-tradable asset in the household portfolio. Labor income is used
to fund most of household consumption, and so for a majority of households this dominates
the financial capital side of the household portfolio (Campbell, 1980). Life insurance serves
as an actuarial hedge against the loss of income whereas other financial assets seek to reduce
diversifiable risk (Collins and Lam, 2011). Life cycle hypothesis supports the use of financial
capital to supplement an unexpected loss of human capital to mitigate consumption shocks
that can jeopardize financial goals.

A household’s age in the life cycle influences life insurance needs. In a broad sense,
younger households with greater human capital should possess adequate life insurance more
than older households with less human capital to protect. All households should rationally
prefer a smooth transition from one stage of the life cycle to the next, but this is not always
possible.

Older adults, specifically baby boomers in the period of analysis, are still in the building
stage and susceptible to income and consumption shocks that may alter life insurance needs
or preferences. In short, their life cycle path can become steeper depending on unexpected
variation in income and/or the economic environment. This leads to greater need for life
insurance adequacy (not just coverage) compared with elders with greater stability in income
and/or less exposure to the stock market.

Significant predictors of demand life insurance include household size, number, and age
of dependent children, and income (Baek & DeVaney, 2005). Lewis (1989) developed his
life insurance model based on the survivor’s preferences for insurance. Demand for life
insurance should decline with age as the value of human capital decreases (Baek and
DeVaney, 2005). However, demand for life insurance should theoretically terminate at
retirement as the value of human capital shrinks to zero (Collins and Lam, 2011; Finke,
Huston, and Waller, 2009). However, many households continue to hold onto policies
beyond retirement age, most specifically, cash value life insurance policies for a number of
reasons (Brown, 1999).

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4. Methodology

4.1. Model

To determine life insurance adequacy, the following method adopted from Finke, Huston,
and Waller (2009) is used. First, it is necessary to determine the number of children under
age 18 present in the household. Then, using the U.S. Census Bureau household poverty and
income information, we determined if a household is above or below the poverty line based
on income and dependents. The sample is then censored to households ages 35 to 70 (35 to
76 in 2010) who are working full-time. The 2010 sample is increased to age 76 to account
for the senior generation. Using Bernheim et al. (2001) we adjust for household economies
of scale to assess replacement needs in a two adult household. Taxes are estimated based on
filing status, adjusted gross income, and personal exemptions. Unlike Finke, Huston, and
Waller (2009), we use the original filing status question in the Survey of Consumer Finances
(SCF) to be consistent with the survey years.

Insurance coverage is calculated based on the face value of both term and cash value life
insurance. Instead of recreating the insurance ratio developed by Finke, Huston, and Waller
(2009), it seems more straightforward to view the insurance ratio as current life insurance to
life insurance needs. The life insurance adequacy model is presented in Eq. (1) below.

Adq LI �

�
P�1

P Vp

�It � Tt � f� � ��1 � �1 � rrr�
�W�

rrr
� (1)

Life insurance adequacy is a function of human capital and household financial charac-
teristics. Where Vp in the numerator represents the face value of cash value and term life
insurance policies; w, the difference between the respondent’s age and retirement age; It, the
household’s current income; f, household economies of scale ratio (ability to pool resources
in a dual-income household); Tt, estimated taxes based on filing status, personal exemptions,
and standard deduction; rr, expected real interest rate. A household has adequate life
insurance when its insurance value (in the numerator) to insurance need (represented by the
denominator) is greater than or equal to one. We assume that income growth is equal to the
rate of inflation and to determine overall replaceable need, a discount rate of 2.3% is used.
The regression model is shown below in Eq. (2).

Adequate Life Insurance � �0 � �1Age � �2Financial Professional

� �3Demographic Characteristics

� �4Financial Characteristics

� �5Financial Attitudes � � (2)

Adequate life insurance is a binary variable equal to 1 if the household has an insurance
coverage to insurance needs ratio is greater than or equal to 1. Age includes boomers, seniors,

295J.K. Scott, J. Gilliam / Financial Services Review 23 (2014) 287–304



and generations younger than boomers. Financial Professional includes the use of a financial
planner and non-financial planner. Demographic Characteristics is a vector of independent
variables representing race, education, children, and marital status. Financial Characteristics
includes net worth, income, self-insurability, self-employment, and homeownership. Finan-
cial Attitudes contains a bequest preference, a substantial risk tolerance level, the expectation
of greater income in the future, and spending more than annual income.

4.2. Dataset

As we are examining life insurance adequacy among baby boomers pre and post the 2008
financial crisis, the 2004 and 2010 SCF datasets are used. This survey contains the necessary
household demographic and financial characteristics for this research study. There were
4,519 respondents in 2004 and 6,482 in 2010. For the descriptive analyses, the SCF
population weights will be used to represent the U.S. population as a whole but not for the
multivariate analysis (Rubin, 1987).

Following Finke, Huston, and Waller (2009), the sample in 2004 was censored to married
households working full-time, between age 35 and 70 (expanded to age 76 in 2010) and
possessing income above the poverty line.

4.3. Descriptive statistics

Descriptive statistics are presented in Tables 2 and 4. Table 3 shows the coding for each
variable in the study. Table 2 displays the mean insurance and mean insurance needs for all
respondents. Of the generational groups, boomers have the highest insurance mean of
$345,297 in 2004 but a greater insurance need than seniors in both years. Insurance holdings
on average are higher among respondents who report seeking advice from a financial planner
($478,396) compared with those who use another financial professional ($284,421). How-
ever, insurance needs are greater (by �$81,000) for households with a financial planner.

Table 4 displays demographic, financial, and other household characteristics. The first
column for each year includes all respondents and the second column is censored/restricted
based on age, households with more than one member and income above the poverty line.
The sample size in 2004 for the censored sample is 1,966 households and 2,612 in 2010.

Table 2 Mean insurance and insurance need

2004 2010

Insurance Insurance need Insurance Insurance need

Boomers $345,297.34 $676,507.76 $419,124.74 $ 700,545.65
Seniors $235,741.31 $325,580.83 $295,727.41 $ 286,945.90
GenX and below $235,952.48 $808,799.39 $342,860.90 $1,212,846.14
Financial planner $478,396.10 $736,178.60 $586,766.69 $ 888,523.82
Non-financial planner $284,421.30 $655,043.47 $351,424.69 $ 872,127.81

296 J.K. Scott, J. Gilliam / Financial Services Review 23 (2014) 287–304



Approximately 15% of these households possess adequate life insurance in 2004 and 14%
have adequate life insurance in 2010. In both survey years, the majority of respondents are
baby boomers followed by seniors in 2004 and GenX and below in 2010. The use of a
financial planner is greater in the restricted sample for respondents versus the use of a planner
in the full sample. Financial attitudes such as leaving a bequest and expecting to leave a
sizeable estate did not change greatly from 2004 to 2010 in the restricted samples.

Table 3 Coding for each variable from the 2004 and 2010 Survey of Consumer Finances data

Variables Coding

Adequate life insurance (dependent) 1 � adequate life insurance
Boomers 1 � age between 39 and 58, 0 otherwise in 2004; 1 � age

between 45 and 64, 0 otherwise in 2010
Seniors 1 � age � 59, 0 otherwise in 2004; 1 � age � 65,

0 otherwise in 2010
Generation X and below 1 � age � 39, 0 otherwise in 2004; 1 � age � 45,

0 otherwise in 2010
Less than high school 1 � yes, 0 otherwise
High school graduate 1 � yes, 0 otherwise
Some college 1 � yes, 0 otherwise
College graduate 1 � yes, 0 otherwise
Single 1 � single, divorced, or widowed, 0 otherwise
Non-single 1 � married, 0 otherwise
White 1 � yes, 0 otherwise
Black 1 � yes, 0 otherwise
Hispanic 1 � yes, 0 otherwise
Non-financial planner 1 � banker, accountant, or broker, 0 otherwise
Financial planner 1 � yes, 0 otherwise
Spends more than income 1 � yes, 0 otherwise
Expect income growth 1 � yes, 0 otherwise
Substantial risk taker 1 � yes, 0 otherwise
Self-employed 1 � yes, 0 otherwise
Log of net worth continuous
Self-insurable 1 � assets is greater than the present value of human capital,

0 otherwise
Social security income 1 � yes, 0 otherwise
Income �$35,150 1 � yes, 0 otherwise
Income between $35,150–$90,800 1 � yes, 0 otherwise
Income between $90,800–$147,050 1 � yes, 0 otherwise
Income between $147,050–$288,350 1 � yes, 0 otherwise
Income �$288,350 1 � yes, 0 otherwise
Poor health 1 � yes, 0 otherwise
Good or excellent health 1 � yes, 0 otherwise
Bequest motive 1 � very important/important, or positive, differing among

spouses, weak positive, or negative � 0
Have children 1 � kids living at home or away from home, 0 otherwise
Expect to leave sizeable estate 1 � yes or possibly, 0 otherwise
Homeowner 1 � own ranch/farm/mobile home/house/condo/coop/�,

0 otherwise

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5. Results

A Pearson correlation test was implemented with all variables in the regression models
(e.g., between net worth and income) to avoid multi-collinearity issues. We did not detect
any evidence of multi-collinearity. Two binomial logistic regression models are tested. The
first, shown in Table 5, represents all respondents in the censored sample, while Table 6
shows results for only baby boomers in the censored sample.

Table 4 Weighted frequencies of all respondents and censored sample (used for adequate life insurance; in %)

2004 2010

All
respondents
(N � 4,519)

Restricted
sample
(N � 1,966)

All
respondents
(N � 6,482)

Restricted
sample
(N � 2,612)

Adequate life insurance (dependent) 15.41 14.16
Cohorts

Boomers 69.18 64.36 59.58 70.81
Seniors 16.02 28.05 5.70 11.08
GenX and below 14.80 7.59 34.72 18.11

Education
Less than high school education 9.16 3.30 9.91 4.59
High school grad 18.97 15.51 20.72 16.76
Some college 17.90 17.16 19.82 14.32
College grad 53.97 64.03 49.55 64.32

Good or excellent health 88.56 91.42 86.73 88.11
Financial professional

Financial planner 15.51 21.78 15.68 22.16
Non-financial planner 84.49 78.22 84.32 77.84

Marital status
Married 81.99 89.77 80.37 98.38
Single 18.01 10.23 19.63 1.62

Race
Black 7.22 5.28 8.66 2.97
Hispanic 7.27 1.98 9.79 3.78
White 85.50 92.74 81.55 93.24

Have children 93.08 95.38 92.82 95.41
Attitudes/expectations

Spends � income 13.12 10.89 15.45 11.35
Expect income growth 32.25 35.64 23.06 27.03
Substantial risk taker 5.54 6.27 5.03 6.22
Bequest motive 57.27 54.46 55.01 54.05
Expect to leave sizeable estate 68.41 74.92 66.84 75.41

Self-employed 39.01 47.19 32.27 42.43
Homeowner 85.10 94.06 81.27 95.14
Ability to self-insure 47.91 71.62 45.34 62.16
Social security benefits 5.95 9.57 5.93 12.43
Income

�$35,150 12.77 6.27 12.88 2.43
$35,150–$90,800 32.25 26.40 33.94 24.59
$90,800–$147,050 14.39 14.85 17.13 17.30
$147,050–$288,350 12.46 17.16 13.38 23.51
�$288,350 28.13 35.31 22.67 32.16

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In the first regression (see Table 5) generational groups vary significantly according to
amounts of adequate life insurance in 2010. The baby boomer generation was 62% more
likely than the senior generation to have adequate life insurance. The financial crisis also
impacted racial disparities among household life insurance holdings. In 2004, Hispanic
households were less likely than White households to have adequate life insurance; however,
there was not a significant difference in 2010.

Households who can afford to self-insure, having assets greater than human capital,
demonstrated greater life insurance adequacy in both survey years. In 2010, married house-
hold as compared with single households were more likely to have adequate life insurance
coverage. This is consistent with what we expected, given household economies of scale.

Table 5 Regression results: DV � adequate insurance (insurance ratio �1)

Variables 2004 (N � 1,966) 2010 (N � 2,563)

Parameter
estimate

Odds
ratio

Parameter
estimate

Odds
ratio

Adequate life insurance (dependent)
Generation (senior)

Boomer �0.06 0.70 0.34** 1.62
GenX and below �0.25 0.57 �0.20 0.95

Education (�high school)
High school grad 0.14 1.99 0.11 1.42
Some college 0.22 2.14 �0.09 1.15
College grad 0.18 2.07 0.22 1.58

Marital status (single)
Non-single 0.14 1.32 1.11*** 9.14

Race (White)
Black 0.42 1.17 �0.12 0.66
Hispanic �0.68* 0.39 �0.17 0.63

Financial professional (non-financial planner)
Financial planner 0.21** 1.53 0.14 1.33

Spends more than income 0.06 1.12 �0.08 0.84
Expect income growth 0.05 1.10 0.04 1.08
Substantial risk taker 0.03 1.06 0.07 1.15
Self-employed �0.05 0.91 �0.02 0.95
Log of net worth �0.01 0.99 0.00 1.00
Self-insurable 0.52*** 2.84 0.25*** 1.66
Social security income 0.11 1.25 0.33* 1.93
Income (�$35,150)

$35,150–$90,800 0.04 1.33 0.19 3.70
$90,800–$147,050 0.04 1.32 0.20 3.72
$147,050–$288,350 0.27 1.67 0.63*** 5.73
�$288,350 �0.11 1.15 0.09 3.34

Health (poor)
Good or excellent health 0.03 1.06 �0.11 0.80

Bequest motive �0.11 0.80 �0.04 0.93
Have children 0.16 1.38 0.15 1.35
Expect to leave sizeable estate �0.09 0.83 �0.09 0.83
Homeowner 0.26 1.70 0.29* 1.79

Intercept �2.23 �3.40

Data are from the Survey of Consumer Finances.
*p � 0.05, **p � 0.01, ***p � 0.001.

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Other positive predictors include receiving social security income, being a homeowner and
possessing income greater than $147,000. Specifically, respondents reporting income be-
tween $147,050 and $288,350 represented the highest odds of insurance adequacy, 473%
higher compared with the lowest income group (less than $35,150).

Having a financial planner was a significant and positive predictor of insurance adequacy
in 2004, highlighting greater comprehensive planning in risk management than among other
financial professionals. However, post the 2008 crisis, having a planner had no significant
effect on life insurance adequacy.

The second regression analysis includes only baby boomers (see Table 6). As with the all
respondent censored sample in 2004, the odds of a boomer having adequate life insurance
were 156% greater if they can self-insure in comparison with respondents with insufficient

Table 6 Regression results censored by baby boomers: DV � adequate insurance (insurance ratio �1)

Variables 2004 (N � 1,360) 2010 (N � 1,527)

Parameter
estimate

Odds
ratio

Parameter
estimate

Odds
ratio

Adequate life insurance (dependent)
Education (�high school)

High school grad 0.16 2.69 0.22 1.69
Some college 0.38 3.37 �0.03 1.32
College grad 0.29 3.07 0.12 1.53

Marital status (single)
Non-single �0.04 0.93 1.07*** 8.48

Race (White)
Black 0.64* 1.68 �0.37 0.48
Hispanic �0.77* 0.41 0.00 0.70

Financial professional (non-financial planner)
Financial planner 0.17 1.41 0.10 1.23

Spends more than income 0.01 1.02 0.02 1.04
Expect income growth 0.01 1.03 0.00 1.00
Substantial risk taker 0.05 1.10 0.04 1.08
Self-employed �0.02 0.96 �0.07 0.87
Log of net worth 0.03 1.03 �0.03 0.97
Self-insurable 0.47*** 2.56 0.37*** 2.12
Social security income �0.25 0.61 0.64*** 3.63
Income (�$35,150)

$35,150–$90,800 0.14 1.65 0.08 4.95
$90,800–$147,050 �0.04 1.38 0.26 5.89
$147,050–$288,350 0.31 1.96 0.87*** 10.87
�$288,350 �0.05 1.37 0.30 6.15

Health (poor)
Good or excellent health 0.05 1.10 �0.11 0.81

Bequest motive �0.05 0.91 0.01 1.01
Have children 0.15 1.35 0.27 1.71
Expect to leave sizeable estate �0.12 0.79 �0.12 0.79
Homeowner 0.30 1.81 0.40 2.22

Intercept �3.11 �2.68

Data are from the Survey of Consumer Finances.
*p � 0.05, **p � 0.01, ***p � 0.001.

300 J.K. Scott, J. Gilliam / Financial Services Review 23 (2014) 287–304



resources to self-insure. If an individual can self-insure, coverage may be unnecessary but
adequate.

In 2004, Hispanic boomers were 59% less likely to be adequately insured than White
boomer households. As expected from previous research, Black boomers were more likely
to be adequately insured than White boomers in 2004; however, in 2010, there was not a
remarkable discrepancy. Examining over-insurance among Black households would be a
worthwhile research topic in the future.

Post 2004 we see similar results in the boomer sample. In 2010, there was a positive
relation between life insurance adequacy and boomers who were married, receiving social
security income, having assets to self-insure, and being within the second highest income
category. Variables related to net worth and income had more of an impact post the 2008
financial crisis, whereas racial status, in addition to having substantial assets, influenced
insurance adequacy before the crisis. This is not surprising because higher net worth
households can draw on assets in difficult economic times more so than those with lower net
worth.

6. Conclusion

Little in the literature exists that specifically examines how the financial crisis of 2008
affected life insurance adequacy among the baby boomer generation. This study aims to
expand that literature by addressing the unique characteristics and challenges that define the
boomer’s generation and economic context, and by examining boomer life insurance ade-
quacy before and after the financial crisis of 2008 as compared with older and younger
generations.

Because life insurance is often sold not bought, we did not expect to see differences in
adequacy within the survey years used in the study. However, using binomial logistic
regression analyses for the 2004 and 2010 SCF years, we find compelling disparities between
baby boomers and the senior generation in 2010 but not in 2004, revealing that the boomer
generation is 62% more likely than the older cohort to have adequate life insurance post the
financial crisis of 2008. These results were surprising, given that boomers display a higher
risk tolerance than the senior generation, but positive for boomer households in a post-
financial crisis economic context.

When restricting the sample to only boomers, the regression analysis demonstrated similar
results to the analysis of the senior generation and the younger generation insofar as race,
self-insurability, income, and marital status impacted life insurance adequacy in the survey
years. For the 2004 SCF survey year, both samples reflected racial discrepancies wherein
Black households are more likely to be adequately insured than White households, and
Hispanic households are at a greater risk of being inadequately insured; however, there is
little racial difference in 2010. Households whose assets exceed human capital, and can
afford to self-insure, showed significant life insurance adequacy. In some cases when an
individual can self-insure, coverage may not even be necessary, though it is certainly
adequate. Married households, in 2010, are more likely than single households to be
adequately insured. Social security income is also a positive predictor of life insurance

301J.K. Scott, J. Gilliam / Financial Services Review 23 (2014) 287–304



adequacy. Consistent with prior studies, social security acts as a substitute for life insurance
but is also indicative of household wealth (Browne and Kim, 1993; Lewis, 1989).

The use of a financial planner is higher among households with adequate life insurance
compared with the all respondents sample. Furthermore, having a financial planner compared
with households without a planner is a significant predictor in the all respondent regression
sample in 2004, suggesting that they are making a positive impact on household insurance
behavior.

The results indicate that variables related to net worth (specifically assets used to calculate
self-insurability) drive life insurance adequacy. Those who can afford to fully insure, having
a ratio of insurance to insurance need greater than or equal to one, are able to hold suitable
amounts of life insurance or none at all. Though there is not enough evidence to reject the
null hypothesis post 2008, as boomers had better life insurance protection than the senior
generation, this topic warrants further investigation and has pressing implications to financial
planning practitioners.

Given longevity and changes in the definition and the delay of retirement for many, it is
important to better devise ways to aid households in acquiring and sustaining adequate life
insurance. Financial planning practitioners and life insurance agents can improve their
services to clients by recognizing generational cohort differences and illustrating dynamic
life insurance needs analysis in front of clients. This needs analysis may be different for each
generation. For example, younger consumers are more interested in the price of insurance,
whereas older households want to see product comparisons (LifeJacket Study, 2011).
Purchase preferences of baby boomers are different than younger age cohorts. Boomers
prefer face-to-face interaction, especially those households who have been divorced, are
widowed or separated (Mitchell, 2011).

Sales strategies that worked to attract boomers may not work for later generations such as
Generation Y. Technology innovation, in addition to the increase in speed of accessing
information now than in the past, provides a new ground on which practitioners can capture
both younger and older age groups. Regarding life insurance purchase via the Internet,
purchase strategies tailored specifically to men may be worthwhile, because more males than
females shop for life insurance online (Mitchell, 2011). For example, using language that
evokes emotion, for example, “breadwinner,” or “do not leave your family unprotected,”
rather than deterring consumers with morbid language is important.

Social policy implications are evident from the study. Auerbach and Kotlikoff (1991)
suggest that employers may consider increasing group life insurance coverage. Other con-
siderations to lessen potential hardships from the lack of adequate life insurance include
expanding social security survivor benefits. However, both of these suggestions warrant
further research and resources.

Education is key (Thomas, 2006) and insurance agents have cultivated a reputation in the
industry—whether good or bad. However, agents must realize that trust precedes education,
because it is a vital factor in purchasing decisions, especially among boomers. For example,
Blacks are more likely than Whites to report that agents are trustworthy and females are more
likely than males to have a positive view of insurance salespersons (Mitchell, 2011). Being
transparent about fees and sales charges is another integral part of educating clients and
building trust among all age cohorts (Thomas, 2006). Taking generational differences into

302 J.K. Scott, J. Gilliam / Financial Services Review 23 (2014) 287–304



consideration can be of tremendous value to insurance agents, financial service professionals,
and educators. We are in an indispensable position to help manage preferences and shape
perceptions about the future.

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