RETIREMENT 

SECURITY 

Women Still Face 

Challenges 

Report to the Chairman, Special 

Committee on Aging, U.S. Senate 

July 2012 

GAO-12-699 

United States Government Accountability Office

GAO 
United States Government Accountability Office

Highlights of GAO-12-699, a report to the 

Chairman, Special Committee on Aging, 

U.S. Senate 

July 2012 

RETIREMENT SECURITY

Women Still Face Challenges

Why GAO Did This Study

Elderly women, who comprise a 

growing portion of the U.S. population, 

have historically been at greater risk of 

living in poverty than elderly men. 

Several factors contribute to the higher 

rate of poverty among elderly women 

including their tendency to have lower 

lifetime earnings, take time out of the 

workforce to care for family members, 

and outlive their spouses. Other factors

could affect older women’s financial

insecurity. These include the economic 

downturn and changing trends in 

pension plan offerings. In light of these 

circumstances, GAO was asked to 

examine (1) how women’s access to

and participation in employersponsored retirement plans compare to 

men’s and how they have changed 

over time, (2) how women’s retirement 

income compares to men’s and how 

the composition of their income—the 

proportion of income coming from 

different sources—changed with 

economic conditions and trends in 

pension design, (3) how later-in-life 

events affect women’s retirement 

income security, and (4) what policy 

options are available to help increase 

women’s retirement income security.

To answer these questions, GAO 

analyzed data from two nationally 

representative surveys, conducted a 

broad literature review, and 

interviewed a range of experts in the 

area of retirement security. 

GAO is making no recommendations.

GAO received technical comments on 

a draft of this report from the 

Department of Labor, the Department 

of the Treasury and the Social Security 

Administration, and incorporated them, 

as appropriate.

What GAO Found

Over the last decade, working women’s access to and participation in employersponsored retirement plans have improved relative to men. Indeed, from 1998 to 

2009, women surpassed men in their likelihood of working for an employer that 

offered a pension plan, largely because the proportion of men covered by a plan 

declined. Furthermore, as employers have continued to terminate their defined 

benefit (DB) plans and have switched to defined contribution (DC) plans, the 

proportion of women who worked for employers that offered a DC plan increased. 

Correspondingly, women’s participation rates in DC plans increased slightly over 

this same period while men’s participation fell, thereby narrowing the participation 

difference between men and women to 1 percentage point. At the same time, 

however, women contributed to their DC plans at lower levels than men.

Although the composition of income for women age 65 and over did not vary 

greatly over the period—despite changes in the economy and pension system— 

women continued to have less retirement income on average and live in higher 

rates of poverty than men in that age group. The composition of women’s income 

varied only slightly, in part, because their main income sources—Social Security 

and DB benefits—were shielded from fluctuations in the market. Women, 

especially widows and those age 80 and over, depended on Social Security 

benefits for a larger percentage of their income than men. For example, in 2010, 

16 percent of women age 65 and over depended solely on Social Security for 

income compared to 12 percent of men. At the same time, the share of 

household income women received from earnings increased over the period, but 

was consistently lower than for men. Moreover, women’s median income was

approximately 25 percent lower than men’s over the last decade, and the poverty 

rate for women in this age group was nearly two times higher than men’s in 2010. 

For women approaching or in retirement, becoming divorced, widowed or 

unemployed had detrimental effects on their income security. Moreover, divorce

and widowhood had more pronounced effects for women than for men. For 

example, women’s household income, on average, fell by 41 percent with 

divorce, almost twice the size of the decline that men experienced. For 

widowhood, women’s household income fell by 37 percent—while men’s

declined by only 22 percent. Unemployment also had a detrimental effect on 

income security, though the effects were similar for women and men; household 

assets and income fell by 7 to 9 percent. 

A range of existing policy options could address some of the income security 

challenges women face in retirement. For example, some would expand existing 

tax incentives to save for retirement while others would improve access to 

annuities. All of these options have advantages and disadvantages that would 

need to be evaluated prior to implementation. For example, increasing Social 

Security benefits for widows could provide additional income for women who 

have few options to increase their retirement savings. However, increasing 

benefits would also increase costs to the Social Security program and have 

implications for its long-term solvency. 

View GAO-12-699. For more information, 

contact Charles Jeszeck at (202) 512-7215 or 

jeszeckc@gao.gov. 
Page i GAO-12-699 Women’s Retirement Security 

Letter 1 

Background 4

Working Women’s Access to and Participation in EmployerSponsored Pension Plans Have Improved Relative to Men 9

While Income Composition Changed Only Slightly for Women Age 

65 and Over, They Continue to Have Less Retirement Income 

Than Men 18

Divorce, Widowhood, and Unemployment Had a Detrimental 

Effect on Older Women’s Income Security 27

Existing Policy Options Could Address Retirement Security Issues 

Facing Women 36

Concluding Observations 46

Agency Comments 47

Appendix I Objective, Scope, and Methods 49

Section 1: Information Sources 49

Section 2: Methods for Comparing Working Women’s and Men’s 

Access to and Participation in Employer-Sponsored Pension 

Plans 54

Section 3: Methods for Comparing the Income of Women and Men 

Age 65 and Over 73

Section 4: Methods for Analyzing the Effects of Events Occurring 

Later in Life on Women’s and Men’s Household Income and 

Assets 74

Appendix II GAO Contact and Staff Acknowledgments 89

Tables

Table 1: Estimated Effects of Life Events on Household Assets and 

Income by Gender 28

Table 2: Percent of Women and Men Reporting Their Health Is 

Poor Is Similar across Age Groups 35

Table 3: Proposals to Expand Use of Existing Tax Incentives to 

Save for Retirement 37

Table 4: Proposals to Expand Eligibility and Opportunities to 

Accumulate Social Security Credits 39

Table 5: Proposals to Expand Access to Retirement Savings and 

Strengthen Spousal Protections 40

Contents
Page ii GAO-12-699 Women’s Retirement Security 

Table 6: Proposals to Expand Opportunities for Saving Later in Life 

and Delay Social Security Benefit Receipt 41

Table 7: Proposals to Ensure Lifetime Income 43

Table 8: Proposals to Ensure Income Adequacy 44

Table 9: Data Sources Used for Each Reporting Objective 49

Table 10: SIPP Panels, Waves, and Questionnaires Used to Answer 

Objective 1 and Objective 2 50

Table 11: Birth Years for the HRS Cohorts and the Year Data 

Collection Began for Each Cohort 52

Table 12: Information Used from SIPP to Construct Key Variables 55

Table 13: Characteristics of the Working Population over Time 58

Table 14: Factors Associated with Working for an Employer That 

Offers a Plan, 2009 63

Table 15: Factors Associated with Eligibility for EmployerSponsored Pension Plan, 2009 67

Table 16: Factors Associated with Participation in an EmployerSponsored Pension Plan, 2009 70

Table 17: Descriptive Statistics of Women and Men in the 

HRS by Age 76

Table 18: Proportion of Individuals Changing Status between 

Observations 79

Table 19: Divorce Effect on Household Assets and Income 84

Table 20: Widowhood Effect on Household Assets and Income 85

Table 21: Unemployment Effect 86

Table 22: A Decline in Health’s Effect on Household Assets and 

Income 87

Table 23: Effects of Providing Financial Assistance or Physical 

Care on Household Assets and Income 88

Figures

Figure 1: Labor Force Participation Rates for Women, Ages 25 to 64 5

Figure 2: In 2009, Working Women and Working Men Were Similar 

in Their Access to and Participation in EmployerSponsored Pension Plans 10

Figure 3: Proportion of Working Women and Men with Employers 

That Offered Any Type of Pension Plan and DC Plans 

Specifically 11

Figure 4: The Proportion of Working Women and Working Men 

with Employers That Offered DC Pension Plans Varied, by 

Race 13
Page iii GAO-12-699 Women’s Retirement Security 

Figure 5: The Proportion of Working Women and Men Who Were 

Eligible for Their Employer’s Pension Plans (among the 

Population Whose Employers Offered a Plan) 14

Figure 6: The Proportion of Eligible Women and Men That 

Participated in Any Type of Employer-Sponsored Pension 

Plan or in DC Plans (among the Population That Was 

Eligible for a Plan) 15

Figure 7: The Proportion of Working Women and Working Men 

(among Those Who Were Eligible) Who Participated in 

Their Employer’s Defined Contribution Pension Plans, by 

Race 16

Figure 8: The Composition of Household Income for Women and 

Men Age 65 and Over Did Not Fluctuate Greatly Over 

Time 19

Figure 9: Differences in the Composition of Household Income for 

Women and Men Age 65 and Over, by Marital Status, 2010 20

Figure 10: Differences in the Composition of Household Income for 

Women and Men Age 65 and Over, by Age Group, 2010 21

Figure 11: Differences in the Composition of Household Income for 

Women and Men Age 65 and Over, by Race and Ethnicity, 

2010 23

Figure 12: Median Household Incomes in 2010 for Individuals 65 

and Over by Age Group 25

Figure 13: Poverty Rates by Demographic Categories in 2010 for 

Women and Men Age 65 and Over 26

Figure 14: Estimated Effects of Divorce and Separation on Total 

Household Assets and Income 30

Figure 15: Estimated Effects of Widowhood on Total Household 

Assets and Income 32

Figure 16: Estimated Effects of Unemployment on Total Household 

Assets and Income 33

Figure 17: Estimated Effects of a Decline in Health on Total 

Household Assets and Income 34
Page iv GAO-12-699 Women’s Retirement Security 

Abbreviations

AHEAD Asset and Health Dynamics of the Oldest Old

CODA Children of the Depression Era

DB defined benefit

DC defined contribution

ERISA Employee Retirement Income Security Act of 1974 

HRS Health and Retirement Study

IRA individual retirement account

SCF Survey of Consumer Finances 

SIPP Survey of Income and Program Participation

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Page 1 GAO-12-699 Women’s Retirement Security 

United States Government Accountability Office 

Washington, DC 20548

July 19, 2012

The Honorable Herb Kohl

Chairman

Special Committee on Aging

United States Senate

Dear Mr. Chairman,

Historically, elderly women have been at greater risk of living in poverty 

than elderly men. Several economic and demographic factors contribute 

to their higher poverty rates in old age. First, women’s average annual 

earnings are consistently lower than men’s. Second, women are more 

likely to take time out of the workforce to care for children and elderly 

relatives. These employment patterns result in lower retirement savings, 

reduced Social Security benefits,1 and smaller pension benefits for 

women in comparison to men. Third, women tend to live longer than men, 

increasing the risk of exhausting their retirement savings before death. 

Finally, women are more likely than men to live alone in old age,2

Recent economic events affecting both men and women have the

potential to exacerbate older women’s financial insecurity. The financial 

crisis and recent recession have resulted in depressed home values and 

high unemployment rates among younger and older Americans alike. At 

the same time, health care costs continue to rise. Efforts to address the 

financial challenges of Social Security and Medicare could lead to a 

increasing their vulnerability to unexpected economic and health shocks 

due to the inability to pool resources with a partner or benefit from 

spousal care-giving in the event of an illness.

 

1

Generally, Social Security retirement benefits are based on up to 35 years of a worker’s 

indexed earnings. Average lower earnings over a lifetime and fewer years in the workforce 

lead to significantly lower average benefit amounts for women as compared to men. In 

2009, the average annual Social Security income received by retired women was $12,155 

compared to $15,620 for men, according to one study. See Carroll L. Estes, Terry O’Neill 

and Heidi Hartmann, Breaking the Social Security Glass Ceiling: A Proposal to Modernize 

Women’s Benefits, Institute for Women’s Policy Research, National Committee to 

Preserve Social Security & Medicare Foundation, and National Organization for Women 

Foundation (May 2012).

2

This is due to at least two factors: women have longer life expectancies, and in marriages 

the husband is, on average, older than the wife by 3 years.

 
 

Page 2 GAO-12-699 Women’s Retirement Security 

reduction in benefits for retirees.3

In light of this unique confluence of circumstances, the Senate Special 

Committee on Aging requested that we explore the issue of women’s 

retirement income security with a special focus on the effects of the 

recent financial crisis and subsequent recession, and the persistent trend 

of employers to replace DB with DC plans.

In addition, the burden of saving for 

retirement and paying for old-age health care has been shifting from 

employers to employees in both the private and public sectors. In the 

private sector, for example, many employers continue to replace defined 

benefit (DB) pension plans with defined contribution (DC) plans and 

reduce or eliminate retiree health insurance benefits. At the same time, 

many employed in the public sector have seen a reduction in their 

pension benefits or an increase in employee contributions for those 

benefits.

4

To address these questions, we analyzed two nationally-representative 

datasets, conducted an extensive literature review, and consulted with 

numerous experts. Specifically, to analyze plan coverage and 

participation rates among the working-age population, we used data for 

the late 1990s through 2009 from the Survey of Income and Program 

Participation (SIPP), a nationally-representative survey.

Specifically, this report 

examines (1) how women’s access to and participation in employersponsored retirement plans compare to men’s and how they have 

changed over time, (2) how women’s retirement income compares to 

men’s and how the composition of their income changed with economic 

conditions and trends in pension design, (3) how events occurring later in 

life affect women’s retirement income security, and (4) what policy options 

are available to help increase women’s retirement income security.

5

 

3

In 2008, about 69 percent of single women 65 and over living alone would have been 

living in poverty if it were not for Social Security benefits they received, according to a 

study published by the Institute for Women’s Policy Research. See Jeff Hayes, Heidi 

Hartmann, and Sunhwa Lee, Social Security: Vital to Retirement Security for 35 Million 

Women and Men, Institute for Women’s Policy Research Briefing Paper, IWPR 

Publication #D487 (March 2010).

With these data, 

4

This report builds upon our past work for this committee. See GAO, Retirement Security: 

Women Face Challenges in Ensuring Financial Security in Retirement, GAO-08-105

(Washington, D.C.: Oct. 11, 2007).

5

Specifically, we used data from the 1996, 2001, 2004, and 2008 SIPP panel surveys, 

which are administered over a period of several years.
 

Page 3 GAO-12-699 Women’s Retirement Security 

we computed descriptive statistics on plan coverage, eligibility, and 

participation rates and conducted an econometric analysis of each of 

these. To analyze median incomes and the income composition of the 

retirement-age population, we computed descriptive statistics using SIPP 

data from the late 1990s through 2010.6 To understand the factors that 

affect women’s income and assets, we developed a statistical model to 

estimate the effects of events occurring later in life, such as widowhood, 

using the Health and Retirement Study (HRS), a nationally representative 

dataset that tracks Americans 51 years or older over time.7 We conducted 

a data reliability assessment of selected SIPP and HRS data and found 

that, for the purposes of our analysis, the data that we analyzed were 

sufficiently reliable. Finally, to identify policy options that could increase 

retirement income security among women, we conducted an extensive 

literature review and interviewed a range of experts in the area of 

retirement income security.8

We conducted this performance audit from March 2011 through July 2012 

in accordance with generally accepted government auditing standards. 

Those standards require that we plan and perform the audit to obtain 

sufficient, appropriate evidence to provide a reasonable basis for our 

findings and conclusions based on our audit objectives. We believe that 

the evidence we obtained provides a reasonable basis for our findings 

and conclusions based on our audit objectives. For more information on 

our scope and methodology, see appendix I.

 

6

Data on income were available through 2010, while data on retirement plan coverage 

and participation were only available through 2009.

7

Specifically, we used a statistical technique called “fixed-effects regression.” Because the 

HRS tracks individuals over time, we were able to estimate the percentage change in 

household income and assets that occurs for an individual after a life event, relative to an 

individual that did not experience that life event, but also became older. In this way, we 

were able to isolate the effect of the life event from other factors. We used all available 

years of HRS data, including early release data for 2010. For more information on 

methods, see appendix I. 

8

To ensure that we obtained a balanced perspective, we interviewed experts with a range 

of viewpoints and from different types of organizations including government, academia, 

advocacy groups, and the private sector. For a list of organizations, see appendix I.
 

Page 4 GAO-12-699 Women’s Retirement Security 

Since the early 1900s, female life expectancy has exceeded male life 

expectancy, resulting in women outnumbering men in the older age 

groups. Although gender differences in life expectancy have been 

decreasing, women age 65 and over continue to outnumber men age 65 

and over. This trend is projected to continue over the next 4 decades. 

Further, the population age 65 and over is expected to more than double 

from 2010 to 2050.9 The population of women among the “oldest-old”—

those 85 and over—is also projected to grow.10 Today, of those age 65 

and over, one-sixth of women and one-tenth of men are among the 

oldest-old and this is projected to grow to almost one-quarter of women 

and one-fifth of all men by 2050.11

Women’s workforce participation surged over the last half of the 20th 

century. Among women ages 25 to 54, the rate of labor force participation 

jumped from 42 percent by the end of the 1950s to about 74 percent by 

the late 1980s. The rate continued to grow in the 1990s but at a slower 

pace. Over the last decade, the rate declined slightly from its peak of 76.8 

percent in 1999, and was 74.7 percent in 2011. Labor force participation 

rates have varied by generation, with women born in the baby boom 

generation much more likely to be in the workforce than preceding 

generations.12

 

9

Linda A. Jacobsen, Mary Kent, Marlene Lee, and Mark Mather, “America’s Aging 

Population,” Population Bulletin, Population Reference Bureau, vol. 66, no. 1 (2011).

As baby boomers have aged, workforce participation rates 

have increased significantly for women ages 55 to 64 (see fig. 1). 

10Ibid.

11Ibid. 

12The baby boom generation consists of individuals born from 1946 to 1964.

Background

Demographic and Labor Force 

Trends Affecting Women’s 

Retirement Income Security 
 

Page 5 GAO-12-699 Women’s Retirement Security 

Figure 1: Labor Force Participation Rates for Women, Ages 25 to 64

Despite their economic gains, women continue to have lower annual 

earnings than men, on average, and much lower lifetime earnings. In 

2010, the median earnings of women working full-time were about 

$36,900, compared to $47,700 for men.13 One study reported that a 25-

year-old woman with a college degree will make about $523,000 less in 

wages over her lifetime compared to a man with a college degree.14

Further, the study noted that of those retiring at age 62 in 2000, women 

were in the workforce for 12 years less than men, on average, primarily

because they spent more time than men out of the workforce caring for 

family members.15

 

13Carmen DeNavas-Walt, Bernadette D. Proctor, and Jessica C. Smith, “Income, Poverty, 

and Health Insurance Coverage in the United States: 2010” Current Population Reports, 

Consumer Income, United States Census Bureau, P60-239 (September 2011).

14Cindy Hounsell, The Female Factor 2008: Why Women Are at Greater Financial Risk in 

Retirement and How Annuities Can Help (Washington, D.C.: Americans for Secure 

Retirement, 2008).

15Ibid.
 

Page 6 GAO-12-699 Women’s Retirement Security 

Although the composition of retirement income—the proportion of income 

coming from different sources—varies greatly for individual households, 

Social Security benefits, pension income, and earnings make up the bulk 

of income for the U.S. population age 65 and over. Social Security 

provides retirement benefits to eligible workers, based on their work and 

earnings history. Social Security also provides benefits to eligible workers 

who become disabled before reaching retirement age, as well as 

spouses, widow(er)s, and children of eligible workers. Although all Social 

Security benefits are based upon a common formula, they are calculated 

in different ways for each beneficiary type.16 The level of the monthly 

benefit is adjusted for inflation and varies depending on the age at which 

the beneficiary chooses to begin receiving benefits. Generally, 

beneficiaries may begin receiving retirement benefits at age 62; however, 

the payments will be higher if they wait to receive benefits at their full 

retirement age, which varies from 65 to 67, depending on the 

beneficiary’s birth year. The monthly retirement benefit continues to rise 

for workers who delay benefits beyond their full retirement age, up to age 

70. Employees and employers pay payroll taxes that finance Social 

Security benefits. However, Social Security faces a long-term financing 

shortfall resulting largely from lower birth rates and longer life spans. 

According to the Social Security Trustees, the Social Security Trust 

Funds could be exhausted by 2033 and unable to pay full benefits.17

Pension income from employer-provided retirement plans falls into two 

broad categories: DB and DC pension plans. DB plans typically provide 

retirement benefits to each retiree in the form of an annuity that provides a 

monthly payment for life, the value of which is typically determined by a 

formula based on particular factors specified by the plan, such as salary or 

years of service. Under DC plans, workers and employers may make 

 

16For example, wives may be eligible to receive a spousal benefit equal to 50 percent of 

their husbands’ benefits. If a wife receiving this benefit becomes widowed, then the benefit 

becomes a survivor benefit, and may equal up to 100 percent of the husband’s benefit. 

For more information on how the different types of benefits are calculated, see GAO, 

Social Security Reform: Issues for Disability and Dependent Benefits, GAO-08-26 

(Washington, D.C.: Oct. 26, 2007).

17The Board of Trustees, Federal Old-Age and Survivors Insurance and Federal Disability 

Insurance Trust Funds, The 2012 Annual Report of the Board of Trustees of the Federal 

Old-Age and Survivors Insurance and Federal Disability Insurance Trust Funds 

(Washington, D.C.: Apr. 25, 2012).

Sources of Retirement Income
 

Page 7 GAO-12-699 Women’s Retirement Security 

contributions into individual accounts.18 Workers can also save for 

retirement through an individual retirement account (IRA). IRAs allow 

workers to receive favorable tax treatment for making contributions to an 

individual account.19

At retirement, participants’ distribution options vary depending on the type 

of pension plan. Private sector DB plans must offer participants a benefit in 

the form of a lifetime annuity (either immediately or deferred). An annuity 

can help to protect a retiree against risks, including the risk of outliving 

one’s assets (longevity risk) and, when an inflation-adjusted annuity is 

provided, the risk of inflation diminishing one’s purchasing power. Some DB 

plans also give participants a choice to take a lump sum cash settlement 

(distribution) or roll over funds to an IRA, instead of taking a lifetime 

annuity.20

In addition, whether a pension plan is a DB or DC has implications for 

whether a spouse is entitled to the pension’s benefits. The Employee 

Retirement Income Security Act of 1974 (ERISA) requires that DB plans

include a survivor’s benefit, called a qualified joint and survivor annuity. 

Thus, after a worker with a DB plan dies, the surviving spouse continues 

to receive an annuity, but typically at a reduced level.

In contrast, DC plan sponsors are not required to offer a lifetime 

annuity and more often provide participants with a lump sum distribution as 

the only option. Other options for DC participants may include leaving 

money in the plan, taking a partial distribution, rolling their plan savings into 

an IRA, or purchasing an annuity, which are typically only available outside 

of the plan.

21

 

18The most common type of DC plans are 401(k) plans, which typically allow workers to 

choose to contribute a portion of their pretax compensation to the plan. 

A qualified joint 

and survivor annuity may only be waived through a written spousal

consent. Under most DC plans, the plan is written so that the employee 

19The tax treatment differs depending on the type of IRA. For example, with traditional 

IRAs, workers who meet certain conditions can take an income tax deduction on some or 

all of the contributions they make to their IRA, but they must pay taxes on amounts they 

withdraw from the IRA. Workers below certain income limits may also contribute to Roth 

IRAs, which do not provide an income tax deduction on contributions, but permit tax-free 

withdrawals after a specified time period.

20Rolling funds over to an IRA allows participants to preserve the tax benefits enjoyed by 

the plan. 

21The qualified joint and survivor annuity must provide at least a 50 percent benefit 

continuation to the surviving spouse.
 

Page 8 GAO-12-699 Women’s Retirement Security 

may, during his or her lifetime, make withdrawals from the account or roll 

over the balance into an IRA without spousal consent, provided that the

employee’s vested account balance is payable in full on death to the 

surviving spouse. 

Over the past quarter-century, the percentage of private sector workers 

participating in employer-sponsored pension plans has held steady at 

about 50 percent. Although some workers choose not to participate in an 

employer-sponsored pension plan, the large majority of nonparticipating 

workers do not have access to one.22 In addition, over the last 3 decades, 

the U.S. retirement system has undergone a major transition from one 

based primarily on DB plans to one based on DC plans, increasing 

workers’ exposure to economic volatility and usually shifting the burden of 

saving to the individual worker, which makes them more reliant on their 

own decision making. As we have previously reported, from 1990 to 

2008, the number of active participants in private sector DB plans fell by 

28 percent, from about 26 million to about 19 million. Over the same 

period, the number of active participants in DC plans increased by 90 

percent, from about 35 million to about 67 million.23 DC plans generally do 

not offer annuities, so retirees are left with increasingly important 

decisions about managing their retirement savings to ensure they have 

income throughout retirement.24 These decisions may be more difficult to 

make in times of economic volatility. For example, two recent 

recessions—one beginning in March 2001 and ending in November 2001 

and the other beginning in December 2007 and ending in June 200925

 

22GAO, Retirement Savings: Automatic Enrollment Shows Promise for Some Workers, but 

Proposals to Broaden Retirement Savings for Other Workers Could Face Challenges, 

—

resulted in major stock indices falling dramatically. The long-term effects 

of financial market fluctuations on retirement income security are 

GAO-10-31 (Washington, D.C.: Oct. 23, 2009).

23GAO, Retirement Income: Ensuring Income throughout Retirement Requires Difficult 

Choices, GAO-11-400 (Washington, D.C.: June 7, 2011). 

24DC participants can purchase annuities on the retail market. However, retail annuities 

are typically more expensive for women than for men because of women’s longer life 

expectancy, whereas in-plan annuity options, when they are offered, must be at genderneutral rates. In addition, in-plan rates may be lower than retail rates because the in-plan 

rate may be able to take advantage of a lower, institutional price. Nonetheless, research 

shows that most people choose not to annuitize DC savings.

25These recession periods were identified by the National Bureau of Economic Research 

Business Cycle Dating Committee. 

National Trends Affecting 

Retirement Security for Men 

and Women
 

Page 9 GAO-12-699 Women’s Retirement Security 

uncertain, but the effects may vary based on factors such as age, type of 

pension plan, and employment status.26 Employment status, in particular, 

can pose serious challenges for retirement security. As we recently 

reported, long-term unemployment can reduce an older worker’s future 

monthly retirement income in numerous ways such as by reducing the 

number of years the worker can accumulate DB plan retirement benefits 

or DC plan savings, by motivating workers to claim Social Security at an 

earlier age, and by leading workers to draw down retirement savings to 

pay for expenses during unemployment.27

From 1998 to 2009, working women surpassed men in their likelihood of 

having an employer that offered a pension plan, but were slightly less 

likely to be eligible for and to participate in those plans.28

 

26GAO, Private Pensions: Some Key Features Lead to an Uneven Distribution of Benefits, 

However, this 

gap, narrowed over time. In fact, by 2009, the same proportion of working 

women and men ultimately participated in some type of plan (either a DB 

or a DC) as shown in figure 2. Nonetheless, women’s contribution rates to 

DC plans remained lower than those of men.

GAO-11-333 (Washington, D.C.: Mar. 30, 2011).

27See GAO, Unemployed Older Workers: Many Experience Challenges Regaining 

Employment and Face Reduced Retirement Security, GAO-12-445 (Washington, D.C.: 

Apr. 25, 2012).

28The statistics we present in this section are unadjusted point estimates computed from 

the SIPP data without taking into account differences between men and women in 

demographic and occupational characteristics. To adjust these point estimates by taking 

into account different factors that might explain gender differences in these three 

outcomes—working for an employer that offers a plan, plan eligibility, and participation—

we also conducted multivariate analysis. The detailed results of these analyses are 

presented in appendix I. 

Working Women’s 

Access to and 

Participation in 

Employer-Sponsored 

Pension Plans Have 

Improved Relative to 

Men
 

Page 10 GAO-12-699 Women’s Retirement Security 

Figure 2: In 2009, Working Women and Working Men Were Similar in Their Access 

to and Participation in Employer-Sponsored Pension Plans

Note: Percentage estimates in this figure have 95 percent confidence intervals that are within +/- 1 

percent of the estimate itself. 

While working men and women were just as likely to have employers that 

offered pension plans in 1998, by 2009, these women were more likely 

than men to work for employers that offered pension plans (see fig. 3). 

This may be due to the sectors and industries in which women worked. 

For example, a greater proportion of women than men worked in the 

public and nonprofit sectors—sectors that have higher proportions of 

workers with access to plans offered by employers—than the for-profit 

sector. Women were also more likely to work in the education and health 

industries—industries that have higher proportions of workers with access 

to plans offered by employers.29

 

29For more information on women’s and men’s occupations and industries and other 

factors associated with working for an employer that offers a plan, see appendix I.

In contrast, men had higher rates of selfemployment over this period, and self-employed individuals were much 

less likely to have retirement plans. In addition, from 1998 to 2009, the 

proportion of working women and men with employers that offered 

pension plans declined after 2003, possibly reflecting the decline in the 

Women Surpassed Men in 

Their Likelihood of 

Working for an Employer 

That Offers a Pension Plan
 

Page 11 GAO-12-699 Women’s Retirement Security 

number of employers offering DB plans.30

Figure 3: Proportion of Working Women and Men with Employers That Offered Any 

Type of Pension Plan and DC Plans Specifically

Furthermore, the proportion of 

women working for employers offering DC plans increased, rising from 41 

to 49 percent (see fig. 3). With the exception of 1998, women were more 

likely to work for employers that offered DC plans than were men.

Note: Percentage estimates in this figure have 95 percent confidence intervals that are within +/- 1 

percent of the estimate itself. 

 

30In prior work, GAO reported that net new plan formation between 2003 and 2007 had 

been very small (about 1 percent) and that new plan formation was offset by plan 

terminations or mergers. In addition, 92 percent of newly-formed plans were DC plans and 

were generally small, with 96 percent having fewer than 100 participants. See GAO, 

Private Pensions: Some Key Features Lead to an Uneven Distribution of Benefits, 

GAO-11-333 (Washington, D.C.: Mar. 30, 2011). GAO also reported that plan sponsors 

voluntarily terminated over 61,000 sufficiently funded single-employer DB plans from 1990 

to 2006 and that a number of large employers, representing a significant portion of 

participants in the DB pension system, had announced their intention to freeze one or 

more of their DB plans. See GAO, Defined Benefit Pensions: Plan Freezes Affect Millions 

of Participants and May Pose Retirement Income Challenges, GAO-08-817 (Washington, 

D.C.: July 21, 2008).
 

Page 12 GAO-12-699 Women’s Retirement Security 

Moreover, as shown in figure 4, while the proportion of working women 

with an employer that offered a DC plan increased through 2009—though 

not always steadily—it varied by racial and ethnic groups. White and 

Black women, for example, were the most likely to work for an employer 

that offered a plan, while Hispanic women were the least likely.31

 

31Individuals in the White, Black, and Asian racial and ethnic categories are non-Hispanic.

Interestingly, with only a few exceptions (i.e., Whites in 1998 and Asians 

in 2003 and 2009), the proportion of women working for an employer 

offering a plan was equal to or higher than that of men of the same race.
 

Page 13 GAO-12-699 Women’s Retirement Security 

Figure 4: The Proportion of Working Women and Working Men with Employers That 

Offered DC Pension Plans Varied, by Race

Note: For Whites, percentage estimates in this figure have 95 percent confidence intervals that are 

within +/-2 percentage points or less of the estimate itself. For Blacks, Hispanics, and Asians, the 95 

percent confidence intervals are within +/-3, 3 and 6 or fewer percentage points of the estimate itself 

respectively. For Asians, the variation by year may be due to their relatively small sample size. 
 

Page 14 GAO-12-699 Women’s Retirement Security 

Among those working for an employer offering a pension, the vast 

majority of both women and men were eligible to participate in the plan, 

and their eligibility rates generally increased over time (see fig. 5). 

Moreover, women’s eligibility rates increased more than men’s, thereby 

narrowing the gap between men and women from 7 to 4 percentage 

points.

Figure 5: The Proportion of Working Women and Men Who Were Eligible for Their 

Employer’s Pension Plans (among the Population Whose Employers Offered a Plan)

Note: Percentage estimates in this figure have 95 percent confidence intervals that are within +/-2 

percent or less of the estimate itself. 

Of the women who were not eligible to participate in their employer’s 

pension plan in 2009, the majority reported that they were not eligible 

because they did not work enough hours, weeks, or months per year at 

their place of employment. Correspondingly, women that worked parttime were significantly less likely to be eligible for their employer’s plan, 

according to our analysis.32

 

32For more information on other factors associated with employer-plan eligibility, see 

appendix I.

In contrast, men most frequently cited 

insufficient tenure as the reason for ineligibility.

Women Working for 

Employers Offering Plans 

Made Gains in Plan 

Eligibility
 

Page 15 GAO-12-699 Women’s Retirement Security 

Among those eligible to participate in their employer’s pension plan, 

women had lower rates of participation than men, but this gap diminished 

over time as men’s participation rates declined. Specifically, the 

participation rate for women in any type of plan (DB or DC) declined 

slightly from 87 percent in 1998 to 86 percent in 2009, while the 

participation rate for men declined from 91 to 87 percent (see fig. 6). 

Among those eligible for DC plans, women’s participation rates increased 

by one percentage point over the years we analyzed, while men’s 

declined by 2 percentage points. Taken together, the gender participation 

gap in DC take-up rates narrowed from 4 to 1 percentage points.

Figure 6: The Proportion of Eligible Women and Men That Participated in Any Type 

of Employer-Sponsored Pension Plan or in DC Plans (among the Population That 

Was Eligible for a Plan)

Note: Percentage estimates in this figure have 95 percent confidence intervals that are within +/-2 

percent or less of the estimate itself. 

Women’s participation rates in DC plans also varied by race. As shown in 

figure 7, White and Asian women had the highest participation rates in 

DC plans, ranging from 79 and 78 percent respectively in 1998 to 80 and 

85 percent in 2009. Black and Hispanic women had lower participation 

rates, but the rate for Black women increased over time from 66 to 70 

percent. With some exceptions, across all racial and ethnic groups, 

eligible women tended to have lower participation rates than eligible men 

across all 4 years.

The Gender Gap in Plan 

Participation Narrowed
 

Page 16 GAO-12-699 Women’s Retirement Security 

Figure 7: The Proportion of Working Women and Working Men (among Those Who 

Were Eligible) Who Participated in Their Employer’s Defined Contribution Pension 

Plans, by Race

Note: For Whites, percentage estimates in this figure have 95 percent confidence intervals that are 

within +/-2 percentage points or less of the estimate itself. For Blacks, Hispanics, and Asians, the 95 

percent confidence intervals are within +/-5, +/-6, and +/-7 or fewer percentage points of the estimate 

respectively. 

Several characteristics of women help to explain their lower participation 

rates in DC plans. For one, women had significantly lower levels of 

household income than men across all 4 years. Our analysis, coupled 

with studies conducted by outside experts, indicates that higher incomes 
 

Page 17 GAO-12-699 Women’s Retirement Security 

are associated with higher rates of plan participation.33 Further, despite 

women’s increasing attachment to the labor force, they continue to be 

more likely than men to work part-time and to have less tenure—factors 

we and others have found to be associated with lower DC participation 

rates.34 At the same time, a higher proportion of women are singleparents—a factor that we found to be negatively associated with plan 

participation. After accounting for these differences (and differences in 

other factors) between men and women, women did not have significantly 

lower participation rates than men in 2009.35

In addition to having lower rates of participation, women also contributed 

to their DC plans at lower levels than men. Among those reporting their 

contributions as shares of their salaries, women’s contribution rates 

hovered around 6.7 percent of their salaries while men’s contribution 

rates averaged around 7.2 percent over the years of our analysis.36

Among those reporting their contributions in dollar amounts, women’s 

annual contributions were consistently around 30 percent lower than 

men’s over the study period.

 

33See Alicia H. Munnell, Annika Sundén, and Catherine Taylor, “What Determines 401(k) 

Participation and Contributions?” Social Security Bulletin, vol. 64, no. 3 (2001/2002). See 

appendix I for additional information on our modeling analyses. 

34See Lois Shaw and Catherine Hill, The Gender Gap in Pension Coverage: What Does 

the Future Hold?, Institute for Women’s Policy Research, IWPR Publication #E507 (May 

15, 2001). Shaw and Hill find that hours worked per week and job tenure are positively 

related with participating in a pension plan. 

35These results are consistent with those of outside researchers. For example, one study 

found that before controlling for differences between men and women in other factors that 

might affect participation, women had significantly lower participation rates than men. 

However, after controlling for differences between men and women, women were 6.5 

percent more likely to participate in a DC plan. See Gur Huberman, Sheena S. Iyengar, 

and Wei Jiang, “Defined Contribution Pension Plans: Determinants of Participation and 

Contributions Rates,” Journal of Financial Services Research (January 2007). For more 

information on other factors associated with employer-plan participation, see appendix I.

36These estimates of contribution levels are consistent with estimates (for both men and 

women combined) from other studies using recent SIPP data. See, for example, 

“Retirement Plan Participation: Survey of Income and Program Participation (SIPP) Data, 

2009” Employee Benefit Research Institute Notes, vol. 31, no.11 (November 2010): 2.
 

Page 18 GAO-12-699 Women’s Retirement Security 

The composition of women’s and men’s retirement income did not vary 

greatly over the last decade despite changes in the economy and pension 

system, largely because their main income sources—Social Security and 

DB plans—were shielded from fluctuations in the financial market. 

However, women, especially widows and those 80 years and over, 

depended on Social Security benefits for a larger percentage of their 

income than men. In contrast, women received a lower share of their 

income from earnings than men. Women age 65 and over also had less 

retirement income on average and higher rates of poverty than men in 

that age group. Specifically, for the population age 65 and over, women’s 

median income was approximately 25 percent lower than men in the 

same age group for all years.37 Moreover, women in this age group were 

nearly twice as likely to be living in poverty than men.

The composition of household income for women and men age 65 and 

over fluctuated only slightly from 1998 to 2010, despite changes in the 

economy and the pension system (see fig. 8). The composition of 

household income did not fluctuate drastically largely because Social 

Security and DB benefits comprised nearly three-quarters of household 

income for women and slightly less (around 70 percent) for men, 

providing them with guaranteed monthly income for life. Women tended to 

receive a higher proportion of household income from Social Security. In 

fact, in 2010, 16 percent of women age 65 and over depended solely on 

Social Security for income compared to 12 percent of men. At the same 

time, the share of income from earnings increased slightly for men and 

women, but was consistently lower for women than for men. Furthermore, 

the share of income from DC plans was very low (1 to 2 percent) across 

the entire period for both men and women. This is due to the fact that the 

lion’s share of people age 65 and over did not report receiving any 

income from regular distributions from DC plans.38

 

37For the analysis in this section, we used SIPP data from 1998, 2003, 2006, and 2010. 

See appendix I for more details on the data and our analyses.

38This may be due to the fact that retirees tend to withdraw funds from DC accounts 

irregularly, instead of annuitizing. To the extent that nonregular (lump sum) distributions 

comprise a significant portion of income, our estimates of income shares from other 

sources, such as Social Security, might be overstated. However, because of the 

irregularity of these lump sum distributions, it is difficult to observe them with household 

survey data because surveys generally measure income only at a particular point in time.

While Income 

Composition Changed 

Only Slightly for 

Women Age 65 and 

Over, They Continue 

to Have Less 

Retirement Income 

Than Men

The Composition of 

Income for Women and 

Men Age 65 and Over Did 

Not Fluctuate Greatly 

Despite Changes in the 

Economy and Pension 

System
 

Page 19 GAO-12-699 Women’s Retirement Security 

Figure 8: The Composition of Household Income for Women and Men Age 65 and Over Did Not Fluctuate Greatly Over Time

Notes: Estimates for men and women include spousal income. The category for income from defined 

contribution pensions reflects total household distributions from IRAs, as well as 401(k) pension plans 

and similar defined contribution pension plans. Nonregular (lump sum) withdrawals from IRA and 

401(k) plans are not included. The “other” category includes income from cash public assistance and 

property income including interest, dividends, rent and royalties. Percentages may not add to 100% 

due to rounding. Percentages are based on household incomes for each source including zero 

values. Percentage estimates of the income shares from Social Security, earnings, defined benefit 

pension, and defined contribution pensions have 95 percent confidence intervals that are within +/- 

2.5 percent of the estimate itself. For information on how these percentages were estimated, see 

appendix I. 

As shown in figures 9 to 11, in 2010, the composition of household 

income for individuals age 65 and over also varied by demographic 

group. Among marital-status categories, widowed women depended on 

Social Security benefits for a larger percentage of their income (58 

percent) than other women (see fig. 9). In fact, about 21 percent of all 

widowed women depended on Social Security as their sole source of 

income. Separated women and men received higher shares of income 

from earnings, and married women and men received relatively higher 

shares of their income from DB plans.
 

Page 20 GAO-12-699 Women’s Retirement Security 

Figure 9: Differences in the Composition of Household Income for Women and Men Age 65 and Over, by Marital Status, 2010

Notes: In the category for married individuals, estimates for men and women include spousal income. 

The category for income from defined contribution pensions reflects total household distributions from 

IRAs, as well as 401(k) and similar defined contribution pension plans. Nonregular (lump sum) 

withdrawals are not included. The “other” category includes income cash public assistance and property 

income including interest, dividends, rent and royalties. Percentages may not add to 100% due to 

rounding. Percentage estimates of the income shares from Social Security have 95 percent confidence 

intervals that are within +/-2, +/-3, +/-4, +/-10 and +/-6 percent of the estimate itself for married, widowed, 

divorced, separated and never married individuals respectively. Percentage estimates of the income 

shares from earnings have 95 percent confidence intervals that are within +/-2, +/-2, +/-3, +/-11 and +/-6 

percent of the estimate itself for married, widowed, divorced, separated and never married individuals 

respectively. Percentage estimates of the income shares from defined benefit plans have 95 percent

confidence intervals that are within +/-2, +/-3, +/-3, +/-7 and +/-5 percent of the estimate itself for 

married, widowed, divorced, separated and never married individuals respectively. Percentage 

estimates of the income shares from defined contribution plans have 95 percent confidence intervals 

that are within +/- 2 percent of the estimate itself for all marital status categories.

As shown in figure 10, among different age groups, women age 80 and 

over received the highest share of their income from Social Security (61 

percent). In fact, about 20 percent of them depended on Social Security 

for their sole source of income. Men in the youngest age category (65 to 

69) received a higher share of their income from earnings (31 percent) 

relative to other groups, while individuals in the oldest age categories 

received the smallest share of income from earnings, likely reflecting the 

declining ability to work at older ages.
 

Page 21 GAO-12-699 Women’s Retirement Security 

Figure 10: Differences in the Composition of Household Income for Women and Men Age 65 and Over, by Age Group, 2010

Notes: Estimates for men and women include spousal income. The category for income from defined 

contribution pensions reflects total household distributions from IRAs, as well as 401(k) and similar 

defined contribution pension plans. Nonregular (lump sum) withdrawals are not included. The “other” 

category includes income from cash public assistance and property income including interest, 

dividends, rent and royalties. Percentages may not add to 100 percent due to rounding. Percentage 

estimates of the income shares from Social Security have 95 percent confidence intervals that are 

within +/-2, +/-4, +/-3, and +/-2 percent of the estimate itself for individuals in the 65-69, 70-74, 75-79, 

and 80+ age categories respectively. Percentage estimates of the income shares from earnings have 

95 percent confidence intervals that are within +/-2 percent of the estimate itself for individuals in all 

age categories respectively. Percentage estimates of the income shares from defined benefit pension 

plans have 95 percent confidence intervals that are within +/-2, +/-2, +/-2, and +/-4 percent of the 

estimate itself for individuals in the 65-69, 70-74, 75-79, and 80+ age categories respectively. 

Percentage estimates of the income shares from defined contribution pension plans have 95 percent 

confidence intervals that are within +/-0.5, +/-3, +/-1, and +/-1 percent of the estimate itself for 

individuals in the 65-69, 70-74, 75-79, and 80+ age categories respectively. 
 

Page 22 GAO-12-699 Women’s Retirement Security 

Finally, among racial and ethnic groups, White and Black women and 

men age 65 and over received the highest share of income from Social 

Security (see fig. 11). In contrast, Asians and Hispanics tended to receive 

a lower share of their incomes from Social Security.39

 

39In “Racial and Ethnic Differences in Women’s Retirement Security,” Journal of Women, 

Politics & Policy, 30 (2009): 141-171, Sunhwa Lee also notes that Social Security is the 

most common source of retirement income and that differences in immigrant status do not 

entirely account for the lower rates of Social Security receipt among Hispanics and 

Asians. Maya Rockeymoore and Meizhu Lui highlight that Hispanics are disproportionately 

represented in job categories that were previously excluded from the Social Security 

program, such as agricultural and household workers. They point out that, although these 

job categories are now covered, earnings in these categories might not be recorded 

accurately in Social Security tax payment records, which could lead to lower payments 

and therefore a lower share of income from Social Security. See Maya M. Rockeymoore 

and Meizhu Lui, Plan for a New Future: The Impact of Social Security Reform on People 

of Color (Washington, D.C.: Commission to Modernize Social Security, 2011).

Asian men and 

women received a disproportionately higher share of income from 

earnings relative to other racial and ethnic categories. White and Black 

women and men received higher shares of income from DB plans, 

compared to Hispanics and Asians.
 

Page 23 GAO-12-699 Women’s Retirement Security 

Figure 11: Differences in the Composition of Household Income for Women and Men Age 65 and Over, by Race and Ethnicity, 2010

Notes: Estimates for men and women include spousal income. The category for income from defined 

contribution pensions reflects total household distributions from IRAs, as well as 401(k) and similar 

defined contribution pension plans. Nonregular (lump sum) withdrawals are not included. The “other” 

category includes income from cash public assistance and property income including interest, 

dividends, rent and royalties. Percentages may not add to 100 percent due to rounding. The size of 

the 95 percent confidence intervals for estimates presented in this figure varies by racial/ethnic 

category. Percentage estimates of the income shares from Social Security have 95 percent 

confidence intervals that are within +/-2, +/-4, +/-5, and +/-6 percent of the estimate itself for White, 

Black, Hispanic, and Asian individuals respectively. Percentage estimates of the income shares from 

earnings have 95 percent confidence intervals that are within +/-1, +/-3, +/-5, and +/-7 percent of the 

estimate itself for White, Black, Hispanic, and Asian individuals respectively. Percentage estimates of 

the income shares from defined benefit plans have 95 percent confidence intervals that are within +/-

2, +/-3, +/-3, and +/-7 percent of the estimate itself for White, Black, Hispanic, and Asian individuals 

respectively. Percentage estimates of the income shares from defined contribution plans have 95 

percent confidence intervals that are within +/-1 percent for all the racial and ethnic categories. 
 

Page 24 GAO-12-699 Women’s Retirement Security 

Women age 65 and over had consistently lower median incomes than 

men across age and most race groups over time.40

 

40We used SIPP data to analyze household income among individuals 65 and over from 

1998 to 2010.

Over the last decade, 

the median incomes of women age 65 and over were approximately 25 

percent lower than their male counterparts. Median incomes, did, 

however, vary by demographic category (see fig. 12). Demographic 

groups with the lowest median incomes included women who were either 

unmarried—especially those who had been separated or never married—

over the age-of 80, or Black or Hispanic.

Median Household Income 

for Women Age 65 and 

Over Was 25 Percent 

Lower Than Men’s
 

Page 25 GAO-12-699 Women’s Retirement Security 

Figure 12: Median Household Incomes in 2010 for Individuals 65 and Over by Age 

Group

Notes: Estimates for men and women include spousal income. Estimates of median incomes have 95 

percent confidence intervals that are within +/-$900 for women and +/-$1,200 for men in the entire 

U.S., +/-$1,600 for married women, +/-$1,000 for widowed women, +/-$1,900 for divorced women, +/-

$5,200 for separated women, +/-$4,000 for never married women, +/-$1,800 for married men, +/-

$2,000 for widowed men, +/-$4,100 for divorced men, +/- $8,000 for separated men, +/-$3,500 for 

never married men, +/-$1,800 for women ages 65-69, +/-1,700 for woman age ages 70-74, +/-$2,100 

for women ages 75-79, +/-$900 for women 80 and older, +/-$2,700 for men ages 65-69, +/-$2,300 for 

men ages 70-74 and 75-79, +/-$2,200 for men 80 and over, +/-$1,000 for White women, +/-$1,400 for 

Black women, +/- $4,300 for Hispanic women, +/-$5,000 for Asian women, +/-$1,400 for White men, 

+/-$2,900 for Black men, +/-$5,300 for Hispanic men, and +/-$7,100 for Asian men. 

In addition, a greater proportion of women age 65 and over lived in 

households with incomes below the poverty line than men in the same 

age group. Consistent with their relatively lower median incomes, the 

demographic groups with the highest poverty rates were women who 
 

Page 26 GAO-12-699 Women’s Retirement Security 

were not married, over the age of 80, or non-White (see fig. 13).41

Figure 13: Poverty Rates by Demographic Categories in 2010 for Women and Men Age 65 and Over

In 

contrast, married people and White men had the lowest poverty rates.

Note: Estimates for men and women include spousal income. Percentage estimates of poverty rates 

have 95 percent confidence intervals that are within +/-1 percent for the category for the entire U.S.; 

+/-1 percent for married, +/-2 percent for widowed, +/-3 percent for divorced, +/-12 percent for 

separated, and +/-6 percent for never married individuals; +/-2 percent for all age-categories; +/-1 

percent for Whites, +/-4 percent for Blacks, +/-5 percent for Hispanics, and +/-8 percent for Asians. 

 

41Lee (2009) and Rockeymoore, et al. (2011) find similar results regarding higher poverty 

rates among unmarried and non-White women. 
 

Page 27 GAO-12-699 Women’s Retirement Security 

When women nearing or in retirement—women over age 50—became 

divorced, widowed or unemployed, the effects on their households’ total 

assets and income were detrimental, according to our analysis (see table 

1).42 Further, divorce and widowhood had more pronounced effects for 

women than for men. These effects may be contributing to elderly 

women’s higher poverty rates and lower levels of income compared to 

men’s. We also found, not surprisingly, that a decline in health after age 

50 had a negative effect on household assets and income.43 Lastly, we 

also examined the effect of caring for elderly parents on income and 

assets, but we did not find statistically significant negative relationships. 

All of these effects may not be generalizable to younger cohorts as 

women’s labor force participation and, correspondingly, their assets and 

income, have changed over the last several decades.44

 

42We estimated these effects using fixed-effects panel regressions. We used all available 

years of HRS data, from 1992 up through the early release data for 2010. Because the 

HRS tracks individuals over time, we were able to estimate the percent change in 

household assets and household income that occurs for an individual after a life event, 

relative to an individual that did not experience that life event, but also became older. In 

this way, we were able to isolate the effect of the life event from other factors. We 

analyzed the effect of each event individually. If a woman were to experience multiple 

events simultaneously, such as becoming divorced and unemployed, the effects on her 

household assets and income could be even larger. For more details on our methodology 

and results, including standard errors, see appendix I.

43For our analysis, we used a user-friendly longitudinal dataset created by RAND, a 

research organization. For total household assets, we used RAND’s variable that includes 

all household assets except for secondary residences. For income, we used RAND’s total 

household income variable. For more information on the RAND dataset, see appendix I.

44Respondents in our sample were born prior to 1954; the HRS grouped these individuals 

into five generational cohorts. In addition, these analyses did not adjust for the size of the 

household, but show the effect on total household income and assets for a person 

experiencing the event. When we adjusted our models for household size, we found 

smaller effects for divorce and widowhood, but these effects were still significant. See 

appendix I for more information.

Divorce, Widowhood, 

and Unemployment 

Had a Detrimental 

Effect on Older 

Women’s Income 

Security
 

Page 28 GAO-12-699 Women’s Retirement Security 

Table 1: Estimated Effects of Life Events on Household Assets and Income by 

Gender

Percent change

Total 

household assets

Total 

household income

Women Men Women Men

Became divorced or separated -41a -39a -41a,b -23a,b

Became widowed -32a,b -27a,b -37a,b -22a,b

Became unemployed -7a -7a -9a -7a

Health declined -8a -10a -4a -3a

Helped parents financially 3a 3a 6a 7a

Helped parents with daily activities 1 1 2a 2a

Source: GAO analysis of HRS data.

Notes: We used fixed-effects regression models to estimate the percent change in total household 

assets and income that occurs for an individual after a life event, relative to an individual that did not 

experience that life event. Total assets and income for the household were applied to each individual 

in the household. The estimated effects represent the average percent difference in household assets 

and income between all survey periods in which the household does experience an event and all 

survey periods in which the household does not experience an event. The event may have occurred 

in any year after the household entered the survey. For more details on the models, see appendix I. 

a

Estimate is significantly different from zero. 

b

Difference between women and men is statistically significant. 

As shown in figure 14, the effects of divorce or separation after age 50 

had substantial, negative effects on women’s total household assets and 

income. For both women and men, assets fell by about 40 percent with a 

divorce or separation.45

 

45Our estimated effects represent the average percent difference in household assets and 

income between all survey periods in which the household does experience an event and 

all survey periods in which the household does not experience an event.

The effects were less substantial for those living 

in households where at least one member was age 65 or over, but these 

women and men still lost about one-third of their total assets. The effects 

for income were more pronounced for women than for men. Women’s 

income fell by 41 percent, nearly twice that of men’s (23 percent). The 

effects were largest for women living in households where all members 

Became Divorced or 

Separated after Age 50
 

Page 29 GAO-12-699 Women’s Retirement Security 

were age 64 or younger; for these women, income fell by 44 percent.46

However, while divorce had very detrimental effects, we found that, for 

women ages 51 and over, divorce or separation was less prevalent than 

widowhood. Specifically, for those age 85 and over in our sample, 4 

percent of women and 2 percent of men had been divorced or 

separated.47

 

46Researchers have hypothesized that the drop in assets is due to households saving 

their assets for a rainy day and are primarily drawn down at the time of precipitating 

shocks, such as divorce. See James M. Poterba, Steven F. Venti, and David A. Wise, 

Family Status Transitions, Latent Health, and the Post-Retirement Evolution of Assets, 

NBER Working Paper 15789, issued in February 2010. Also, Wilmoth and Koso 

hypothesize that the mechanisms that systematically allocate wealth when a marriage 

ends are more effective at maintaining wealth for those who are widowed compared to 

those who are divorced. They conclude that divorce should be more detrimental to longterm wealth accumulation than widowhood. See Janet Wilmoth and Gregor Koso, “Does 

Marital History Matter? Marital Status and Wealth Outcomes Among Preretirement 

Adults,” Journal of Marriage and Family, vol. 64, no. 1 (2002).

47Further, some of these women and men could have been divorced prior to entering our 

sample.
 

Page 30 GAO-12-699 Women’s Retirement Security 

Figure 14: Estimated Effects of Divorce and Separation on Total Household Assets and Income

Notes: All estimates in this figure have 95 percent confidence intervals within +/-8 percentage points of 

the estimate itself. For statistical comparisons of the estimates across different groups, see appendix I. 

We used fixed-effects regression models to estimate the percent change in total household assets and 

income that occurs for an individual after a life event, relative to an individual that did not experience that 

life event. Total assets and income for the household were applied to each individual in the household. 

The estimated effects represent the average percent difference in household assets and income 

between all survey periods in which the household does experience an event and all survey periods in 

which the household does not experience an event. The event may have occurred in any year after the 

household entered the survey. For more details on the models, see appendix I.

Not only did women’s total household assets and income decline 

substantially with widowhood, but the effects were more pronounced for 

women than for men (see fig. 15). For example, while men’s income fell 

22 percent after widowerhood, women’s income fell by an even greater 

amount—37 percent. The effects were larger for women living in younger 

households than women living in older households. Specifically, women 

in households where all members were age 64 or younger experienced a 

Became Widowed after 

Age 50
 

Page 31 GAO-12-699 Women’s Retirement Security 

31 percent decrease in assets and a 47 percent decrease in income.48

 

48A widow’s assets may be depleted by medical and other expenses incurred prior to the 

death of her spouse. See Kathleen McGarry and Robert F. Schoeni, “Medicare Gaps and 

Widow Poverty,” Social Security Bulletin, vol. 66, no. 1 (2005). In addition, women’s 

income may fall after widowhood if their husbands did not elect to take the husband’s 

pension benefits in the form of a joint and survivor benefit. See Karen C. Holden and 

Angela Fontes, “Economic Security in Retirement: How Changes in Employment and 

Marriage Have Altered Retirement-Related Economic Risks for Women,” Journal of 

Women, Politics & Policy, vol. 30, no. 2-3 (2009).

Adding to these effects, widowhood was a much more common 

experience for women than men in our sample. In fact, women were at 

least twice as likely as men to become widowed between any two survey 

periods. Consequently, 70 percent of women age 85 and over were 

widowed compared to only 24 percent of men age 85 and over.
 

Page 32 GAO-12-699 Women’s Retirement Security 

Figure 15: Estimated Effects of Widowhood on Total Household Assets and Income

Notes: Because widows appear much more often in households where at least one person is over the 

age of 65 than in households where everyone is age 64 or younger, part of the overall effect is likely a 

comparison of the household’s assets over time. This explains why the effect for the larger population 

is larger than the effect for each of the groups. Estimates for the “all households” and “households 

where at least one person is age 65 or older” categories have 95 percent confidence intervals within 

+/-5 percentage points of the estimate itself. Estimates for the “households where everyone is age 64 

or younger” category have 95 percent confidence intervals within +/-10 percentage points of the 

estimate itself. For statistical comparisons of the estimates across different groups, see appendix I. 

We used fixed-effects regression models to estimate the percent change in total household assets 

and income that occurs for an individual after a life event, relative to an individual that did not 

experience that life event. Total assets and income for the household were applied to each individual 

in the household. The estimated effects represent the average percent difference in household assets 

and income between all survey periods in which the household does experience an event and all 

survey periods in which the household does not experience an event. The event may have occurred 

in any year after the household entered the survey. For more details on the models, see appendix I. 

Similar to becoming widowed, unemployment had negative effects on 

total household assets and income, although the effects were similar for 

women and men (see fig. 16).49

 

49We defined unemployment as being out of work and actively looking for a job.

Women and men saw their assets and 

income decline by about 7 to 9 percent. The effects on income were most 

acute for households where at least one member of the household was 

age 65 or over. For these households, men’s assets fell by 14 percent 

Became Unemployed 

after Age 50
 

Page 33 GAO-12-699 Women’s Retirement Security 

and their income fell by 12 percent. For women, there was not a 

significant decline in assets but their income fell by 13 percent. In 

addition, older workers may have difficulty finding another job.50 However, 

unemployment was not very prevalent in the HRS sample, in part 

because many survey respondents were retired.51

Figure 16: Estimated Effects of Unemployment on Total Household Assets and Income

On average, only 1 

percent of men and women reported being out of work and actively 

looking for a job. For men and women ages 51 to 64, this percentage 

rose slightly to 2 percent.

Notes: Estimates for the “all households” and “households where everyone is age 64 or younger” 

categories have 95 percent confidence intervals within +/-6 percentage points of the estimate itself. 

Estimates for the “households where at least one member is age 65 or older” category have 95 

percent confidence intervals within +/-15 percentage points of the estimate itself. For statistical 

comparisons of the estimates across different groups, see appendix I. We used fixed-effects 

regression models to estimate the percent change in total household assets and income that occurs 

for an individual after a life event, relative to an individual that did not experience that life event. Total 

assets and income for the household were applied to each individual in the household. The estimated 

effects represent the average percent difference in household assets and income between all survey 

periods in which the household does experience an event and all survey periods in which the 

household does not experience an event. The event may have occurred in any year after the 

household entered the survey. For more details on the models, see appendix I. 

 

50We have previously reported that older workers generally have longer spells of 

unemployment than younger workers and that older workers report facing difficulties 

finding new jobs after being laid off. See GAO-12-445. 

51When individuals enter the HRS sample, they are between the ages of 51 and 61. 

However, because this is a longitudinal study, all the survey members age over time. For 

example, someone who was age 61 at the time of the first HRS survey in 1992 was age 

79 in 2010.
 

Page 34 GAO-12-699 Women’s Retirement Security 

As shown in figure 17, a decline in self-reported health status also had 

negative effects on total household income and assets, although to a 

lesser degree than widowhood, divorce, and unemployment. For all 

households in our sample, income fell by 4 percent for women and 3 

percent for men when self-reported health status changed from excellent, 

very good or good to fair or poor.52 The effects of a decline in health on 

assets varied by household type. The differences between women and 

men were the largest for younger households, where all members were 

age 64 or younger. For example, the loss of assets was greater for men 

(13 percent) compared to women (5 percent).53

Figure 17: Estimated Effects of a Decline in Health on Total Household Assets and Income

Notes: All estimates in this figure have 95 percent confidence intervals within +/-3 percentage points 

of the estimate itself. For statistical comparisons of the estimates across different groups, see 

appendix I. We used fixed-effects regression models to estimate the percent change in total 

household assets and income that occurs for an individual after a life event, relative to an individual 

that did not experience that life event. Total assets and income for the household were applied to 

each individual in the household. The estimated effects represent the average percent difference in 

household assets and income between all survey periods in which the household does experience an 

event and all survey periods in which the household does not experience an event. The event may 

have occurred in any year after the household entered the survey. For more details on the models, 

see appendix I. 

 

52This difference between women and men is not statistically significant.

53Health care costs may deplete elderly individuals’ resources. See McGarry and Schoeni 

(2005). Also see Richard W. Johnson, Gordon B.T. Mermin, and Cori E. Uccello, When 

the Nest Egg Cracks: Financial Consequences of Health Problems, Marital Status 

Changes, and Job Layoffs at Older Ages (Urban Institute: January 2006).

Health Declined after 

Age 50
 

Page 35 GAO-12-699 Women’s Retirement Security 

Although the effects of a decline in health were smaller than the effects of 

some of the other life events in our analysis, more individuals 

experienced this event than any other. Almost 30 percent of individuals 

ages 65 to 84 reported being in poor health (see table 2). For individuals 

ages 85 and over, 40 percent reported being in poor health. Interestingly, 

as shown in table 2, women and men suffered from poor health at similar 

rates across age categories. Further, we found that, between any two 

HRS surveys, about 2 percent of both women and men reported entering 

a period of poor health.

Table 2: Percent of Women and Men Reporting Their Health Is Poor Is Similar 

across Age Groups

Percent reporting their health is poor

Women Men

Ages 51-64 21 20

Ages 65-84 28 28

Ages 85 and over 40 40

Source: GAO analysis of HRS data.

Lastly, we found that providing elderly parents with financial assistance or 

helping parents with basic activities of daily living (i.e., bathing, dressing, 

and eating) had a slightly positive effect on household assets and income. 

However, often these effects were not significantly different from zero, 

possibly because of limitations in our data and methods.54

 

54Although the fixed-effects method offers several advantages over other regression 

methods, it also has limitations that may affect our estimates. For example, while the 

fixed-effects method controls for all characteristics within a household that do not change 

over time, it is possible that the relationship between providing care for parents and 

household assets changes over time and works in multiple directions. For example, if a 

household sees an increase in the value of its assets, it may decide to use some of this 

new wealth to finance care for elderly parents. However, using these assets causes total 

household assets to fall. The fixed-effects method cannot control for these simultaneous 

effects and, thus, the two effects may cancel each other out. For more information on our 

analysis of the effects of providing help to elderly parents and an analysis describing the 

individuals who provided care to parents, see appendix I.

In addition, we 

found that only a small percentage of the sample provided these types of 

assistance to their parents. Also, women and men age 51 through 64 

were much more likely to provide assistance than women and men age 

65 and over. But, as the baby boomers age, more children may be called 

upon to help their parents financially or with basic activities.
 

Page 36 GAO-12-699 Women’s Retirement Security 

Through our interviews with experts and our literature review, we found 

that a range of existing policy options could help improve retirement 

income security for women.55

All of the options have cost implications that would need to be considered 

prior to implementation. Moreover, as with federal spending programs, 

any option that results in reduced or deferred federal tax revenue may 

require an offset, such as raising revenue elsewhere or cutting spending. 

While the federal government could bear some of these costs, workers 

and plan sponsors could be responsible for others. Also, although some 

of the options could have positive effects on women on their own, there 

could be an offsetting effect. If the plan sponsor, for example, is 

responsible for the increased cost of sponsorship and makes changes to 

the plan to offset those increased costs, women may not ultimately 

benefit from the policy option. Lastly, some of these changes may require 

legislative changes.

Our analysis focuses on how women would 

be affected by these policy options. While each of these options would be 

available for both women and men, they could help address some of the 

specific challenges women face in ensuring a secure retirement. For 

example, some options would expand the use of existing tax incentives, 

encouraging women to save more. Another set of options would expand 

access to and strengthen spousal protections for retirement savings. 

These options could increase women’s retirement savings and preserve 

their retirement income if they become divorced or widowed. Other sets of 

options could motivate women nearing retirement to work longer and 

save more, ensure lifetime retirement income, or enhance benefit 

adequacy. These options could help shield women from the effects of 

divorce, widowhood, and unemployment and decrease their risk of living 

in poverty.

 

55To identify and analyze policy options that could enhance women’s retirement security, 

we conducted an extensive literature review and interviewed a range of experts. To 

ensure that we obtained a balanced perspective, we interviewed experts with a range of 

perspectives and from different types of organizations including government, academia, 

advocacy groups, and the private sector. For more information on our literature review and 

expert interviews, see appendix I. Some of the options have been proposed in various 

permutations. Our analysis is not intended to describe any one proposal. Rather, we 

describe the basic features of the option; these features may be common across 

proposals. GAO did not independently evaluate the efficacy of these options, nor by 

including them in this report are we providing a position on or endorsing any of these 

options.

Existing Policy 

Options Could 

Address Retirement 

Security Issues Facing 

Women
 

Page 37 GAO-12-699 Women’s Retirement Security 

Some of the policy options we identified could expand the use of existing 

tax incentives for individuals to save for retirement during their working 

years (see table 3). These options could help lower- and moderateincome workers, as well as workers who take time out of the workforce to 

care for family members. Since women have lower earnings than men, on 

average, and are more likely to take time out of the workforce to care for 

family members, women may especially benefit from these options. 

However, pension experts are concerned that women may not be as 

financially literate as men, hindering them from taking full advantage of 

options for saving for retirement.56

Table 3: Proposals to Expand Use of Existing Tax Incentives to Save for Retirement

Policy option Description of policy option Potential effects on women

Automatic IRA Employers who do not sponsor a pension plan would 

be required to automatically enroll employees in an IRA 

unless the employee opted out.a Automatic IRA 

proposals have been introduced before the four most 

recent Congresses.b However, this option would result 

in a loss of federal tax revenue.c Further, this kind of 

requirement could pose administrative burdens and 

costs for employers.

According to one study, lower- and moderate-income 

workers may be more likely to be eligible for automatic 

IRAs.d Women have lower incomes and retirement 

savings than men, but experts reported that automatic 

enrollment in IRAs could increase the number of 

women saving for retirement or increase their 

retirement savings. However, women from lowerincome households may not be able to afford to make 

contributions to an IRA.

Expansion of 

Saver’s Credit

The Saver’s Credit—a tax credit for retirement savings 

for low- and middle-income workers—could be 

expanded in a number of ways. For example, some 

experts have called for making the credit refundable.e

This option would result in a reduction in tax revenue.f

By enhancing the tax incentives to save for retirement, 

low- and middle-income workers may save more for 

retirement. However, women from lower-income 

households may choose not to take advantage of the 

credit because they may not be able to afford to 

contribute. Our previous work has shown that while the 

number of workers benefiting from an expansion of the 

Saver’s Credit could be small, the increase in 

retirement savings could be sizable for those who do 

benefit.g

 

56We have previously reported that there is a need to improve individuals’ financial 

literacy. Financial skills are increasingly important for ensuring a comfortable standard of 

living in retirement. GAO, Financial Literacy: Enhancing the Effectiveness of the Federal 

Government’s Role, GAO-12-636T (Washington, D.C.: Apr. 26, 2012) and Financial 

Literacy: Strengthening Partnerships in Challenging Times, GAO-12-299SP (Washington, 

D.C.: Feb. 9, 2012).

Proposals to Expand the 

Use of Existing Tax 

Incentives to Save for 

Retirement
 

Page 38 GAO-12-699 Women’s Retirement Security 

Policy option Description of policy option Potential effects on women

Caregiver 

contributions to 

IRAs

Allow all caregivers to contribute to IRAs up to the

qualified contribution limit, which would be based on the 

individual’s adjusted gross income in the year prior to 

becoming a qualified caregiver. Currently, a married 

caregiver who has no compensation or whose 

compensation is less than her spouse, and who files a 

joint return, can contribute to an IRA by using her 

spouse’s compensation in determining her maximum 

contributions to an IRA. If implemented, tax revenue 

could fall.

Women, who are more likely to take time out of the 

workforce to provide care for family members, could 

continue to save for retirement while providing care. 

However, women from lower-income households may 

not be able to afford to make contributions to an IRA 

while providing care to relatives.

Expand catch-up 

contributions

Currently, workers age 50 and over are permitted to 

make additional, annual “catch-up” tax-deferred 

contributions of up to $5,500 to their DC plans. Under 

this option, workers ages 40-49 would become eligible 

to make such contributions, and the contribution limits 

would be raised. Simultaneously, a campaign could be 

launched to promote the catch-up contribution option. 

By expanding tax incentives, however, more tax 

revenue could be deferred.

Women would be able to make larger contributions to 

DC plans for an additional decade, increasing their 

retirement savings. However, as we have previously 

reported, men are three times more likely than women 

to make catch-up contributions.h Because they have 

lower earnings than men, women may be constrained 

in their ability to save more. As a result, women may 

not choose to take advantage of extra years to make 

catch-up contributions. 

Source: GAO analysis of literature and expert interviews.

a

It has been proposed that certain types of firms, such as those with fewer than 10 employees, would 

be exempt from the automatic IRA requirement. Our prior work has analyzed the automatic IRA 

proposal. See GAO, Retirement Savings: Automatic Enrollment Shows Promise for Some Workers, 

but Proposals to Broaden Retirement Savings for Other Workers Could Face Challenges, GAO-10-31 

(Washington, D.C.: Oct. 23, 2009) and Private Pensions: Low Defined Contribution Plan Savings May 

Pose Challenges to Retirement Security, Especially for Many Low-Income Workers, GAO-08-8 

(Washington, D.C.: Nov. 29, 2007). 

b

See The Automatic IRA Act of 2012, H.R. 4049, 112th Cong. (2012) and the Automatic IRA Act of 

2011, S. 1557, 112th Cong. (2011); the Automatic IRA Act of 2010, S. 3760 and H.R. 6099, 111th 

Cong. (2010); the Automatic IRA Act of 2007, S. 1141 and H.R. 2167, 110th Cong. (2007); and the 

Automatic IRA Act of 2006, S. 3952 and H.R. 6210, 109th Cong. (2006). 

c

Treasury has estimated that if automatic enrollment in IRAs and doubling an existing employer tax 

credit for starting an employer-sponsored pension plan were implemented by the end of calendar 

year 2013, then the revenue loss would be about $15 billion for fiscal years 2013-2022. 

d

Benjamin H. Harris and Ilana Fischer, The Population of Workers Covered by the Auto IRA: Trends 

and Characteristics, AARP Public Policy Institute (Washington, D.C.: Feb. 2012). 

e

Currently, the Saver’s Credit is nonrefundable. A nonrefundable tax credit can reduce tax owed to 

zero, but it cannot be used to generate a refund payment to the filer in excess of taxes paid. 

f

The cost of expanding the Saver’s Credit would depend on how the credit was expanded. For 

example, the President’s fiscal year 2011 budget proposed expanding the Saver’s Credit by making 

the credit refundable and providing a 50 percent match on retirement contributions of up to $1,000 for 

families earning $85,000 or less. The estimated cost of this expansion was $29.8 billion for fiscal 

years 2011–2020. See Office of Management and Budget, Budget of the U.S. Government: Fiscal 

Year 2011 (Washington, D.C., Feb. 1, 2010). 

g

See GAO, Private Pensions: Some Key Features Lead to an Uneven Distribution of Benefits, 

GAO-11-333 (Washington, D.C.: Mar. 30, 2011). 

h

See GAO-11-333. 
 

Page 39 GAO-12-699 Women’s Retirement Security 

Experts also identified a set of policy options that would offer new 

opportunities to accumulate earnings credits for Social Security (see table 

4). These options could enhance the retirement security of workers who 

experience a period of unemployment or who take time out of the 

workforce to care for family members. For example, counting 

unemployment insurance payments as creditable earnings under Social 

Security may be particularly helpful for women who become unemployed 

later in life and experience a notable decrease in their assets and income. 

However, because they would extend eligibility or increase benefits, these 

options would increase costs for Social Security and decrease solvency.

Table 4: Proposals to Expand Eligibility and Opportunities to Accumulate Social Security Credits

Policy option Description of policy option Potential effects on women

Count 

unemployment 

insurance 

payments as 

creditable earnings 

under Social 

Security 

Currently, workers do not receive earnings credits for 

unemployment compensation. However, two experts 

told us some countries consider unemployment 

compensation as creditable earnings under their social 

security systems. This allows workers to continue 

accruing earnings credits while unemployed. This 

option could increase costs and would decrease Social 

Security solvency.

According to two of the experts we spoke with, women 

who experience bouts of unemployment would receive 

more earnings credits under Social Security, 

potentially increasing their benefits. This option may 

also help women become eligible for benefits.

Allow care-giving 

credits for Social 

Security benefit 

calculations

Under the current system, Social Security eligibility and 

benefit amounts depend on the amount of time a 

worker spends in covered employment. Under this 

option, workers who take time out of the workforce to 

provide care could have their Social Security benefits 

adjusted. For example, the benefits formula could 

impute earnings for years with zero or low earnings due 

to care-giving.a In addition, this option would increase 

Social Security costs and decrease solvency.

Crediting time spent providing care could increase 

women’s Social Security benefits or make them 

eligible for benefits. Our past work has shown that 

more women than men could benefit from care-giving 

credits.b However, as we have previously reported, 

care-giving credits may not reach the target 

population. For example, low-income people are less 

likely to be able to take time off from work. Therefore, 

people who have relatively higher incomes may benefit 

more from the creation of care-giving credits.c

Source: GAO analysis of literature and expert interviews.

a

SSA’s Office of the Chief Actuary has estimated the effect of providing a care-giving credit to parents 

with a child under 6 for up to 5 years. In 2011, the Office of the Chief Actuary estimated these 

proposals would decrease solvency by 0.24 percent of payroll. See 

http://www.ssa.gov/oact/solvency/provisions/index.html. 

b

See GAO-08-105. 

c

See GAO-10-101R. 

Other policy options could either expand access to retirement savings in 

DC plans and IRAs or strengthen spousal protections for retirement 

savings (see table 5). These options could address a variety of 

challenges women face, including their lower levels of income in 

retirement. In addition, they could preserve retirement income after a 

divorce or after becoming widowed. For example, requiring that a wife 

Proposals to Expand 

Opportunities to 

Accumulate Social 

Security Credits

Proposals to Expand 

Access to Retirement 

Savings and Strengthen 

Spousal Protections
 

Page 40 GAO-12-699 Women’s Retirement Security 

provides consent whenever a husband takes a distribution from his DC 

savings would protect the wife’s access to household income in 

retirement. However, these options could increase costs for plan 

sponsors. For example, requiring notarized spousal consent whenever a 

husband takes a distribution could increase the administrative costs that 

must be paid by plan sponsors.

Table 5: Proposals to Expand Access to Retirement Savings and Strengthen Spousal Protections 

Policy option Description of policy option Potential effects on women

Lower DC plan 

eligibility 

requirements

Currently, employees are generally eligible for DC 

plans once they have at least 1,000 hours of service 

during a 12-month period. One proposal would require 

employers to offer DC plans to employees that have at 

least 500 hours of service per year for 3 years. This 

option could, in turn, increase costs for plan sponsors. 

It would also result in increased deferral of tax revenue 

if more workers made contributions to DC plans 

because DC contributions are typically tax-deferred.

Women, who tend to move in and out of the workforce 

and/or work part-time, could become eligible to 

participate in DC plans. If they choose to participate, 

their retirement savings would increase. However, over 

75 percent of women covered by a pension are eligible 

to participate, so the number of women affected by this 

option may be limited. Further, part-time workers have 

lower earnings than full-time workers and may not be 

able to make contributions to DC plans. 

Lower DC plan 

vesting 

requirements

Currently, ERISA requires that employees become 

vested in DC plans in no more than 3 or 6 years, 

depending on whether the plan calls for graded or cliff 

vesting, respectively.a Experts have called for lowering 

these vesting requirements. For example, one proposal 

calls for lowering vesting requirements to 2 years for 

plans with cliff vesting and 3 years for plans with 

graded vesting. Such options, however, could increase 

costs for plan sponsors and result in an increased 

deferral of tax revenue.

Women, who tend to move in and out of the workforce 

and/or work part-time, would become more likely to 

vest more of their employer-sponsored pension plans, 

improving their access to pension benefits and 

retirement savings. In our 2008 report on women’s 

retirement income security, we simulated lowering 

vesting requirements. We found that women in the 

lowest income quintile saw the largest change in 

benefits. Similarly, never married and divorced women 

saw a bigger increase in benefits than did married and 

widowed women.b

Provide spousal 

protection 

provisions for DC 

savings

Currently, spousal consent is not required when 

married individuals take distributions from their IRA or 

DC savings. Under tax-qualified DB plans, the spouse 

must provide consent in order to elect a DB benefit that 

is not a qualified joint and survivor annuity. One 

proposal calls for requiring spousal consent for any 

distribution from an IRA or DC plan other than a joint 

and survivor annuity. This option could increase costs 

for plan sponsors and would defer tax revenue if 

requiring spousal consent results in individuals delaying 

withdrawals.

Spousal protections for DB and DC plans would be 

similar. These changes would help to ensure that 

women were involved with decisions that would affect 

their retirement income and, in turn, would help 

improve the adequacy of their retirement income. 

However, officials and experts have noted that 

spouses often give consent to select a DB benefit 

other than a joint and survivor annuity, raising 

questions about the effectiveness of placing the same 

spousal consent requirements on DC plans.

Source: GAO analysis of literature and expert interviews.

a

ERISA, as amended, governs vesting periods. Plans with cliff vesting have a specified point at which 

participants have a right to all benefits accrued to date and benefits accrued thereafter. Plans with 

graded vesting give participants a right to an increasing percentage of their total accrued benefit over 

time. For more information, see GAO, Answers to Key Questions about Private Pension Plans, 

GAO-02-745SP (Washington, D.C.: Sept. 18, 2002). 

b

See GAO-08-105. 
 

Page 41 GAO-12-699 Women’s Retirement Security 

Experts identified three policy options that could motivate women nearing 

retirement to remain in the workforce and delay claiming Social Security 

benefits, thereby giving them more time to save for retirement and 

increasing their Social Security benefits (see table 6). Because women 

tend to have less income in retirement than men, and because elderly 

women face higher poverty rates than elderly men, these options for 

boosting retirement savings and benefits may improve women’s overall 

retirement income security. For example, the full retirement age for Social 

Security could be increased, thus providing workers who are able to work 

with an incentive to keep doing so—potentially saving more for retirement 

in the process. However, each of these options has disadvantages. In the 

case of increasing the full retirement age, this option may not prove to be 

effective because women may not be able to work longer or may choose 

to exit the workforce before the full retirement age. They would, in turn, 

suffer reductions in Social Security income.

Table 6: Proposals to Expand Opportunities for Saving Later in Life and Delay Social Security Benefit Receipt

Policy option Description of policy option Potential effects on women

Education on 

benefits of waiting 

to start collecting 

Social Security 

benefits 

According to experts, many people do not realize that 

waiting to claim Social Security benefits can 

significantly increase monthly benefit amounts for the 

rest of their lives. Better educational outreach could 

increase awareness. If workers delay claiming Social 

Security benefits, income and payroll tax revenues 

would be increased and solvency would be improved. 

Employer pension costs could be increased if workers 

continue participating in their pension plans.

A larger monthly income could help many women 

avoid poverty in retirement and better protect against 

outliving their retirement assets. On the other hand, 

women may not have the savings they need or be able 

to keep working to have enough income to delay 

claiming. 

Increase the early 

or full retirement 

ages

Experts told us the Social Security early or full 

retirement ages could be increased. By increasing the 

Social Security retirement ages, workers may choose to 

work longer, resulting in additional payroll tax revenue, 

which would improve solvency.a However, employer 

pension costs could be increased if workers continue 

participating in their pension plans.

Some experts told us that these changes could 

encourage people to delay retirement, potentially 

increasing their retirement savings. Others are 

concerned that these options would be harmful for 

women. For example, if the full retirement age is 

increased and women who planned to claim at the old 

full retirement age do not delay collecting Social 

Security benefits, they would receive a lower benefit. 

Increase duration 

of unemployment 

benefits in lieu of 

applying for Social 

Security early

According to one expert we spoke with, the eligibility 

period for unemployment compensation could be 

extended further for older workers. This could increase 

federal tax revenue because unemployment 

compensation is taxable. However, paying more in 

unemployment benefits would exacerbate the financial 

challenges state unemployment insurance programs 

face.b

 

Unemployment can have a negative effect on women’s 

income security. This option would provide additional 

income to unemployed older women, who may find it 

difficult to find another job. Instead of applying for early 

Social Security benefits, which results in a 

permanently lower benefit level, women could rely on 

unemployment compensation, thus preserving the 

value of their Social Security benefits.

Source: GAO analysis of literature and expert interviews.

Proposals to Expand 

Opportunities for Saving 

Later in Life and Delay 

Social Security Benefit 

Receipt
 

Page 42 GAO-12-699 Women’s Retirement Security 

a

SSA’s Office of the Chief Actuary has estimated the effect various proposals to increase the full 

retirement age would have on solvency. In 2011, the Office of the Chief Actuary estimated these 

proposals would improve solvency by 0.32 to 0.98 percent of payroll. See 

http://www.ssa.gov/oact/solvency/provisions/index.html. 

b

In April 2010, we reported that state unemployment insurance trust funds stood in historically poor 

financial condition. See GAO, Unemployment Insurance Trust Funds: Long-standing State Financing 

Policies Have Increased Risk of Insolvency, GAO-10-440 (Washington, D.C.: Apr. 14, 2010). 

Experts also identified several policies that would ensure lifetime 

retirement income for women (see table 7). Women may especially 

benefit from these options, given that they (1) have lower levels of 

retirement income than men, (2) are more likely to live longer, and (3) are 

also more likely to become widowed. For example, Treasury recently 

proposed modifying the required minimum distribution rules so that 

individuals could use part of their retirement savings to purchase a 

longevity annuity.57 This option would provide older women with 

guaranteed additional income, which may be helpful if they live long lives 

or outlive a spouse. These options, however, often have cost implications

for either federal tax revenue or plan sponsors. For example, if individuals 

purchased longevity annuities using tax-qualified retirement savings, the 

tax revenue generated from withdrawing these savings would be deferred 

until the annuity started paying out.

 

57Certain provisions of the Internal Revenue Code set required minimum distributions from 

tax-deferred accounts, such as traditional IRAs and qualified plans, starting generally by 

April 1 in the year following the year in which the account holder reaches age 70 1⁄2. These 

required minimum distributions help to ensure that account holders withdraw tax-deferred 

savings in retirement rather than accumulate savings for their estate.

Proposals to Ensure 

Lifetime Income
 

Page 43 GAO-12-699 Women’s Retirement Security 

Table 7: Proposals to Ensure Lifetime Income

Policy option Description of policy option Potential effects on women

Encourage DC 

plan sponsors to 

offer annuities as a 

distribution option 

for a portion or the 

entire DC account 

balance

Experts reported that steps could be taken to decrease 

the risks employers face when they offer an annuity as 

a distribution option for DC plans. For example, one 

expert told us the rules for using DC savings to 

purchase an annuity could be revised. These options 

could introduce greater costs and administrative 

burdens for plan sponsors. 

More DC plan participants could have the opportunity 

to secure guaranteed lifetime income. This could be 

especially beneficial for women given that they tend to 

live longer than men, have higher poverty rates, and 

are more likely to be widowed.

Modify required 

minimum 

distribution rules to 

allow for longevity 

annuities

This option would modify the required minimum 

distribution rules so that it is easier to purchase 

longevity annuities with a portion of DC plan assets.a In 

February, Treasury proposed a regulation that would 

alter the required minimum distribution rules to make it 

easier for individuals to use a portion of their savings to 

purchase longevity annuities.b Tax revenue would be 

deferred until the annuity starts paying out.

A longevity annuity would decrease the chances that a 

woman would outlive her retirement savings. Given 

women’s tendency to live longer than men, as well as 

their higher poverty rates and likelihood of being 

widowed, this option could be especially beneficial for 

improving women’s retirement income security. 

Reduce eligibility 

requirements for 

divorced spousal 

benefits under 

Social Security

Currently, a divorced spouse can receive benefits 

based on a retired worker’s earnings record if the 

marriage lasted at least 10 years, and the spouse is 

unmarried and at least 62 years old. Experts have 

recommended expanding eligibility for divorce benefits 

to require a minimum of 7 years of marriage. 

Additionally, some experts have suggested marriage 

years could also be accumulated across multiple 

marriages. This option would increase Social Security 

costs and the administrative burden for SSA, while

decreasing solvency. 

More divorced women would qualify for spousal 

benefits. One study estimated that lowering the 

marriage-duration requirement from 10 to 7 years 

would increase benefits for about 8 percent of all 

divorced women age 62 and over in the year 2030.c

However, as we have previously reported, this option 

could benefit higher-income women who are not 

economically vulnerable and it would not benefit 

women who were never married.d

Source: GAO analysis of literature and expert interviews.

a

A longevity annuity (sometimes referred to as “longevity insurance” or a “deeply deferred annuity”) is 

an income stream that can be purchased at or near retirement but begins at an advanced age—for 

example, age 85—and continues as long as the individual lives. 

b

Longevity Annuity Contracts, 77 Fed. Reg. 5443 (Feb. 3, 2012). 

c

Christopher R. Tamborini and Kevin Whitman, “Lowering Social Security’s Duration-of-Marriage 

Requirement: Distributional Effects for Future Female Retirees,” Journal of Women and Aging vol. 22 

(2010). 

d

GAO, Social Security: Options to Protect Benefits for Vulnerable Groups When Addressing Program 

Solvency, GAO-10-101R (Washington, D.C.: Dec. 7, 2009). 

There are also a number of policy options that could enhance Social 

Security benefits for vulnerable groups at risk of not having sufficient 

income or assets in retirement, including widows, divorced women, lowProposals to Ensure 

Income Adequacy
 

Page 44 GAO-12-699 Women’s Retirement Security 

income women and women age 85 and over (see table 8).58

Table 8: Proposals to Ensure Income Adequacy

For example, 

increasing the Social Security Survivor’s benefit to 75 percent of the 

deceased worker’s benefit would provide widows with more monthly 

income, helping to keep some women out of poverty. However, all of 

these options would increase existing costs or introduce new costs and, 

in turn, would decrease the solvency of the system.

Policy option Description of policy option Potential effects on women

Use consumer 

price index for the 

elderly (CPI-E) to 

calculate Social 

Security cost-ofliving adjustments

Currently, the Consumer Price Index for Urban Wage 

Earners and Clerical Workers (CPI-W) is used to 

calculate annual cost-of-living adjustments for Social 

Security benefits. However, some experts argue that 

the CPI-W does not accurately reflect expenses for the 

elderly. The CPI-E, an index designed to represent 

expenses of those age 62 and over,a could be used to 

calculate cost-of-living adjustments for Social Security 

recipients. Experts say an advantage of the CPI-E is 

that it more accurately reflects the typically larger share 

of expenditures older Americans spend on medical 

care. This option would decrease Social Security 

solvency because it would generally increase benefit 

levels and, therefore, costs.b

Advocates for the CPI-E reported that it more 

accurately reflect expenses for retirees, thereby 

improving income adequacy by providing more 

appropriate cost-of-living adjustments. While all Social 

Security recipients would benefit, women could benefit 

more than men as they tend to live longer. Moreover, 

benefit increases compound over time. However, 

some advocates believe benefits would still be 

insufficient under the CPI-E. 

Update the Social 

Security Special 

Minimum Benefit

Currently, Social Security includes a Special Primary 

Insurance Amount (also referred to as the Special 

Minimum Benefit) that is intended to reduce poverty 

among retired lifetime low-wage workers. However, 

very few people receive this benefit.c There are several 

options for increasing the minimum benefit. For 

example, one proposal would increase the minimum 

benefit and index it to wages.d While benefits would 

increase, decreasing poverty for some beneficiaries, 

this option would increase costs and decrease 

solvency.

An increased Special Minimum Benefit could keep 

more elderly women out of poverty by increasing their 

monthly income. In addition, our past work found that 

while the share of women affected by the minimum 

benefit was fairly similar across marital statuses 

(never-married, divorced, married and widowed), 

never-married and divorced women had much larger 

percent changes in median benefits.e

Provide an 

additional Social 

Security benefit to 

the oldest old

Social Security recipients over the age of 80 or 85 

could receive an additional benefit, such as an extra 5 

percent on top of their regular benefit. While this option 

would increase benefits for the oldest old, it would also 

increase costs and decrease solvency.f

Women, who tend to live longer than men, would be 

more likely to receive this extra benefit. Older women 

may need extra benefit as income and assets may 

have been used to care for a deceased spouse or to 

pay for increasing medical costs. An additional benefit 

may be particularly helpful for low-income women.

 

58Experts we spoke with also identified women without long-term care insurance as a 

vulnerable population. Although the lack of long-term care insurance does put women at 

risk of income insecurity, in general, we did not identify any long-term care policy options 

that addressed retirement income specifically.
 

Page 45 GAO-12-699 Women’s Retirement Security 

Policy option Description of policy option Potential effects on women

Increase Social 

Security Survivor’s 

benefits to 75%

Currently, when someone is widowed, total household 

income from Social Security decreases by one-third if 

the couple’s benefits had been based on one spouse’s 

work history and up to 50 percent if both spouses had 

been receiving retired worker benefits. Survivor’s 

benefits could be increased to 75 percent of the 

couple’s retired-workers benefits. Experts have 

proposed calculating this new benefit in different ways. 

For example, the surviving spouse could receive 75 

percent of the couple’s retired-workers benefit but the 

benefit would be capped at the maximum earner’s 

benefit or at the benefit of the “lifelong average earner.” 

However, increasing benefits would increase costs and 

decrease solvency.

Increasing Survivor’s benefits would increase income 

for widowed women. Widowhood can have a 

devastating effect on women’s household assets and 

income. Further, women are more likely than men to 

be widowed so they would be more likely to benefit 

from an increase in the survivor’s benefit. In fact, when 

we simulated the effects of this option in 2007, we 

found that three times the number of women as men 

were affected. However, the magnitude of the benefit 

increase was larger for men than for women.g

Increase Social 

Security spousal 

benefits for 

divorced spouses 

Currently, divorced spouses who qualify for spousal 

benefits receive a benefit equal up to 50 percent of the 

worker’s benefits. This option would raise benefits for 

divorced spouses to 75 percent of the former spouse’s 

benefit while the former spouse is still alive. Upon the 

death of the former spouse, the divorced spouse would 

receive the full widow’s benefit of 100 percent. This 

benefit increase would decrease solvency because it 

would increase costs.

Divorce can result in a substantial loss of assets and 

income for women. Some experts argue that a 50 

percent benefit is not enough to keep divorced women 

from falling into poverty. It has been estimated that 

increasing the benefit rate for divorced spouses to 75 

percent would lower the poverty rate among divorced 

spouses from 30 percent to 11 percent.h

Increase Social 

Security benefits 

for disabled 

surviving spouses

Currently, to qualify for disabled surviving spouse 

benefits, disabled surviving spouses must be at least 

age 50 and have become disabled before or within 7 

years of the spouse’s death or before or within 7 years 

after last being eligible for benefits as a caretaking 

parent or eligible surviving child. In addition, disabled 

surviving spouses younger than the full retirement age 

generally receive lower benefits than those who wait to 

receive their benefits until the full retirement age. This 

option would raise benefits for disabled surviving 

spouses to 100 percent of the deceased spouse’s 

benefit. It would also remove the 7 year limitation and 

the age 50 requirement. Lastly, it would make divorced 

spouses who are disabled eligible for benefits on the 

same basis as disabled surviving spouses. Although 

benefits would increase, Social Security solvency 

would decrease.

Both divorce and widowhood can result in a decrease 

in retirement security. Further, disabled surviving 

spouses, including those who have been divorced, 

cannot work and may have no partner to depend on 

for support. In addition, disability issues affect a 

surprisingly high number of divorced spouses, making 

them more vulnerable to income insecurity. One study 

estimated that more than one-fifth of all divorced 

spouses had health problems that meet disability 

criteria established by SSA.i

Increase 

continuation 

percentage for 

qualified joint-andsurvivor annuities

Currently, if a worker receives a joint and survivor 

annuity, when the worker passes away, the spouse 

continues to receive the annuity, but at not less than 50 

percent of the amount the worker received. This option 

would increase the minimum continuation percentage 

to 66 or 75 percent. 

It is about 40 percent more expensive to live as a 

single retiree than as a married retiree. After becoming 

widowed, household annuity income would be reduced 

by a smaller amount than it is currently. However, by 

increasing the continuation percentage, the cost of the 

joint-and-survivor annuity could increase.

Source: GAO analysis of literature and expert interviews.

a

The CPI-E is an experimental index developed by the Bureau of Labor Statistics. It takes into 

account increased utilization of medical care by the elderly. Officials from the Bureau of Labor 

Statistics have cautioned against using the CPI-E for pension and other adjustments because it is 

only an approximation of an index for older Americans. See GAO, Income Security: Older Adults and 

the 2007-2009 Recession. GAO-12-76 (Washington, D.C.: Oct. 17, 2011). 
 

Page 46 GAO-12-699 Women’s Retirement Security 

b

SSA’s Office of the Chief Actuary has estimated the effect of using the CPI-E to calculate cost-ofliving-adjustments would have on solvency. In 2011, the Office of the Chief Actuary estimated that 

solvency would be decreased by 0.35 percent of payroll. See 

http://www.ssa.gov/oact/solvency/provisions/index.html. 

c

Currently, few people qualify for the special minimum benefit because the eligibility threshold has not 

kept pace with wage growth. 

d

SSA’s Office of the Chief Actuary has estimated the effects various proposals to increase the Special 

Minimum Benefit would have on solvency. In 2011, the Office of the Chief Actuary estimated these 

proposals would decrease solvency by 0.10 to 0.28 percent of payroll. For these estimates, see 

http://www.ssa.gov/oact/solvency/provisions/index.html. 

e

See GAO-08-105. 

f

SSA’s Office of the Chief Actuary has estimated the effects various proposals to increase benefits for 

those age 85 and over would have on solvency. In 2011, the Office of the Chief Actuary estimated 

these proposals would decrease solvency by 0.10 to 0.13 percent of payroll. For these estimates, see 

http://www.ssa.gov/oact/solvency/provisions/index.html. 

g

See GAO-08-105. 

h

Alison M. Shelton and Dawn Nuschler, Social Security: Revisiting Benefits for Spouses and 

Survivors, Congressional Research Service (Washington, D.C.: Nov. 5, 2010). 

i

David A. Weaver, “The Economic Well-Being of Social Security Beneficiaries, with an Emphasis on 

Divorced Beneficiaries,” Social Security Bulletin, vol. 60, no. 4 (1997). 

To retirement security experts, our findings paint a familiar if disconcerting 

picture. Although increases in women’s labor force and retirement plan 

participation have led to a marginal improvement in women’s prospects 

for achieving a more secure retirement, our report also highlights the 

substantial risks women continue to face in accumulating adequate 

retirement income. Yet, despite the differential risks women face, 

retirement security in America continues to be a national dilemma that 

transcends gender differences. It is important to note that much of the 

relative improvement in women’s retirement security has been a 

consequence of deterioration in men’s retirement security. Recent 

economic volatility, coupled with the continued shift toward defined 

contribution plans, exposes all workers to more financial risk than 

previous generations. Further, older workers’ financial security is 

increasingly dependent on individual choices regarding how much to 

save, how to invest those savings, at what age to retire, and how to make 

those savings last throughout retirement. Much of the total workforce 

continues to approach retirement age with no traditional pension. 

Unchecked, this problem will only grow in severity.

Nevertheless, women face a unique set of circumstances, which warrant

special attention. In particular, our findings show that the disruptions that 

occur as a result of later-in-life events, such as divorce and widowhood, 

can be financially devastating for women. In addition, women’s greater 

likelihood of being single, higher life expectancy, and lower average 

Concluding 

Observations
 

Page 47 GAO-12-699 Women’s Retirement Security 

earnings continue to make saving for retirement and avoiding late-life 

poverty a challenge.

The challenges facing women’s retirement income security do not lack for 

potential resolutions. In fact, our discussions with experts identified a 

number of policy options that would improve retirement income security 

for women. These options range from changes to Social Security to 

altering the private pension system. While these options involve tradeoffs 

and difficult choices, they have the potential to improve the retirement 

income security of men as well. Ultimately, such efforts provide 

opportunities to improve the retirement security of many Americans.

We provided a draft of this report to the Department of Labor, the 

Department of the Treasury, and the Social Security Administration for 

review and comment. While none of the agencies provided official 

comments, each provided technical comments, which we incorporated as 

appropriate.

Agency Comments
 

Page 48 GAO-12-699 Women’s Retirement Security 

As agreed with your office, unless you publicly announce its contents 

earlier, we plan no further distribution until 30 days after the date of this 

letter. At that time, we will send copies of this report to the Secretary of 

Labor, the Secretary of the Treasury, the Commissioner of Social 

Security, and other interested parties. In addition, the report will be 

available at no charge on the GAO website at http://www.gao.gov. 

If you or your staff have any questions about this report, please contact 

me at (202) 512-7215 or jeszeckc@gao.gov. Contact points for our 

Offices of Congressional Relations and Public Affairs may be found on 

the last page of this report. GAO staff who made contributions to this 

report are listed in appendix II.

Sincerely yours,

Charles A. Jeszeck

Director

Education, Workforce, 

and Income Security
Appendix I: Objective, Scope, and Methods

Page 49 GAO-12-699 Women’s Retirement Security 

To analyze factors that affect women’s retirement security, we examined 

(1) how women’s access to and participation in employer-sponsored 

retirement plans compare to men’s and how they have changed over 

time; (2) how women’s retirement income compares to men’s and how 

the composition of their income has changed with economic conditions 

and trends in pension design; (3) how events occurring later in life affect 

women’s retirement income; and (4) what policy options are available to 

help increase women’s retirement income security. This appendix 

provides a detailed account of the information and methods we used to 

answer these questions. Section 1 describes the key information sources 

we used. Sections 2 through 4 describe the empirical methods we used to 

answer questions 1 through 3 respectively and the results of 

supplementary analyses.

To answer our questions, we obtained information from a variety of 

sources including two nationally representative surveys—the Survey of 

Income and Program Participation (SIPP) and the Health and Retirement 

Study (HRS)—the academic literature on retirement security, and a range 

of experts in the area of women’s retirement security. Table 9 

summarizes the data sources used to answer each question. This section 

provides a description of our data sources and the steps we took to 

ensure their reliability.

Table 9: Data Sources Used for Each Reporting Objective

SIPP data HRS data

Academic 

literature

Expert 

opinionsa

Objective 1: Women and men’s 

access to employer-sponsored 

pension plans 

X X X 

Objective 2: Women’s and 

men’s retirement income 

sources 

X X X 

Objective 3: Impact of late-inlife events on retirement 

income and assets

X X X 

Objective 4: Policy options X X 

Source: GAO.

a

Expert opinions were gathered from the literature and our interviews. We interviewed experts from 

government, academia, advocacy groups, and the private sector. For more information about our 

literature review and expert interviews, see below. 

Appendix I: Objective, Scope, and Methods

Section 1: Information 

Sources
Appendix I: Objective, Scope, and Methods

Page 50 GAO-12-699 Women’s Retirement Security 

To answer Questions 1 and 2, we analyzed data collected through the 

SIPP, a nationally representative survey conducted by the U.S. Census 

Bureau that collects detailed information on income sources and pension 

plan coverage, among many other areas. The survey is conducted in a 

series of national panels, with sample sizes ranging from approximately 

14,000 to 36,700 interviewed households. The duration of each panel 

ranges from 2 1⁄2 years to 4 years. Within each panel, the data are 

collected in a series of “waves” which take place in 4-month cycles. 

Within each wave, Census administers a core survey consisting of 

questions that are asked at every interview, and several modules relating 

to a particular topic. We used data from the core survey and the topical 

module on retirement and pension coverage from the last four SIPP 

panels, which began in 1996, 2001, 2004, and 2008 respectively. For all 

but the 2008 panel, the topical module on retirement and pension 

coverage was administered in Wave 7. For objective 1, we matched core 

data from Wave 3 of the 2008 panel with the topical module data, which 

was also administered in Wave 3. This ensured that the demographic 

data used in the analysis for that objective would match the time frame of 

the topical module data. However, to obtain the most up to date income 

data for objective 2, we used core data from Wave 7, which was the most 

recently available data as of October 2011. Table 10 shows the waves 

and questionnaires we used to answer each objective. It also shows the 

years that the data were collected during each panel and wave listed. The 

bolded years correspond to the years of data that are presented in the 

figures in objectives 1 and 2.

Table 10: SIPP Panels, Waves, and Questionnaires Used to Answer Objective 1 and 

Objective 2

Year data 

were collected Objective 1 Objective 2

1996 Panel, Wave 7, Core 

questionnaire 

1997, 1998a X X 

1996 Panel, Wave 7, Topical Module 

on Retirement and Pension Plan 

Coverage

1997,1998a X 

2001 Panel, Wave 7, Core 

questionnaire

2002, 2003a X X 

2001 Panel, Wave 7, Topical Module 

on Retirement and Pension Plan 

Coverage

2002, 2003a X 

2004 Panel, Wave 7, Core 

questionnaire

2005, 2006a X X 

Survey of Income and 

Program Participation
Appendix I: Objective, Scope, and Methods

Page 51 GAO-12-699 Women’s Retirement Security 

Year data 

were collected Objective 1 Objective 2

2004 Panel, Wave 7, Topical Module 

on Retirement and Pension Plan 

Coverage

2005, 2006a X 

2008 Panel, Wave 3, Core 

questionnaire

2009 X X 

2008 Panel, Wave 3, Topical Module 

on Retirement and Pension Plan 

Coverage

2009 X 

2008 Panel, Wave 7, Core 

questionnaire

2010 X 

Source: GAO. 

a

In this report, the data are described by referring to the year from which the majority of the data was 

collected. For example, the 2001 Wave 7 data is described as “2003 data” because the reference 

periods for 10 of the 16 rotation groups in this wave were in calendar year 2003. 

In comparison to other nationally representative surveys, the SIPP had 

several main advantages. First, the SIPP collects separate information on 

defined benefit (DB) and defined contribution (DC) plans. Other surveys, 

such as the Current Population Survey, do not distinguish between 

income from and participation in DB and DC plans. Second, the SIPP 

sample is larger than comparable surveys, such as the Survey of 

Consumer Finances (SCF). Consequently, it is possible to produce point 

estimates for demographic subcategories with a higher degree of 

reliability. Further, in comparison to the SCF, which oversamples wealthy 

households, the SIPP oversamples lower-income households—arguably 

an important component of an analysis of income security.

Despite its advantages, the SIPP has two limitations for our analysis. 

First, as with most survey data, SIPP data are self-reported. This can be 

problematic for the reporting of data on income sources and pension plan 

participation. For example, respondents might incorrectly report that they 

participate in a pension plan when they do not participate in one.1

 

1

For more information regarding such misreporting, see Irena Dushi, Howard M. Iams, 

and Jules Lichtenstein, “Assessment of Retirement Plan Coverage by Firm Size, Using 

W-2 Tax Records,” Social Security Bulletin, vol. 71, no. 2 (2011). 

Second, despite the fact that SIPP differentiates between participation in 
Appendix I: Objective, Scope, and Methods

Page 52 GAO-12-699 Women’s Retirement Security 

a DB or DC plan, it does not contain full information on whether an 

individual’s employer offers a DB plan.2

To answer question 3—on the effects of events occurring later in life on 

women’s retirement income security—we analyzed data collected through 

the HRS, a nationally representative survey primarily sponsored by the 

National Institute of Aging and conducted by the Institute for Social 

Research at the University of Michigan. This longitudinal survey collects 

data on individuals over age 50 and contains detailed information on 

health, marital status, assets, income, and care for elders. Respondents 

were first surveyed in 1992, when they were age 51 to 61 and continued 

to be surveyed every 2 years. Additional cohorts were added in later 

years to maintain the representation of the older population. Table 11 

presents the cohorts that are included in the HRS sample. Respondents 

are resurveyed every 2 years. The data in our analysis span from the 

initial 1992 survey through the early release data for 2010, the most 

current data available. Our analysis follows over 30,000 individuals from 

the HRS sample.

Table 11: Birth Years for the HRS Cohorts and the Year Data Collection Began for 

Each Cohort

Cohort Birth years

Year data 

collection began

AHEADa 1923 and earlier 1993

Children of the Depression Era (CODA)a 1924-1930 1998

Original HRS cohort 1931-1941 1992

War Babiesa 1942-1947 1998

Early Baby Boomers 1948-1953 2004

Source: RAND HRS Data Documentation, Version L.

a

The Asset and Health Dynamics of the Oldest Old (AHEAD) survey began collecting data in 1993. 

Originally, the HRS and AHEAD were separate but related surveys. The AHEAD survey was initially 

funded as a supplement to the HRS. In 1998, the two surveys merged and the CODA and War 

Babies cohorts were added to the survey. 

 

2

The survey contains catch-all questions for whether an individual’s employer offers a DC 

plan, but it does not contain similar questions for DB plans. Specifically, those who are not 

included in their employer’s plan are not asked whether their employer offers a DB plan.

Health and Retirement 

Study
Appendix I: Objective, Scope, and Methods

Page 53 GAO-12-699 Women’s Retirement Security 

One of the main advantages of the HRS is that the same households are 

interviewed at different points of time, allowing us to examine the 

correlation of changes in life events to changes in household assets and 

income. Further, RAND, a research organization, cleans and processes 

the HRS data to create a user-friendly longitudinal dataset that has 

consistent and intuitive naming conventions, model-based imputations for 

missing wealth and income data, and spousal counterparts of most 

individual-level variables. We used these data for our analysis.

However, there are three limitations for our analysis. First, the women 

currently in the HRS survey may have very different retirement 

experiences from women in the workforce today due to changes in 

demographic trends and workforce participation. Second, as with the 

SIPP, data from the HRS are self-reported. Third, total household assets 

cannot be broken out at the individual level.

For each of the datasets described above, we conducted a data reliability 

assessment of selected variables by conducting electronic data tests for 

completeness and accuracy, reviewing documentation on the dataset, or 

interviewing knowledgeable officials about how the data are collected and 

maintained and their appropriate uses. When we learned that particular 

fields were not sufficiently reliable, we did not use them in our analysis. 

For example, we chose not to use data from the SIPP Topical Module on 

Annual Income and Retirement Accounts because many of the fields in

that survey are not edited by the Census Bureau. For the purposes of our 

analysis, we found the variables that we ultimately reported on to be 

sufficiently reliable.

To gain an understanding of the challenges women face in attaining a 

secure retirement and policy options that could enhance women’s 

retirement security, we conducted an extensive literature review and 

interviewed a range of experts. To identify existing studies, we conducted 

searches of various databases, such as EconLit, Electronic Collections 

Online, ProQuest, Academic OneFile, WorldCat, and Policy File. From 

these sources, we identified 128 articles that appeared in journals since 

2007 and were relevant to our research objective on policy options that 

could enhance women’s retirement security. From the articles identified in 

the preliminary search, we reviewed article abstracts, when available, to 

determine which articles contained information germane to our report and 

reviewed those articles. In addition, we reviewed articles that were 

collected during the previous GAO study on women’s retirement security 

Data Reliability

Literature Review and 

Interviews
Appendix I: Objective, Scope, and Methods

Page 54 GAO-12-699 Women’s Retirement Security 

that contained information relevant to our empirical analyses, described 

below, and reviewed articles that were suggested to us by the experts we 

interviewed. We performed these searches and identified articles from 

May 2011 to October 2011.

To supplement the literature review, we conducted interviews with 

experts. To ensure that we obtained a balanced perspective, we 

interviewed experts with a range of perspectives and from different types 

of organizations including government, academia, advocacy groups, and 

the private sector. We also consulted several experts in government and 

academia on technical issues related to our analysis. Specifically, we 

interviewed agency officials at the departments of the Treasury and 

Labor, the Social Security Administration, and the Bureau of the Census; 

academic experts at the Employee Benefits Research Institute, Heritage 

Foundation, University of Pennsylvania, Stanford University, Urban 

Institute, and Wellesley College; and industry experts and advocates from 

the American Council on Life Insurers, Anna Rappaport Consulting, 

Financial Engines, the Institute for Women’s Policy Research, the 

National Women’s Law Center, AARP, the Pension Rights Center, the 

National Academy of Social Insurance, Social Security Works, and the 

Women’s Institute for a Secure Retirement.

To determine the proportion of men and women that (1) work for an 

employer that offers a plan, (2) are eligible for a plan, and (3) participate 

in a plan, we used data from the SIPP topical module on retirement and 

pension plan coverage. Specifically, we constructed five dummy variables 

using a combination of various questions in the SIPP. Table 12 shows the 

information we used to construct each variable. For each of these 

variables, we used SIPP individual-level weights to compute point 

estimates and, in conjunction with other factors, calculate the standard 

errors of those estimates so that we could accurately account for the 

complex survey design. We consulted statisticians from the U.S. Bureau 

of the Census on the appropriate use of these weights.

Section 2: Methods 

for Comparing 

Working Women’s and 

Men’s Access to and 

Participation in 

Employer-Sponsored 

Pension Plans
Appendix I: Objective, Scope, and Methods

Page 55 GAO-12-699 Women’s Retirement Security 

Table 12: Information Used from SIPP to Construct Key Variables

Variable Constructed with:

Worker has employer that offers either 

a DB or a DC pension plan to some 

employees 

A combination of two questions. One question asks whether the individual’s job or business 

has any kind of pension or retirement plan for anyone in the company or organization, and 

a subsequent clarifying question asks if the individual’s job or business offers a DC plan. 

Worker has employer that offers a DC 

pension plan to some employees

A combination of questions. If the respondent replied yes to the question listed above, a 

follow-up question is asked about whether the respondent participates in the plan, and if 

so, the type of plan. This series of questions enables us to identify, among those who 

participate, whether the individual’s employer offers a DC plan. For those that said that 

their employer does not offer a pension or retirement plan, and those who said that their 

employer offers a plan but it does not include a DC-type component, SIPP asks a follow-up 

question about whether the employer offers a DC-type plan. By combining these two sets 

of information, we were able to construct a dummy variable to indicate whether the 

individual’s employer offers a DC plan.

Worker is eligible for employersponsored planA question in the SIPP topical module on retirement and pension plan coverage that asks 

the reason for not participating in the employer’s plan. We defined individuals as not 

eligible if they listed one of the following reasons for not participating: no one in their type of 

job is eligible; they don’t work enough hours, days, weeks or months; they don’t have 

enough tenure in the job; they are too young; they started their job too close to retirement. 

We defined individuals as eligible if they participated in the plan or listed some other reason 

for not participating. 

Worker participates in employersponsored DB or DC planA combination of two questions. One question asks whether the individual participates in 

the employer-sponsored plan, and a subsequent clarifying question asks if the individual 

participates in an employer-sponsored DC plan.

Worker participates in employersponsored DC planA combination of questions. If the respondent replied yes to the question above and the 

respondent indicates that the type of plan in which he or she participated was a DC plan.

Source: GAO analysis of SIPP questionnaire. 

To better understand the factors that might explain gender differences in 

each of these variables, we developed a series of empirical models. 

Following the literature, we controlled for the following factors in our 

models: (1) demographic characteristics including gender, age, marital 

status, children present in the household, single parenthood, race and 

ethnicity, citizenship, immigrant status, and education level; and (2) 

occupational characteristics including part-time employment status, selfemployment status, years of tenure, work experience, occupation, 
Appendix I: Objective, Scope, and Methods

Page 56 GAO-12-699 Women’s Retirement Security 

industry, sector, union status, and size of employing firm.3

We conducted the modeling analyses in a series of steps whereby with 

each step, the sample of men and women that was included in the 

analysis was conditional on the previous step. Specifically, the first 

analysis involved analyzing the probability of working for an employer that 

offered a pension plan for all workers in the sample. The second analysis 

involved analyzing the probability of being eligible for a plan for those 

men and women that worked for an employer offering a plan. The third 

analysis involved analyzing the probability of participating in a plan for 

those that were eligible for their employer-sponsored plan.

To estimate 

these models, we used logistic regression—an appropriate technique 

when the dependent variable is binary, or has two categories such as 

participating in a plan or not participating in a plan. Logistic regression 

also allows for the coefficients to be converted into odds ratios, which are 

described below.

In conjunction with understanding the factors associated with each 

dependent variable in our models, it is essential to also understand how 

women and men differ in those factors. Taken together, the information 

from the model and information from a comparison of men’s and women’s 

characteristics enables us to understand what factors make women more 

or less likely to be employed by an employer that offers a plan, be eligible 

for the plan, and participate in the plan. For example, if we know that 

women are disproportionately more likely to work part-time and that parttime status is an important factor associated with plan participation, we 

can infer that women’s higher rates of part-time status might contribute to 

their lower rates of plan participation. Table 13 compares the 

characteristics of men and women for each of the factors that we control 

for, across each year of the study period.

 

3

Note that in the models we present, we did not include income as a control variable. 

Income can be considered to be endogenously (or simultaneously) determined with an 

individual’s decision to work for a particular employer that might be offering a plan and

therefore have the potential to bias the model estimates. For example, one might 

deliberately choose to work in a lower-paid government position to ensure access to a DB 

plan. We did run versions of our model with income included as a control and found that it 

was significantly associated with the likelihood of working for an employer that offers a 

plan and of participating in a plan. 

Changes in the Working 

Population Over Time by 

Gender
Appendix I: Objective, Scope, and Methods

Page 57 GAO-12-699 Women’s Retirement Security 

Generally, the characteristics of men and women in the working 

population did not change dramatically over the study period. 

Correspondingly, when we compare men and women in each year, 

several relationships between them were consistent across all of the 

study years. In terms of demographic characteristics, women were more 

likely than men to be widowed and divorced. Women were also more 

likely to have children present in the household, be single parents, and 

work part time. A higher proportion of men than women were Hispanic, 

and this proportion increased over the study period.4

In terms of occupational characteristics, several gender differences 

persisted across the study years. Women consistently had higher levels 

of education and were more likely to work in the public or nonprofit 

sectors. Men were more likely to work in the private sector, be selfemployed, have longer tenure at their current position, have more work 

experience, and to be in a union.

Although the occupational and industry categories in the SIPP data 

changed midway through the study periods, the distributions of men and 

women across occupations and industry were generally consistent for the 

last 2 study years. Specifically, the top three occupations for women were 

office and administrative support; sales and related services; and 

education, training, and library services, with 20, 10, and 10 percent of 

women working in these occupations respectively in 2009. Men tended 

not to be as concentrated in just a few occupations. In 2009, the highest 

proportions of men were employed in management (9 percent), sales and 

related occupations (8 percent), construction and extraction (8 percent), 

and transportation and material moving (8 percent). Similarly, in 2009, the 

top three industries for women were health care and social assistance (21 

percent), educational services (14 percent), and retail trade (10 percent). 

For men in this year, the top three industries in which men were 

employed were manufacturing (13 percent), construction (9 percent), and 

retail trade (9 percent).

 

4

This result is consistent with Census findings, which note a higher male-to-female ratio 

among the Hispanic population in the United States than among the general population. 
Appendix I: Objective, Scope, and 

Methods

Page 58 GAO-12-699 Women’s Retirement Security 

Table 13: Characteristics of the Working Population over Time 

 1999 2003 2006 2009

Percentage of Percentage of Percentage of Percentage of

 Men Women Men Women Men Women Men Women

Gender 53 47 53 47 53 47 53 47

Age groups 

18-24 12 13 12 13 13 13 12 13

25-34 26 25 24 23 23 22 23 22

35-44 29 29 27 27 26 25 24 23 

45-54 22 22 24 25 24 25 25 26

55-64 11 11 13 13 14 14 16 16

Marital status 

Married 62 57 61 57 59 56 59 55

Widowed 1 3 1 2 1 2 1 2 

Divorced 9 13 10 14 10 13 9 13

Separated 2 3 2 3 2 2 2 2 

Never married 26 23 27 24 29 26 29 27

Children in the household 46 49 44 46 44 47 42 44

Single parent 8 16 7 16 8 16 8 16

Race and ethnicity 

White, Non-Hispanic 76 75 73 72 69 70 69 70

Black, Non-Hispanic 9 12 9 12 10 12 9 12

Hispanic 11 9 14 11 15 11 16 12

Asian, Non-Hispanic 3 4 4 4 4 3 4 4 

Other, Non-Hispanic 1 1 1 1 2 3 2 3

Citizenship 

Noncitizen 7 6 9 6 10 7 10 6 

Immigrant status 

Naturalized immigrant 4 4 5 5 6 6 7 7

Education level 

No high school diploma 12 9 12 8 8 5 8 5
Appendix I: Objective, Scope, and 

Methods

Page 59 GAO-12-699 Women’s Retirement Security 

 1999 2003 2006 2009

Percentage of Percentage of Percentage of Percentage of

 Men Women Men Women Men Women Men Women

High school diploma 32 30 29 27 30 26 27 23

Some college 30 34 30 35 35 39 35 39

Bachelor’s degree or higher 26 27 29 29 28 31 30 33

Part-time statusa 

Part time 22 37 23 38 22 36 26 37

Self-employment status 

Self-employed 16 10 15 10 15 10 16 10

Average years of tenure at current job 8.0 6.9 8.0 7.0 7.8 7.2 8.2 7.7

Work experience

Less than 5 years 26 29 26 31 25 28 26 30

5 to 9 years 14 17 14 15 14 16 14 16

10 to 15 years 11 12 11 11 10 11 12 12

More than 15 years 49 43 49 43 50 45 48 41

Average years of total work experience 10.8 9.4 11.1 9.7 11.4 10.3 11.9 10.7

Sector

Private for profit 70 63 69 62 71 62 68 61

Private not for profit 4 10 4 10 4 10 4 10

Government 13 18 13 19 12 18 14 19

Family worker without pay 1 1 0 1 0 1 0 1 

Not in universe 13 7 13 8 12 8 13 8 

Union status

In union 17 12 15 12 14 12 15 13

Occupation 

Management NA NA NA NA 9 7 9 7 

Business and Financial Operations NA NA NA NA 3 4 3 5 

Computer and Mathematical NA NA NA NA 3 2 4 1 

Architecture and Engineering NA NA NA NA 3 1 3 1

Life, Physical, and Social Services NA NA NA NA 1 1 1 1 

Community and Social Services NA NA NA NA 1 2 1 2
Appendix I: Objective, Scope, and 

Methods

Page 60 GAO-12-699 Women’s Retirement Security 

 1999 2003 2006 2009

Percentage of Percentage of Percentage of Percentage of

 Men Women Men Women Men Women Men Women

Legal NA NA NA NA 1 1 1 1 

Education, Training, and Library NA NA NA NA 3 10 3 10

Arts, Design, Entertainment, Sports, and Media NA NA NA NA 1 1 1 1

Healthcare Practitioners and Technical NA NA NA NA 2 8 2 8 

Healthcare Support NA NA NA NA 0 4 0 4 

Protective Service NA NA NA NA 3 1 3 1 

Food Preparation and Serving Related NA NA NA NA 4 6 4 6 

Building and Grounds Cleaning and 

Maintenance

NA NA NA NA 4 3 4 3 

Personal Care and Service NA NA NA NA 1 4 1 4 

Sales and Related NA NA NA NA 8 10 8 10

Office and Administrative Support NA NA NA NA 7 22 6 20

Farming, Forestry, and Fishing NA NA NA NA 1 0 1 0 

Construction and Extraction NA NA NA NA 9 0 8 0 

Installation, Repair, and Maintenance NA NA NA NA 6 0 6 0 

Production NA NA NA NA 9 4 7 3 

Transportation and Material Moving NA NA NA NA 9 2 8 2 

Not in universeb NA NA NA NA 12 7 14 8

Industry

Agriculture NA NA NA NA 1 0 1 1

Mining NA NA NA NA 1 0 1 0 

Utilities NA NA NA NA 1 0 1 0 

Construction NA NA NA NA 10 1 9 1 

Manufacturing NA NA NA NA 15 7 13 6

Wholesale Trade NA NA NA NA 4 2 3 2 

Retail Trade NA NA NA NA 10 10 9 10

Transportation and Warehousing NA NA NA NA 5 2 5 2 

Information NA NA NA NA 2 2 2 2 

Finance and Insurance NA NA NA NA 3 6 3 6 
Appendix I: Objective, Scope, and 

Methods

Page 61 GAO-12-699 Women’s Retirement Security 

 1999 2003 2006 2009

Percentage of Percentage of Percentage of Percentage of

 Men Women Men Women Men Women Men Women

Real Estate and Rental and Leasing NA NA NA NA 1 2 1 1 

Professional, Scientific, and Technical NA NA NA NA 5 5 5 5 

Management, Administrative and Support NA NA NA NA 4 3 4 3

Educational Services NA NA NA NA 5 14 6 14

Health Care and Social Assistance NA NA NA NA 4 19 4 21

Arts, Entertainment, and Recreation NA NA NA NA 1 2 2 2 

Accommodations and Food Services NA NA NA NA 5 7 6 8 

Other Services (Except Public Administration) NA NA NA NA 3 4 3 4 

Public Administration NA NA NA NA 6 5 5 5

Active duty NA NA NA NA 1 0 1 0 

Not in universeb NA NA NA NA 12 7 13 8

Household income bracket 

Less than $20,000 7 8 6 8 7 8 8 9 

$20,000-$40,000 17 18 16 18 16 17 16 16

$40,000-$60,000 20 20 19 19 19 19 18 19

$60,000-$80,000 18 17 17 17 16 16 16 15

Greater than $80,000 38 36 41 39 42 41 41 40

Firm size 

Under 25 employees 18 19 18 19 19 19 18 18

25 to 100 employees 12 11 12 11 11 11 11 11

100+ employees 58 62 58 62 57 63 58 63

Not in universeb 13 7 13 8 12 8 13 8 

Source: GAO analysis of SIPP data.

Note: The categories for occupation and industry changed between the 2001 and 2003 SIPP panels. 

We present the categories for the two most recent panels. 

a

Part-time status is defined as working 35 hours or less per week during the reference period. 

b

The category “Not in universe” includes self-employed individuals. 
Appendix I: Objective, Scope, and Methods

Page 62 GAO-12-699 Women’s Retirement Security 

Table 14 shows the results of two models that analyze factors associated 

with the probability of working for an employer that offers (1) any type of 

pension plan (DB or DC) or (2) a DC plan. The first column presents the 

variables that were included in each model. The third and fifth columns 

present odds ratios that are estimated for each variable in the model.51

The interpretation of the odds ratio for a particular variable depends on 

whether the variable has only two or more than two categories.62

As shown in the body of the report, before controlling for differences 

between men and women in demographic and occupational 

characteristics, a greater proportion of women worked for employers that 

offered plans in 2009. Interestingly, table 14 shows that after accounting 

for demographic and occupational characteristics, women have slightly 

lower odds of working for an employer that offers a DC plan than men. In 

fact, the positive gender effect for women is eliminated when we control 

for occupational characteristics using a statistical model (results not 

shown below). In other words, women’s higher likelihood of working for an 

employer that offers a plan is largely due to the types of occupations and 

industries in which women work. (The odds ratios for the specific 

occupations and industries, which are too numerous to discuss here, are 

listed in the table.)

For 

dichotomous (or dummy) variables, odds ratios that are statistically 

significant and greater than 1.00 indicate that individuals with that 

characteristic are more likely to work for an employer that offers a plan. 

For example, an odds ratio of 1.25 for women would mean that women 

are 1.25 times more likely to work for an employer that offers a plan. 

Odds ratios that are significantly lower than 1.00 indicate that individuals 

with that characteristic are less likely to work for an employer that offers a 

plan. For categorical variables with more than two categories, a 

statistically significant odds ratio that is greater/less than 1.00 indicates 

that individuals in that category are more/less likely to work for an 

employer that offers a plan than individuals in the category that is chosen 

as the referent or comparison category.

 

5

Odds (O) are mathematically related to but not the same as probabilities (P), that is 

O=P/[1-P]. 

6

While dummy and categorical variables are both discrete variables, a dummy variable 

takes on a value of 0 or 1. A categorical variable takes a value that is one of several 

possible categories and there is no intrinsic ordering to the categories.

Factors Associated with 

Working for an Employer 

That Offers a Plan
Appendix I: Objective, Scope, and Methods

Page 63 GAO-12-699 Women’s Retirement Security 

We found that several other factors are associated with the likelihood of 

working for an employer that offers a plan. While the details are shown in 

the table, the factors that were positively associated with working for an 

employer that offers either a DB or DC plan (and that were statistically 

significant at the 95 percent confidence level) included age; being 

divorced (relative to married); education level; U.S. citizenship; working in 

the government or nonprofit sector (in comparison to the private sector); 

having 5 to 9 years of work experience (in comparison to having less than 

5 years); union membership; job tenure; and firm size.

Factors that were negatively associated with working for an employer that 

offers a plan included being never married (in comparison to being 

married); being a single parent; being Black, Hispanic, or Asian (in 

comparison to White, non-Hispanics); being a naturalized immigrant; 

working part time; and being self-employed. While the results across both 

models were generally consistent, some results were significant in one 

model but not the other.

Table 14: Factors Associated with Working for an Employer That Offers a Plan, 2009

Dependent variable

Unadjusted 

proportion with 

employer that 

offers a DB 

or DC plan

Employer 

offers a DB or 

DC plan

Unadjusted 

proportion with 

employer that 

offers a DC plan

Employer 

offers a DC 

plan

Explanatory variables: 

Gender (omitted category is men) 58% 46% 

Women 61% 0.948 49% 0.938**

Age groups (omitted category age 18-24) 42% 33% 

25-34 60% 1.494*** 49% 1.615***

35-44 62% 1.499*** 50% 1.608***

45-54 64% 1.518*** 51% 1.620***

55-64 63% 1.229*** 48% 1.300***

Marital status (omitted category married) 63% 50% 

Widowed 59% 1.059 46% 1.083

Divorced 64% 1.135** 51% 1.097**

Separated 53% 1.008 42% 1.000

Never married 52% 0.906** 41% 0.965

Children in the household 59% 1.101** 47% 1.027

Single parent 49% 0.793*** 39% 0.869**
Appendix I: Objective, Scope, and Methods

Page 64 GAO-12-699 Women’s Retirement Security 

Dependent variable

Unadjusted 

proportion with 

employer that 

offers a DB 

or DC plan

Employer 

offers a DB or 

DC plan

Unadjusted 

proportion with 

employer that 

offers a DC plan

Employer 

offers a DC 

plan

Race and ethnicity (omitted category White) 63% 51% 

Black, Non-Hispanic 61% 0.750*** 46% 0.758***

Hispanic 43% 0.605*** 32% 0.663***

Asian, Non-Hispanic 56% 0.761*** 46% 0.882

Other, Non-Hispanic 59% 0.855* 47% 0.897

Education level (omitted category No high school 

diploma)

30% 24% 

High school diploma 51% 1.297*** 39% 1.196***

Some college 61% 1.772*** 48% 1.543***

Bachelor’s degree or higher 72% 1.997*** 57% 1.606***

Citizen 62% 1.577*** 49% 1.499***

Naturalized immigrant 54% 0.737*** 42% 0.787***

Part-time status (omitted category is full time)a 66% 52% 

Part-time 46% 0.763*** 38% 0.925***

Sector (omitted category private sector) 60% 50% 

Private not for profit 73% 1.430*** 59% 1.243***

Government worker 88% 2.142*** 61% 1.062

Occupation (omitted category Management) 76% 64% 

Business and Financial Operations 82% 1.133 70% 1.053

Computer and Mathematical 85% 1.222* 73% 1.036

Architecture and Engineering 88% 1.737*** 73% 1.196

Life, Physical, and Social Services 87% 1.067 68% 0.779*

Community and Social Services 74% 0.895 54% 0.701***

Legal 77% 1.139 66% 1.190

Education, Training, and Library 81% 0.605*** 57% 0.600***

Arts, Design, Entertainment, Sports, and Media 64% 0.729** 52% 0.745**

Healthcare Practitioners and Technical 82% 1.314*** 68% 1.003

Healthcare Support 57% 0.635*** 46% 0.617***

Protective Service 77% 0.684*** 54% 0.631***

Food Preparation and Serving Related 34% 0.530*** 27% 0.524***

Building and Grounds Cleaning and Maintenance 42% 0.619*** 30% 0.545***

Personal Care and Service 33% 0.326*** 25% 0.363***

Sales and Related 60% 0.634*** 49% 0.620***

Office and Administrative Support 69% 0.864* 55% 0.785***

Farming, Forestry, and Fishing 16% 0.265*** 12% 0.290***
Appendix I: Objective, Scope, and Methods

Page 65 GAO-12-699 Women’s Retirement Security 

Dependent variable

Unadjusted 

proportion with 

employer that 

offers a DB 

or DC plan

Employer 

offers a DB or 

DC plan

Unadjusted 

proportion with 

employer that 

offers a DC plan

Employer 

offers a DC 

plan

Construction and Extraction 44% 0.690*** 31% 0.595***

Installation, Repair, and Maintenance 66% 0.856 56% 0.929

Production 66% 0.607*** 53% 0.628***

Transportation and Material Moving 61% 0.673*** 48% 0.627***

Not in universeb 15% 0.894 10% 0.411***

Industry (omitted category Agriculture) 19% 16% 

Mining 69% 1.515 54% 1.235

Utilities 89% 3.134*** 69% 1.785**

Construction 45% 1.379 33% 1.145

Manufacturing 76% 2.697*** 63% 2.036***

Wholesale Trade 69% 2.725*** 55% 1.923***

Retail Trade 62% 2.052*** 51% 1.668**

Transportation and Warehousing 71% 1.763** 55% 1.525*

Information 76% 2.228*** 63% 1.761**

Finance and Insurance 84% 3.571*** 73% 2.614***

Real Estate and Rental and Leasing 49% 1.301 41% 1.255

Professional, Scientific, and Technical 71% 2.197*** 61% 1.884***

Management, Administrative and Support 42% 1.059 34% 1.013

Educational Services 84% 2.120*** 60% 1.461

Health Care and Social Assistance 67% 1.733** 55% 1.559*

Arts, Entertainment, and Recreation 51% 1.453 40% 1.268

Accommodations and Food Services 34% 0.996 28% 0.905

Other Services (Except Public Administration) 38% 1.144 30% 0.972

Public Administration 89% 2.198*** 64% 1.499

Work experience (omitted category Less than 5 years) 56% 45% 

5 to 9 years 67% 1.140*** 53% 1.069*

10 to 15 years 71% 1.033 56% 1.013

More than 15 years 57% 0.978 45% 0.989

Union status (omitted category not in a union) 63% 51% 

In a union 87% 1.903*** 62% 1.094**

Self-employment status 19% 0.525*** 14% 0.671***

Number of employees at current place of employment 

(omitted category Under 25 employees))

25% 19% 

25 to 100 employees 57% 3.291*** 46% 3.021***

100+ employees 79% 7.618*** 63% 5.528***
Appendix I: Objective, Scope, and Methods

Page 66 GAO-12-699 Women’s Retirement Security 

Dependent variable

Unadjusted 

proportion with 

employer that 

offers a DB 

or DC plan

Employer 

offers a DB or 

DC plan

Unadjusted 

proportion with 

employer that 

offers a DC plan

Employer 

offers a DC 

plan

Years of tenure at current job 1.042*** 9% 1.015***

Tenure categories 

Less than 5 years 56% 45% 

5 to 9 years 69% 54% 

10 to 15 years 76% 60% 

More than 15 years 82% 63% 

Number of observations 37,038 37,038

Source: GAO analysis of SIPP data.

*Indicates that the variable is statistically significant at the 90 percent level. 

**Indicates that the variable is statistically significant at the 95 percent level. 

***Indicates that the variable is statistically significant at the 99 percent level. 

a

Part-time status is defined as working 35 hours or less per week during the reference period. 

b

The category “Not in universe” includes self-employed individuals. 

Table 15 shows the results of a model we estimated to analyze factors 

associated with whether an individual is eligible for their employer’s plan. 

It is presented in the same format as table 14. As shown in the body of 

the report, women had lower rates of plan eligibility across all 4 study 

years. The results of the model show that, even after controlling for 

demographic and occupational differences between men and women, 

women had significantly lower rates of eligibility in 2009. Perhaps most 

interesting is the odds ratio for part-time status, which indicates that parttime workers are approximately one-third as likely to be eligible for their 

employer’s plan as full-time workers. In addition, work experience and 

tenure are also significantly and positively related with eligibility. Union 

status is also positively associated with plan eligibility.

Factors Associated with 

Eligibility for EmployerSponsored Pension Plan
Appendix I: Objective, Scope, and Methods

Page 67 GAO-12-699 Women’s Retirement Security 

Table 15: Factors Associated with Eligibility for Employer-Sponsored Pension Plan, 2009

Dependent variable

Unadjusted proportion 

eligible for a DB or DC plan

Individual is eligible 

for a DB or DC plan

Gender (omitted category is men) 91% 

Women 87% 0.861**

Age groups (omitted category age 18-24) 55% 

25-34 88% 2.589***

35-44 93% 2.957***

45-54 94% 2.846***

55-64 93% 2.106***

Marital status (omitted category married) 92% 

Widowed 88% 0.637**

Divorced 92% 1.021

Separated 89% 0.998

Never married 77% 0.795***

Children in the household 89% 0.906

Single parent 77% 0.963

Race and ethnicity (omitted category White) 89% 

Black, Non-Hispanic 87% 0.998

Hispanic 87% 1.028

Asian, Non-Hispanic 90% 1.011

Other, Non-Hispanic 86% 1.023

Education level (omitted category No high school diploma) 82% 

High school diploma 87% 0.881

Some college 86% 0.872

Bachelor’s degree or higher 93% 1.128

Citizen 89% 1.235

Naturalized immigrant 91% 0.886

Part-time status (omitted category is full time)a 94% 

Part-time 73% 0.315***

Sector (omitted category private sector) 87% 

Private not for profit 87% 0.867

Government worker 92% 0.996

Occupation (omitted category Management) 96% 

Business and Financial Operations 95% 0.958

Computer and Mathematical 95% 0.941

Architecture and Engineering 96% 1.088

Life, Physical, and Social Services 95% 0.924
Appendix I: Objective, Scope, and Methods

Page 68 GAO-12-699 Women’s Retirement Security 

Dependent variable

Unadjusted proportion 

eligible for a DB or DC plan

Individual is eligible 

for a DB or DC plan

Community and Social Services 90% 0.579**

Legal 94% 0.823

Education, Training, and Library 88% 0.492***

Arts, Design, Entertainment, Sports, and Media 87% 0.535**

Healthcare Practitioners and Technical 90% 0.595***

Healthcare Support 79% 0.346***

Protective Service 92% 0.533***

Food Preparation and Serving Related 65% 0.395***

Building and Grounds Cleaning and Maintenance 83% 0.396***

Personal Care and Service 69% 0.299***

Sales and Related 81% 0.466***

Office and Administrative Support 87% 0.474***

Farming, Forestry, and Fishing 89% 0.598

Construction and Extraction 92% 0.693

Installation, Repair, and Maintenance 93% 0.638**

Production 92% 0.482***

Transportation and Material Moving 85% 0.417***

Not in universeb 96% 1.461

Industry (omitted category Agriculture) 90% 

Mining 92% 0.765

Utilities 98% 1.572

Construction 91% 0.684

Manufacturing 94% 1.055

Wholesale Trade 92% 1.090

Retail Trade 79% 0.682

Transportation and Warehousing 90% 0.717

Information 91% 0.952

Finance and Insurance 92% 1.006

Real Estate and Rental and Leasing 89% 0.907

Professional, Scientific, and Technical 93% 0.854

Management, Administrative and Support 85% 0.656

Educational Services 88% 0.599

Health Care and Social Assistance 88% 0.831

Arts, Entertainment, and Recreation 75% 0.462

Accommodations and Food Services 67% 0.538

Other Services (Except Public Administration) 86% 0.738
Appendix I: Objective, Scope, and Methods

Page 69 GAO-12-699 Women’s Retirement Security 

Dependent variable

Unadjusted proportion 

eligible for a DB or DC plan

Individual is eligible 

for a DB or DC plan

Public Administration 95% 1.076

Work experience (omitted category Less than 5 years) 78% 

5 to 9 years 92% 1.419***

10 to 15 years 95% 1.435***

More than 15 years 92% 0.895*

Union status (omitted category not in a union) 87% 

In a union 95% 2.070***

Self-employment status 91% 0.864

Number of employees at current place of employment 

(omitted category Under 25 employees)

85% 

25 to 100 employees 88% 1.165*

100+ employees 89% 1.300***

Years of tenure at current job 1.169***

Tenure categories 

Less than 5 years 78% 

5 to 9 years 93% 

10 to 15 years 97% 

More than 15 years 99% 

Number of observations 24,274

Source: GAO analysis of SIPP data.

*Indicates that the variable is statistically significant at the 90 percent level. 

**Indicates that the variable is statistically significant at the 95 percent level. 

***Indicates that the variable is statistically significant at the 99 percent level. 

a

Part-time status is defined as working 35 hours or less per week during the reference period. 

b

The category “Not in universe” includes self-employed individuals. 

Table 16 shows the results of two models we estimated to analyze factors 

associated with the probability of participating in (1) any type of pension 

plan (DB or DC) or (2) a DC plan. Again, it is presented in the same 

format as tables 14 and 15.

As shown in the body of the report, before controlling for differences 

between men and women in demographic and occupational 

characteristics, a smaller proportion of women participated in an 

employer-sponsored pension plan. Our analysis shows that the gender 

differences in plan participation are largely accounted for by differences 

between men and women in demographic and occupational 

characteristics.

Factors Associated with 

Participation in an 

Employer-Sponsored 

Pension Plan
Appendix I: Objective, Scope, and Methods

Page 70 GAO-12-699 Women’s Retirement Security 

Similar to our other models, we identify a number of factors that are 

related to plan participation. The factors that were positively related to 

participating in either a DB or a DC (and that are statistically significant at 

the 95 percent level) include age; education-level; being Asian (relative to 

whites); U.S. citizenship; working in the nonprofit or government sector 

(relative to the private sector); work-experience; union membership; and 

tenure. Factors that were negatively related to participating in a plan 

included being a single parent; working part-time; and being Black or 

Hispanic. A number of industries and occupations, too numerous to list, 

were statistically significant as shown in the table below.

Table 16: Factors Associated with Participation in an Employer-Sponsored Pension Plan, 2009

Dependent variable

Unadjusted 

proportion 

participating in 

a DB or DC plan

Individual 

participates in a 

DB or DC plan

Unadjusted 

proportion 

participating in 

a DC plan

Individual 

participates in a 

DC plan

Gender (omitted category is men) 87% 79% 

Women 86% 0.973 78% 1.099*

Age groups (omitted category age 18-24) 63% 54% 

25-34 83% 1.547*** 75% 1.659***

35-44 87% 1.627*** 80% 1.821***

45-54 91% 1.843*** 83% 1.924***

55-64 92% 1.691*** 82% 1.642***

Marital status (omitted category married) 90% 82% 

Widowed 90% 1.173 82% 1.129

Divorced 86% 0.867 78% 0.911

Separated 79% 0.871 68% 0.784

Never married 78% 0.888 71% 0.961

Children in the household 87% 1.125 79% 1.138*

Single parent 76% 0.805** 68% 0.844*

Race and ethnicity (omitted category White) 88% 81% 

Black, Non-Hispanic 81% 0.705*** 68% 0.579***

Hispanic 77% 0.684*** 69% 0.737***

Asian, Non-Hispanic 90% 1.304* 85% 1.500***

Other, Non-Hispanic 86% 1.108 77% 0.950

Education level (omitted category No high school 

diploma)

69% 61% 

High school diploma 82% 1.275** 72% 1.190

Some college 85% 1.617*** 77% 1.548***

Bachelor’s degree or higher 92% 2.318*** 84% 1.871***

Citizen 87% 1.619*** 79% 1.570***
Appendix I: Objective, Scope, and Methods

Page 71 GAO-12-699 Women’s Retirement Security 

Dependent variable

Unadjusted 

proportion 

participating in 

a DB or DC plan

Individual 

participates in a 

DB or DC plan

Unadjusted 

proportion 

participating in 

a DC plan

Individual 

participates in a 

DC plan

Naturalized immigrant 87% 0.991 80% 1.055

Part-time status (omitted category is full time)a 88% 80% 

Part-time 81% 0.791*** 74% 0.851***

Sector (omitted category private sector) 83% 77% 

Private not for profit 88% 1.274*** 80% 1.219***

Government worker 94% 1.902*** 82% 1.239**

Occupation (omitted category Management) 92% 87% 

Business and Financial Operations 91% 0.885 85% 0.847

Computer and Mathematical 91% 0.823 86% 0.790

Architecture and Engineering 94% 1.256 89% 0.969

Life, Physical, and Social Services 96% 1.387 90% 1.147

Community and Social Services 88% 0.636** 82% 0.808

Legal 92% 0.883 86% 0.856

Education, Training, and Library 92% 0.606*** 79% 0.520***

Arts, Design, Entertainment, Sports, and Media 86% 0.661* 79% 0.609**

Healthcare Practitioners and Technical 87% 0.712** 80% 0.694**

Healthcare Support 75% 0.545*** 64% 0.457***

Protective Service 93% 0.727 80% 0.713**

Food Preparation and Serving Related 63% 0.556*** 53% 0.488***

Building and Grounds Cleaning and Maintenance 76% 0.570*** 63% 0.542***

Personal Care and Service 73% 0.516*** 63% 0.483***

Sales and Related 82% 0.734** 75% 0.678***

Office and Administrative Support 84% 0.576*** 76% 0.574***

Farming, Forestry, and Fishing 82% 0.913 78% 1.014

Construction and Extraction 89% 0.914 79% 0.681*

Installation, Repair, and Maintenance 85% 0.627*** 77% 0.613***

Production 82% 0.476*** 75% 0.523***

Transportation and Material Moving 83% 0.723** 73% 0.650***

Not in universeb 94% 2.604* 88% 0.765

Industry (omitted category Agriculture) 76% 72% 

Mining 94% 5.874*** 91% 5.571***

Utilities 94% 3.325*** 84% 1.871*

Construction 89% 2.673*** 81% 2.222**

Manufacturing 88% 2.907*** 82% 2.401***

Wholesale Trade 86% 2.567** 82% 2.330**

Retail Trade 77% 1.770* 69% 1.435

Transportation and Warehousing 87% 1.937* 77% 1.683

Information 88% 2.520** 82% 2.107**

Finance and Insurance 92% 4.287*** 86% 2.868***

Real Estate and Rental and Leasing 77% 1.346 68% 1.120

Professional, Scientific, and Technical 89% 2.555*** 84% 2.059**
Appendix I: Objective, Scope, and Methods

Page 72 GAO-12-699 Women’s Retirement Security 

Dependent variable

Unadjusted 

proportion 

participating in 

a DB or DC plan

Individual 

participates in a 

DB or DC plan

Unadjusted 

proportion 

participating in 

a DC plan

Individual 

participates in a 

DC plan

Management, Administrative and Support 74% 1.511 68% 1.291

Educational Services 92% 2.231** 80% 1.612

Health Care and Social Assistance 83% 1.824* 76% 1.513

Arts, Entertainment, and Recreation 75% 1.253 66% 1.117

Accommodations and Food Services 60% 1.057 55% 1.017

Other Services (Except Public Administration) 81% 1.845* 71% 1.183

Public Administration 96% 4.284*** 85% 1.868*

Work experience (omitted category 

Less than 5 years)

77% 69% 

5 to 9 years 85% 1.150** 77% 1.185**

10 to 15 years 89% 1.250*** 82% 1.305***

More than 15 years 91% 1.195** 84% 1.250***

Union status (omitted category not in a union) 85% 

In a union 93% 1.579*** 80% 0.980

Self-employment status 91% 1.020 85% 0.860

Number of employees at current place of employment 

(omitted category Under 25 employees)

83% 79% 

25 to 100 employees 82% 0.916 77% 0.878

100+ employees 87% 1.172* 79% 0.936

Years of tenure at current job 1.084*** 1.036***

Tenure categories 

Less than 5 years 77% 69% 

5 to 9 years 87% 80% 

10 to 15 years 92% 85% 

More than 15 years 96% 87% 

Number of observations 21,494 17,067

Source: GAO analysis of SIPP data.

*Indicates that the variable is statistically significant at the 90 percent level. 

**Indicates that the variable is statistically significant at the 95 percent level. 

***Indicates that the variable is statistically significant at the 99 percent level. 

a

Part-time status is defined as working 35 hours or less per week during the reference period. 

b

The category “Not in universe” includes self-employed individuals. 
Appendix I: Objective, Scope, and Methods

Page 73 GAO-12-699 Women’s Retirement Security 

To compute median incomes and income composition for men and women 

in different demographic groups, we used information from the core 

questionnaire of the SIPP data (as described above). We used the last 

month of the 4-month reporting period (within each “wave”) with the 

assumption that individuals will more accurately recollect income from the 

most recent month than income from 4 months ago. To obtain an annual 

income estimate, we multiplied the monthly reported income by 12.73

The poverty rate was computed using a SIPP variable that indicates the 

poverty threshold for an individual’s household. The Census Bureau uses 

a set of money-income thresholds that vary by family size and 

composition to determine who is in poverty. If a family’s total income is 

less than the family’s threshold, then that family and every individual in it 

is considered in poverty. The official poverty thresholds do not vary 

geographically, but they are updated for inflation using Consumer Price 

Index (CPI-U). The official poverty definition uses money income before 

taxes and does not include capital gains or noncash benefits (such as 

public housing, Medicaid, and food stamps).

All of our income composition, median, and poverty level estimates were 

computed at the individual level, using household-level information. In 

other words, median incomes were computed by applying all household 

income to each individual in the household and taking the median across 

all individuals within a certain category (e.g., gender, or gender and race). 

For married individuals, this means that spousal income was included in 

these estimates. Correspondingly, we used SIPP individual-level weights 

to compute our point estimates and, in conjunction with other factors, 

calculate the standard errors of those estimates so that we could 

accurately account for the complex survey design.

The point estimates for household income for married men and married 

women may not be equal for a couple of reasons. First, the criteria for 

including an individual in the sample in our analysis was that he or she 

was 65 or above. While there are more women than men among all 

people over 65 in our sample, among married people over 65 there are 

more men than women.84

 

7

This method might result in overstated estimates from earnings if workers do not work all 

12 months of the year. 

One reason this might occur is due to 

8

These patterns held across all the years we analyzed.

Section 3: Methods 

for Comparing the 

Income of Women and 

Men Age 65 and Over 
Appendix I: Objective, Scope, and Methods 

Page 74 GAO-12-699 Women’s Retirement Security 

demographic patterns of life-expectancy and the ages of marital 

partners.95

Since women typically marry older men, and women typically 

have longer life-expectancies than men, it is not surprising that a sample 

of older individuals will include fewer married women than married men, 

as the spouses of older women are more likely to have died than the 

spouses of older men. For this reason, the sample of married older 

women could differ from the sample of married older men, so their 

household characteristics—including income—may not be the same. 

Further, the difference between the ages of the spouses of married men 

and married women could also result in different estimates of median 

income and income composition. For example, if women tended to be 

married to older men, the income composition of the household might be 

skewed away from earnings and towards Social Security. Conversely, if 

men tended to be married to younger women, a higher share of income 

might come from earnings. 

We estimated the relationship between events that occur later in life and 

income and assets using fixed-effects panel regressions. The main 

advantage of fixed-effects models is that they are designed to isolate the 

effect of the event from all other permanent characteristics of the 

individual. We estimated our models using data from the HRS, which 

follows households over time. Our analysis focuses on life events that 

occur after age 50, as the HRS follows individuals age 51 and over. 

Prior to analyzing the effect of the life events on assets and income, we 

first estimated the differences in the frequency of life events by gender. 

We estimated these differences in two ways. First, we estimated the 

proportion of women and men that had a life event across all the periods 

(e.g., proportion that were divorced). Second, we estimated the proportion 

of women and men that had that life event change between two periods 

 9

It is also possible that the survey response rate was higher for married men than for 

married women. 

Section 4: Methods 

for Analyzing the 

Effects of Events 

Occurring Later in 

Life on Women’s and 

Men’s Household 

Income and Assets 

Descriptive Analysis of the 

Frequency of Life Events 

by Gender 
Appendix I: Objective, Scope, and Methods

Page 75 GAO-12-699 Women’s Retirement Security 

of observation (e.g., proportion that became divorced between period 1 

and period 2).

Table 19 uses the first method and presents some descriptive statistics 

on the women and men in our sample. Specifically, it shows the average 

values of characteristics for different ages for women and men.

• Real assets and real income. At ages 51 to 64 women and men have 

similar levels of assets. However, after age 65, men’s average level of 

household assets becomes larger than the average level for women. 

Men’s average levels of household income are higher than women’s 

at every age level.

• Marital status. The rates of marriage and widowhood are relatively 

comparable between women and men before age 65. For example, 6 

percent of women and 1 percent of men younger than age 65 were 

widowed. However, at older ages, more women were estimated to be 

widowed than men.

• Poor health. Individuals were classified as being in poor health based 

on a survey question of self-reported health, which asked the 

individual to rate his or her health on a scale from 1 to 5, where 1 is 

excellent and 5 is poor. An answer of “fair” or “poor” was classified as 

being in poor health. As table 17 shows, rates of poor health were 

comparable between women and men at all age groups.

• Unemployment. This variable captures the percentage of individuals 

that responded to a labor force question as being “unemployed”. It is 

important to note that this is not equivalent to an unemployment 

rate—as individuals classified as not in the labor force were included 

in the denominator. Women and men were equally likely to report 

being unemployed.

• Helping parents financially or with daily activities. These variables 

capture the percentage of households that provided financial help or 

assistance with basic daily activities to either the parents of the 

respondent or spouse. Again, it appears that these rates were 

comparable for women and men.
Appendix I: Objective, Scope, and Methods

Page 76 GAO-12-699 Women’s Retirement Security 

Table 17: Descriptive Statistics of Women and Men in the HRS by Age

Age Estimate 

Standard 

error

Lower bound 

of 95 percent 

confidence 

interval

Upper bound 

of 95 percent 

confidence 

interval

Error over 

estimate

Women

Mean real household assets Under age 51 $446,436 $18,911 $409,372 $483,500 4.24%

Ages 51-64 $537,262 $9,039 $519,546 $554,978 1.68%

Ages 65-84 $522,190 $6,020 $510,391 $533,989 1.15%

Ages 85-99 $359,269 $12,341 $335,071 $383,447 3.44%

Mean real household income Under age 51 $128,325 $6,899 $114,803 $141,847 5.38%

Ages 51-64 $98,116 $1,185 $95,794 $100,438 1.21%

Ages 65-84 $55,014 $348 $54,332 $55,696 0.63%

Ages 85-99 $32,728 $746 $31,275 $34,201 2.28%

Percent married Under age 51 87% 0.46% 86% 88% 0.52%

Ages 51-64 78% 0.19% 78% 78% 0.24%

Ages 65-84 64% 0.20% 63% 64% 0.32%

Ages 85-99 23% 0.48% 22% 24% 2.05%

Percent divorced or separated Under age 51 6% 0.33% 5% 6% 5.67%

Ages 51-64 12% 0.16% 12% 13% 1.27%

Ages 65-84 8% 0.12% 7% 8% 1.55%

Ages 85-99 4% 0.23% 4% 5% 5.71%

Percent widowed Under age 51 1% 0.11% 0% 1% 16.19%

Ages 51-64 6% 0.10% 6% 6% 1.74%

Ages 65-84 26% 0.19% 26% 26% 0.72%

Ages 85-99 70% 0.53% 69% 71% 0.76%

Percent in poor health Under age 51 15% 0.45% 14% 16% 3.01%

Ages 51-64 21% 0.18% 21% 21% 0.87%

Ages 65-84 28% 0.19% 28% 29% 0.66%

Ages 85-99 40% 0.57% 39% 41% 1.41%

Percent unemployed Under age 51 3% 0.22% 3% 3% 7.34%

Ages 51-64 2% 0.06% 2% 2% 3.48%

Ages 65-84 0.1% 0.01% 0% 0% 13.11%

Ages 85-99 0% 0.01% 0% 0% 100.00%

Percent who helped their parents 

financially

Under age 51 16% 0.48% 15% 17% 3.00%

Ages 51-64 11% 0.15% 11% 11% 1.33%

Ages 65-84 2% 0.06% 2% 2% 3.06%

Ages 85-99 0.1% 0.03% 0% 0% 48.61%

Percent who helped their parents with 

daily activities

Under age 51 8% 0.34% 7% 8% 4.56%

Ages 51-64 9% 0.13% 9% 9% 1.51%

Ages 65-84 3% 0.07% 2% 3% 2.70%

Ages 85-99 0.1% 0.03% 0% 0% 52.68%
Appendix I: Objective, Scope, and Methods

Page 77 GAO-12-699 Women’s Retirement Security 

Age Estimate 

Standard 

error

Lower bound 

of 95 percent 

confidence 

interval

Upper bound 

of 95 percent 

confidence 

interval

Error over 

estimate

Men

Mean real household assets Under age 51 $369,106 $19,9401 $330,023 $408,189 5.40%

Ages 51-64 $540,761 $9,581 $521,982 $559,541 1.77%

Ages 65-84 $638,166 $8,352 $621,796 $654,537 1.31%

Ages 85-99 $528,611 $17,682 $493,955 $563,268 3.35%

Mean real household income Under age 51 $107,801 $3,371 $101,194 $114,409 3.13%

Ages 51-64 $112,785 $1,726 $109,402 $116,168 1.53%

Ages 65-84 $72,767 $1,718 $69,400 $76,133 2.36%

Ages 85-99 $48,073 $1,023 $46,068 $50,078 2.13%

Percent married Under age 51 76% 1.25% 74% 79% 1.63%

Ages 51-64 83% 0.20% 83% 84% 0.24%

Ages 65-84 85% 0.17% 85% 85% 0.19%

Ages 85-99 71% 0.62% 70% 72% 0.87%

Percent Divorced or Separated Under age 51 9% 0.85% 7% 11% 9.61%

Ages 51-64 10% 0.17% 10% 11% 1.60%

Ages 65-84 6% 0.11% 5% 6% 2.02%

Ages 85-99 2% 0.21% 2% 3% 8.62%

Percent widowed Under age 51 0.1% 0.10% 0% 0% 70.66%

Ages 51-64 1% 0.06% 1% 2% 4.24%

Ages 65-84 7% 0.11% 6% 7% 1.66%

Ages 85-99 24% 0.59% 23% 26% 2.41%

Percent in poor health Under age 51 18% 1.11% 15% 20% 6.34%

Ages 51-64 20% 0.20% 20% 21% 0.98%

Ages 65-84 28% 0.19% 28% 29% 0.68%

Ages 85-99 40% 0.66% 39% 41% 1.65%

Percent unemployed Under age 51 3% 0.49% 2% 4% 15.70%

Ages 51-64 2% 0.07% 2% 2% 3.58%

Ages 65-84 0.2% 0.02% 0% 0% 9.73%

Ages 85-99 0% 0.00% 0% 0% . 

Percent who helped their parents 

financially

Under age 51 17% 1.14% 15% 20% 6.56%

Ages 51-64 13% 0.17% 13% 13% 1.34%

Ages 65-84 4% 0.09% 4% 4% 2.26%

Ages 85-99 0.2% 0.06% 0% 0% 28.54%

Percent who helped their parents with 

daily activities

Under age 51 10% 0.91% 8% 12% 9.17%

Ages 51-64 9% 0.14% 8% 9% 1.67%

Ages 65-84 4% 0.09% 4% 4% 2.27%

Ages 85-99 0.3% 0.10% 0% 1% 28.65%

Source: GAO analysis of HRS data.
Appendix I: Objective, Scope, and Methods

Page 78 GAO-12-699 Women’s Retirement Security 

Table 18 uses the second method to show the proportion of women and 

men that had a life event status change during the period of analysis. As 

table 18 shows:

• Divorce/separation. During the period in which both members of the 

household are less than 65, less than 1 percent of men experienced 

divorce or separation between any of the two waves. For women, the 

proportion was negative – indicating that more women went from 

divorced or separated to married than from married to divorced or 

separated.

• Widowhood. During the earlier period, about 1 percent of women 

became widowed between any of the two waves. This proportion 

increased to more than 2 percent as the household aged and was 

twice the rate for men.

• Decline into poor health. The rate of health decline was similar for 

women and men. On average, approximately 2 percent of women and 

men reported a decline in health from one period to another.

• Unemployment. Very few women and men reported a change to and 

from unemployment in our data.

• Helping parents financially or with daily activities. The proportion of 

women’s and men’s households providing personal or financial 

assistance fell as the household aged. This may be because older 

households were less likely to have living parents requiring 

assistance.

• Percent change in real assets. In the earlier period, assets for women 

and men increased at a rate of about 6 percent per 2-year period. 

Alternatively, the rate of asset growth became negative as the 

household aged.

• Percent change in real income. In both younger and older 

households, incomes fell at a rate of approximately 5 percent per 2-

year period, on average.
Appendix I: Objective, Scope, and Methods

Page 79 GAO-12-699 Women’s Retirement Security 

Table 18: Proportion of Individuals Changing Status between Observations

Household type Estimate 

Standard 

error

Lower bound 

of 95 percent 

confidence 

interval

Upper bound 

of 95 percent 

confidence 

interval

Error over 

estimate

Women

Divorced or separated Households where everyone is 

age 64 or younger

-0.0022 0.0008 -0.0038 -0.0007 (35.40%)

Households where at least one 

person is 65 or over

-0.0011 0.0005 -0.002 -0.0001 (46.32%)

All households -0.0016 0.0005 -0.0025 -0.0007 (28.13%)

Widowhood Households where everyone is 

age 64 or younger

0.0106 0.0007 0.0094 0.0119 6.13%

Households where at least one 

person is 65 or over

0.0237 0.0007 0.0223 0.0251 3.05%

All households 0.0177 0.0005 0.0168 0.0187 2.79%

Decline in health Households where everyone is 

age 64 or younger

0.0128 0.0019 0.009 0.0165 14.93%

Households where at least one 

person is 65 or over

0.026 0.0016 0.0229 0.0291 6.07%

All households 0.02 0.0012 0.0176 0.0224 6.12%

Unemployment Households where everyone is 

age 64 or younger

-0.0026 0.0011 -0.0047 -0.0005 (40.90%)

Households where at least one 

person is 65 or over

-0.0003 0.0003 -0.001 0.0003 (90.77%)

All households -0.0014 0.0005 -0.0024 -0.0004 (37.43%)

Helped parents financially Households where everyone is 

age 64 or younger

-0.0028 0.0018 -0.0064 0.0008 (65.46%)

Households where at least one 

person is 65 or over

-0.006 0.0008 -0.0074 -0.0045 (12.81%)

All households -0.0045 0.0009 -0.0064 -0.0027 (20.76%)

Helped parents with daily 

activities

Households where everyone is 

age 64 or younger

0.0069 0.0019 0.0031 0.0107 27.91%

Households where at least one 

person is 65 or over

-0.0048 0.0009 -0.0065 -0.0031 (18.32%)

All households 0.0006 0.001 -0.0014 0.0025 177.50%

Real household assets Households where everyone is 

age 64 or younger

0.0533 0.0058 0.0419 0.0646 10.87%

Households where at least one 

person is 65 or over

-0.0361 0.004 -0.0439 -0.0283 (11.09%)

All households 0.0041 0.0034 -0.0026 0.0107 84.14%
Appendix I: Objective, Scope, and Methods

Page 80 GAO-12-699 Women’s Retirement Security 

Household type Estimate 

Standard 

error

Lower bound 

of 95 percent 

confidence 

interval

Upper bound 

of 95 percent 

confidence 

interval

Error over 

estimate

Real household income Households where everyone is 

age 64 or younger

-0.0542 0.0051 -0.0642 -0.0441 (9.448%)

Households where at least one 

person is 65 or over

-0.054 0.0027 -0.0593 -0.0487 (4.992%)

All households -0.0541 0.0028 -0.0595 -0.0487 (5.085%)

Men

Divorced or separated Households where everyone is 

age 64 or younger

0.0007 0.0009 -0.0011 0.0025 126.10%

Households where at least one 

person is 65 or over

0.0009 0.0005 0 0.0019 52.34%

All households 0.0008 0.0005 -0.0002 0.0019 62.40%

Widowhood Households where everyone is 

age 64 or younger

0.003 0.0005 0.002 0.004 17.07%

Households where at least one 

person is 65 or over

0.0133 0.0006 0.0122 0.0145 4.46%

All households 0.0082 0.0004 0.0074 0.009 4.79%

Decline in health Households where everyone is 

age 64 or younger

0.0171 0.0021 0.013 0.0212 12.33%

Households where at least one 

person is 65 or over

0.0348 0.0019 0.0311 0.0384 5.39%

All households 0.026 0.0014 0.0232 0.0288 5.42%

Unemployment Households where everyone is 

age 64 or younger

-0.0002 0.0011 -0.0024 0.002 (513.2%)

Households where at least one 

person is 65 or over

0 0.0003 -0.0007 0.0006 ( 4975%)

All households -0.0001 0.0006 -0.0012 0.001 (520.0%)

Helped parents financially Households where everyone is 

age 64 or younger

-0.0021 0.002 -0.0061 0.0019 (95.72%)

Households where at least one 

person is 65 or over

-0.0068 0.001 -0.0087 -0.0049 (14.16%)

All households -0.0045 0.0011 -0.0067 -0.0023 (24.88%)

Helped parents with daily 

activities

Households where everyone is 

age 64 or younger

0.0061 0.002 0.0022 0.0101 32.59%

Households where at least one 

person is 65 or over

-0.0042 0.0011 -0.0063 -0.0021 (25.43%)

All households 0.0009 0.0011 -0.0013 0.0031 120.90%
Appendix I: Objective, Scope, and Methods

Page 81 GAO-12-699 Women’s Retirement Security 

Household type Estimate 

Standard 

error

Lower bound 

of 95 percent 

confidence 

interval

Upper bound 

of 95 percent 

confidence 

interval

Error over 

estimate

Real household assets Households where everyone is 

age 64 or younger

0.0566 0.0061 0.0447 0.0684 10.70%

Households where at least one 

person is 65 or over

-0.0268 0.0041 -0.0349 -0.0188 (15.37%)

All households 0.0137 0.0036 0.0066 0.0209 26.41%

Real household income Households where everyone is 

age 64 or younger

-0.0486 0.0052 -0.0587 -0.0385 (10.60%)

Households where at least one 

person is 65 or over

-0.0536 0.0031 -0.0596 -0.0475 (5.767%)

All households -0.0511 0.003 -0.057 -0.0453 (5.835%)

Source: GAO analysis of HRS data.

In order to examine whether the effects of certain events occurring later in 

life differ by gender, we used fixed-effects regression models. For 

example, we estimated how changes in health lead to changes in 

household assets and income. Researchers use the fixed-effects method 

because much of the differences in income and wealth between 

households are consistent over time (as poorer households tend to stay 

poor and richer households tend to stay rich). The fixed-effects method 

sweeps away these “time invariant” differences, thus better isolating the 

effect of health or other life events from other aspects of households that 

could explain differences.106

 10In addition to the fixed-effects analysis, we also developed “cross-section” regression 

models. In these models, we attempted to control for a set of demographic and other 

variables, such as education and age that could be correlated with life events, household 

assets, and household income. A challenge to this approach is that many factors that 

affect assets and income are unobserved, and lead to mistaken conclusions. For example, 

if an individual earns a low wage, that may be connected with poor health and the 

accumulation of assets. So, while the researcher is attempting to estimate the effect of 

health on income, what is actually measured is the effect of income on health. In general, 

in our cross-section models, we found that effects were larger in magnitude than in the 

fixed-effects models, but these models were not as good a fit to the data as the fixedeffects models.

Estimating the Effects of 

Events Occurring Later in 

Life on Assets and Income
Appendix I: Objective, Scope, and Methods

Page 82 GAO-12-699 Women’s Retirement Security 

Specifically, we estimated variations of the following equation, separately 

by gender:

(1) Log (Household Assets or Income) = αi + αt + β*(poor health) + χ

*(marital status) + δ*(other control variables)

Where, αi and αt indicate fixed effects for the individual and wave. β is the 

effect of poor health and δ and χ are the effect of other control variables 

and marital status.117

By including a dummy variable for each wave, we 

attempted to control for all national-level changes that could have affected 

assets and income, and also have been associated with the life events. 

Therefore, β can be interpreted as the effect of poor health, measured as 

the percent difference in average assets between periods where an 

individual reports poor versus not-poor health. Due to the additional 

controls, this average percent difference is measured relative to the 

changes over time, and also relative to the other time-variant measures 

captured, such as changes in marital status.128

However, while some of the life-events are likely associated with the 

passage of time, the regression does not assume that relationship. For 

example, if an individual switches from poor health to good health, the 

fixed-effects regression will also use those transitions to estimate the size 

of the effect. Similarly, the fixed-effects regression will also use transitions 

from married to widowed, as well as widowed to married, to estimate the 

effect of widowhood.

As is common among all regressions, a limitation of the fixed-effects 

method is that some important variable could be omitted from the model. 

While the fixed effect controls for all time-invariant attributes, there is still 

 11Other control variables that we included were age (measured as date of wave minus 

birth year), race and education (categorical), cohort of HRS survey, Census region, region 

of birth (12 categories, including non-U.S.). In general, in the cross-section models, we 

found that education was positively related to assets and income, while minority status 

was negatively related. With some slight variation, we based our choice of control 

variables on Coile and Milligan. (See Courtney Coile and Kevin Milligan, “How Household 

Portfolios Evolve After Retirement: The Effect of Aging and Health Shocks,” The Review 

of Income and Wealth, vol. 55 no. 2 (Malden, MA: June 2009)).

12In order to estimate effects in terms of percents, we estimated the effects on the log of 

assets or income. In addition, we transformed the coefficients to more closely approximate 

percent changes by taking the exponent of the estimated coefficient and subtracting 1. 

Regression variables were weighted by household weights. 
Appendix I: Objective, Scope, and Methods

Page 83 GAO-12-699 Women’s Retirement Security 

the possibility of endogenous relationships. For example, if an individual’s 

health declined because income fell, and not the other way around, that 

bias could affect our findings.

Some of the life events we examined were likely correlated with changes 

in household structure, such as changes in marital status. However, if the 

income of a household falls when an individual leaves, the remaining 

individuals may not be worse off when it comes to resources because the 

household now requires fewer resources to meet its needs. To address 

this, we adjusted the estimated effects by household size; the 

household’s income and assets were scaled by the square root of the 

individuals in the household. The rationale for using the square root is 

because the effect of reducing members is diminishing (changing from 1 

to 2 has a larger effect than going from 9 to 10). In addition, this analysis 

estimated the effect of an individual’s life event on household assets or 

income. We did not attempt to determine to what extent a spouse’s life 

event (for married individuals) may have affected household assets or 

income).

Table 19 contains the effects of the first event we analyzed: divorce. We 

analyzed the effect of divorce on household assets and income, both with 

and without controlling for the number of people in the household. Across 

almost all the groups and specifications, the effect of divorce is to reduce 

assets and income, with larger effects for women than for men. Adjusting 

for household size tended to reduce the magnitude of the effects.

• Effect on assets. Divorce tended to reduce assets for more women 

than men, with comparable sizes of effects for women and men. For 

example, among all households, the decline in assets associated with 

divorce was 41 percent for women and 39 percent for men. When the 

size of the household was adjusted for, the size of the effect declined, 

but was still statistically significant.

• Effect on income. Divorce reduced income for both women and men, 

with larger effects for women than men. For example, among all 

households, the decline in income associated with divorce was 41 

percent for women and 23 percent for men. When household size was 

adjusted for, the size of the effects were much smaller in magnitude.

Divorce
Appendix I: Objective, Scope, and Methods

Page 84 GAO-12-699 Women’s Retirement Security 

Table 19: Divorce Effect on Household Assets and Income

All households

Households where everyone 

is age 64 or younger

Households where at least 

one person is 65 or over

Women Men Women Men Women Men 

Effect on assets

Log point change -0.53 -0.50 -0.54 -0.50 -0.39 -0.38

Standard error (0.022) (0.02) (0.03) (0.03) (0.04) (0.040)

Percent change - 41% -39% - 41% - 39% - 32% - 32%

Effects on assets per household member

Log point change -0.37 -0.32 -0.41 -0.32 -0.18 -0.24

Standard error (0.022) (0.022) (0.03) (0.03) (0.04) (0.04)

Percent change - 31% - 28% - 33% - 28% - 17% - 21%

Effect on income

Log point change -0.52 -0.26 - 0.58 -0.29 -0.49 -0.27

Standard error (0.02) (0.02) (0.03) (0.025) (0.02) (0.025)

Percent change - 41% - 23% - 44% - 25% - 39% - 23%

Effect on income per household member

Log point change -0.37 -0.09 -0.46 -0.12 -0.29 -0.13

Standard error (0.02) (0.02) (0.03) (0.03) (0.020) (0.025)

Percent change - 31% - 9% - 37% -11% - 25% - 12%

Source: GAO analysis of HRS data.

Table 20 contains the results for widowhood. As with divorce, we 

analyzed the effect of widowhood on household assets and income, both 

with and without controlling for the number of people in the household. 

Across almost all the groups and specifications, the effect of widowhood 

is to reduce assets and income, with larger effects for women than for 

men. Adjusting for household size tended to reduce the magnitude of the 

effects.

• Effect on assets. Widowhood reduced assets for both women and 

men, with larger effects for women than men. For example, among all 

households, the decline in assets associated with widowhood was 32 

percent for women and 27 percent for men. However, part of this 

effect seems to be associated with the size of the household. Among 

the households in which at least one member was 65 and over, the 

decline in assets was not significant when household size was 

adjusted for.

Widowhood
Appendix I: Objective, Scope, and Methods

Page 85 GAO-12-699 Women’s Retirement Security 

• Effect on income. Widowhood reduced income for both women and 

men, with larger effects for women than men. For example, among all 

households, the decline in income associated with widowhood was 37 

percent for women and 22 percent for men. Again, part of this effect 

seems to be associated with the size of the household. When 

household size was adjusted for, the size of the effects were much 

smaller in magnitude.

Table 20: Widowhood Effect on Household Assets and Income

All households

Households where 

everyone is age 64 or 

younger

Households where at least 

one person is 65 or over

Women Men Women Men Women Men 

Effect on assets

Log point change -0.39 -0.31 -0.37 -0.26 -0.26 -0.20

Standard error (0.01) (0.02) (0.034) (0.051) (0.02) (0.02)

Percent change -32% -27% -31% -23% -23% -18%

Effect on assets per household member

Log point change -0.19 -0.11 -0.20 -0 .03 -0.02 -0.00

Standard error (0.01) (0.02) (0.03) (0.05) (0.02) (0.02)

Percent change -17% -10% -18% -3% -2% - .3%

Effect on income

Log point change -0.46 -0.25 -0.63 -0.36 -0.43 -0.23

Standard error (0.01) (0.02) (0.03) (0.04) (0.01) (0.01)

Percent change -37% -22% -47% -30% -35% -21%

Effect on income per household member

Log point change -0.27 -0.06 -0.48 -0.17 - 0.20 - 0.04

Standard error (0.01) (0.02) (0.03) (0.04) (0.01) (0.02)

Percent change -23% -6% -38% -16% -18% -4%

Source: GAO analysis of HRS data.

As shown in table 21, unemployment tended to reduce assets and 

income, with comparable effects for women and men. The effects did not 

seem to dissipate when household size was adjusted for.

• Effect on assets. Unemployment reduced assets for both women and 

men, with comparable effects for women and men. For example, 

among all households, the decline in assets associated with 

unemployment was 7 percent for women and 7 percent for men. An 

Unemployment
Appendix I: Objective, Scope, and Methods

Page 86 GAO-12-699 Women’s Retirement Security 

exception to this difference was in cases in which at least one 

member was 65 or over. For those individuals, the decline in 

household assets was only 2 percent for women and 15 percent for 

men.

• Effect on income. Unemployment reduced income for both women 

and men, with comparable effects for women and men. For example, 

among all households, the decline in income associated with 

unemployment was 6 percent for women and 8 percent for men.

Table 21: Unemployment Effect

All households

Households where 

everyone is age 64 or 

younger

Households where at least 

one person is 65 or over

Women Men Women Men Women Men 

Effect on assets

Log point change -0.07 -0.07 -0.09 -0.07 -0.02 -0.15

Standard error (0.02) (0.02) (0.03) (0.03) (0.07) (0.075)

Percent change -7% -7% -9% -7% -2% -14%

Effects on assets per household member

Log point change -0.06 -0 .08 -0.08 -0.08 -0 .03 -0 .16

Standard error (0.02) (0.02) (0.03) (0.03) (0.07) (0.076)

Percent change -6% -8% -8% -8% -3% -15%

Effects on income

Log point change -0.09 -0.07 -0.10 -0.06 -0.13 -0.12

Standard error (0.02) (0.02) (0.02) (0.02) (0.04) (0.05)

Percent change -9% -7% -9% -6% -13% -12%

Effects on income per household member

Log point change -0.09 -0.08 -0.09 -0.07 -0.14 -0.13

Standard error (0.02) (0.02) (0.02) (0.02) (0.04) (0.05)

Percent change -8% -7% -8% -7% -13% -12%

Source: GAO analysis of HRS data.

In general, across the specifications, the effect of a decline into poor 

health tended to reduce assets and income, with comparable effects for 

women and men (see table 22). One notable difference however, were 

the larger estimated effects of men’s poor health on assets, but only in 

the case where both members of the household were less than 65 years 

of age. Specifically, we found that for individuals living in these 

A Decline in Health
Appendix I: Objective, Scope, and Methods

Page 87 GAO-12-699 Women’s Retirement Security 

households, poor health in men was associated with a drop in household 

assets of 13 percent, but 5 percent for women.139

In general, the magnitude of the effect on assets was in the 10 percent 

range for both women and men, and is statistically significant. The effects 

on income are about half that magnitude, but follow the same direction as 

the effects on assets. There is little difference in the effects when the level 

of assets and income are estimated with a correction for the size of the 

household.

Table 22: A Decline in Health’s Effect on Household Assets and Income

All households

Households where everyone 

is age 64 or younger

Households where at least 

one person is 65 or over

Women Men Women Men Women Men 

Effect on assets

Log point change -0.09 -0.10 -0.05 -0.14 -0.06 -0.04

Standard error (0.008) (0.008) (0.01) (0.01) (0.01) (0.01)

Percent change -8% -10% -5% -13% -6% -4%

Effects on assets per household member

Log point change -0.09 -0.11 -0.06 -0.14 -0.06 -0.05

Standard error (0.008) (0.008) (0.01) (0.01) (0.01) (0.01)

Percent change -9% -10% -5% -13% -6% -5%

Effect on income

Log point change -0.04 -0.03 -0.05 -0.03 -0.03 -0.02

Standard error (0.006) (0.006) (0.01) (0.01) (0.01) (0.01)

Percent change -4% -3% -5% -3% -3% -2%

Effect on income per household member

Log point change -0.05 -0.04 -0.05 -0.03 -0.03 -0.02

Standard error (0.006) (0.006) (0.01) (0.01) (0.01) (0.01)

Percent change -5% -4% -5% -3% -3% -2%

Source: GAO analysis of HRS data.

 13We tested this result by using an alternative measure of health: the extent to which there 

are challenges in daily living. In this case, we did not find that men’s health had a larger 

effect.
Appendix I: Objective, Scope, and Methods

Page 88 GAO-12-699 Women’s Retirement Security 

As shown in table 23, the results for either helping parents financially or 

with basic daily activities—eating, dressing, and bathing—were not as 

consistently significantly negative as the other life events. In the fixedeffects regression, the effect of personal assistance did not appear to be 

statistically significant, while the effect of financial assistance tended to be 

significantly positive. It may be that when households have more assets 

or income they are more likely to provide assistance—which could explain 

these findings. There is little difference in the effects when the level of 

assets and income are estimated with a correction for the size of the 

household. To further understand these relationships, we explored the 

characteristics of those helping their parents with the basic daily activities 

of bathing, dressing, and eating. We found that only 2 percent of the 

sample provided both financial help and help with basic daily activities. 

Further, those in the labor force (i.e., working or unemployed and looking 

for work) were more likely to help their parents with basic daily activities 

than those retired or not in the labor force.

Table 23: Effects of Providing Financial Assistance or Physical Care on Household Assets and Income

Helped parents financially

Helped parents with basic daily 

activities

Women Men Women Men 

Effect on assets

Log point change 0.028 0.034 0.0 0.01

Standard error (0.01) (0.01) (0.01) (0.01)

Percent change 3% 3% 1% 1%

Effects on assets per household member

Log point change 0.032 0.038 0.004 0.01

Standard error (0.01) (0.01) (0.01) (0.02)

Percent change 3% 4% 0.4% 1%

Effect on income

Log point change 0.056 0.071 0.016 0.020

Standard error (0.008) (0.008) (0.008) (0.008)

Percent change 6% 7% 2% 2%

Effect on income per household member

Log point change 0.059 0.073 0.013 0.018

Standard error (0.008) (0.008) (0.008) (0.008)

Percent change 6% 8% 1% 2%

Source: GAO analysis of HRS data.

Helping Parents 

Financially or with Daily 

Activities
Appendix II: GAO Contact and Staff 

Acknowledgments

Page 89 GAO-12-699 Women’s Retirement Security 

Charles Jeszeck, (202) 512-7215 or jeszeckc@gao.gov

Michael Collins, Assistant Director; Erin M. Godtland, Senior Economist, 

and Jennifer Gregory, Senior Analyst, led the engagement. In addition, 

James Bennett, Benjamin Bolitzer, David Chrisinger, Cynthia Grant, Jean 

Lee, Grant Mallie, Ashley McCall, Michael Morris, Rhiannon Patterson, 

Mark Ramage, James Rebbe, Douglas Sloane, Jeff Tessin, Shana 

Wallace, and Erin White made valuable contributions. 

Appendix II: GAO Contact and Staff 

Acknowledgments 

GAO Contact

Staff 

Acknowledgments

(131071)
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