Retirement Income Data
Improvements Could Better Support Analysis of Future Retirees' Prospects Gao ID: GAO-03-337 March 21, 2003Future demographic trends include a doubling of the nation's retiree population and only modest labor force growth, leading to concerns about retirement income adequacy for future generations. Credible projections of the effects of policy proposals on federal spending and future retirees' income are necessary. Because adequate data is critical to the analysis of retirement income and wealth, GAO was asked to identify data improvements that experts say are a priority for the study of retirement income and wealth, as well as factors limiting efforts to obtain the needed information.
Experts consulted by GAO cited priorities for improving retirement data that fit into two broad categories: (1) obtaining better data from employers on employee benefits and (2) obtaining better data by linking more individual and household surveys with administrative data (such as employer records, and Social Security earnings history records). Information from employers, such as documents describing the features of their pension plans, would enable analysts to forecast future retirement income of pension holders, based on the specific features of their pension plans and the likely distribution of pension income and wealth for different segments of the population. Linking individual and household surveys with administrative data creates new information, such as the demographic characteristics of employees whose pensions are affected by the formulas that employers use to calculate contributions or pension payments. Analysts attribute the shortcomings in retirement income data primarily to fragmentation of the responsibility for data collection and analysis, the burden of data collection on respondents, and confidentiality considerations that restrict access to these data. Fragmentation of responsibility occurs, in their view, because no single agency has a statutory mandate to collect or to analyze all the data needed to support a more comprehensive study of retirement income and wealth. With regard to respondent burden, some information on pension plans is no longer collected, in part, out of concern that it was an unnecessary burden on the firms having to submit it. Finally, certain kinds of data needed to make projections are not widely available to all analysts because of the confidentiality laws that authorize their collection.
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Report to the Ranking Minority Member, Subcommittee on Employer-
Employee Relations, Committee on Education and the Workforce, House of
Representatives:
United States General Accounting Office:
GAO:
March 2003:
Retirement Income Data:
Improvements Could Better Support Analysis of Future Retirees‘
Prospects:
GAO-03-337:
GAO Highlights:
Highlights of GAO-03-337, a report to Ranking Minority Member,
Subcommittee on Employer-Employee Relations, Committee on Education
and the Workforce, House of Representatives
Why GAO Did This Study:
Future demographic trends include a doubling of the nation‘s retiree
population and only modest labor force growth, leading to concerns
about retirement income adequacy for future generations. Credible
projections of the effects of policy proposals on federal spending and
future retirees‘ income are necessary. Because adequate data is
critical to the analysis of retirement income and wealth, GAO was
asked to identify data improvements that experts say are a priority
for the study of retirement income and wealth, as well as factors
limiting efforts to obtain the needed information.
What GAO Found:
Experts consulted by GAO cited priorities for improving retirement
data that fit into two broad categories: (1) obtaining better data
from employers on employee benefits and (2) obtaining better data by
linking more individual and household surveys with administrative data
(such as employer records, and Social Security earnings history
records). Information from employers, such as documents describing the
features of their pension plans, would enable analysts to forecast
future retirement income of pension holders, based on the specific
features of their pension plans and the likely distribution of pension
income and wealth for different segments of the population. Linking
individual and household surveys with administrative data creates new
information, such as the demographic characteristics of employees
whose pensions are affected by the formulas that employers use to
calculate contributions or pension payments.
Analysts attribute the shortcomings in retirement income data
primarily to fragmentation of the responsibility for data collection
and analysis, the burden of data collection on respondents, and
confidentiality considerations that restrict access to these data.
Fragmentation of responsibility occurs, in their view, because no
single agency has a statutory mandate to collect or to analyze all the
data needed to support a more comprehensive study of retirement income
and wealth. With regard to respondent burden, some information on
pension plans is no longer collected, in part, out of concern that it
was an unnecessary burden on the firms having to submit it. Finally,
certain kinds of data needed to make projections are not widely
available to all analysts because of the confidentiality laws that
authorize their collection.
What GAO Recommends:
The Congress should consider directing Labor to obtain from plan
administrators electronic filings of SPDs and summaries of material
modifications and make them publicly available. In addition, GAO
recommends that the Secretary of Labor
*direct the Bureau of Labor Statistics to prepare a plan to improve
data for analyzing retirement income and wealth in coordination with
other agencies and *obtain copies of summary plan descriptions in
cases where analysts working on federally-conducted or sponsored
research seek them for statistical purposes.
GAO recommends that the Internal Revenue Service publish tabulations
of information filed in IRS forms 5498, 1099R and W-2.
www.gao.gov/cgi-bin/getrpt?GAO-03-337
To view the full report, including the scope and methodology, click on
the link above. For more information, contact Barbara Bovbjerg (202)
512-7215 or Robert Parker (202) 512-9750.
Contents:
Letter:
Results in Brief:
Background:
Experts Cited Need for Better Data and Better Data Set Linkage:
Many Factors Limit Needed Retirement Income and Wealth Data:
Conclusions:
Matter for Congressional Consideration:
Recommendations:
Agency Comments:
Appendix I: Scope and Methodology:
Appendix II: Status of Recommendations from the 1997 Report
of the Panel on Retirement Income Modeling:
Appendix III: GAO Survey on Retirement Income Data Needs and
List of Respondents:
List of Respondents to the Survey:
Appendix IV: Views of GAO‘s Expert Panel on Retirement Income Data
Needs:
Need for Better Matched Data:
More Employer Information Needed on the Value and Provisions of
Employer Provided Pensions:
Appendix V: Characteristics of Selected Surveys for Analysis of
Retirement Income and Wealth:
Appendix VI: Comments from the Department of Commerce:
Appendix VII: Comments from the Department of Labor:
Appendix VIII: GAO Contacts and Staff Acknowledgments:
GAO Contacts:
Staff Acknowledgments:
Tables:
Table 1: Examples of Federal Agency Retirement Income-Related Data
Collection:
Table 2: Federal Outlays for Selected Longitudinal Studies--Fiscal
Years 1997-2001:
Table 3: Summary Table of Selected Survey Data Sources:
Abbreviations:
BLS: Bureau of Labor Statistics
CPS: Current Population Survey:
EBRI: Employee Benefit Research Institute
EBSA: Employee Benefits Security Administration
ERISA: Employee Retirement Income Security Act of 1974
HRS: Health and Retirement Study:
IRA: Individual Retirement Account
IRS: Internal Revenue Service:
OMB: Office of Management and Budget
PBGC: Pension Benefit Guaranty Corporation
PSID: Panel Study of Income Dynamics
SCF: Survey of Consumer Finances:
SIPP: Survey of Income and Program Participation
SPD: summary plan description
SOI: Statistics of Income:
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United States General Accounting Office:
Washington, DC 20548:
March 21, 2003:
The Honorable Robert E. Andrews
Ranking Minority Member
Subcommittee on Employer-Employee Relations
Committee on Education and the Workforce
House of Representatives:
Dear Mr. Andrews:
The nation‘s retiree population will double within the next few
decades, while at the same time the labor force will grow only
modestly, potentially stressing the national economy. In light of these
demographic trends, policymakers have been moved to consider how the
future economy can support the large retiree population, and whether
retirement income levels will be adequate in the future.[Footnote 1] To
increase their understanding about issues related to retirement,
policymakers need credible projections of the effects of their
proposals on federal spending and on future retirees‘ income. Analysts
will be better able to develop accurate projections if they have
relevant, reliable, and timely data on patterns of saving and actual
retirement income and wealth.
Because adequate data will be so important to analysis of retirement
income and wealth for future retirees, including people in the ’baby
boom“ generation and later generations, you asked us to assess the
adequacy of data available for making such projections. In response to
your request, as agreed, we identified (1) data improvements that
experts say are a priority for the study of retirement income and
wealth and (2) factors limiting efforts to obtain the needed
information.
To address these topics, we conducted a Web based survey of nearly 200
individuals with retirement income expertise, held a daylong meeting
with a diverse group of 11 retirement income experts, and interviewed
retirement income analysts and officials of the Departments of Labor
(Labor), Commerce, and Treasury. We conducted our work between February
and December 2002 in accordance with generally accepted government
auditing standards. (For more details about our scope and methodology,
see app. I.):
Results in Brief:
Acknowledging that there is a great deal of missing data related to
retirement income, experts we consulted cited priorities for data
improvements that fit into two broad categories: (1) obtaining better
data from employers on employee benefits and (2) obtaining better data
by linking more individual and household surveys with administrative
data (such as employer records and Social Security earnings history
records). The kinds of information from employers that analysts
indicated are missing included the documents employers provide to
employees describing the features of their pension plans, such as the
plan‘s normal retirement age and reductions for early retirement. This
information would help analysts to forecast future retirement income of
pension holders, based on the specific features of their pension plans
and the likely distribution of pension income and wealth for different
segments of the population. With regard to linking datasets, currently
linkages between individual and household survey data and
administrative data are limited. Linking data creates new information
by matching survey data about individuals (using names, or taxpayer
identification numbers) to a second set of records, such as
administrative records on pension plans. There is inadequate
information, for example, about which demographic groups have different
types of pensions. Thus, while analysts may know the prevalence of
certain formulas used to calculate employer contributions or pension
payments, they generally lack reliable information about the
demographic characteristics of the employees whose pensions are
affected by these formulas.
Analysts attribute the shortcomings in retirement income data primarily
to fragmentation of the responsibility for data collection and
analysis, the burden of data collection on respondents, and
confidentiality considerations that restrict access to these data.
Fragmentation of responsibility occurs, in their view, because no
single agency has a statutory mandate to collect or to analyze all the
data needed to support a more comprehensive study of retirement income
and wealth. For example, while the Department of Labor‘s Bureau of
Labor Statistics (BLS) collects data on pensions, and the Census Bureau
collects data on individuals‘ and households‘ income, neither agency is
responsible for all of the data needed to project future retirement
income and wealth. Other agencies such as the Department of Labor‘s
Employee Benefits Security Administration (EBSA)--formerly called the
Pension Welfare and Benefits Administration--and the Social Security
Administration also collect data, but the extent to which these
agencies share data is limited. With regard to respondent burden, some
information on pension plans is no longer collected out of concern that
it was an unnecessary burden on the firms having to submit it, as well
as concern about the Department of Labor‘s costs for storing the
information. For example, the 1997 Taxpayer Relief Act (P.L. 105-34)
ended the requirement that employers file with the Department of Labor
copies of documents summarizing the features of the pension plans they
offer. Finally, certain kinds of data needed to make projections are
not widely available to all analysts because of the confidentiality
laws that authorize their collection. The Census Bureau and others are
exploring options for expanding access without compromising the
confidentiality of the data. For example, the Census Bureau has
established additional research data centers throughout the country
where approved researchers with approved projects can work with
confidential data and produce statistical summaries that meet strict
disclosure requirements.
We are offering a Matter for Congressional Consideration and making
recommendations to the Department of Labor and the Department of the
Treasury that seek cost-effective approaches to help fill some of the
data needs while taking into account respondent concerns about
increased reporting burdens and agency concerns about maintaining
confidentiality.
We provided a draft of this report to the Departments of Commerce,
Labor, the Treasury and the Internal Revenue Service (IRS). We received
technical comments from all four and incorporated their suggestions as
appropriate. We also provided a draft of this report to the 11 members
of our expert panel and modified the draft as appropriate in response
to their comments. Commerce had no major comments on the report (see
app. VI). Labor agreed on the need for access to accurate data but did
not agree with our recommendations to the Secretary of Labor (see app.
VII). Labor indicated that it did not have authority to require that
summary plan descriptions (SPD) be filed electronically. Accordingly,
we changed one of our draft recommendations to the Secretary of Labor
into a Matter for Congressional Consideration. Labor also had concerns
about the burdens our recommendations might pose. Although we
acknowledge their concerns, nonetheless, we conclude that the need for
improvements in retirement income data outweighs the likely costs
involved. We therefore continue to address two recommendations to the
Secretary of Labor and one to the IRS.
Background:
Forecasting future retirement income needs--and how well they will be
met through current savings, pension plans, and Social Security
benefits--is a challenge, in part because of the many variables
involved. Although Social Security is the primary source of income for
many retirees, private pensions and other sources of income serve as
key supplements and help retirees receive adequate income in
retirement. In order to measure a person‘s current income and wealth,
information is needed about many items, including the person‘s wage and
nonwage income, home equity, pension, and nonfinancial assets and
liabilities. In addition, to project a person‘s future income and
wealth, researchers need information such as a person‘s earnings
history, whether he or she chooses to participate in the pension plan
offered by an employer, and how the person might respond to changing
incentives for saving and investing for retirement. Other factors
include whether the person chooses to accumulate savings apart from
retirement plans, how long the person remains in one job, whether the
person decides to cash out his or her retirement plan when changing
employment, level of indebtedness, and the availability of health
insurance during retirement. In addition, individuals‘ retirement funds
depend on employer decisions, such as what kinds of pension plans and
the availability and cost of retiree medical and long-term care
insurance. To make estimates for people in different demographic
groups, not just aggregate estimates for entire generations, analysts
need to know how these factors vary based on individuals‘ demographic
characteristics. Estimates of future income adequacy also rely heavily
on projections of macroeconomic factors, including estimates of future
rates of inflation, and rates of return on stocks and bonds and changes
in home values. Furthermore, retirement income data needs keep
changing, in part, as a result of trends in the pension industry and
the labor force. The pension industry provides a growing variety of
pension products with different features and legal structures.
Forecasting pension income becomes more complicated with, for example,
firms‘ converting of traditional pension plans into new pension hybrid
products such as cash balance plans. These plans combine features of
both defined benefit[Footnote 2] and defined contribution[Footnote 3]
plans, which adds to their complexity.[Footnote 4] Changes in
employment patterns, such as the decrease in the length of time
employees spend in a single job, will also have an effect on pension
income.
The federal government collects a great deal of data pertinent to the
analysis of retirement income and wealth. Surveys of individuals and
households collected by or sponsored by the Census Bureau, the Federal
Reserve Board, BLS, and the National Institute on Aging are important
sources of information. Similarly, surveys of businesses by BLS provide
information about the pension and health care benefits firms offer
their employees. A great deal more information pertinent to the
analysis of retirement income and wealth is contained in the
administrative documents that businesses and individuals must provide
to state and federal agencies that administer governmental programs and
enforce regulations. For example, many private employers must file, on
a Form 5500, annual reports concerning their employee benefit plans for
the IRS, Labor‘s EBSA, and the Pension Benefit Guaranty Corporation
(PBGC).[Footnote 5] Many pieces of information concerning pensions and
retirement savings are also provided on forms that employers and
financial institutions file with the IRS.
In addition to the federal government‘s collection of retirement income
related data, several private entities also conduct surveys that
provide useful information concerning retirement income. For example,
the Health and Retirement Study (HRS) conducted by the University of
Michigan‘s Institute for Social Research, is a longitudinal survey of
adults over the age of 50. The information collected includes such
topics as respondents‘ physical and mental health, insurance coverage,
financial status, family support systems, labor market status, and
retirement planning. The HRS is supported primarily by the National
Institute on Aging, with additional funding over the years from the
Social Security Administration, Labor‘s EBSA, the Department of Health
and Human Services Assistant Secretary for Planning and Evaluation, and
the state of Florida. Also, private benefit consulting firms and
organizations, such as the Employee Benefit Research Institute (EBRI),
conduct surveys of employers concerning pension plans.
Retirement income analysts currently use available retirement income
and wealth data to project future retirement income needs. For example,
the Social Security Administration has developed a forecasting model,
Modeling Income in the Near Term (MINT), to project demographic
changes, retirement income, and Social Security benefits generally for
persons born between 1931 and 1960. The Congressional Budget Office has
also developed the Congressional Budget Office Long-Term model to study
the range of possible outcomes for the balance of the Social Security
trust fund.[Footnote 6]
In a 1997 report, the National Research Council‘s Panel on Retirement
Income Modeling reviewed the available sources of data on retirement
income and recommended several improvements.[Footnote 7] While the
individual recommendations covered various topics, many involved the
collection of additional information, as well as the establishment of
an interagency task force for coordination purposes. While some of the
panel‘s recommendations have been adopted, others have not. For
example, as the panel recommended, the federal government has continued
to support longitudinal studies. However, Labor has not acted on the
panel‘s recommendation that it establish an interagency task force on
employer data to plan collection of retirement income related data. In
some respects, less data are available than was the case when the
report was prepared. (See app. II for details.):
Much of the data needed to assess retirement income and wealth are
subject to federal laws protecting the confidentiality of information
reported to the federal government. Laws limit the access to this
information. Without access, it is not possible to pull together data
from different sources to provide more complete information about
individuals or organizations. The success of data gathering efforts by
federal agencies and others relies on widespread trust that personal
data will be kept confidential, protected from disclosure, and used
only for specified purposes.[Footnote 8]
Experts Cited Need for Better Data and Better Data Set Linkage:
Experts we consulted cited priorities for improving retirement data
that fit into two broad categories: (1) obtaining better data from
employers on employee benefits and (2) obtaining better data from
individual and household surveys by linking them with administrative
data. The kinds of information concerning employers and employer-
sponsored benefit plans that analysts sought included the features of
their pension plans, such as minimum and maximum allowable
contributions, or formulas for calculating benefits from defined
benefit pension plans. Retirement income experts believed these data
would allow them to more accurately measure or project retirement
income and wealth now and in the future and estimate effects of
potential retirement policy changes. Linkage of data from different
sources creates new information by providing data about individuals
matched to other data about the individuals from a second set of
records, such as administrative records on pension plans. Analysts are
able to use general data on some employer-sponsored pension plans and
data on households and individuals. However, without linkages between
these types of data it is difficult to obtain information about
retirement offerings for specific households. As a result, analysis of
pension offerings by demographic groups is limited.
Experts Place Priority on Improvement in Data from Employers:
Most of the experts responding to our survey on retirement income data
needs assigned better retirement income-related data from employers to
the high or highest priority category. (See app. III for results of the
survey.) In addition, the experts asserted that employers, rather than
employees, could provide more accurate information about pension plans.
Participants on our expert panel expressed interest in improving access
to the mandatory pension plan disclosure reports, such as summary plan
descriptions (SPD). (See app. IV for a summary of the expert panel‘s
discussion.) Employers must provide these documents to employees who
participate in a plan (such as a pension plan) in order to provide them
with an understandably written description of their rights and benefits
under the plan. To improve projections of future retirement income and
the effects of policy options, panelists also expressed interest in
data provided to the IRS on forms such as 1099-R and 5498.[Footnote 9]
Employer Documents Are an Important Source of Information on Retirement
Plans:
Analysts responding to our survey, reported as their highest or high
priority, the kind of information reported on some employer-submitted
forms. Because pension plans vary widely, panel experts said they
especially needed details of employee pension plans, such as the type
of pension plan (defined benefit, defined contribution, or other),
eligibility for participation and benefits, the plan‘s early retirement
age, sources of contributions to the plan, and the method by which the
amount of the contributions and benefits are calculated. Panelists
believed this information would help analysts project future private
pension benefits and the effects of proposed policy changes. Panel
members also recommended that such pension data be obtained directly
from employers, citing the need for accuracy as an important factor.
Inconsistencies have been found between employee and employer provided
data. One study, for example, compared employees‘ reports concerning
the employer-sponsored pension plans they were participating in, or
that were available to them, with the information about those pension
plans obtained directly from the employers.[Footnote 10] It found
significant discrepancies between the two sets of data, large enough
for the authors to urge a great deal of caution in using the household
survey data for reliable information about the actual characteristics
of employer-sponsored pension plans. For example, among employees whose
employers reported that they were covered by a defined benefit plan,
only 56 percent of the employees thought that they had such a plan.
Likewise, there seemed to be high levels of error in other basic
details about pension plans, such as the eligibility date for early
retirement.
Using employer-submitted forms as a source of information was suggested
as one way to increase the accuracy of pension data. Retirement income
experts agreed that the Form 5500 is an important source of pension
information available in government administrative records.[Footnote
11] Sponsors or administrators of employee benefit plans subject to
ERISA[Footnote 12] must file this form annually. The Form 5500 was
intended, in part, to measure employers‘ compliance with both the
fiduciary and funding provisions laid out in ERISA legislation. The
Form 5500 filed for pension plans contains useful aggregate information
about plans. It provides information about the financial condition of
the plan, annual amounts contributed by participants, and the plan‘s
income on investments. The form also provides information on plan
characteristics, such as plan type (defined benefit or defined
contribution), method of funding, and numbers of employees,
participants, and employees who are excluded from the plan for various
reasons.
While the Form 5500 provides aggregate data about plans, it does not
contain information useful for calculating individual‘s contributions
or benefits. For example, it does not provide information on formulas
for calculating employer contributions to plans or for calculating
retirees‘ benefits.[Footnote 13] In addition, it does not provide any
data for pension plans outside the reporting requirements of ERISA,
such as those for governmental employers, certain nonqualified plans
for highly compensated people,[Footnote 14] simplified employee pension
(SEP) [Footnote 15] plans, or savings incentive match plans for
employees (SIMPLE).[Footnote 16] Reporting and processing requirements
also mean that data from Form 5500 reports may not be available to
researchers for up to 3 years after the plan year. Finally, Labor
officials find frequent errors in information submitted on the
forms.[Footnote 17]
Partly because of the limitations surrounding the Form 5500s,
retirement income experts are increasingly interested in access to the
SPDs, which are summaries of employers‘ pension offerings. The
requirements of ERISA call for SPDs to include specific details about
employee pension plans, including the type of pension plan, eligibility
requirements, normal retirement age, vesting[Footnote 18] and
disqualification rules, sources of contributions to the plan, and
method by which the amount of the contribution is calculated. ERISA
required employers to file SPDs and documents, called ’summaries of
material modifications,“ describing changes to the plans with Labor.
These were made publicly available at Labor‘s public disclosure room in
Washington, D.C. The SPDs served many purposes: (1) they were a source
of information to employees about the offerings included in their own
pension plans, (2) they were a means of informing Labor about what
types of plans a company was offering so Labor could perform monitoring
and enforcement, (3) they also provided researchers with a high level
of detail on pension offerings. EBSA officials noted, however, that the
SPDs received by Labor were often out of date and that it was costly to
store them. In 1993 we agreed that Labor should stop collecting paper
copies of SPDs, and instead provide access to electronic
versions.[Footnote 19]
Labor no longer collects SPDs and public access to them has become much
more limited in the last 5 years. The Taxpayer Relief Act of 1997 (P.L.
105-34) amended ERISA so that employers no longer need to file SPDs
with Labor. Instead, Labor was authorized to request SPDs from
employers as needed, and uses this authority primarily to assist plan
participants and beneficiaries in obtaining copies, though it has
authority to request them for other purposes. However, since the law,
Labor no longer requires that SPDs be filed, and SPDs prepared after
the Taxpayer Relief Act are not publicly accessible, either for the
general public or for researchers looking to model pension behavior.
Tax Information Returns Are a Source of Information on Retirement
Plans:
Our expert panelists noted that some of the pension details they need
can be found in the administrative data provided by employers and
others to the IRS. In addition to its collection of income tax returns,
the IRS also collects ’information“ returns, such as the W-2, which
contain details of employee information that provides valuable details
relevant to future retirement income, such as wages, tax-deferred
retirement contributions, lump sum distributions, rollovers, and
retirement asset balances. In discussing pension data that the IRS has
access to from its tax forms, experts from our panel reported that
information from the Forms W-2, 5498, or 1099-R could provide important
pension details. These forms provide detail on the extent of
investments in retirement plans, such as the amount of contributions
made to an Individual Retirement Account (IRA) or the amount of money
contributed by the employee to deferred compensation plans.[Footnote
20]
Form W-2 is a valuable source of pension data because it provides
information on whether the employer provides some form of qualified
retirement plan. The W-2 also includes amounts deducted from wages for
contributions to pension plans, as well as codes that provide more
detail on the different kinds of plans to which the contribution was
made, such as whether the plan is a SIMPLE, SEP, or some other kind of
deferred compensation plan. Besides giving more detailed information on
deferred compensation, the W-2 has another advantage in terms of the
pension information it provides: employers are required to submit one
for every employee. This requirement covers all workers for whom
federal income tax or Social Security tax is withheld, including those
who do not earn enough to be required to file individual income tax
returns and those who are not covered by any pension plan.
Form 5498 is a form that financial institutions are required to file
for all participants to report all contributions and the fair market
value of their IRA accounts. It includes valuable pension information,
including IRA contributions; rollover contributions;[Footnote 21] and
SEP, SIMPLE, and Roth IRA contributions.[Footnote 22] Experts from the
panel stated that the pension information from Form 5498 could be
important in tracking an individual‘s retirement income balance with a
specific custodial financial institution because it provides
information on the fair market value of those assets held by the
individual. While it does not give information on whether an employee
who has separated from an employer converts the IRA into another tax
protected IRA or pension account, this information should be reflected
in the employee‘s federal income tax return.
Form 1099-R is another source of information for pension experts, which
could provide additional information on pension resources. Form 1099-R
is a statement filed by trustees concerning distributions to
individuals from pensions, annuities, retirement or Profit-Sharing
Plans, and IRAs. However, in many cases the form does not indicate
whether the distributions are lump-sum distributions or rollovers into
IRAs or other qualified plans.
The IRS makes some tax information publicly available through its
Statistics of Income (SOI) program, which provides numerous tabulations
and articles from its analysis of tax return data. From a sample of
Form 1040s, the SOI currently provides aggregate tabulations of
information, including taxable IRA distributions, deductible payments
to an IRA, payments to a self-employed retirement (Keogh) plan, and
taxable pensions and annuities.[Footnote 23] This information is
provided as a sum total of amounts accrued for the entire U.S.
population that filed income tax returns, and is also broken out in
detail by income level. For example, for the year 2000, the SOI
provides taxable IRA distributions for about 9 million returns, with
distributions totaling about $100 billion. While SOI breaks down these
totals by income brackets, the tables do not provide other useful
pension information such as pension accrual amounts by race or
ethnicity. These demographic characteristics could be added to the data
if individual tax return records were linked to the Census Bureau‘s
detailed household survey records.
The SOI staff are preparing an article on retirement related data
available from the IRS and, in doing so, will make some retirement
related aggregate data, including information from Forms 5498 and W-2,
publicly available for the first time. They told us that they are
considering making this information available as a part of regular SOI
releases, but they currently have no formal plans to do so. The SOI
tabulations being prepared include the fair market value of pension
plans, broken down by 10-year cohorts. Our expert panelists said that
these kinds of aggregate data from IRS forms could help them ensure
that their analyses reflect accurate information about retirement
assets, such as the fair market value of IRA accounts.
Experts Place Priority on Linking Data on Individuals to Administrative
Data:
Given different possible options for improving retirement income data,
retirement experts showed the greatest interest in increasing the
availability of, and expanding researchers‘ access to, data sets on
individuals or households linked to administrative data sets. (For
characteristics of selected survey data sources, see table 3.) Eighty-
one percent of respondents assigned this as a high or highest priority.
Data linkage creates new information by matching data about individuals
(using names or taxpayer identification numbers) to a second set of
records, such as administrative records on pension plans, which provide
additional information. The linked data are then preserved as a new
data set, with personal identification information removed, that can
generate new, fuller information on the population. Linking existing
sources of data can provide detailed information with no additional
respondent burden and at a much lower cost than is associated with
collecting new survey data.
Our expert panelists made several suggestions for linking individual
and household survey data with administrative data sources to help
improve the analysis of retirement income and projections of the
effects of policy changes on future retirement income. For example,
they suggested expanding linkage between the Survey of Income and
Program Participation (SIPP) and administrative data sources.[Footnote
24] SIPP is a survey of households conducted by the Census Bureau
providing wide-ranging demographic information, including different
age cohorts, which makes it an attractive source of information when
linked to administrative records. It provides, for example, information
about benefits households receive from government programs. One
component of this survey deals with retirement and pension plan
coverage, in which several pension and retirement related questions are
asked. However, it lacks definitive information on features of
respondents‘ pension plans. Linking SIPP information to administrative
data sets is a powerful way to expand information about how different
groups will be covered in retirement. For example, linked data sets can
indicate the extent to which the availability of various pension
features differ for people in different age and demographic groups.
Such linkage can also indicate how much knowledge respondents have
about their pension plans and their retirement savings options.
Panelists said that linkage to SPDs, Form 5500 data, and Social
Security earnings and benefit histories would be especially valuable
for projecting retirement income for different demographic groups.
Survey data on individuals have already been linked to administrative
data sources in order to improve retirement income data. The Census
Bureau is already linking SIPP records with administrative data related
to retirement income, including Social Security earnings and benefit
records. However, many potential linkages are hampered by lack of
access to needed administrative data. For example, the University of
Michigan Institute for Social Research has linked information gathered
from HRS survey participants to SPDs gathered either from the employers
or by Labor prior to 1997. Unfortunately, this process was made more
difficult, and the information less satisfactory, because the HRS
researchers could only obtain about 50 percent of the SPDs they were
seeking, in part, because employers chose not to provide the SPDs. HRS
researchers have also experimented with linking respondent surveys to
Social Security earning histories for two-thirds of the respondents who
permitted SSA to provide the records.
Many Factors Limit Needed Retirement Income and Wealth Data:
Experts we consulted believed that data needed for the study of
retirement income are not collected or made available because of
factors that include the fragmentation of data collection
responsibility, the burden of data collection on respondents, and
confidentiality considerations that restrict access. Fragmentation
stems from no single agency having a statutory mandate to collect and
analyze all the data needed to support a more comprehensive study of
retirement income and wealth. Some information is no longer collected
out of concern that it was an unnecessary burden on the firms having to
submit it and because it was only being used to a limited extent by the
government. Finally, certain kinds of data needed to make retirement
income projections are not made available because they contain
information that must by law be carefully protected against
unauthorized disclosure and misuse.
Fragmented Retirement Data Responsibilities Contributes to Data
Shortcomings:
Although many federal agencies are involved in collecting and analyzing
retirement income and wealth data for a variety of different purposes,
no single agency is responsible for these activities. Instead, some
agencies--including the Bureau of the Census, Labor, Federal Reserve
Board, IRS, and SSA--collect data needed for their specific purposes.
For example, the Census Bureau collects retirement income and wealth
information on individuals and households using the Current Population
Survey (CPS) and SIPP. Labor collects data on pensions for both ERISA
enforcement purposes and to track pensions for statistical purposes.
The IRS collects data from individuals and firms for tax enforcement
purposes. Table 1 shows the major agencies involved in retirement
income and wealth data collection, the purpose of their data
collection, and a brief description of the information collected. None
of these agencies is charged with coordinating all retirement income
data collection efforts or planning improvements needed in data
collection and analysis.
Table 1: Examples of Federal Agency Retirement Income-Related Data
Collection:
Agency: Census Bureau; (Department of Commerce); Data collection
program: Survey of Income and Program Participation (SIPP); Purpose of
data collection: Provide information about income and government
program participation; Examples of data collected: -Work experience; -
Earnings; -Program participation; -Benefits received; -Property
Income; -Demographic characteristics.
Agency: Bureau of Labor Statistics; (Department of Labor); Data
collection program: National Compensation Survey; Purpose of data
collection: Provide information on wages salaries and benefits;
Examples of data collected: -Occupational earnings; -Compensation
trends; -Benefits offered; -Benefit participation; -Detailed plan
provisions.
Agency: Employee Benefits Security Administration; (Department of
Labor); Data collection program: Form 5500; Purpose of data collection:
Enforce ERISA pension requirements; Examples of data collected: -Type
of plan; -Number of employees; -Number of participants; -Plan
amendments; -Plan financial position; -Actuarial assumptions; -
Employer & employee contributions.
Agency: Social Security Administration; Data collection program: SSA
earnings and benefit records; Purpose of data collection: Administer
the Social Security benefit programs; Examples of data collected: -
Earnings histories; -Social Security benefit histories; -Supplemental
Security Income benefit histories.
Agency: Internal Revenue Service; (Department of the Treasury); Data
collection program: IRS tax records; Purpose of data collection:
Administer/enforce the tax code; Examples of data collected: -IRS
individual 1040 returns; -IRS Information returns; -Account balances; -
Withdrawals.
Source: GAO‘s analysis of data from the U .S. Census Bureau, the U.S.
Department of Labor, Social Security Administration, and the U.S.
Treasury Department.
[End of table]
Agencies involved in the analysis of retirement income and wealth data
often limit their analysis to a portion of the retirement income and
wealth information. Panel members noted that many of the agencies place
little or no priority on a comprehensive analysis of retirement income
and wealth data. Instead, agencies focus their data collection and
analysis on data needed to address their mission. For example, Labor‘s
EBSA collects information on compliance with ERISA regulations,
including Form 5500 submissions. Although EBSA‘s strategic plan
includes retirement income data analysis efforts, its principal focus
is on enforcement of ERISA. Similarly, the Bureau of the Census
collects retirement related information in the SIPP and other surveys
but its analysis of this information is primarily in the context of its
income and poverty measurement mission. The SSA‘s MINT model uses an
estimate of workers‘ pensions based on SIPP data from the Census
Bureau, which generally relies on survey responses, has been criticized
for using inaccurate estimates of nonearnings income, including
retirement income. Because the Census Bureau data provided to the SSA
for the MINT was not gathered with it in mind or coordinated for its
use, the MINT model has had to use simplifications and assumptions of
these data which makes its final model less useful for policy
makers.[Footnote 25]
Despite this fragmentation, some agencies have attempted to increase
communication between federal agencies concerning data collection
efforts related to retirement income. For example, the BLS‘ strategic
goals include improving the accuracy, efficiency, and relevancy of U.S.
economic statistics and enhancing coordination with other agencies. The
Census Bureau‘s strategic goals likewise include an emphasis on
providing accurate, timely, and accessible information on the U.S.
population and economy, and to maintain relationships with agencies
compiling administrative record data. Both the Census Bureau and the
BLS are members of the Federal Interagency Forum on Aging Related
Statistics,[Footnote 26] which has a goal of improving both the quality
and the use of aging related data. In addition, BLS is one of three
agencies that share responsibility for leading the Inter-Departmental
Committee on Employment-Related Health Insurance Surveys. This
committee of a dozen members was created in 1998 to improve
coordination and reduce respondent burden by reducing redundant
requests for information.
Respondent Burden Considerations Limit Available Data:
Members of our expert panel reported that respondent burden, as well as
requirements set up to limit respondent burden, could hinder agencies‘
efforts to obtain retirement-related information. Panel members noted
that answering survey questions about retirement income and wealth
could be a substantial burden on respondents. They acknowledged that
asking for too much information could result in partial responses,
erroneous responses, or, in some cases, a reduction in the overall
response rate.
However, efforts to reduce respondent burden may also limit the
collection of retirement information. Legislation requires OMB to
review surveys before they are used to collect data. The Paperwork
Reduction Act of 1995 (P.L. 104-13) and similar previous
legislation[Footnote 27] is designed to minimize the paperwork burden
on the public while at the same time recognize the importance of
information to the successful completion of agency missions. The act
requires OMB to approve all existing and new collections of information
by federal agencies. In approving agency collection efforts, OMB must
weigh the burden to the public against the practical utility of the
information to the agency. Panel members noted that agencies were
reluctant to propose additional data collection unless they could
clearly establish that the benefit outweighed the perceived burden.
Panel members noted that efforts to reduce existing data collection
requirements sometimes result in a loss of information. For example,
the 1997 elimination of the requirement that firms routinely submit
SPDs was connected to an effort to reduce the respondent burden on
employers.
Privacy and Confidentiality Concerns Limit the Collection and Use of
Retirement Data:
While restrictions on the collection and use of retirement data are
critical for the protection of personal information, some panel members
noted that these restrictions also limit the availability of such
information. Several laws exist to protect individuals‘ rights to
privacy and protect the confidentiality of personal and proprietary
information held by federal agencies. For example, laws set strict
requirements to protect data collected by the Census Bureau and to
limit the use of taxpayer data.[Footnote 28]
Implementing such laws requires federal agencies to restrict access to
data they collect. For example, the Census Bureau‘s data set that links
the SIPP with earnings and benefit records from SSA is not available to
the public. Protecting the confidentiality of such linked data sets is
particularly crucial because linked data sets may be more detailed or
more sensitive than the component data sets were before they were
linked. Agency officials must remove personal identifiers such as
Social Security numbers, names, and addresses. Even without these
personal identifiers, as more and more information is linked, the risks
that individuals could be identified increases. The computer files for
these nonpublic data sets are available only at a limited number of
secure research data centers to approved analysts working on approved
projects.[Footnote 29] Outside analysts working with these data sets
must be sworn Census Bureau officers and their work must serve, at
least in part, to support the Census Bureau‘s mission. If analysts
permitted to use these data combine any other data with the restricted
data, the combined data are subject to the Title 13 protections.
Analysts are not allowed to make copies of the data or remove data from
the secure data center.[Footnote 30] Before taking any of the results
of their work from the center, Census Bureau staff must review the
results to ensure that they meet the agency‘s requirements for
confidentiality protection. Thus, the results that can be taken out of
the center are limited to statistical results that do not disclose data
for specific individuals. Also, the external researchers must agree
that the results of their work will be available in the public domain
and not maintained as proprietary information.
However, despite the government‘s efforts to protect the information
they collect from misuse, surveys of the public and Census Bureau
interviewers indicate that people are apprehensive about the
government‘s use of personal information. In a survey conducted both
before and after (or just prior to) the 2000 Census of Population and
Housing, about half of the respondents (51 percent before and 50
percent during) indicated they thought the Census Bureau‘s promise of
confidentiality could be trusted, down from about 79 percent in 1990. A
smaller, but still substantial proportion of the workers conducting
census interviews and providing those promises to respondents also
indicated a lack of trust in the Census Bureau‘s assurances. A 1998
study indicated that 16.7 percent of Census Bureau interviewers and
32.2 percent of non-Census Bureau interviewers believed that the Bureau
would give individual survey data to government agencies such as the
Federal Bureau of Investigation, the Central Intelligence Agency, the
Immigration and Naturalization Service, and the IRS. Federal law
prohibits the Census Bureau from sharing information about individuals
with these agencies. Census Bureau information about particular
individuals or businesses is only available for statistical purposes,
not for law enforcement purposes.
Public distrust of federal agencies‘ use of their personal information
can undermine people‘s willingness to participate in federal surveys,
potentially making the information collected less reliable.[Footnote
31] An article in the Journal of Official Statistics noted that in the
1990s the rate at which people refused to participate had risen for six
surveys conducted by the Census Bureau.[Footnote 32] For questions
about types of income in the March 1999 CPS survey, for example, the
percentage of respondents providing data for particular items ranged
from 33 percent to 78 percent. Low response rates can undermine
analysts‘ statistical projections if the individuals who choose not to
respond differ in important respects from those who provide data. If
the remaining respondents are dissimilar to the population being
surveyed, conclusions about the population may not be reliable. For
example, if those who chose not to respond have higher incomes,
estimates of the populations‘ income may not be reliable. Statisticians
make adjustments that can mitigate this problem, but the lower response
rates are, the more uncertainties remain.
Federal agencies and researchers continue to explore options to
maximize data usefulness without compromising respondent privacy and
confidentiality.[Footnote 33] For example, the Census Bureau has
received permission from the IRS to link the survey records to
additional items from IRS and SSA records.[Footnote 34] In addition,
the Census Bureau has recently increased the number of its research
data centers where approved analysts working on approved projects can
access confidential data.
Researchers continue to explore statistical techniques for providing
more information from survey data sets while reducing the risks that
confidential information will be compromised. One well-known technique
for doing this, ’top coding,“ involves reporting in data files only
that an individual respondent‘s income, for example, exceeds the ’top
code“ amount, not the actual value. In this way, so many individuals
are included in the high-income group that their identities cannot be
determined. More sophisticated techniques include the use of methods to
substitute artificial records containing estimated values based on
knowledge of the real data. These simulated subjects are assigned
number values selected to ensure that relationships between important
variables are preserved. This allows people to remain anonymous to the
researchers using the data. However, pension experts state that this
method can only accommodate certain kinds of variables and, therefore,
complex relationships between variables may not be maintained.
[Footnote 35]
Recent legislation may enable the Census Bureau and BLS to link their
data on businesses for statistical purposes. In December 2002, the
Congress enacted the Confidential Information Protection and
Statistical Efficiency Act of 2002 as part of the E-Government Act of
2002 (P.L. 107-347). This act permits designated statistical agencies
to share information concerning businesses for statistical purposes,
but not information concerning individuals or households. It authorizes
three agencies--the Census Bureau, the Bureau of Economic Analysis, and
BLS--to share data on businesses with one another for statistical
purposes.
Conclusions:
With the proportion of retirees to workers expected to increase
dramatically over the next couple of decades, important decisions lie
ahead. Access to retirement income data needed to inform those
decisions has actually decreased in some respects, despite the
recommendations of the 1997 National Research Council‘s Panel on
Retirement Income Modeling. Although many sources of useful retirement
income data remain, retirement analysts we consulted cited
shortcomings. They noted, for example, that data shortcomings persist
when no one federal agency is responsible for coordinating efforts to
fill retirement income data needs.
Indeed, several such data needs could be met with information the
federal government already possesses or to which it already has access.
For example, Labor has the authority to obtain existing documents
describing the features of private pension plans. However, though it
has this authority, it gives employers in its National Compensation
Survey a choice about whether to provide them to support Labor‘s BLS
statistical studies of pension plans. To encourage voluntary
participation in the survey, Labor does not make them available to
other agencies, outside analysts or the general public. The Census
Bureau gathers or collects information about some general features of
private pension plans through surveys of households and individuals but
has not yet had the opportunity to corroborate and supplement this data
using information from respondents‘ employers available through Labor.
While information on pension and individual retirement accounts is
gathered through forms collected by the IRS, the data are not regularly
tabulated or linked to survey data, and thus, are not available for the
study of pensions.
While improvements in data are essential for more reliable forecasts of
retirement income, protecting respondents‘ information and minimizing
the burden data collection efforts impose on firms and individuals are
also crucial. To sustain programs for compiling statistics about firms
and individuals, respondents must be able to trust that their personal
information will not be misused. Finding an appropriate balance between
providing wider access to data to support policy analysis and keeping
data secure is a persistent and evolving challenge that policymakers
must continually address. In addition, federal agencies need to
consider both the federal cost of these efforts and the financial and
nonfinancial costs imposed on respondents in comparison with the
benefits expected from improvements in data. While taking into account
these cost considerations, respondent concerns about increased
reporting burden, and agency concerns about maintaining
confidentiality, the Congress, and the Departments of Labor and the
Treasury could take the next steps to help fill some of the data needs.
Matter for Congressional Consideration:
To facilitate plan participants‘, beneficiaries‘, and analysts‘ timely
access to information about employer-provided pension plans, the
Congress should consider directing the Secretary of Labor to obtain
from plan administrators electronic filings of all SPDs and summaries
of material modifications required by ERISA and make them publicly
available in electronic form.
Recommendations:
To help provide the data needed to inform important policy decisions
concerning retirement programs, the Secretary of Labor should direct
the Bureau of Labor Statistics to prepare a plan to improve data for
analyzing retirement income and wealth in coordination with OMB, the
Federal Reserve Board, IRS, and the agencies represented in the Federal
Interagency Forum on Aging Related Statistics, including the Census
Bureau, SSA, and the National Institute on Aging. The plan should
include cost-effective strategies to:
* make better use of existing statistics by linking survey and
administrative data,
* improve access to linked data consistent with privacy and
confidentiality legislation, and:
* improve data collected from employers related to retirement income
and wealth.
For plans in place before these new filing requirements go into effect,
and where it is cost-effective, the Secretary of Labor should use
existing authority to obtain copies of summary plan descriptions and
summaries of material modifications in cases where analysts working on
federally conducted or federally sponsored research seek SPDs for
statistical purposes. This should assist analysts of retirement income
in obtaining information about the features of employer-sponsored
benefit plans that are not electronically available.
To help analysts improve analyses of retirement plan finances, the
Internal Revenue Service should publish on an annual basis aggregate
tabulations, such as those prepared in the Statistics of Income
Bulletin, of information filed on IRS Forms 5498, 1099-R, and W-2.
Agency Comments:
We provided a draft of this report to the Departments of Commerce,
Labor, the Treasury, and the IRS and received technical comments from
all four. In response we modified the draft as appropriate. We also
provided a draft of this report to the 11 members of our expert panel
and modified the draft as appropriate in response to their comments.
Commerce had no major comments on the report (see app. VI). Labor
agreed on the need for access to accurate data but did not agree with
our recommendations to the Secretary of Labor (see app. VII).
Regarding our recommendation to collect electronic copies of SPDs,
Labor concluded that this is at odds with the Taxpayer Relief Act of
1997, which eliminated requirements that SPDs be regularly filed with
Labor. Although Labor still has authority to request SPDs, it had
indicated in final regulations concerning SPDs that it generally
intended to limit the exercise of its authority to requesting SPDs on
behalf of participants and beneficiaries. Labor also indicated that
there was little public interest in the SPDs. Although there was not
substantial public demand for paper copies of SPD‘s in Labor‘s Public
Disclosure Room in Washington, D.C., in the last decade there has been
a great increase in policymakers‘ demand for better data on retirement
income in light of the rapid future increase in the retiree population.
Although in both 1993 and 1995 we supported elimination of paper filing
requirements, we also endorsed electronic access to SPDs. We continue
to believe that it is time to phase in a requirement that SPDs be filed
electronically. The costs involved should be considerably less than
those incurred filing and storing paper copies of the documents. The
burden imposed on plan administrators would not be unreasonable. Labor
estimated in 1998, for example, that it would cost an average of $1.55
to provide SPDs for health benefit plans to each plan participant, of
which $1.00 was the estimated cost of materials and postage.[Footnote
36] Cognizant of the shortcomings of many SPDs, experts we consulted
nonetheless indicated that better access to SPDs is a top priority for
improving retirement income data. Accordingly, we changed our
recommendation to a Matter for Consideration for the Congress to direct
the Secretary of Labor to obtain from plan administrators electronic
filings of all SPDs and summaries of material modifications required by
ERISA and make them publicly available in electronic form.
Regarding our recommendation that BLS prepare a plan to improve data
for analyzing retirement income and wealth, Labor indicated that past
efforts to coordinate improvements in retirement income data have not
been successful due to privacy concerns, and other issues. They stated
that the type of planning and coordination we envisioned usually is the
purview of OMB‘s Office of Statistical Policy, and that BLS could
participate in that coordination. Furthermore, the extra demands placed
on staff would not be negligible. In our view, the need for
improvements in retirement income data warrants renewed efforts to
address the priorities identified by the experts we consulted. The
recommendations of these experts focused primarily on improved use of
existing data to support policy analysis, and not on additional data
collection. We recognize OMB‘s role overseeing information collection
and developing policies to improve government statistics. However, this
does not preclude efforts by other agencies to take the lead in
developing plans for improvements focused on data within specific
subject areas such as retirement income. Because OMB does not have the
retirement income focus needed to coordinate in this way, we have
retained our original recommendation. That recommendation specifically
identifies OMB as one of the agencies that should be involved in the
development of a plan, and the plan should be developed in a manner
consistent with OMB‘s policy.
With respect to our recommendation regarding provision of SPDs before
new electronic filing requirements go into effect, Labor stated that
the need to protect the confidentiality of survey data may hamper wider
access to SPDs. BLS, for example, assures respondents to its National
Compensation Survey that their identities will be kept confidential.
The Secretary‘s authority to request SPDs is delegated to EBSA. If BLS
were to obtain SPDs from EBSA it would have to reveal the identity of
its respondents and therefore would have to obtain their consent. We
conclude that the need for improvements in retirement income data
warrants Labor‘s use of its existing authority to obtain SPDs for
analysts engaged in federally conducted or federally sponsored
research. Arrangements could be developed through which BLS and other
statistical agencies could both obtain SPDs and protect the identity of
respondents. They could, for example, request SPDs from a larger number
of employers without identifying which employers were being surveyed.
This is the kind of improved access to data that we envisioned BLS
could take the lead in identifying in coordination with other agencies.
We are sending copies of this report to the Secretary of Labor, the
Secretary of the Treasury, the Secretary of Commerce, and the
Commissioner of the Internal Revenue Service. We will also make copies
available to others on request. In addition, the report will be
available at no charge on GAO‘s Web site at http://www.gao.gov/.
If you have any questions concerning this report, please contact
Barbara Bovbjerg at (202) 512-7215, Robert Parker at (202) 512-9750.
See appendix VIII for other contacts and staff acknowledgments.
Sincerely yours,
Barbara D. Bovbjerg
Director, Education, Workforce
and Income Security Issues:
Robert P. Parker
Chief Statistician:
Signed by Barbara D. Bovbjerg and Robert P. Parker:
[End of section]
Appendix I: Scope and Methodology:
To identify information that experts say is a priority for improving
data for the study of retirement income and wealth, we conducted a Web
based survey of experts in the field and convened an 11 member panel of
experts to discuss opportunities for improving these data. We used the
Web based survey instrument to survey 276 experts in retirement income
data.[Footnote 37] Before implementing the survey, we contacted
respondents via email and asked them to participate. Out of our initial
list of 326 experts, 27 declined to participate, with the majority
citing busy schedules or lack of sufficient expertise as their reasons.
In addition, we concluded that we had inaccurate or out-of-date E-mail
addresses for 23 of the experts.
We studied available research and interviewed experts in order to
develop a questionnaire of options to improve retirement income. The
questionnaire asked respondents to indicate the priority (from highest
to lowest) they would place on 22 actions to improve retirement income
data. Respondents were asked to rate each action independently, without
making comparisons between the actions. We pretested the content and
format of the questionnaire with 6 experts in the area of retirement
income. The questionnaire was then refined and posted on our Web site
and an E-mail message informed participants of its availability. This
E-mail message also contained a unique user name and password that
allowed each respondent to log on and fill out his or her own
questionnaire.
As of December 12, 2002, 190 of the experts responded to the survey (a
69% response rate). Eighteen percent of respondents indicated that they
were affiliated with federal agencies, about half were affiliated with
colleges and universities, 24 percent were affiliated with other
nonprofit organizations, and the remaining 9 percent were affiliated
with for profit or other organizations.
Our preliminary results of the survey identified two areas for
improvement that respondents most often cited as having the highest
priority: (1) matching survey and administrative data and (2) employer
data. We used these areas to serve as the principal topics at a 1-day
expert panel meeting at our headquarters on September 10, 2002. The 11
panelists included 5 federal officials with responsibilities related to
retirement income data, 3 university based analysts, and 3 from private
not-for-profit agencies. Barbara Bovbjerg, Director, Education,
Workforce, and Income Security Issues, and Robert Parker, Chief
Statistician, moderated the discussion. (For a summary of the panel‘s
discussion and a list of panelists, see app. IV.):
To identify factors limiting the availability of information needed for
the study of retirement income and wealth, we reviewed documents
obtained from and interviewed officials at the Department of Labor‘s
(Labor) Employee Benefit Security Administration (EBSA), and Bureau of
Labor Statistics (BLS), the Census Bureau, the Treasury Department‘s
Office of Tax Analysis, the Internal Revenue Service‘s (IRS) Statistics
of Income Division, the National Institute of Health‘s National
Institute on Aging, and the Social Security Administration‘s (SSA)
Office of Research, Evaluation, and Statistics. We also attended
conferences related to retirement income analysis sponsored by the
Retirement Research Consortium and the Society of Actuaries and
interviewed analysts at the Urban Institute, The Brookings Institution,
the Employee Benefit Research Institute, and the National Research
Council.
The scope of our work did not include an evaluation of estimated costs
and benefits of specific proposals for improving retirement income
data. We did not independently verify the federal funding figures
provided to us by longitudinal survey administrators or agencies
sponsoring the surveys.
[End of section]
Appendix II: Status of Recommendations From the 1997 Report of the
Panel
on Retirement Income Modeling:
Below are recommendations concerning retirement income data needs
excerpted from the 1997 report of the National Research Council‘s Panel
on Retirement Income Modeling followed by summaries on the status of
each as of December 2002.[Footnote 38]
1. Continue support of longitudinal studies:
Recommendation: Existing panel surveys of middle-aged and older people
should receive continued government support. Longitudinal data from
these surveys are essential to analyze retirement and savings decisions
and determine behavioral responses to changes in public and private
sector policies. Such analyses in turn are essential to develop better
models for forecasting the likely effects of alternative policy
proposals on retirement income security. In particular, the Health and
Retirement Study (HRS) and Asset and Home Dynamics Among the Oldest Old
(AHEAD) surveys should receive continued support. These surveys should
be refreshed periodically with new cohorts in order to offer insight
into how behavior changes over time.
Status: As shown in table 2, the amounts of federal support for three
major longitudinal surveys have been sustained. The HRS and AHEAD
studies, which are now jointly funded, have increased after taking the
effects of inflation in account.
Table 2: Federal Outlays for Selected Longitudinal Studies--Fiscal
Years 1997-2001:
Millions of constant fiscal year 2001 dollars[A].
HRS and AHEAD; 1997: $6.8; 1998: $7.0; 1999: $7.4;
2000: $9.0; 2001: $9.4; 2002: $10.1.
National Longitudinal Studies[B];
1997: 14.0;
1998: 11.8;
1999: 13.2;
2000: 12.8;
2001: 12.8;
2002: 12.4.
Panel Study of Income Dynamics[C];
1997: 2.5;
1998: 2.5;
1999: 3.7;
2000: 3.7;
2001: 3.6;
2002: 2.8.
Total;
1997: $23.3;
1998: $21.3;
1999: $24.3;
2000: $25.5;
2001: $25.8;
2002: $25.3.
Source: GAO analysis of data from the National Institute of Aging and
the University of Michigan‘s Institute for Social Research.
[A] These figures are adjusted for inflation using the Bureau of
Economic Analysis‘s gross domestic product price index.
[B] NLS:
[C] PSID:
[End of table]
The National Institute on Aging continues to fund the HRS and AHEAD
studies. Supplemental funding also comes from SSA. Both the AHEAD and
HRS studies have been refreshed with new cohorts. In 1998, interviews
began for a cohort of people born from 1924 to 1930 and a cohort of
people born from 1942 to 1947.
The National Science Foundation continues to fund the PSID. Additional
support comes from the National Institute on Aging, the National
Institute on Child Health and Human Development, and the Departments of
Health and Human Services, Agriculture, Housing and Urban Development
(HUD), and Labor.
Labor sponsors the National Longitudinal Survey (NLS) through BLS. The
NLS is conducted under contract with researchers at Ohio State
University, the University of Chicago, the Census Bureau and the
University of Wisconsin. In addition to Labor funding, financial
support has come from agencies including the National Institute of
Child Health and Human Development, the National Institute on Aging,
the National Institute on Drug Abuse, the National Institute on Alcohol
Abuse and Alcoholism, and the Departments of Defense, Justice, and
Education.
2. Measure expenditures:
Recommendation: Panel surveys of middle-aged and older people should
experiment with methods to develop measures of families‘ total
expenditures and expenditures on housing and medical care. Such
consumption measures are important for projections of economic well
being in retirement.
Status: The HRS and AHEAD surveys provide on a longitudinal basis
respondents‘ estimates of many categories of expenditures including
housing expenditures, total out-of-pocket medical expenditures, and
total expenditures, total expenditures relative to income, as well as
information on savings preferences. Labor‘s Consumer Expenditure Survey
provides cross-sectional rather than longitudinal data on many types of
expenditures, including housing expenditures, and medical
expenditures, and total expenditures and related income. The American
Housing Survey, sponsored by HUD, provides detail on housing
expenditures . The proposed American Community Survey also would
provide limited detail on housing expenditures. The Medical Expenditure
Panel Survey (MEPS) provides extensive data on medical expenditures.
3. Gather more data on younger people:
Recommendation: Panel surveys of younger people, such as the National
Longitudinal Survey of Youth (NLSY), should include detailed
questionnaire modules on pension coverage, wealth, health status, and
retirement-and savings-related expectations. Such information is
needed to fully understand life-cycle behavior and to track the
disparities in income and wealth that are evident by middle age.
Status: The NLSY asks about the total amount of retirement savings,
amounts contributed, and amounts withdrawn, and pension coverage. It
also provides information about assets and debt and limited information
about health (height, weight, and general evaluation of health), but
not retirement or savings expectations.
In 1995-99 interviews, the National Longitudinal Survey of Young Women
(NLSYW) asked respondents the extent to which they agreed or disagree
with statements such as ’Work is the most meaningful part of life“ and
’People who don‘t retire when they can afford to are foolish.“ The
NLSYW also asked respondents about the availability of a retirement or
pension plans in 1978 and in each round from 1978, 1983, through 1999.
The 1991 and 1995-99 rounds of the survey included more detailed
questions on amounts in retirement plans, formula for calculating
benefits for defined benefit plans provided by current and previous
employers, vesting status, and expectations about retirement, such as
expected amounts of benefits.
4. Collaborate to improve data quality and utility:
Recommendation: Agencies and researchers involved in retirement income-
related panel surveys of individuals, and other surveys as appropriate
(such as the Survey of Consumer Finances (SCF) and the Survey of Income
and Program Participation (SIPP)), should collaborate regularly in
reviewing questionnaire content and data collection practices to
identify ways to improve data quality and utility. For example, the
bracketing technique used in HRS and AHEAD that has been demonstrated
to reduce nonresponse to important items should be adopted in other
surveys. Also, such surveys might include a common core of questions on
specific topics. The National Institute on Aging should facilitate such
collaborative efforts.
Status: Federal agencies collaborate through entities such as (1) the
Federal Interagency Forum on Aging-Related Statistics, originally
established by the National Institute on Aging, National Center for
Health Statistics, and Census Bureau and (2) the Inter-Departmental
Committee on Employment-Related Health Insurance Surveys, headed by the
BLS, National Center for Health Statistics, and the Agency for
Healthcare Research and Quality. The Federal Committee on Statistical
Methodology and the Interagency Committee on Confidentiality and Data
Access have coordinated research on techniques such as the bracketing
technique are now widely used and researchers do collaborate on
questionnaire design. In addition, the Census Bureau and other
statistical agencies seek comments from a wide range of researchers on
the content of questions before fielding survey instruments. For
example, the Interagency Committee on the SIPP, which consists of
representatives of interested federal agencies, and the American
Statistical Association‘s Survey Research Methods Section SIPP Working
Group, which consists of federal and non-federal analysts, both advise
the Census Bureau on that survey.
5. Establish interagency task force on employer data:
Recommendation: Labor should establish an interagency task force on
employer data to specify an integrated plan for collecting retirement
income-related information. The plan should specify short-term and
long-term goals that consider user needs, resource constraints, and the
problems of obtaining information from employers due to such factors as
low response rates, locating the appropriate respondents, and
confidentiality concerns. The task force should involve researchers,
private benefit consultants, and representatives of public and private
employers in its work.
Status: According to officials at the Department‘s EBSA, Labor has not
made this a priority because its resources are limited.
6. Gather more data on benefit plan offerings:
Recommendation: The employer data collection plan should include short-
term and long-term goals for obtaining improved information on the
distribution across employers of all benefit plan offerings (including
pensions, health insurance, disability insurance, retiree health
insurance, life insurance). Comprehensive baseline information is a
priority need, along with a plan for regular updating. Needed data
elements include benefit plan characteristics and costs, employer
characteristics (e.g., number of employees, financial characteristics,
wage structure), and workforce characteristics (e.g., age structure)
for public and private employers and the self-employed.
Status: Labor‘s BLS has increased the amount of information gathered
through its National Compensation Survey, which includes components
that had been gathered through the Employee Benefits Survey, the
Employment Cost Index survey, and the Occupational Compensation Survey.
The Employee Benefits Survey did not provide tabulations of the
estimated percentage of establishments providing specified types of
benefits, but the National Compensation Survey does. The survey
includes components for state and local government employers, medium
and large private employers, and small private employers, but not
federal employers or the self-employed. The survey provides data on
number of employees, employer and employee costs, wage structure, and
the characteristics of retirement benefit plans. It does provide data
on the employer‘s cost of providing defined benefit and defined
contribution retirement programs. It does not provide information on
financial characteristics of plans (such as assets and liabilities) and
does not provide information on the age structure of the workforce.
In addition, the MEPS, sponsored by the Agency for Healthcare Research
and Quality, provides additional data on health insurance plans.
7. Redesign and enhance employee benefits survey.
Recommendation: The employer data collection task force should give
priority to redesigning and enhancing existing data collection systems
on employer benefit offerings and related topics. Such systems include
the Employee Benefits Survey, which currently provides information for
broad categories of employe[rs] but not for employe[es], and the Form
5500 data series, which serves regulatory purposes and currently has
limited research use. Consideration should be given to improving the
Form 5500 series, including:
* making the data more timely and accessible (e.g., on-line);
* linking records over time to provide panel data;
* merging the Form 5500 benefit plan information with the kind of
employer financial characteristics found in the Compustat database;
* working to standardize the reporting for health care and disability
plans, so that they can be added to the Form 5500 database; and:
* finding ways to add information about benefit plan features to the
database, perhaps by abstracting analytically useful information from
the narrative plan descriptions that are filed with the Form 5500.
Status: The Employee Benefits Survey (now part of the National
Compensation Survey) continues to provide data for categories of
employers, not categories of employees. It provides data by employer
industry group, employer employment size group, employee union status,
employee occupational group, and employer geographic location. BLS has
begun providing aggregate estimates for all private employers, rather
than only providing data separately for small private employers, and
large private employers, as it did in the past. However, the survey
does not cover federal, military, agricultural, fishing, forestry, or
private household employers.
Data from IRS Form 5500 continues to become available well after the
end of the reporting year. (Data for 1998 or the 1998-99 reporting year
became available in 2002.) In part, this is because the IRS deadline
for submitting the forms is 7 months after the end of the reporting
year. For example, for a firm with a 1998 reporting year beginning
December 15, 1998, and ending December 14, 1999, the Form 5500 was due
July 31, 2000. In addition, Labor takes several months to review and
edit the returns before making them publicly available. Labor makes
Form 5500 data files available to researchers and policy analysts, but
its Web site does not include links to the data. A private firm
provides a Web site with images of the completed forms, but not
compiled data sets. Labor does not link Form 5500 reports by firm to
facilitate longitudinal analysis. Linking these consolidated reports of
publicly held companies with Form 5500 data is difficult because these
reports can cover only parts of a company, more than one company, or
privately held companies. Some researchers have linked these data for
selected firms.
Labor no longer requires that it receives the summary plan descriptions
regularly, and as a result the public no longer has access rights to
new or revised versions. Labor does, however, incorporate some data
from these plans in its National Compensation Survey data. This
includes, for example, information on normal retirement ages and
formulas for calculating employer contributions to pension plans.
8. Gather more data on labor demand for older workers:
Recommendation: The employer data collection plan should include short-
term and long-term goals for obtaining information on labor demand for
older workers and the factors that may affect that demand. Needed data
elements include employment patterns of older workers, compensation and
benefit costs by age, and worker productivity by age. Very little
information on these topics is currently available, and some raise
difficult measurement issues. A reasonable short-term goal is to
sponsor case studies of employers that can help identify important
variables and feasible means of collecting them on a larger scale.
Status: The Health and Retirement Study and other surveys provide much
data on employment patterns and salary and wages of older workers.
Little has been done, however, concerning compensation and benefits
costs or productivity by age.
9. Conduct longitudinal survey of employers and their workers:
Recommendation: The employer data collection task force should consider
the feasibility and cost-effectiveness of a panel survey, which is
periodically refreshed that collects detailed information on employers
and their workers. Such a survey should cover the full universe,
including private for profit, nonprofit, and government employers, and
the self-employed. Longitudinal data from an employer-based survey are
needed to analyze the factors that affect employer decisions about
recruitment and retention of older workers and benefit plan offerings
and how these decisions, in turn, affect workers.
Status: Such a task force has not been formed and no survey like the
one the panel recommended has been undertaken. BLS has developed a
longitudinal database of business establishments, the ’LDB“, based on
data from states‘ unemployment insurance programs, and the Census
Bureau continues to maintain a longitudinal establishment database
covering all private nonagricultural establishments. Neither of these
databases includes data on pensions or other retirement plans. The BLS
database provides data on employees‘ hours and wages. The Census Bureau
database also provides data on employment and wages, and periodically
includes data on employer contributions to pension plans and health
insurance. To some extent the HRS links data from individuals and their
employers on a longitudinal basis, but it tracks the individuals, not
the firms over time. The E-Government Act of 2002 (P.L. 107-347) may
facilitate collaboration between the Census Bureau and BLS and could
provide for linking National Compensation Survey (NCS) data on
retirement plans to the Census Bureau‘s data on business
establishments.
10. Gather more data from employers of HRS/AHEAD sample members:
Recommendation: HRS and AHEAD should develop and implement a plan for
obtaining information on a continuing basis on the pension and health
insurance offerings of the employers of the HRS/AHEAD sample members.
Status: Data from HRS sample members‘ employers is available. Similar
efforts have been undertaken with other surveys, such as the National
Longitudinal Study of Mature Women.
11. Match panel survey responses and key administrative records:
Recommendation: Matched files of panel survey responses and key
administrative records should be regularly produced for retirement-
income-related policy analysis and projection purposes. Examples
include exact matches of survey records and Social Security earnings
histories and benefit records, Medicare and Medicaid records, and the
National Death Index. The added information in matched files is
obtainable at low marginal cost and is essential for analysis of
retirement and savings decisions and the effect of medical care use and
expenditures on retirement security.
Status: Some matches between administrative data and panel survey data
have been achieved. HRS investigators have completed matches between
HRS and Social Security earnings and benefit record data, National
Death Index data, and Medicare records. These are available on a
restricted basis to selected researchers and policy analysts.
The Census Bureau has matched SIPP data with Social Security earnings
records and extracts from individuals‘ IRS tax return data. The Census
Bureau‘s Longitudinal Employer Household Dynamics (LEHD) project is
exploring options for more extensive matches between Form 5500 data
from employers and Census Bureau survey data on
establishments.[Footnote 39] Recently finalized Treasury regulations
give the Census Bureau access to specified IRS tax return records to
support SIPP and LEHD data linkage efforts.[Footnote 40]
Also, researchers at the Employee Benefit Research Institute (EBRI)
linked survey data to state Medicaid records in order to develop state
specific projections of Medicaid expenditures.
12. Increase researchers‘ access to exact match files safeguarding
confidentiality:
Recommendation: Agencies should collaborate on the development and
oversight of matched data sets for individuals and employers, with
input from researchers on content. They should also vigorously explore
creative solutions for providing research access to exact match files
that safeguard the confidentiality of individual responses. Possible
solutions include: (1) developing public use files that contain summary
variables derived from the administrative records portion of the
matched file (2) requiring researchers to sign nondisclosure agreements
with significant penalties for violations; and (3) providing
researchers with access to matched files on site at secure data
centers.
Status: Access to linked data sets remains quite limited. Access to HRS
linked data for example, is typically made available via a rigorous
application process resulting in a data use agreement with the
University of Michigan. To date, none of the linked data sets are
available in encrypted public use files. However, according to HRS
researchers, ’The HRS, in conjunction with several other funded
projects, has established a secure data facility to broaden access to
the restricted datasets. We are exploring ways to eventually implement
a system for encrypted online delivery of sensitive data files, as well
as extend access to our restricted data.“ (One such method is the
further use of data centers, which provide access to restricted
information, including linked data sets, for approved researchers
working on data sets. For more information on data centers, see page
19).
13. Fund regular evaluation of data quality:
Recommendation: Budgets for retirement income-related surveys should
include sufficient resources for regular evaluation of data quality.
Evaluation methods include reinterviewing sub-samples of respondents to
measure consistency of reporting; experimentation with alternative
question wording to identify possible reporting problems; and comparing
survey estimates with administrative records to determine the
completeness and accuracy of survey reporting, taking care to adjust
for differences in definitions and other aspects of the two sources.
Status: Several studies using the recommended methods have been
conducted, with mixed results. The Census Bureau conducted a study
comparing estimates of various types of 1990-96 incomes in SIPP and CPS
to benchmark data estimated by the Census Bureau from the personal
income estimates in the National Income and Product Accounts. The study
found disparities between the survey based Census estimates and the
administrative record based personal income estimates that could not be
explained by differences in definitions.[Footnote 41] For 1996, the
aggregate wages and salary estimate based on CPS survey data was 102
percent of the benchmark based on administrative records and the CPS
social security and railroad retirement benefit payments data were 92
percent of the benchmark. In contrast, the study found more substantial
disparities for several other types of income. The aggregate CPS data
for property income was 71 percent of the benchmark, and CPS data for
pension income was 77 percent of the benchmark. The study is being
replicated with data for 1999. Other studies have noted definitional
and quality differences between estimates of personal savings from the
Flow of Funds Accounts and National Income and Product
Accounts.[Footnote 42] Another study compared estimates of wealth from
the SCF, PSID, and SIPP.[Footnote 43]
The Department of Treasury‘s Office of Tax Analysis has compared
estimates of pension plan participation and contributions with
estimates from the Census Bureau survey data. The Office of Tax
Analysis linked W-2 data with Statement of Income (SOI) data from Form
1040. The results from this data set matched results from Census Bureau
surveys, except for low-income households. The tax records obviously
don‘t include nonfilers, but in addition, by design, the SOI sample
includes relatively few low-income filers (in the order of 1 in 5,000
filers), but all filers in the highest income brackets. The Census
Bureau surveys such as the SIPP over sample low income households and
have much less data for the highest income households. For most income
brackets, however, the data match quite well, according to Treasury
officials.
The Census Bureau periodically assesses the quality of CPS data by
reinterviewing a subsample of respondents, but none of the
reinterviewing has covered questions on income for at least the last 4
years, according to the Census Bureau quality assurance staff.
The Census Bureau has also studied the accuracy of respondent data by
matching income data in the March CPS with selected income detail on
individual IRS income tax returns and SSA earnings and benefit records.
A similar effort is underway using 1999 data.
One of the components of the BLS‘s National Compensation Survey is a
program of re-interviews of a sub-sample of respondents to verify and
clarify survey data, including data on retirement plans.
HRS investigators have compared employee responses about retirement
income to employer provided data and Social Security records and found
wide discrepancies. It is unclear to what extent these result from
respondents‘ limited knowledge of their pensions or data errors.
[End of section]
Appendix III: GAO Survey on Retirement Income Data Needs and List of
Respondents:
Figure 1: Questionnaire:
[See PDF for image]
[End of figure]
Survey Results:
Table 3: 1. Data on households and individuals: Please indicate the
priority you would place on taking the following actions to improve
retirement income data.
Increase support for longitudinal studies of individuals over 50 years
of age, such as the HRS;
Highest priority (percent): 27.6;
High priority (percent): 40.0;
Medium priority (percent): 23.8;
Low priority (percent): 5.9;
Lowest priority (percent): 2.2;
No opinion (percent): 0.5;
Number of cases: 185.
Expand longitudinal studies of retirement savings of younger
individuals (age 50 or below);
Highest priority (percent): 26.9;
High priority (percent): 39.2;
Medium priority (percent): 24.2;
Low priority (percent): 7.5;
Lowest priority (percent): 1.6;
No opinion (percent): 0.5;
Number of cases: 186.
Increase support for other studies of households and individuals‘
retirement and wealth, such as the SIPP, and the SCF;
Highest priority (percent): 18.2;
High priority (percent): 28.3;
Medium priority (percent): 40.6;
Low priority (percent): 10.7;
Lowest priority (percent): 1.1;
No opinion (percent): 1.1;
Number of cases: 187.
Improve measurement of family and household consumption expenditures in
surveys such as the CEX and in panel surveys such as HRS;
Highest priority (percent): 15.2;
High priority (percent): 33.2;
Medium priority (percent): 32.1;
Low priority (percent): 12.0;
Lowest priority (percent): 6.0;
No opinion (percent): 1.6;
Number of cases: 184.
[End of table]
Table 4: 2. Data on employers and employee benefits: Please indicate
the priority you would place on taking the following actions to improve
retirement income data.
Improve the design and reporting of retirement income-related data from
employers, such as mandatory pension plan disclosures and surveys on
benefit plan offerings;
Highest priority (percent): 33.0;
High priority (percent): 31.4;
Medium priority (percent): 25.0;
Low priority (percent): 8.0;
Lowest priority (percent): 1.6;
No opinion (percent): 1.1;
Number of cases: 188.
Conduct research on labor demand for older workers and the factors that
may affect that demand;
Highest priority (percent): 13.8;
High priority (percent): 28.2;
Medium priority (percent): 31.9;
Low priority (percent): 19.1;
Lowest priority (percent): 6.4;
No opinion (percent): 0.5;
Number of cases: 188.
Conduct a longitudinal survey of employers and their workers;
Highest priority (percent): 14.0;
High priority (percent): 25.3;
Medium priority (percent): 33.9;
Low priority (percent): 21.5;
Lowest priority (percent): 3.2;
No opinion (percent): 2.2;
Number of cases: 186.
Improve data from the employers of respondents in surveys such as the
HRS, and the AHEAD;
Highest priority (percent): 30.1;
High priority (percent): 35.5;
Medium priority (percent): 21.9;
Low priority (percent): 7.1;
Lowest priority (percent): 2.2;
No opinion (percent): 3.3;
Number of cases: 183.
[End of table]
Table 5: 3. Other areas for improvement: Please indicate the priority
you would place on taking the following actions to improve retirement
income data.
Improve national data on aggregate retirement and non retirement assets
such as Flow of Funds, and National Income and Product Accounts;
Highest priority (percent): 9.2;
High priority (percent): 20.0;
Medium priority (percent): 30.3;
Low priority (percent): 28.6;
Lowest priority (percent): 8.1;
No opinion (percent): 3.8;
Number of cases: 185.
Improve matching of survey respondents with key administrative records,
while protecting confidentiality;
Highest priority (percent): 45.2;
High priority (percent): 30.1;
Medium priority (percent): 14.5;
Low priority (percent): 5.4;
Lowest priority (percent): 2.2;
No opinion (percent): 2.7;
Number of cases: 186.
Increase researchers‘ access to datasets on individuals or households
matched with administrative data sets;
Highest priority (percent): 56.8;
High priority (percent): 25.1;
Medium priority (percent): 9.8;
Low priority (percent): 4.4;
Lowest priority (percent): 2.7;
No opinion (percent): 1.1;
Number of cases: 183.
Improve collaboration between agencies and researchers to improve
questionnaires and data collection and dissemination practices;
Highest priority (percent): 24.1;
High priority (percent): 40.1;
Medium priority (percent): 27.3;
Low priority (percent): 7.0;
Lowest priority (percent): 0.5;
No opinion (percent): 1.1;
Number of cases: 187.
[End of table]
Table 6: 4. Crosscutting actions: Please indicate the priority you
would place on taking the following actions to improve retirement
income data.
Collect additional data in existing surveys;
Highest priority
(percent): 23.0;
High priority
(percent): 36.1;
Medium priority
(percent): 31.1;
Low priority
(percent): 6.6;
Lowest priority
(percent): 0.5;
No opinion
(percent): 2.7;
Number
of cases: 183.
Begin new surveys;
Highest priority
(percent): 4.0;
High priority
(percent): 14.7;
Medium priority
(percent): 29.9;
Low priority
(percent): 35.0;
Lowest priority
(percent): 13.6;
No opinion
(percent): 2.8;
Number
of cases: 177.
Improve the quality of existing surveys;
Highest priority
(percent): 25.7;
High priority
(percent): 44.3;
Medium priority
(percent): 22.4;
Low priority
(percent): 2.7;
Lowest priority
(percent): 2.2;
No opinion
(percent): 2.7;
Number
of cases: 183.
Improve the timeliness of existing data;
Highest priority
(percent): 21.6;
High priority
(percent): 33.0;
Medium priority
(percent): 24.9;
Low priority
(percent): 14.1;
Lowest priority
(percent): 4.3;
No opinion
(percent): 2.2;
Number
of cases: 185.
Improve researchers‘ access to existing administrative data, such as
Social Security earnings records or Medicare records;
Highest priority
(percent): 50.8;
High priority
(percent): 28.6;
Medium priority
(percent): 13.5;
Low priority
(percent): 3.8;
Lowest priority
(percent): 2.2;
No opinion
(percent): 1.1;
Number
of cases: 185.
Improve techniques for protecting the privacy of respondents‘ survey
and administrative data;
Highest priority
(percent): 20.5;
High priority
(percent): 22.2;
Medium priority
(percent): 34.1;
Low priority
(percent): 16.2;
Lowest priority
(percent): 3.2;
No opinion
(percent): 3.8;
Number
of cases: 185.
Fund research on retirement income and wealth;
Highest priority
(percent): 28.1;
High priority
(percent): 38.9;
Medium priority
(percent): 22.7;
Low priority
(percent): 7.6;
Lowest priority
(percent): 1.6;
No opinion
(percent): 1.1;
Number
of cases: 185.
Fund expanded data collection efforts;
Highest priority
(percent): 18.4;
High priority
(percent): 45.3;
Medium priority
(percent): 27.4;
Low priority
(percent): 5.0;
Lowest priority
(percent): 1.7;
No opinion
(percent): 2.2;
Number
of cases: 179.
Fund increased or improved matching of data; Highest priority
(percent): 31.1;
High priority
(percent): 37.3;
Medium priority
(percent): 22.0;
Low priority
(percent): 5.6;
Lowest priority
(percent): 1.7;
No opinion
(percent): 2.3;
Number
of cases: 177.
Fund new or improved modeling efforts; Highest priority
(percent): 11.7;
High priority
(percent): 18.4;
Medium priority
(percent): 40.8;
Low priority
(percent): 20.7;
Lowest priority
(percent): 6.1;
No opinion
(percent): 2.2;
Number
of cases: 179.
[End of table]
Table 7: 5. Are there other types of actions that are important for
improving the availability, timeliness, or quality of retirement income
and wealth data?
Percent writing comments: 43.2; Number of cases: 190.
[End of table]
Figure 2: 6. Which of the following describe the way that you work with
retirement income and wealth data? (Check all that apply.):
(Continued From Previous Page)
Data collection and/or data management; Percent
checking: 26.7; Number of cases: 187.
Primary data analysis; Percent
checking: 53.5; Number of cases: 187.
Secondary data analysis; Percent
checking: 58.8; Number of cases: 187.
Policy analysis or development; Percent
checking: 74.3; Number of cases: 187.
Other; Percent
checking: 9.1; Number of cases: 187.
6a. If you checked …other‘ (above), please specify the way you work
with retirement income data in the text box below.; Percent
checking: 100; Number
of cases: 17.
[See PDF for image]
[End of figure]
[End of table]
Table 8: 7. Which of the following describes your affiliation?
Federal government; Percent
checking: 18.0; Number
of cases: 189.
State or local government; Percent
checking: 0.0; Number
of cases: 189.
University or college; Percent
checking: 48.7; Number
of cases: 189.
Other not-for-profit organization; Percent
checking: 24.3; Number
of cases: 189.
Private for profit organization; Percent
checking: 7.4; Number
of cases: 189.
Other; Percent
checking: 1.6; Number
of cases: 189.
7a. If you checked ’other“ (above), please
specify your affiliation in the text
box below.; Percent
checking: 66.7; Number
of cases: 3.
[End of table]
Table 9: 8. Which of the following data sets have you used in your work
during the past 5 years? (Check all that apply.):
AHEAD; Percent
checking: 20.1; Number
of cases: 184.
CEX; Percent
checking: 35.9; Number
of cases: 184.
CPS; Percent
checking: 76.6; Number
of cases: 184.
Flow of funds data; Percent
checking: 30.4; Number
of cases: 184.
HRS; Percent
checking: 63.6; Number
of cases: 184.
IRS Form 5500 data; Percent
checking: 38.0; Number
of cases: 184.
NCS (incorporating the Employee Benefits Survey; Percent
checking: 17.9; Number
of cases: 184.
National Income and Product Accounts data; Percent
checking: 35.9; Number
of cases: 184.
PSID; Percent
checking: 35.9; Number
of cases: 184.
SSA administrative files; Percent
checking: 36.4; Number
of cases: 184.
SCF; Percent
checking: 47.3; Number
of cases: 184.
SIPP; Percent
checking: 51.1; Number
of cases: 184.
Other; Percent
checking: 21.7; Number
of cases: 184.
8a. If you checked ’other“ (above), please
specify the data sets in the text box below.; Percent
checking: 100; Number
of cases: 40.
[End of table]
Table 10: Additional comments: If you would like to make additional
comments concerning any topic covered in this questionnaire, please
enter them in the textbox below.
Percent writing comments: 14.7; Number of cases: 190.
[End of table]
List of Respondents
to the Survey:
Henry J. Aaron
The Brookings Institution:
Julie Agnew
College of William and Mary:
John Ameriks
TIAA-CREF Institute:
Joseph M. Anderson
Capital Research Associates:
Kenneth Apfel
University of Texas at Austin:
Katherine Baicker
Dartmouth College:
Vickie Bajtelsmit
Colorado State University:
Dean Baker
Center for Economic and Policy Research:
Laurel Beedon
Public Policy Institute, AARP:
Dan Beller
Employee Benefits Security Administration:
Department of Labor:
Keith A. Bender
University of Wisconsin-Milwaukee:
Mark C. Berger
University of Kentucky:
B. Douglas Bernheim
Stanford University:
Merton C. Bernstein
Washington University:
Joydeep Bhattacharya
Iowa State University:
Andrew Biggs
Cato Institute:
Emily Blank
Howard University:
Robert B. Blancato
Matz, Blancato & Associates, Inc.
Henning Bohn
University of California - Santa Barbara:
Christopher M. Bone
Actuarial Science Associates:
Barry P. Bosworth
The Brookings Institution:
Linda Smith Brothers
University of Wisconsin - Madison:
Charlie Brown
University of Michigan:
Jeffrey Brown
Harvard University:
Richard V. Burkhauser
Cornell University:
Gary Burtless
The Brookings Institution:
John Y. Campbell
Harvard University:
William J. Carrington
Welch Consulting:
Yung-Ping Chen
University of Massachusetts Boston:
Constance F. Citro
National Research Council:
Robert L. Clark
North Carolina State University:
Denise M. Clark
Feder Semo Clark & Bard, P.C.
Joao Cocco
London Business School:
Lee Cohen
Social Security Administration:
Steven B. Cohen
Agency for Healthcare Research and Quality|
Department of Health and Human Services:
Courtney C. Coile
Wellesley College:
Craig Copeland
EBRI:
Christopher Cornwell
University of Georgia:
Julia Lynn Coronado
Federal Reserve Board:
David Cutler
Harvard University:
Kimberly Darling
SAG Corporation:
Angus Deaton
Princeton University:
Jeff Dominitz
Carnegie Mellon University:
Stuart Dorsey
Baker University:
Karen Dynan
Federal Reserve Board:
Ryan D. Edwards
Stanford University:
Douglas W. Elmendorf
Federal Reserve Board:
Gary V. Engelhardt
Syracuse University:
Eric M. Engen
American Enterprise Institute:
William E. Even
Miami University:
Jeff Faux
Economic Policy Institute:
Melissa Favreault
Urban Institute:
Karen W. Ferguson
Pension Rights Center:
Douglas Fore
TIAA-CREF Institute:
Jonathan Barry Forman
University of Oklahoma:
Leora Friedberg
University of Virginia:
Robert B. Friedland
Georgetown University:
Don Fullerton
University of Texas at Austin:
William G. Gale
The Brookings Institution:
Ron Gebhardtsbauer
American Academy of Actuaries:
Thomas Glass
Glass & Co. CPAs:
Jagdeesh Gokhale
Federal Reserve Bank of Cleveland:
Carol Gold
Internal Revenue Service:
Nancy M. Gordon
Census Bureau, Department of Commerce:
Pierre-Olivier Gourinchas
Princeton University:
Brian Graff
American Capital Strategies:
Matthew Greenwald
Matthew Greenwald & Associates, Inc.
Lijia Guo
University of Central Florida:
Alan L. Gustman
Dartmouth College:
Steven Haider
RAND:
Eric Hanushek
Stanford University:
Brian Headd
Small Business Administration:
Joni Hersch
Harvard University:
Roger Hickey
Institute for America‘s Future:
Catherine Hill
National Academy of Social Insurance:
Richard Hinz
World Bank (formerly, Department of Labor):
Lorrie L. Hoffman
University of Central Florida:
Karen C. Holden
University of Wisconsin-Madison:
Sarah Holden
Investment Company Institute:
Kevin M. Hollenbeck
W.E. Upjohn Institute:
Martin Holmer
Policy Simulation Group:
Marjorie Honig
City University of New York:
M. Cindy Hounsell
Women‘s Institute for a Secure Retirement:
Warren Hrung
Department of the Treasury:
Michael D. Hurd
RAND:
Edwin C. Hustead
The Hay Group:
Robert M. Hutchens
Cornell University:
Howard M. Iams
Social Security Administration:
Estelle James
Consultant:
David C. John
Heritage Foundation:
Richard W. Johnson
Urban Institute:
David Joulfaian
Department of the Treasury:
F. Thomas Juster
University of Michigan:
Arthur B. Kennickell
Federal Reserve Board:
Surachai Khitatrakun
University of Wisconsin-Madison:
Kilolo Kijakazi
Center on Budget and Policy Priorities:
Geoffrey Kollmann
Congressional Research Service:
Sophie M. Korczyk
Analytical Services:
Marvin H. Kosters
American Enterprise Institute:
Douglas L. Kruse
Rutgers University:
Julia Lane
Urban Institute:
Annamaria Lasardi
Dartmouth College:
Ronald Lee
University of California, Berkeley:
Jules Lichtenstein
AARP:
Jeffrey B. Liebman
Harvard University:
Dennis Logue
Price College:
Robin Lumsdaine
Brown University:
David A. Macpherson
Florida State University:
Brigitte C. Madrian
University of Chicago:
Joyce Manchester
Social Security Administration:
Charles F. Manski
Northwestern University:
Ann A. McDermed
North Carolina State University:
Andrew Metrick
University of Pennsylvania:
Daniel J. Mitchell
Heritage Foundation:
Olivia S. Mitchell
University of Pennsylvania:
H. Fred Mittelstaedt
University of Notre Dame:
Catherine Phillips Montalto
Ohio State University:
James H. Moore
Social Security Administration:
Kathryn L. Moore
University of Kentucky:
Brent R. Moulton
Bureau of Economic Analysis, Department of Commerce:
James Musumeci
Southern Illinois University at Carbondale:
Randall J. Olsen
Ohio State University:
Van Doorn Ooms
Committee for Economic Development:
Peter R. Orszag
The Brookings Institution:
Beverly J. Orth
William M. Mercer, Inc:
Michael Packard
Pension Benefit Guaranty Corporation:
Michael G. Palumbo
Federal Reserve Board:
Constantijn W. A. Panis
RAND:
Jonathan A. Parker
Princeton University:
Donald O. Parsons
George Washington University:
Christina Paxson
Princeton University:
Cynthia D. Perry
Massachusetts Institute of Technology:
Pamela J. Perun
Urban Institute:
Joseph S. Piacentini
Employee Benefits Security Administration:
Department of Labor:
Christopher Polk
Northwestern University:
James Poterba
Massachusetts Institute of Technology:
Elizabeth T. Powers
University of Illinois at Urbana-Champaign:
Patrick J. Purcell
Congressional Research Service:
John W. R. Phillips
Social Security Administration:
Anna M. Rappaport
William M. Mercer, Inc.
Robert R. Reed III
University of Kentucky:
Cordelia W. Reimers
Hunter College:
John C. Rother
AARP:
John E. Sabelhaus
Congressional Budget Office:
Dallas L. Salisbury
EBRI:
Andrew A. Samwick
Dartmouth College:
Thomas R. Saving
Texas A & M University:
Patricia L. Scahill
Ernst & Young LLP:
Sylvester J. Schieber
Watson Wyatt Worldwide:
Robert F. Schoeni
University of Michigan:
James H. Schultz
Brandeis University (retired):
John C. Scott
American Benefits Council:
Lois B. Shaw
Institute for Women‘s Policy Research:
Stuart A. Sirkin
Pension Benefit Guaranty Corporation:
Jonathan S. Skinner
Dartmouth College:
Timothy A. Smeeding
Syracuse University:
Kent Smetters
Wharton School:
Karen E. Smith
Urban Institute:
James P. Smith
RAND:
Paul Smith
Department of the Treasury:
Ralph Smith
Congressional Budget Office:
Frank P. Stafford
University of Michigan:
Norman Stein
University of Alabama:
Thomas L. Steinmeier
Texas Tech University:
C. Eugene Steuerle
Urban Institute:
Ann Huff Stevens
Yale University:
Annika E. Sundén
Boston College:
Richard M. Suzman
National Institute on Aging:
Kenn B. Tacchino
Widener University:
Albert Teplin
Federal Reserve Board (Retired):
Lawrence H. Thompson
Urban Institute:
Shripad Tuljapurkar
Mountain View Research:
Cori E. Uccello
Urban Institute:
Jack L. VanDerhei
Temple University:
Steven F. Venti
Dartmouth College:
Alice Wade
Social Security Administration:
Daniel Weinberg
Census Bureau, Dept. of Commerce:
David R. Weir
University of Michigan:
Joseph White
Case Western Reserve University:
William J. Wiatrowski
Bureau of Labor Statistics, Department of Labor:
Joshua L. Wiener
Oklahoma State University:
Ernest Wilcox
Bureau of Economic Analysis, Department of Commerce:
Samuel H. Williamson
Miami University:
Robert J. Willis
University of Michigan:
Doug A. Wolf
Syracuse University:
Aliya Wong
Thelen Reid & Priest, LLP:
Jing Jian Xiao
University of Rhode Island:
Paul J. Yakoboski
American Council of Life Insurers:
Sheila R. Zedlewski
Urban Institute:
Stephen P. Zeldes
Columbia University:
[End of section]
Appendix IV: Views of GAO‘s Expert Panel on Retirement Income Data
Needs:
This appendix provides the summary of discussion by members of an
expert panel that we convened on retirement income data needs on
September 10, 2002. The panel consisted of 11 nationally recognized
experts who, during a day-long meeting, discussed the issues the
federal government should address in order to improve the quality of
retirement income data statistics. All the ideas presented in this
appendix may not represent the view of every member of the panel.
Moreover, these ideas should not be considered to be our views.
Members of Our Expert Panel:
The following individuals were members of our expert panel on
retirement income data:
* Eric Engen, Resident Scholar, The American Enterprise Institute:
* Melissa Favreault, Research Associate, The Urban Institute:
* Nancy Gordon, Associate Director for Demographic Programs, US Census
Bureau:
* Alan Gustman, Professor of Economics, Dartmouth College:
* Richard Hinz, Chief Economist and Director of Policy and Research,
EBSA, Department of Labor (now at the World Bank):
* Howard Iams, Director, Division of Policy Evaluation, Office of
Policy, Social Security Administration:
* John Sabelhaus, Unit Chief, Long-Term Modeling Group, Congressional
Budget Office:
* Dallas Salisbury, President, Employee Benefit Research Institute:
* Jack VanDerhei, Associate Professor, Department of Risk, Insurance &
Healthcare Management, Fox School of Business and Management, Temple
University:
* William Wiatrowski, Chief, Compensation Data Analysis and Planning
Division, Bureau of Labor Statistics, Department of Labor:
* Robert Willis, Professor of Economics, Institute for Social Research,
University of Michigan:
Views of the Panelists:
The panel members discussed a number of issues the federal government
needs to address in order to improve the quality of retirement income
statistics. Specifically, panelists discussed actions and strategies
the federal government could undertake related to (1) improving
matching of survey and administrative data, (2) improving access to
administrative data, and (3) improving the quality of employer data.
Need for Better Matched Data:
Panelists said that a significant amount of the needed information
about American workers and pension behavior is already being collected
in government and private surveys and government administrative
reports. While no one single survey or report collects all the pension
information panels expressed interest in, they said that some household
surveys could be linked with administrative report data from employers.
Specifically, panelists discussed the following:
* The Survey of Income and Program Participation (SIPP) a household
survey conducted by the Bureau of the Census, has information on
demographic characteristics, labor force participation, and detailed
information on income, including some basic pension information. The
SIPP does not gather detailed information about the characteristics of
these pensions.[Footnote 44]
* Summary Plan Descriptions (SPD), prepared by employers as required
under ERISA, provide detailed information about the characteristics of
the pension plans that they provide to their employees.
* In the past, the Health and Retirement Study (HRS), which is
primarily a household survey conducted by the University of Michigan,
has matched survey data from households who permitted the Social
Security Administration to provide Social Security earnings records and
benefit records, the National Death Index, and to Medicare records for
those individuals who are Medicare eligible. HRS records also have been
matched to SPDs obtained either from Labor or from employers.
* The panelists were interested in the information available from the
1979 National Longitudinal Survey, which is sponsored by the Bureau of
Labor Statistics and gathers a wide range of information over a long
time period. Panelists felt that this information could be potentially
be useful because the participants, who initially participated as
youth, are now approaching retirement age, which would give researchers
access to a lifetime of data.
* In addition to matching currently being done, some panelists said
that they were interested in matching existing pension information to
other sources of employer information and public financial data, such
as information from reports filed with the SEC and available, for
example, from Compustat.
Limitations on Access to Data:
Members of our expert panel felt that there are several sources of
administrative data that could give researchers valuable information,
especially those that could be linked, but legal and logistic
restrictions and limitations prevent access to some of this pension
data. Specifically, panelists discussed different types of limitations
to access.
Legal Restrictions:
* The Federal Code Title 13, Section 9 sets very specific limitations
on the access to any data identifying individuals gathered by the
Census Bureau and any data that are linked to Census data has the Title
13 limitation ’attached“ to it as a result.[Footnote 45]
* Individual records from the IRS have some access restrictions similar
to those of the Census Bureau except that legislation allows specified
agencies access to certain tax return records.[Footnote 46]
* As a result of amendments to ERISA legislation SPDs are no longer
routinely collected by Labor.
Fragmented Retirement Data Responsibilities Contributes to Data
Shortcomings:
* The responsibility for gathering and analyzing pension data is
fragmented between different government agencies. There is no central
agency responsible for retirement data - it is fragmented between the
Pension Benefit Guaranty Corporation, Labor and IRS. As a result,
individual agencies do not have the incentive to provide access to
information or to collect statistics for research purposes.
* While Labor‘s regulations specify that employers must supply SPDs if
requested, it does not specify that employers must have a copy of the
SPDs. As a result, researchers who request SPDs from employers are
frequently told that the Plan Administrator has the documents. The Plan
Administrators in turn tell researchers that they have no authority for
providing them to anyone except plan participants.
* Since 1980, OMB‘s Office of Information and Regulatory Affairs has
provided government wide leadership and oversight of efforts to reduce
the burden on respondents to government information collection,
including statistical surveys“. This ’reduction“ effort has meant that
some research data previously collected in administrative reports has
been eliminated.
Other Suggestions for Improving Access to Data:
The expert panelists made many suggestions for improving access to
pension data. More specifically, panelists discussed the following:
* It was suggested that agencies with access to data, such as Labor,
take advantage of improvements in technology to require and provide
electronic copies of Form 5500s and SPDs.
* Panel experts suggested that some sort of license be issued for
research vehicles (such as the SCF, the SIPP and the HRS) to have legal
access to employer pension information, provided that they take
measures to ensure confidentiality.[Footnote 47]
* Panelists suggested creating more research data centers to match
otherwise restricted data, including Census Bureau data. They suggested
changing legislation so that the Census Bureau‘s data would not make
everything subject to Title 13. The Census Bureau, however, is
concerned about possible reidentification issues.[Footnote 48]
* Panelists suggested studying more closely the Census Bureau‘s results
in its experimentation with the development of ’synthetic data“ in the
LEHD program, a technique in which many relationships between variables
are maintained in a data set, but in a manner that makes it impossible
to identify specific individuals.[Footnote 49] Panelists also
cautioned, however, that in many cases these techniques are not
workable and researchers will need access to the original survey data.
Restricted Access Sites Have Provided Some Increased Opportunities for
Access to Survey Records and Matched Files:
Experts discussed research data centers, operated by several Federal
agencies and private survey organizations, as an effective technique to
make data not available because of confidentiality restrictions more
available to researchers, but with certain restrictions. While the data
centers provide opportunities for conducting research with survey
records or matching records between surveys or with administrative
records, experts said that there are limitations to the data centers,
which make data much more difficult to access. Specifically, panelists
discussed the following:
* Restricted access sites are a useful means of allowing confidential
information to be accessed by researchers, subject to certain
restrictions.
* A federal storage data center where a number of federal data sets
could be brought together could allow agencies to share some otherwise
inaccessible information.
* Data centers could aid the work that researchers are doing by storing
research already conducted in the data center.
* The Census Bureau, which operates Research Data Centers in eight
locations throughout the country, allows researchers with pre-approved
projects to use confidential economic and demographic survey data, such
as SIPP, for which either no public-use version is available, or the
public-use version does not contain the information required by the
researcher. While researchers can access these data at the centers,
they are not allowed to remove individual records from the data center.
This restriction prohibits researchers from matching Census Bureau data
with data sets available to researchers, unless those data are imported
into the data center.
* BLS has a similar data center located in Washington, D.C. in which
data extracted from SPDs collected as part of the National Compensation
Survey are stored. As with the Census Bureau centers, there are
limitations on who can access this information and restrictions on
removing data from the data center.
* Because confidential data cannot be removed from either the BLS or
the Census Bureau data centers, it is currently not possible for
researchers to match data sets from the two agencies.
More Employer Information Needed on the Value and Provisions of
Employer-Provided Pensions:
There was wide agreement on the panel that greater access to employer
information was needed to accurately capture the value and provisions
of employer-provided pensions. More specifically, panelists discussed
the following:
* Employee-provided information about pensions is not a viable source
because individuals often do not have a good understanding of the value
or characteristics of pensions. In addition, agencies expressed concern
about the impact of additional questions on nonresponse, and it may be
difficult to obtain OMB approval for adding questions to statistical
surveys or to administrative reports.
* Valuable information on the value and characteristics of employer
pension information is already collected by the Department of Labor on
the Form 5500s.
* Through the LEHD program, the Census Bureau has been trying to link
together employer information with data from surveys.
* Agencies have concerns about maintaining the privacy and
confidentiality of data. For example, there was concern that linking
SIPP information about individuals with Form 5500 files or summary plan
descriptions could facilitate the reidentification of individual data
reported to the Census Bureau. As a result, those linked data would be
available only within the data centers.
[End of section]
Appendix V: Characteristics of Selected Surveys for Analysis of
Retirement Income and Wealth:
Below is a table highlighting some of the features of selected surveys
pertinent to the analysis of retirement income and projection of future
retirees‘ income.[Footnote 50]
Table 11: Summary Table of Selected Survey Data Sources:
[See PDF for image
[End of table]
[End of section]
Appendix VI: Comments from the Department of Commerce:
THE SECRETARY OF COMMERCE Washington, D.C. 20230:
MAR 4 2003:
Ms. Barbara D. Bovbjerg, Director Education, Workforce, and Income
Security Issues:
U.S. General Accounting Office Washington, DC 20548:
Dear Ms. Bovbjerg:
The U.S. Department of Commerce appreciates the opportunity to comment
on the General Accounting Office‘s draft report entitled Retirement
Income Data: Improvements Could Better Support Analysis of Future
Retirees‘ Prospects. The Department of Commerce has no major comments
to the report. However, we have enclosed suggestions for clarifying the
report.
Sincerel:
Donald L. Evans:
Enclosure:
[End of section]
Appendix VII: Comments from the Department of Labor:
U.S. Department of Labor
200 Constitution Avenue, NW Washington D.C. 20210:
March 12, 2003:
Ms. Barbara D. Bovbjerg Director:
Education, Workforce, and Income Security Issues United States General
Accounting Office 441 G Street, N.W., Room 5930 Washington, D.C. 20548:
Dear Ms. Bovbjerg:
We have reviewed the draft report prepared by the General Accounting
Office (GAO) entitled, Retirement Income Data: Improvements Could
Better Support Analysis of Future Retirees‘ Prospects (GAO-03-337).
Based upon our review of the report, we are providing you with the
following comments. Technical comments have already been provided
directly to your staff.
GAO Recommendation Number 1: ’To help provide the data needed to inform
important policy decisions concerning retirement programs, the
Secretary of Labor should direct the Bureau of Labor Statistics (BLS)
to prepare a plan to improve data for analyzing retirement income and
wealth in coordination with ... [other agencies,“:
Experience indicates that there are a number of concerns that must be
recognized in attempting the types of coordination called for in this
recommendation. Much of the coordination that retirement income
researchers have suggested involves linking data that typically are
collected from individuals (such as demographics and wealth
accumulation) with data typically collected from employers (such as
details of retirement benefit plans and the costs associated with those
plans). Past efforts at coordination of these types of data from
employers and employees by different agencies have had only limited
success, due to privacy concerns and other issues.
Coordination activities such as those recommended that have taken place
in the past have often concluded that different surveys exist because
they have - quite appropriately -different missions. For example,
surveys of employer-provided retirement income benefits conducted by
BLS are part of the Bureau‘s mission to report on all types of
compensation provided to persons in the labor force. Surveys conducted
by other agencies may be directed toward total wealth accumulation by
individuals or toward all sources of retirement income, regardless of
whether the income comes from an employer-sponsored plan. The
operational, statistical, and data confidentiality environments of
these different data-gathering programs make coordination of surveys a
daunting task.
Further, the type of planning and coordination activities envisioned in
the recommendation usually are the purview of the Office of Management
and Budget‘s Office of Statistical Policy. BLS and other statistical
agencies routinely participate in such activities as envisioned in this
GAO recommendation under OMB direction. BLS could participate in the
coordination effort as described in the recommendation, but the extra
demands placed on staff will not be negligible.
GAO Recommendation Number 2: ’To facilitate plan participants‘
beneficiaries‘ and analysts‘ timely access to information about
employer-provided pension plans the Secretary of Labor should obtain
from plan administrators electronic films of all SPDs and summaries of
material modifications required by ERISA and make them publicly
available in electronic form.“:
Although the recommendation that the Employee Benefits Security
Administration (EBSA)I resume the collection of SPDs in electronic form
could help BLS in its attempt to obtain plan provision data, especially
if there were a standard electronic format for such documents, as
discussed below there are various problems associated with implementing
such a requirement.
The recommendation that EBSA resume the collection of summary plan
descriptions is at odds with amendments to ERISA enacted just six years
ago as part of the Taxpayer Relief Act of 1997 (TRA‘97). As noted in
GAO‘s draft report, TRA‘97 amended ERISA to eliminate the requirement
to file copies of summary plan descriptions and summaries of plan
changes (collectively SPDs) with EBSA. Congress also eliminated the
related requirement that EBSA make those documents available to the
public in its public disclosure room. Although TRA‘97 preserved EBSA‘s
authority to make individual requests for copies of SPDs from plan
administrators, that authority would not support re-imposition of a
general SPD filing requirement. Furthermore, EBSA issued final
regulations in 2002 implementing its authority to request SPDs, and
reiterated in the preamble that EBSA generally intends to limit the
exercise of its authority to requesting SPDs on behalf of participants
and beneficiaries.
EBSA‘s experience with pre-TRA‘97 SPD filings indicated that there was
insufficient public interest in obtaining copies of SPDs from EBSA‘s
public disclosure room to justify the compliance costs and burdens
placed on plans. While EBSA maintained approximately 2 million SPDs and
received over 150,000 SPDs and related documents annually before the
filing requirement was eliminated by TRA‘97, we received only
approximately 1,000 requests for SPDs in an average year. The
requesters included participants and beneficiaries, other governmental
agencies, congressional offices, media representatives, and others.
Accordingly, based on EBSA‘s pre-1997 experience, there did not appear
to be broad-based interest in SPDs on file and analysts generally did
not appear to treat the collection as a valuable source of research
data. This situation was due in large part to shortcomings in the type
of detail, consistency, and timeliness of SPDs that would be required
for it to be a useful analytic tool. For example, BLS‘ experience with
the collection of SPDs and other data on employer-sponsored retirement
plans indicates that those representatives of employers who are
interviewed by BLS staff often do not have sufficient knowledge of the
plan to be able to provide the desired information. Comparisons of
information contained in SPDs with information provided by survey
respondents often yield discrepancies because of the wide variety of
plan designs and descriptions adopted by plan sponsors.
Although EBSA establishes content as well as readability and similar
format requirements for SPDs, EBSA is statutorily precluded from
requiring SPDs be submitted on prescribed forms. An underlying
rationale was that administrators needed flexibility to present plan
information in a manner best suited to the particular workplace and
workforce involved. Due to the resulting diversity that exists among
SPDs, having copies of SPDs on file, even in electronic form, might not
provide a usable research database.
Another shortcoming with the SPD filing requirement recommendation is
that EBSA could not give requesters any assurances that the information
on file was up to date due to ERISA‘s provisions which allow summaries
of pension plan changes to be furnished up to 210 days after the end of
the plan year in which a plan amendment or change is adopted. An
electronic filing requirement would suffer from the same shortcoming.
The GAO report suggests an electronic filing requirement would
facilitate timely access to information by plan participants and
beneficiaries, however, EBSA expects that a very small number of
participants and beneficiaries will ask for SPDs because ERISA already
requires plan administrators to automatically furnish SPDs to
participants and beneficiaries within specified time limits set by
statute in ERISA. Administrators are also required to provide
additional copies of SPDs to participants and beneficiaries on request.
Further, if the participant or beneficiary wanted an up to date copy of
the SPD, EBSA would still be required to communicate with the plan
administrator to determine whether the copy we had on file was current
because of the above noted time lag allowed for distributing
information about pension plan changes.
Implementing GAO‘s recommendations would impose costs and burdens on
employee benefit plans to maintain and file electronic SPDs as well as
EBSA to establish a system capable of receiving, storing, and
disclosing the electronically filed documents. Under current law, there
is no requirement that plan administrators prepare SPDs in electronic
form. Although EBSA published regulations in April 2002 designed to
encourage the use of new technologies for disclosing information
electronically to plan participants, we did not require that plan‘s
maintain electronic versions of their SPDs. Such a mandate would have
to be imposed to implement GAO‘s recommendation. Also, to accommodate
such an electronic filing requirement, EBSA would have to develop and
operate a system to receive, process, store and retrieve the electronic
SPDs. The GAO report does not include estimates of the costs and
burdens an electronic filing requirement would impose on plan
administrators and EBSA. At the time the SPD filing requirement was
eliminated, we estimated the change would reduce the aggregate
reporting burden on plans, many of which were maintained by small
employers, by approximately 150,000 burden hours per year.
GAO Recommendation Number 3 : ’For plans in place before these new
filing requirements go into effect and where it is cost-effective the
Secretary of Labor should use existing authority to obtain copies of
summary_ plan descriptions and summaries of material modifications in
cases where analysts working on federally_ conducted or federally-
sponsored research seeks SPDs for statistical purposes. This should
assist analysts of retirement income in obtaining information about the
features of employer-sponsored benefit plans that are not
electronically available.“:
As noted above, EBSA issued final regulations in 2002 implementing its
authority to request SPDs, and reiterated in the preamble that EBSA
generally intends to limit the exercise of its authority to requesting
SPDs on behalf of participants and beneficiaries. Use of this authority
for collection of SPDs as part of a Federal government survey (such as
those conducted by BLS) may be hampered by confidentiality restrictions
placed on the identity of survey respondents.
In closing, the Department supports exploring less burdensome and more
effective means of addressing the shortcomings in available data
identified by GAO‘s Expert Panel. We agree that Congress, federal
agencies, researchers, and others in the private sector need accurate
data to assess employee benefit, tax, and economic trends and policies.
Rather than reinstating an electronic variant of an SPD filing
requirement, the Department would support an effort to identify
alternative sources of such employee benefit plan information and ways
to make that information available to researchers.
Thank you for providing us with an opportunity to comment on your draft
report.
Ann L. Combs Assistant Secretary Employee Benefits Security
Administration:
Kathleen P. Utgoff Commissioner Bureau of Labor Statistics:
Signed by Ann L. Combs and Kathleen P. Utgoff:
[1] EBSA was formerly the Pension and Welfare Benefits Administration.
[2] The GAO electronic filing recommendation appears to repeat a
comment from a 1993 GAO ’Report to Congressional Requesters on
Management Reform“ entitled ’GAO‘s Comments on the National Performance
Review‘s Recommendations, ’ GAO/OCG-94-1. One of the NPR
recommendations was to eliminate the SPD filing and storage
requirements. GAO stated in connection with that recommendation ’[o]ur
work indicates that DOL could reduce costs by reducing or eliminating
storage of Summary Plan Description (SPD) hard copies while continuing
to provide electronic access to SPDs.“ As noted above, however, after
GAO‘s 1993 report, Congress, in 1997 eliminated the SPD filing
requirement without any provision for continuing an electronic
collection program.
[3] The GAO report focuses on data shortcomings related to pension
plans and retirement income. The SPD filing requirement applied more
generally to ERISA-covered pension and welfare plans. Accordingly, the
number of requests for pension plan SPDs would be a smaller subset of
the total annual requests.
[End of section]
Appendix VIII: GAO Contacts and Staff Acknowledgments:
GAO Contacts:
Alicia Puente Cackley (202) 512-7022
Benjamin Pfeiffer (206) 287-4832:
Staff Acknowledgments:
Timothy Fairbanks, Nicholas Larson, Lynn Musser, Emily Pickrell, and
Roger Thomas also contributed to this report.
FOOTNOTES
[1] For a discussion of standards for evaluating retirement income
adequacy, see U.S. General Accounting Office, Social Security:
Program‘s Role in Helping Ensure Income Adequacy, GAO-02-62
(Washington, D.C.: Nov. 30, 2001).
[2] A defined benefit plan is a type of plan where the sponsor provides
a guaranteed benefit generally expressed as monthly benefit based on a
formula that generally combines salary and years of service to the
company.
[3] A defined contribution plan is a type of pension that establishes
individual accounts for employees to which the employer, participants,
or both make periodic contributions. The benefits are based on employer
and participant contributions to and investment returns (gains and
losses) on the individual accounts.
[4] U.S. General Accounting Office, Cash Balance Plans: Implications
for Retirement Income, GAO/HEHS-00-207 (Washington, D.C.: Sept. 29,
2000) and Private Pensions: Implications of Conversions to Cash Balance
Plans, GAO/HEHS-00-185 (Washington, D.C.: Sept. 29, 2000).
[5] The IRS administers and enforces tax code provisions concerning
private pension plans. EBSA enforces Employee Retirement Income
Security Act (ERISA) pension requirements, and the PBGC insures the
benefits of participants in defined benefit pension plans that are
eligible for preferential tax treatment.
[6] For additional information on the Congressional Budget Office‘s
model, see Congress of the United States, Congressional Budget Office,
Uncertainty in Social Security‘s Long-Term Finances: A Stochastic
Analysis (Washington, D.C.: Dec. 2001). The Social Security
Administration and others such as EBRI have supported the development
of other simulation models, such as the Social Security Policy
Simulation Model (SSASIM) to study the effect of changes in the Social
Security program and pension law. More recently the Social Security
Administration and others have supported the development of the GEMINI
model, a policy microsimulation model developed by the Policy
Simulation Group. EBRI has developed its own model, the EBRI Retirement
Income Projection Model.
[7] Constance F. Citro and Eric A. Hanushek, eds., Assessing Policies
for Retirement Income: Needs for Data, Research and Models (Washington,
D.C.: National Academy Press, 1997). The panel was sponsored by Labor‘s
EBSA, the National Institute on Aging, PBGC, the Social Security
Administration, and the Teachers Insurance and Annuity Association-
College Retirement Equities Fund (TIAA-CREF) Institute.
[8] Among other things, the E-Government Act of 2002 (P.L. 103-347)
permits the sharing of information concerning businesses among
designated statistical agencies and provides for additional safeguards
to protect the confidentiality of statistical data collected by all
agencies.
[9] The IRS form titled ’Distributions from Pensions, Annuities,
Retirement or Profit-Sharing Plans, IRAs, Insurance Contracts, etc.“ is
identified as IRS Form 1099-R. The IRS form titled ’IRA and Coverdell
ESA Contribution Information“ is identified as IRS Form 5498.
[10] Alan L. Gustman and Thomas L. Steinmeier, What People Don‘t Know
About Their Pensions and Social Security: An Analysis Using Linked Data
from the Health and Retirement Study (Cambridge, Mass.: National Bureau
of Economic Research, 1999). This paper discusses in detail some of the
problems associated with having respondents provide details of their
own pensions, as opposed to employers directly providing information.
[11] Form 5500 is a disclosure form that private employers with
qualified pension plans are required to file with the IRS, Labor‘s
EBSA, and the PBGC. Schedule SSA to the Form 5500, which is not
publicly disclosable, identifies individuals who leave employment with
deferred vested benefits. The Social Security Administration uses this
information.
[12] The ERISA of 1974 is a federal law that set minimum standards for
pension plans sponsored by private employers. These standards govern
the management, operation, and funding of the plan. Labor‘s EBSA
enforces these ERISA provisions.
[13] U.S. Department of Labor. Pension and Welfare Benefits
Administration, Private Pension Plan Bulletin: Abstract of 1998 Form
5500 Annual Reports, No. 11, Winter 2001-02.
[14] A qualified pension plan is an employer pension plan that receives
preferential tax treatment in exchange for satisfying certain
requirements established in the Internal Revenue Code of 1986.
Employers or employees receive tax benefits for contributions they make
to qualified plans within certain limits. A nonqualified pension plan
is an employer-sponsored pension plan that does not meet these
requirements.
[15] A SEP (402(h) plan is a deferred compensation type retirement plan
that allows employers and employees to make deductible contributions
toward an employee‘s retirement fund. There are specific rules about
contribution and deduction limits, which make the plan easier for a
smaller employer to administer, but less attractive for a larger
employer.
[16] A SIMPLE plan (401(k)(11)) is a deferred compensation type
retirement plan that certain small employers (including self-employed
individuals) can set up for the benefit of their employees.
[17] U.S. General Accounting Office, Pension and Welfare Benefits
Administration: Opportunities Exist for Improving Management of the
Enforcement Program, GAO-02-232 (Washington, D.C.: Mar. 3, 2002).
[18] Vesting refers to when a plan participant has earned a right to a
benefit that cannot be taken away (i.e., a nonforfeitable right to the
participant‘s accrued benefit).
[19] U.S. General Accounting Office, Management Reform: GAO‘s Comments
on the National Performance Review‘s Recommendations, GAO/OCG-94-1
(Washington, D.C.: Dec. 3, 1993).
[20] IRAs authorized by ERISA allow workers to make tax-deductible and
nondeductible contributions to an individual account for retirement
savings.
[21] A rollover contribution is a direct transfer of pension benefits
received as a lump-sum payment to another tax-qualified retirement plan
or an IRA free of taxes. In many cases, however, the IRS forms do not
indicate whether or not distributions were rolled over.
[22] A Roth IRA is a type of individual retirement plan that is similar
to a traditional IRA except that contributions are not tax deductible,
and that qualified distributions are tax free.
[23] Keogh plans are retirement plans for self-employed workers,
authorized by the Self-Employed Individuals Retirement Plan Act of 1962
(P.L. 87-792).
[24] The SIPP data have, for example, been linked with Social Security
earnings records except in cases where respondents were unwilling to
provide their Social Security numbers to the Census Bureau.
[25] SSA statistically matched defined benefit pension plan
characteristics from the Pension Benefit Guarantee Corporation to the
survey responses.
[26] The Federal Interagency Forum on Aging Related Statistics was
established in 1986, with the goal of bringing together federal
agencies that share a common interest in improving aging related data.
Member agencies include: National Institute of Aging, National Center
for Health Statistics, Census Bureau, Administration on Aging, Agency
for Healthcare Research and Quality, BLS, Centers for Medicare and
Medicaid Services, Department of Veterans Affairs, Office of Management
and Budget (OMB), Office of the Assistant Secretary for Planning and
Evaluation in the Health and Human Services Administration, and SSA.
[27] Previous legislation includes the Paperwork Reduction Act of 1980
(P.L. 96-511) and the Paperwork Reduction Reauthorization Act of 1986
(P.L. 99-500).
[28] See 13 U.S.C. 9 and 26 U.S.C. 6103. An exception in 26 U.S.C.
6103(j) authorizes the furnishing of return information to Census ’for
the purpose, but only to the extent necessary in the structuring, of
censuses and—conducting related statistical activities authorized by
law.“
[29] The Census Bureau‘s research data centers are located in
Washington, D.C.; Boston, Massachusetts; Pittsburgh, Pennsylvania; Los
Angeles, California; Berkeley, California; Durham, North Carolina; Ann
Arbor, Michigan; and Chicago, Illinois.
[30] Individuals with access are subject to penalties, including fine
and imprisonment if they disclose any confidential information.
[31] See Eleanor Singer‘s study ’Public Perceptions of Confidentiality
and Attitudes Toward Data Sharing By Federal Agencies“ in
Confidentiality, Disclosure, and Data Access: Theory and Practical
Applications for Statistical Agencies, Pat Doyle, et al., (Amsterdam:
Elsevier Science B.V., 2001). In some cases after controlling for other
factors associated with response rates, such as respondents‘ age, the
length of the form, race, and education, privacy concerns were not
significant predictors of response rates.
[32] B.K. Atrostic et al., ’Nonresponse in U.S. Government Household
Surveys: Consistent Measures, Recent Trends, and New Insights,“ Journal
of Official Statistics, vol. 17 no. 2, 2001, 209-226.
[33] We have discussed options for protecting privacy and
confidentiality while conducting record linkage in U.S. General
Accounting Office, Record Linkage and Privacy: Issues in Creating New
Federal Research and Statistical Information, GAO-01-126SP
(Washington, D.C.: April 2001).
[34] 26 CFR Part 301, Federal Register vol. 68, no. 13, January 21,
2003, p. 2691.The IRS shares responsibility with SSA for protecting the
confidentiality of Social Security earnings records compiled from W-2
forms submitted to the IRS.
[35] Critics of these efforts say that these techniques cannot preserve
all the relationships between variables in a data set. Moreover, the
techniques are not workable for variables, such as the age of
retirement, that do not conform to a simple mathematical pattern. The
frequency at which people retire, for example, is spiked at certain
ages, such as 60, 62, and 65 years of age, which makes it difficult to
summarize the data using a statistical formula. One of our panelists
noted, however, that if only one variable has such characteristics, the
actual data for that variable could be left as long as other variables
were masked.
[36] U.S. Department of Labor, ’Proposed Amendments to Summary Plan
Description Regulations,“ Federal Register, vol. 63, no. 174, September
9, 1998, p. 48384.
[37] We identified these people through literature searches on topics
related to retirement income data and by asking members of our
Retirement Advisory Panel for suggested names and in turn asking them
for additional names.
[38] Constance F. Citro and Eric A. Hanushek, eds., Assessing Policies
for Retirement Income: Needs for Data, Research and Models (Washington,
D.C.: National Academy Press, 1997).
[39] The LEHD program, which was started in 1998, is designed to
evaluate and improve the quality of data collected in the Census
Bureau‘s demographic and economic censuses and surveys through
longitudinal analysis. The program combines longitudinal micro data
from federal and state administrative data on employers and employees
with these census and survey data. In addition to its use to improve
its census and surveys, the Census Bureau conducts policy-relevant
research on labor force and employment issues and creates new data
products. Currently, the LEHD program provides quarterly workforce
indicators for a number of participating states. The linkage of Form
5500 data and Census Bureau establishment data is described in Julia
Lane, et al., ’New Uses of Health and Pension Information: The 5500
file at the Census Bureau, LEHD Technical Paper No. TP-2002-03“
(Washington, D.C.: U.S. Bureau of the Census, January 2002).
[40] Final regulation, ’Disclosure of Return Information to the Bureau
of the Census, Department of the Treasury, Internal Revenue Service, 26
CFR Part 301,“ Federal Register vol. 68, no. 13, January 21, 2003, p.
2691.
[41] Marc I. Roemer, Assessing the Quality of the March Current
Population Survey and the Survey of Income and Program Participation
Income Estimates, 1990-1996, Income Surveys Branch Housing and
Household Economics Statistics Division, U.S. Census Bureau
(Washington, D.C.: June 16, 2000).
[42] U.S. Congressional Budget Office, The Budget and Economic Outlook:
Fiscal Years 2004-13, (Washington, D.C., January 2003), p. 33.
[43] See for example, R. Curtin, F.T. Juster and J. Morgan, ’Survey
Estimates of Wealth: An Assessment of Quality“ in The Measurement of
Saving, Investment and Wealth, R.E. Lipsey and H.S. Tice, editors,
National Bureau of Economic Research, Studies in Income and Wealth, 52
(Chicago: University of Chicago Press, 1989).
[44] While some employee information is gathered from other surveys,
the panel felt that the SIPP survey is extremely important for matching
to administrative records because it gives demographic and labor force
characteristics not available in most administrative record files.
[45] The newly enacted E-Government Act of 2002 (P.L. 107-347) extended
Census type confidentiality restrictions to all data collected in a
federal statistical survey.
[46] See 26 U.S.C. 6103.
[47] Unlike the Census Bureau, some agencies, such as the National
Center for Education Statistics, have authority to use a data license
procedure. Under these licenses, licensees must submit detailed
research plans, sign disclosure protection agreements, and agree to
restrictions similar to those by the Bureau of the Census at their
research data centers. For more detail, see Paul B. Massell and Laura
Zayatz, ’Data Licensing Agreements at U.S. Government agencies and
Research Organizations,“ presented at the International Conference on
Establishment Surveys-II, Buffalo, N.Y., June 17-21, 2000.
[48] Implementation of this suggestion would require changing not only
Title 13 but other laws as well-like the new E-Government Act.
[49] U.S. General Accounting Office, Record Linkage and Privacy: Issues
in Creating New Federal Research and Statistical Information,
GAO-01-126SP (Washington, D.C.: April 2001) p. 88 and Federal Committee
on Statistical Methodology, Report On Statistical Disclosure Limitation
Methodology, Statistical Policy Working Paper, 22 (Washington, D.C.:
May 1994).
[50] AHEAD, HRS, and PSID are conducted by university research entities
with support from federal agencies. The other surveys are conducted by
federal government agencies.
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