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United States Government Accountability Office: 
GAO: 

Report to the Chairman, Subcommittee on Federal Financial Management, 
Government Information, Federal Services, and International Security, 
Committee on Homeland Security and Governmental Affairs, U.S. Senate:

February 2012: 

Federal Statistical System:

Agencies Can Make Greater Use of Existing Data, but Continued Progress 
Is Needed on Access and Quality Issues:

GAO-12-54:

GAO Highlights:

Highlights of GAO-12-54, a report to the Chairman, Subcommittee on 
Federal Financial Management, Government Information, Federal 
Services, and International Security, Committee on Homeland Security 
and Governmental Affairs, U.S. Senate. 

Why GAO Did This Study:

As demand for more and better information increases, rising costs and 
other challenges require that the federal statistical system identify 
efficiencies. To explore opportunities to improve cost-effectiveness, 
GAO was asked to (1) review how the Office of Management and Budget 
(OMB) and agencies improve information collections, (2) evaluate 
opportunities and constraints for agencies to use administrative data 
(information collected as part of the administration of a program or 
held by private companies) with surveys, and (3) assess the benefits 
and constraints of surveys making greater use of the Census Bureau’s 
American Community Survey (ACS) data and resources. GAO focused on 
collections administered to households and individuals, analyzed 
statutory and agency documents, did five case studies of surveys, 
reviewed documentation of representative samples of active surveys, 
and interviewed agency officials and experts. 

What GAO Found:

The Office of Management and Budget (OMB), agencies, and interagency 
statistical committees have distinct roles in identifying 
opportunities to improve federal information collection efforts. OMB 
exercises several authorities that promote the system’s efficiency, 
including overseeing and approving agency information collections. The 
website Reginfo.gov provides the public with information, such as cost 
and burden, on collections that OMB reviews, though GAO’s review 
identified some discrepancies in selected items. OMB periodically 
issues guidance to agencies on complying with federal requirements for 
information collections, but this guidance generally does not 
prescribe specific actions to take. GAO’s analysis of agencies’ 
documentation of active surveys indicated that 77 percent included 
detailed descriptions of efforts to identify duplication, while those 
that did not tended to be for collections that are unlikely to 
duplicate existing information; and 75 percent reported actions beyond 
those required by statute to solicit external input. OMB, through 
enhanced guidance, could promote additional awareness of options 
agencies can take to identify duplication and solicit input. 
Interagency committees, which primarily draw members from the 13 
agencies that have statistics as their primary focus, are particularly 
important in helping ensure collaboration. The committees have 
numerous projects underway aimed at addressing key challenges facing 
the statistical system. However, mechanisms for disseminating 
information about their work are not comprehensive or up-to-date. 
Though member agencies are the most-likely customers of the committees’
products, making information about committee work and priorities more 
accessible could benefit other agencies, academics, and the general 
public. It could also benefit committee members by providing a central 
repository for information. 

Administrative data have greater potential to supplement rather than 
replace survey data. Agencies currently combine the two data sources 
in four key ways to cost-effectively increase efficiency and quality. 
Specifically, agencies use administrative data to: (1) link to survey 
data to create new data products; (2) supplement surveys’ sample 
frames; (3) compare to survey data to improve accuracy and design of 
surveys; and (4) combine with survey data to create, or model, 
estimates. However, expanding the use of administrative data faces key 
constraints related to the access and quality of the data. While 
agencies and committees are taking steps to address these constraints 
and facilitate the process through which agencies work together to 
share data, individual tools may not be sufficient. A more-
comprehensive framework for use by all agencies involved in data-
sharing decisions that includes key questions to consider when 
evaluating potential use of administrative data could make the 
decision process more consistent and transparent. 

ACS, an ongoing monthly survey that provides information about the 
nation’s communities, offers agencies important opportunities to 
increase the efficiency and reduce the costs of their surveys, but its 
current design limits the extent to which agencies can utilize some of 
these opportunities. Uses that do not affect ACS design or the 
survey’s respondents, such as using ACS estimates to inform survey 
design or evaluate other surveys’ results, have widespread potential. 
However, more-intensive uses, such as adding content or supplemental 
surveys to the ACS, currently have limited potential. 

What GAO Recommends: 

GAO recommends that OMB take several actions to improve the broader 
efficiency of the federal statistical system, including implementing 
additional quality-control procedures for selected website data, 
enhancing awareness of ways to meet information collection 
requirements, better disseminating information on interagency 
committees, and developing comprehensive guidance for agencies to use 
when considering data sharing. OMB generally agreed with all of GAO’s 
recommendations. 

View [hyperlink, http://www.gao.gov/products/GAO-12-54]. For more 
information, contact Robert Goldenkoff at (202) 512-2757 or 
goldenkoffr@gao.gov or Ronald S. Fecso at (202) 512-7791 or 
fecsor@gao.gov. 

[End of section] 

Contents:

Letter:

Background:

OMB and Agencies Take a Number of Steps to Ensure Efficient 
Information Collections, Though Opportunities Exist for Refinements:

Administrative Data Could Help Improve Federal Surveys, but Continued 
Progress Is Needed on Access and Quality Issues:

Prospects for Enhanced Use of the ACS with Other Surveys Are Mixed:

Conclusions:

Recommendations for Executive Action:

Agency Comments and Our Evaluation:

Appendix I: Scope and Methodology:

Appendix II: Description of Case-Study Surveys:

Appendix III: Selected Statutes Related to Information Collection:

Appendix IV: Printable Interactive Graphic:

Appendix V: Comments from the Department of Commerce:

Appendix VI: GAO Contacts and Staff Acknowledgments:

Tables:

Table 1: Overview of Interagency Statistical Committees:

Table 2: Key Characteristics of the ACS:

Table 3: Number of Collections, by Stratum:

Table 4: Actions Taken to Address Constraints That Hamper Greater Use 
of Administrative Data:

Figures:

Figure 1: The Thirteen Principal Statistical Agencies and Their Parent 
Organizations:

Figure 2: Most Information Collections from Households and Individuals 
Have Relatively Modest Costs:

Figure 3: Actions Taken to Address Constraints That Hamper Greater Use 
of Administrative Data:

Abbreviations:

ACS: American Community Survey: 

BLS: Bureau of Labor Statistics: 

CE Surveys: Consumer Expenditure Surveys: 

CED: Consumer Expenditure Diary Survey: 

CEQ: Consumer Expenditure Quarterly Interview Survey: 

CIPSEA: Confidential Information Protection and Statistical Efficiency 
Act: 

ERS: Economic Research Service: 

FCSM: Federal Committee on Statistical Methodology: 

ICSP: Interagency Council on Statistical Policy: 

NCHS: National Center for Health Statistics: 

NCSES: National Center for Science and Engineering Statistics: 

NHANES: National Health and Nutrition Examination Survey: 

NHIS: National Health Interview Survey: 

NSCG: National Survey of College Graduates: 

OIRA: Office of Information and Regulatory Affairs: 

OMB: Office of Management and Budget: 

PRA: Paperwork Reduction Act: 

ROCIS: Regulatory Information Service Center and OIRA Consolidated 
Information System: 

SCOPE: Statistical Community of Practice and Engagement: 

SIPP: Survey of Income and Program Participation: 

[End of section] 

United States Government Accountability Office: 
Washington, DC 20548: 

February 24, 2012:

The Honorable Thomas R. Carper: 
Chairman: 
Subcommittee on Federal Financial Management, Government Information, 
Federal Services, and International Security: 
Committee on Homeland Security and Governmental Affairs: 
United States Senate:

Dear Mr. Chairman:

Information is a critical strategic asset, and all levels of 
government, as well as businesses and private citizens, depend on 
relevant, accurate, and timely social, demographic, financial, and 
other federally funded data-collection efforts to inform their 
planning and other decisions. Collectively, this information plays a 
vital role in measuring the health and well-being of the nation, 
informing private-sector investment, allocating federal funding, and 
measuring the outcomes of government programs.

However, the federal statistical system, including (1) agencies that 
collect and analyze data, and (2) the Office of Management and Budget 
(OMB), which oversees the system, faces several challenges. Key among 
them is that the demand for information is increasing, especially as 
organizations look for ways to operate more cost-effectively, while 
the cost of collecting data is growing and response rates to surveys--
both government and private-sector--are declining, driven in part by 
concerns over privacy and confidentiality. In the face of these 
challenges, it will be important for federal statistical agencies to 
identify opportunities to increase their efficiency, while maintaining 
or improving data quality and minimizing respondent burden and 
respecting privacy and confidentiality concerns. Greater use of 
administrative data, which includes information collected as part of 
the execution of government programs as well as information held by 
private companies, has been proposed as one approach to enhance 
efficiency and quality.[Footnote 1] Another potential approach is 
making greater use of the American Community Survey (ACS), a monthly 
survey that replaced the census long form and provides annual data on 
communities' demographic, social, economic, and housing conditions.

At your request, this report (1) reviews the ways in which OMB and 
agencies identify opportunities for improvement and increased 
efficiency; (2) evaluates opportunities and constraints for the 
statistical agencies to use administrative data in conjunction with 
selected surveys; and (3) assesses the benefits and constraints of 
selected surveys making greater use of ACS data and resources.

To achieve our objectives, we focused our review on statistical 
information collections administered to households and individuals, as 
opposed to businesses or other entities, and subject to the Paperwork 
Reduction Act (PRA), which requires OMB approval of certain federal 
data collections.[Footnote 2] Specifically, we performed case studies 
of five federal surveys: the Consumer Expenditure Surveys, sponsored 
by the Bureau of Labor Statistics (BLS); the National Health and 
Nutrition Examination Survey and the National Health Interview Survey, 
both sponsored by the National Center for Health Statistics (NCHS); 
the National Survey of College Graduates, sponsored by the National 
Center for Science and Engineering Statistics (NCSES), part of the 
National Science Foundation; and the Survey of Income and Program 
Participation, sponsored by the Census Bureau. We selected these 
surveys based on several factors, such as their size and cost and 
whether they use or have the potential to use administrative data or 
ACS data. We focused our selection on large surveys, in terms of both 
cost and number of respondents, because potential cost savings and 
efficiency gains are likely greatest for them.

Additionally, to address all three objectives, we examined related 
statutes and regulations, applicable OMB guidance, documentation of 
the ACS and our case study surveys, papers and reports, and our own 
prior work.[Footnote 3] To gain an understanding of the information 
collections in our scope, we reviewed publicly available data from 
Reginfo.gov, a government website with information on agency requests 
for OMB approval of information collections.[Footnote 4] We analyzed 
the subject matter of all of the collections in our scope and, for a 
representative sample of 106 surveys, analyzed agencies' reported 
efforts to identify duplication and consult with persons outside of 
the agency. We interviewed experts on the federal statistical system 
and officials at OMB and the four agencies that administer the case-
study surveys to learn about coordination among agencies, efforts 
agencies take to identify improvement, and experts' and officials' 
perspectives on current and potential uses of administrative data and 
ACS. We also interviewed and discussed these topics with officials at 
the Department of Agriculture's Economic Research Service (ERS), which 
is a member of several interagency statistical committees and the lead 
agency for the Statistical Community of Practice and Engagement. 
[Footnote 5] In evaluating OMB, agency, and interagency actions to 
improve efficiency, we used as criteria the requirements of the PRA 
and practices identified in our prior work on agency collaboration. 
[Footnote 6]

For the purposes of this review, we assessed the reliability of the 
data from the Reginfo.gov website and determined that they were 
reliable for some of our purposes but not others. Specifically, we 
reviewed related documentation, conducted interviews with OMB 
officials, and compared selected data elements from the Reginfo.gov 
website to supporting documents. We determined that the data were 
sufficiently reliable for purposes of identifying the collections 
within our scope and obtaining information on the collections' subject 
matter and actions taken by agencies to identify duplication and 
solicit input. As described later in this report, data provided on the 
website were not sufficiently reliable for the purpose of assessing 
collections' annual cost to the federal government and annual 
respondent burden hours. Appendix I includes additional information on 
our scope and methodology. Appendix II contains more detailed 
descriptions of our case-study surveys.

We conducted this performance audit from December 2010 to February 
2012 in accordance with generally accepted government auditing 
standards. Those standards require that we plan and perform the audit 
to obtain sufficient, appropriate evidence to provide a reasonable 
basis for our findings and conclusions based on our audit objectives. 
We believe that the evidence obtained provides a reasonable basis for 
our findings and conclusions based on our audit objectives.

Background:

In contrast to many other countries, the United States does not have a 
primary statistical agency.[Footnote 7] Instead, the statistical 
system is decentralized, with statistical agencies generally located 
in different government departments. This structure keeps statistical 
work within close proximity to the various cabinet-level departments 
that use the information. There are 13 federal agencies, referred to 
as the principal statistical agencies, which have statistical 
activities as their core mission. These agencies conduct much of the 
government's statistical work, though there are more than 80 
additional federal agencies that carry out some statistical work in 
conjunction with their primary missions. The 13 principal statistical 
agencies are all attached to a cabinet-level department or an 
independent agency that reports to the president. As shown in figure 
1, they are located at different levels within their respective 
departments and agencies.

Figure 1: The Thirteen Principal Statistical Agencies and Their Parent 
Organizations:

[Refer to PDF for image: illustration] 

Department of the Treasury: 
Internal Revenue Service; 
Research, Analysis and Statistics Division; 
[Statistics of Income Division]. 

Department of Labor: 
[Bureau of Labor Statistics]. 

Department of Education: 
Institute of Education Sciences; 
[National Center for Education Statistics]. 

Department of Health and Human Services: 
Centers for Disease Control and Prevention; 
Office of Surveillance, Epidemiology, and Laboratory Services; 
[National Center for Health Statistics]. 

Social Security Administration: 
Office of Retirement and Disability Policy; 
[Office of Research, Evaluation, and Statistics]. 

Department of Energy: 
[Energy Information Administration]. 

Department of Transportation: 
Research and Innovative Technology Administration; 
[Bureau of Transportation Statistics]. 

Department of Agriculture: 
Under Secretary for Research, Education, and Economics; 
[Economic Research Service]; 
[National Agricultural Statistics Service]. 

Department of Commerce: 
Economics and Statistics Administration; 
[Census Bureau]; 
[Bureau of Economic Analysis]. 

Department of Justice: 
Office of the Associate Attorney General; 
Office of Justice Programs; 
[Bureau of Justice Statistics]. 

National Science Foundation: 
Directorate for Social, Behavioral and Economic Sciences; 
[National Center for Science and Engineering Statistics]. 

Sources: OMB, federal agencies.

Note: The 13 principal statistical agencies' names are displayed in 
boxes within the figure. 

[End of figure] 

For fiscal year 2011, $6.83 billion was requested for statistical 
work, which includes the collections in our scope as well as work that 
focuses on entities other than households and individuals, such as 
businesses and farms.[Footnote 8] This amount is about 0.2 percent of 
that year's total federal budget request. Much of this work is 
concentrated in the 13 principal statistical agencies, which account 
for approximately 40 percent of requested funding. The budget request 
for the Census Bureau is among the highest of the principal 
statistical agencies. Excluding funding related to the decennial 
census, the fiscal year 2011 budget request for the Census Bureau was 
$558 million.[Footnote 9] In addition to conducting its own 
statistical activities, the Census Bureau also performs statistical 
work for other agencies on a reimbursable basis.

Most of the collections in our scope have relatively modest annual 
costs. In a sample of 112 information collections that fell within our 
scope and were active as of September 22, 2011, the majority cost less 
than $500,000 annually, and fewer than one in five cost more than $1 
million annually.[Footnote 10] There are a few, more expensive, large 
and broad-based collections such as the Current Population Survey and 
National Health Interview Survey, both of which cost tens of millions 
of dollars each year, and the ACS, which costs over $200 million 
annually (see figure 2).

Figure 2: Most Information Collections from Households and Individuals 
Have Relatively Modest Costs:

[Refer to PDF for image: vertical bar graph] 

Annual federal cost per information collection: less than $0.5 million; 
Number of information collections in our sample of 112: 69. 

Annual federal cost per information collection: $0.5-0.99 million; 
Number of information collections in our sample of 112: 21. 

Annual federal cost per information collection: $1.0-1.49 million; 
Number of information collections in our sample of 112: 2. 

Annual federal cost per information collection: $1.5-1.99 million; 
Number of information collections in our sample of 112: 4. 

Annual federal cost per information collection: $2.0-2.49 million; 
Number of information collections in our sample of 112: 0. 

Annual federal cost per information collection: $2.5-2.99 million; 
Number of information collections in our sample of 112: 3. 

Annual federal cost per information collection: $3.0-3.49 million; 
Number of information collections in our sample of 112: 0. 

Annual federal cost per information collection: $3.5-3.99 million; 
Number of information collections in our sample of 112: 0. 

Annual federal cost per information collection: $4.0-4.49 million; 
Number of information collections in our sample of 112: 1. 

Annual federal cost per information collection: $4.5-4.99 million; 
Number of information collections in our sample of 112: 0. 

Annual federal cost per information collection: $5 million+; 
Number of information collections in our sample of 112: 10. 

Source: GAO analysis of agency data. 

[End of figure]

Various statutes and guidance from OMB and other entities establish 
standards for quality and privacy that apply to the federal 
statistical system. One of the most significant statutes is the PRA, 
which designates OMB as the coordinating body of the federal 
statistical system. The PRA establishes requirements that agencies 
must meet in order to administer information collections, and OMB must 
meet in overseeing the system, including that it issue guidance to 
agencies. Other entities also provide guidance to agencies that 
conduct statistical work.[Footnote 11] In addition, use of information 
must be balanced with protection of privacy and confidentiality. 
Statutes such as the Confidential Information Protection and 
Statistical Efficiency Act (CIPSEA) apply to the federal statistical 
system and focus on ensuring the privacy and confidentiality of 
respondents' information.[Footnote 12] Agency-specific statutes also 
protect the privacy and confidentiality of data collected by those 
agencies. For example, Title 13 of the U.S. Code authorizes the Census 
Bureau to request and collect information from individuals but also 
guarantees the confidentiality of these data and establishes penalties 
for unlawfully disclosing this information. Additional statutes are 
described in more detail in appendix III.

OMB and Agencies Take a Number of Steps to Ensure Efficient 
Information Collections, Though Opportunities Exist for Refinements:

OMB Uses Its Oversight Authority to Improve Efficiency:

Under PRA, OMB, through its Office of Information and Regulatory 
Affairs (OIRA), has responsibility and broad authority to improve the 
efficiency and effectiveness of federal information resources. 
[Footnote 13] In this regard, OMB is charged with the oversight and 
coordination of federal agencies' statistical activities. 
Specifically, these oversight functions are carried out by OIRA's 
Statistical and Science Policy Branch, headed by the Chief 
Statistician, which includes five staff members who work closely on 
these oversight and coordination activities with approximately 25 
other OIRA desk officers. OMB exercises four key authorities that 
contribute to the efficiency of the federal statistical system:

* Oversight and approval of information collections: OMB generally 
must approve information collections that are to be administered to 10 
or more people.[Footnote 14] OMB staff review agencies' information 
collection requests to determine whether proposed collections meet PRA 
standards by assessing such factors as whether they are necessary for 
the mission of the agency and do not unnecessarily duplicate existing 
information. This review also enables OMB to identify opportunities 
for improvement. For example, according to OMB and agency officials, 
if it determines that it is necessary to ask similar questions in 
multiple collections, then OMB works to ensure that agencies ask them 
in a consistent manner, when appropriate.

* Standard-setting and guidance to agencies: OMB is responsible for 
developing and implementing governmentwide policies, principles, 
standards, and guidelines related to statistical issues, such as 
procedures and methods for collecting data and disseminating 
information. Specifically, OMB issues directives, guidance, and 
memorandums, and provides additional information through information 
sessions and presentations, to guide federal data collection and 
promote the quality and efficiency of information collections. For 
example, OMB published "Questions and Answers When Designing Surveys 
for Information Collections," a set of 81 questions and answers on the 
OMB review process for agency information collection requests required 
by PRA.[Footnote 15] OMB also issued Standards and Guidelines for 
Statistical Surveys, which outlines 20 standards and related 
guidelines for the design and methodology of statistical surveys. 
Finally, OMB issues memorandums focusing on various topics, with 
recent ones clarifying the guidance for complying with PRA and 
encouraging agencies to coordinate efforts to share data.

* Budget development and reporting: Although agency budgets are 
initiated within agencies, OMB is responsible, under PRA, for ensuring 
that agency budget proposals are consistent with systemwide priorities 
for maintaining and improving the quality of federal statistics. In 
addition to the budgets themselves, OMB reports information to the 
public and Congress about the identification of key priorities through 
key documents. OMB annually reports on the paperwork burden federal 
collections impose on the public in the Information Collection Budget 
of the United States Government. In addition, OMB annually describes 
statistical program funding and proposed program changes for 
statistical activities in the Statistical Programs of the United 
States Government.

* Other statistical-policy coordination activities: The Chief 
Statistician and staff in OMB's Statistical and Science Policy Branch 
participate in both formal and informal coordination activities with 
agencies. OMB's role and participation in the formal interagency 
committees are discussed later in this report. In general, it 
maintains regular contact with staff at principal statistical 
agencies. Additionally, OMB encourages agencies that are designing 
information collections to collaborate with principal statistical 
agencies because they can help improve survey design and methodology. 
For example, according to OMB and Census Bureau officials, OMB 
encouraged the Corporation for National and Community Service to work 
with the Census Bureau and BLS to sponsor a supplement to the Current 
Population Survey rather than a stand-alone survey. OMB indicated that 
sponsoring this supplement likely resulted in cost savings, improved 
data quality, and greater utility.[Footnote 16]

The Reliability of Information in OMB's Information Collections 
Database Needs to Be Improved:

One tool that OMB uses to facilitate its oversight and coordination 
functions under PRA is an internal system called the Regulatory 
Information Service Center and OIRA Consolidated Information System 
(ROCIS), which contains information on all active collections and 
those pending OMB approval. Agencies use the system to submit 
information collection requests. This system also facilitates OIRA's 
review of the requests and underlies the information provided on the 
public website Reginfo.gov. Agency submissions to OMB typically 
include a copy of the data-collection instrument (e.g., a survey) and 
supporting documentation that, in a standardized form, provides 
information on the collection, such as the estimated annual burden 
hours and cost to the federal government. Further, under PRA, agencies 
must certify that the collection satisfies the act's standards, for 
example that the collection avoids unnecessary duplication. Making 
this information transparent and easily accessible to other agencies 
facilitates coordination and can potentially help agencies avoid 
duplication and identify opportunities for improvement. Furthermore, 
OMB uses the information contained in its internal system to track 
reviews of information collections, and to compile quantitative data 
for the Information Collection Budget of the United States Government.

Despite the benefits of this electronic system, our review identified 
some discrepancies between the Reginfo.gov website's data and the 
underlying documentation for certain key variables. Specifically, we 
reviewed a systematic random sample of 56 of the 555 collections in 
our scope and checked the reported information for annual cost to the 
federal government and annual burden hours. For 11 of the 56 
information collections, the information on cost or burden, or both, 
did not match between the two sources. In cases where annual cost did 
not match, the differences ranged from $1,000 to $19.3 million. In 
cases where annual burden hours did not match, the differences ranged 
from 30 to almost 500,000 hours. OMB confirmed that the information in 
the external Reginfo.gov system is the same as in its internal ROCIS 
system. As a result, these discrepancies raise questions about the 
confidence that users can have in both the internal and external 
databases and may affect OMB's ability to track information collection 
requests. OMB officials told us that responsibility for ensuring data 
reliability is shared between OMB and agencies. The Regulatory 
Information Service Center has issued detailed guidance to agencies on 
how to upload information into ROCIS, and the system has a function 
that allows agencies to check the completeness of data for individual 
information collections to ensure that no required data are missing. 
Entering this information is not always straightforward, however, and 
some interpretation of the underlying documentation may be required. 
The discrepancies that we identified indicate that additional actions, 
such as edit checks, review by an informed staff member, or increased 
clarification in supporting documents are necessary to ensure the 
reliability of Reginfo.gov and ROCIS data.

Agencies Identify Duplication and Solicit Input to Enhance Efficiency:

Our analysis indicated that agencies addressed PRA standards related 
to duplication and public comment in their information collection 
requests to OMB, and in many cases went beyond the actions 
specifically described in PRA and related OMB guidance.

The elements of PRA most directly related to our review were 
identifying duplication and soliciting external input on proposed 
collections. To analyze agencies' actions in these two areas, we 
reviewed a generalizable sample of supporting statements from 106 
active statistical information collections administered to households 
and individuals.[Footnote 17] Each of the supporting statements we 
reviewed addressed those PRA standards, as required, and in many cases 
included detailed descriptions, the content of which we analyzed in 
order to identify the range of actions that agencies took.

Although agencies must address how their proposed collections meet PRA 
standards, the act and OMB guidance do not prescribe many specific 
actions that agencies need to take in addressing these standards. 
Regarding duplication, PRA does not dictate how agencies should 
address the standard. Regarding external input, PRA does require that 
agencies at a minimum provide notice in the Federal Register to allow 
the public to comment on proposed collections as well as consult with 
members of the public and affected agencies. OMB guidance expands 
somewhat on ways that agencies can address these standards, 
particularly in the case of surveys using statistical methods. 
However, just as with PRA, much is left to the discretion of agencies 
and little is specifically required. For example, OMB guidance states 
that agencies should review existing studies and consult with survey 
methodologists and data users.[Footnote 18]

Identifying potential duplication: Our analysis showed that agencies 
took various steps to comply with the PRA requirement that information 
collections do not unnecessarily duplicate an available information 
source.[Footnote 19] Specifically, based on our analysis, we estimated 
the following for the universe of collections in our scope:

* 77 percent included detailed explanations of the actions taken to 
identify potential duplication.[Footnote 20] Those supporting 
statements that did not include detailed explanations were generally 
for information collections that had unique scopes or other 
characteristics that made them unlikely to duplicate existing 
information.

* 57 percent reported reviewing other surveys when looking for 
duplication.[Footnote 21] For example, the National Cancer Institute 
identified seven other surveys that collected information similar to 
that of a Current Population Survey supplement on tobacco use and 
explained why the data from these surveys could not replace those 
collected through the supplement.

* 46 percent indicated that the agency considered administrative data 
as a potential source of data.[Footnote 22]

* About a quarter indicated that they consulted with other entities, 
such as agencies, and a similar number reported that they conducted 
literature searches.[Footnote 23]

* In addition, for six of the information collections in our sample, 
agencies sponsored a collection in the form of a supplement to the 
Current Population Survey rather than creating a stand-alone survey, 
thus piggybacking onto another survey vehicle to potentially avoid 
duplication.

Despite these steps, the collection of similar data in different 
surveys is unavoidable for methodological reasons. In some cases, 
agencies need to ask the same or similar questions because different 
surveys target different populations. Both the National Survey of 
College Graduates and the Current Population Survey ask about 
respondents' college degree and occupation, but the National Survey of 
College Graduates targets individuals in the United States who have 
bachelor's degrees or higher in science or engineering, while the 
Current Population Survey targets a nationally-representative sample 
of U.S. civilians aged 16 and older. Furthermore, according to agency 
officials, assessing relationships among survey variables may require 
asking the same or similar questions in different surveys. For 
example, it is common for surveys to ask for respondents' ages in 
order to analyze how responses to other questions vary according to 
this variable. In addition, asking the same question among surveys 
allows agencies to compare survey estimates and evaluate surveys' data 
quality. In order to facilitate comparisons among surveys, OMB 
encourages asking consistent questions, when possible, about certain 
characteristics such as race and ethnicity. Further, when considered 
from an individual's perspective, duplication of survey questions is 
relatively rare. This is because in a given year a very small 
percentage of households are selected to participate in a single 
collection within our scope.[Footnote 24] The likelihood that a 
household would be selected for participation in more than one 
collection, and thus household members be asked the same question more 
than once, is considerably lower.

Soliciting input and feedback on information collections: Most 
agencies in our scope took steps to seek outside input beyond those 
prescribed by OMB guidance and the PRA. On the basis of our analysis, 
we estimated the following for the universe of collections in our scope:

* 75 percent indicated that the agency reported obtaining external 
feedback in addition to publishing notices in the Federal Register. 
[Footnote 25]

* 57 percent indicated that agencies consulted with experts.[Footnote 
26] For example, the sponsor of the National Survey of Women Veterans, 
a survey on the health-care needs, experiences, and preferences of 
women veterans, consulted with individuals representing a variety of 
research and clinical backgrounds, such as public health, social 
welfare, and psychology.

* Agencies less frequently reported consulting with other agencies, 
contractors or subcontractors, or interagency or advisory committees. 
[Footnote 27] In addition, agencies reported soliciting feedback 
directly from former and potential survey respondents and data users 
and customers.[Footnote 28] They also reported conducting literature 
searches and sponsoring or participating in workshops, panels, or 
other events.[Footnote 29]

Agencies in our sample reported making changes in response to input, 
potentially resulting in improvements to their information 
collections. For example, in response to recommendations made by the 
Committee on National Statistics on a Current Population Survey 
supplement about food security, ERS reported entering into an 
agreement with Iowa State University to study food security 
measurement issues. This collaborative project is exploring 
alternatives to an aspect of the supplement's current design, which 
could result in alternatives to methods used to estimate food security 
prevalence and potentially improve measurement precision and 
reliability. The U.S. Geological Survey also reported incorporating 
changes in response to feedback on its Landsat Survey.[Footnote 30]

Agencies' actions to find duplication and solicit input that we 
identified in our review, as well as others that OMB may identify, 
could be useful for OMB to share with other agencies that sponsor 
information collections. Offering more-detailed guidance in a single 
document that outlines different actions agencies can take to identify 
duplication and solicit input would help ensure that agencies are 
aware of the various options. It would also allow them to easily 
access and reference this information. OMB could include this 
information in one of its periodic memorandums related to compliance 
with the PRA. We previously reported on the importance of establishing 
ways to operate across agency boundaries, and promoting these actions 
is one way OMB can do this.[Footnote 31] Also, just as OMB's guidance 
to agencies in complying with the Information Quality Act gives 
agencies flexibility to determine the most appropriate actions, it is 
important that any new guidance continue to give agencies discretion 
in the number and types of actions they take to identify duplication 
and solicit input. This is because the most appropriate actions will 
vary based on the characteristics of the collection.

Interagency Committees Facilitate Collaboration, but Better 
Communication Could Increase Effectiveness:

Interagency statistical committees offer opportunities for broader 
collaboration to increase the efficiency of the federal statistical 
system. Three key committees are the Interagency Council on 
Statistical Policy (ICSP), the Federal Committee on Statistical 
Methodology (FCSM), and the Statistical Community of Practice and 
Engagement (SCOPE), all of which are either chaired or sponsored by 
OMB.[Footnote 32] Importantly, the activities of the interagency 
committees are consistent with key collaborative practices we 
identified in our previous work.[Footnote 33] For example, each of 
these committees has defined roles and responsibilities, and the 
committees serve as a vehicle for the agencies to operate across 
agency boundaries. Specifically, ICSP serves an advisory function to 
the Chief Statistician and focuses on broader issues related to the 
federal statistical system. In addition, ICSP provides overarching 
guidance to FCSM and SCOPE. FCSM investigates statistical practices 
and methodologies used in federal statistical programs, while SCOPE 
focuses on cross-agency activities of data management and 
dissemination. Table 1 provides an overview of these committees.

Table 1: Overview of Interagency Statistical Committees:

Date established; 
Interagency Council on Statistical Policy (ICSP): 1989[A]; 
Federal Committee on Statistical Methodology (FCSM): 1975; 
Statistical Community of Practice and Engagement (SCOPE): 2009.

Membership; 
Interagency Council on Statistical Policy (ICSP): The heads of the 
principal statistical agencies, plus the statistical unit at the 
Environmental Protection Agency; 
Federal Committee on Statistical Methodology (FCSM): About 20 members 
appointed by the Chief Statistician based on technical expertise and 
history of innovative contributions to the federal statistical system; 
Statistical Community of Practice and Engagement (SCOPE): Appointed 
representatives from the principal statistical agencies, plus the 
statistical unit at the Environmental Protection Agency. 

Mission; 
Interagency Council on Statistical Policy (ICSP): 
* Coordinate statistical work, particularly when activities and issues 
cut across agencies; 
* Exchange information about agency programs and activities; 
* Provide advice and counsel to OMB on statistical matters; 
Federal Committee on Statistical Methodology (FCSM): 
* Communicate and disseminate information on statistical practice 
among all federal statistical agencies; 
* Recommend the introduction of new methodologies in federal 
statistical programs to improve data quality; 
* Provide a mechanism for statisticians in different federal agencies 
to meet and exchange ideas; 
Statistical Community of Practice and Engagement (SCOPE): 
* Provide a collaborative community for statistical agencies to 
produce relevant, accurate, timely, cost-effective data and insightful 
research disseminated through shared state-of-the-art best practices 
to support data-driven decisions. 

Description of selected projects; 
Interagency Council on Statistical Policy (ICSP): 
* Identifying the highest-priority statistical program improvements; 
* Developing views on improving implementation of the PRA; 
* Providing direction to FCSM's subcommittees on privacy and 
administrative data; 
Federal Committee on Statistical Methodology (FCSM): 
* Discussing disclosure limitation methods: 
* Investigating nonresponse issues related to selected surveys; 
* Clarifying legal issues of confidentiality and informed consent; 
* Examining issues related to the quality of administrative data; 
Statistical Community of Practice and Engagement (SCOPE): 
* Surveying tools used by statistical agencies to comply with 
standards for access to electronic and information technology procured 
by agencies, and recommending the best tools for use; 
* Developing protocols for pilot testing of a secure cloud environment 
for storing data and recommended software. 

Source: GAO analysis of OMB and agency data.

[A] ICSP was established in 1989 and codified in the 1995 
reauthorization of the PRA. 

[End of table] 

The committees study statistical issues and methods through 
subcommittees and working groups, most of which rely on volunteers 
from member agencies who take on these responsibilities in addition to 
their current job duties. The work of the subcommittees and working 
groups has been useful to other agencies. For example, an FCSM 
subcommittee produced a checklist that, according to OMB, is used 
around the world to determine whether a public-use data product 
sufficiently protects the confidentiality of individuals' data.

The interagency committees use various methods to disseminate 
information on their activities and products, but they do not do so in 
a timely or comprehensive manner. The committees' work is summarized 
in OMB's annual report Statistical Programs of the United States 
Government, but the report does not always communicate key information 
about it. For example, the fiscal year 2011 report states that one of 
ICSP's activities over the past year was identifying the highest-
priority statistical-program improvements, but does not provide 
information about all of these improvements.[Footnote 34] In addition, 
interagency committees present information about their work at 
statistical seminars. For example, according to OMB officials, FCSM 
has presented work at the biennial FCSM Statistical Policy Seminars. 
Additionally, agency officials noted that members of interagency 
statistical committees utilize a limited-access web-based system to 
facilitate information sharing. Information about FCSM's work is also 
posted on the committee's website or the FedStats website.[Footnote 
35] Neither ICSP nor SCOPE has a dedicated website, though OMB 
believes that this is not necessary or appropriate because the work of 
these groups is deliberative. While the FCSM website offers the 
potential to effectively disseminate information, it is not 
comprehensive or timely. For example, it provides links to the sites 
of various interagency and advisory committees, including three FCSM 
permanent working groups, but does not have pages for any of the 
active FCSM subcommittees.[Footnote 36] Moreover, the websites do not 
appear to be regularly updated with new products produced by the 
committees that could be useful for other agencies. For example, the 
subcommittee on the statistical uses of administrative data published 
a paper in April 2009 highlighting examples of successful data-sharing 
projects using administrative data for statistical purposes, but this 
product is not yet available on the FCSM website.

Providing more-comprehensive and timely information on interagency 
activities could offer benefits. As identified in our previous work, 
developing mechanisms to monitor and report on results is a necessary 
element of a collaborative relationship.[Footnote 37] In this case, 
better reporting of committee activities and products could offer 
benefits to those who are not involved in committee activities, as 
well as committee members. Membership in the committees is made up 
almost exclusively of representatives from the 13 principal 
statistical agencies, so most agencies are not directly involved in 
committee activities. It makes sense that agencies that have 
statistics as their primary focus are the most-heavily involved, but 
those agencies for which statistics is a supporting function to their 
primary mission, and possibly academics and the broader public, could 
benefit from greater access to information and products related to the 
committees' work and priorities. More easily accessible information 
would also benefit member agencies, as it would offer a centralized 
place to maintain committee work and communicate priorities. Much work 
goes into developing the committees' products, and making them easily 
accessible maximizes their value.

Administrative Data Could Help Improve Federal Surveys, but Continued 
Progress Is Needed on Access and Quality Issues:

Administrative Data Have Greater Potential to Supplement, Rather than 
Replace, Federal Surveys:

Administrative data, typically collected to administer a program or 
business, are a growing source of information on individuals and 
households. For example, the Social Security Administration collects 
data on the earnings of U.S. workers from employers and the Internal 
Revenue Service to calculate the amount of benefits for retired 
workers, spouses, children, and other beneficiaries, while businesses 
obtain data, for example, on item and amount of purchases when 
customers use credit cards and store loyalty cards. According to the 
Census Bureau, the amount of administrative data held by private 
companies exceeds the amount held by the government. Researchers 
recently estimated that the amount of digital data in existence, which 
includes some types of administrative data such as retail customer 
databases, more than doubles every 2 years.[Footnote 38] 
Administrative data have been identified as an important resource for 
the future of the statistical system, as some of these publicly and 
privately held data may be analyzed or reported with survey data to 
yield greater value. Furthermore, the increasing capacity to store and 
process administrative data has facilitated this potential use.

For decades, agencies have been working to expand the use of 
administrative data in conjunction with data collected from surveys, 
but certain characteristics of administrative data make it difficult 
to use them to replace surveys or sections of surveys administered to 
households and individuals. There is interest in exploring how 
administrative data may be used to improve data quality, hold down 
costs, and reduce respondent burden. For example, as part of the 
redesign of the Consumer Expenditure Surveys, BLS is investigating the 
potential for replacing some portions of the survey with external 
sources of expenditure data to reduce respondent burden and 
potentially improve data quality. However, agencies we contacted have 
not replaced surveys or sections of surveys administered to households 
and individuals with administrative data because data: (1) are often 
not representative of a survey's population of interest; (2) may not 
correspond to information collected through survey questions; (3) are 
vulnerable to program cancellation or changes; and (4) may take a long 
time to obtain, which delays use and in some cases could cause 
agencies to miss required reporting dates.

Administrative data currently show greater promise for supplementing 
federal surveys. Indeed, the agencies we contacted identified four 
major opportunities to enhance surveys with administrative data in 
order to create efficiencies and enhance data quality.[Footnote 39] 
Current uses of administrative data include the following:

* Creating new data products: Agencies link survey data and 
administrative data to create new, more robust, statistical data 
products, which increases efficiency in two key ways. First, according 
to OMB and agency officials, agencies can use these new data products 
to evaluate and potentially improve federal policies and programs, 
especially those related to the source of the administrative data, 
without adding to respondent burden. Second, combining administrative 
data with survey data can increase efficiency by enhancing previously 
collected survey data. For example, the National Center for Health 
Statistics's (NCHS) record-linkage program links survey data from 
various health-related surveys to different administrative datasets to 
create new data products for studying factors that influence health-
related outcomes, such as disability, health care, and mortality.

* Supplementing surveys' sample frames: Using administrative data to 
supplement surveys' sample frames--the sources from which a survey's 
sample is drawn--can create efficiencies, reduce costs, and enhance 
the quality of surveys. For example, the National Household Food 
Acquisition and Purchase Survey uses administrative data from the 
Supplemental Nutrition Assistance Program to develop a sample frame of 
participating households to potentially include in the survey. ERS 
officials said that using these data to help develop the survey's 
sample frame costs less than the alternative of screening a broader 
group of respondents to determine if they are participating. In 
addition, agencies can use administrative data to augment sample 
frames in areas where the sample is not large enough to fully support 
a survey. For example, the Census Bureau's pilot project studying the 
potential to use ACS data as a sample frame for the National 
Immunization Survey used commercial data to supplement ACS data in a 
county that had a limited ACS sample.

* Comparing data to improve survey accuracy and design: By comparing 
survey data to similar administrative datasets and identifying reasons 
for any discrepancies that may exist, agencies can improve the quality 
of survey data. For example, researchers identified opportunities for 
improving surveys' designs and methodologies after agencies found that 
surveys of enrollment in health-insurance programs provided lower 
estimates than those compiled from administrative data. Agencies can 
also improve the efficiency of their surveys by using administrative 
data as part of nonresponse follow-up activities.

* Modeling estimates: Agencies combine administrative data and survey 
data to create, or model, estimates that are designed to be more 
accurate than estimates based on survey data alone. The main benefit 
of modeling is that it provides the ability to produce estimates for 
smaller geographic areas than is possible using a survey alone. For 
example, the Census Bureau conducts the Small Area Income and Poverty 
Estimates Program to provide updated data on poverty and income, which 
is used to administer federal programs and allocate federal funds to 
local areas. The Census Bureau combines survey data from the ACS with 
population estimates and administrative data and has found that this 
approach produces consistent and reliable data more reflective of 
current conditions than data produced only by existing surveys.

Agencies Are Addressing Issues That Hamper Use of Administrative Data, 
but Additional Actions Could Facilitate Progress:

Despite the benefits of using administrative data to supplement 
federal surveys, agencies face five key constraints related to data 
access and quality:

* Statutory restrictions on data sharing: Federal and state statutes 
sometimes prohibit or limit sharing of data for statistical purposes. 
In cases where specified authorized uses do not include statistical 
use, nothing short of a statutory change can overcome the constraint. 
In other cases, statutes limit sharing to purposes related to program 
administration. For example, the 2008 Farm Bill restricts access to 
data on participants in certain nutrition-assistance programs to uses 
for the "administration or enforcement" of the programs.[Footnote 40] 
Similarly, the Higher Education Act of 1965, as amended, restricts 
federal student aid data to purposes related to the "application, 
award, and administration of aid."[Footnote 41] However, agencies 
holding such restricted data can differ on whether statistical uses 
are related to program administration. The Census Bureau successfully 
negotiated access to the nutrition assistance data because it could 
demonstrate that the linked data would help the federal sponsor and 
state agencies develop better measures of outcomes, such as poverty, 
inequality, and the receipt of government transfers. Conversely, the 
Census Bureau was unable to gain access to the federal student aid 
data for statistical uses because the Department of Education did not 
consider that any of the planned uses related to the program's 
administration.

* Consent: Individuals' consent to allow their administrative and 
survey data to be linked affects uses of administrative data for 
statistical purposes. Seeking consent derives from a core concept of 
personal privacy: the notion that each individual should have the 
ability to control personal information about himself or herself. 
[Footnote 42] Moreover, there can be issues regarding the privacy and 
confidentiality of data collected for one purpose and used for 
another, and agencies use different practices, wording, and level of 
detail to meet consent requirements, according to OMB officials. At 
the time administrative data are collected, an agency can inform 
individuals that their data may be used for statistical purposes, but, 
according to ERS officials, agencies collecting administrative data 
often do not consider possible future statistical uses and therefore 
may not provide such notice. Obtaining consent after data have been 
collected can be time-consuming and costly. In addition, an agency can 
ask survey respondents for permission to link their survey data with 
certain administrative data. Some respondents may not consent, which 
can substantially limit the number of respondents eligible for linkage 
and as a result potentially affect the quality of the linked data. 
[Footnote 43]

* Costs and infrastructure: Because the primary cost of collecting 
administrative data has already been incurred, using these data can, 
in some cases, be more efficient and less costly than new survey 
efforts. However, there still are costs to using administrative data 
for statistical purposes, including up-front and ongoing investments 
to purchase and maintain hardware and software to link data and 
protect their confidentiality. Agencies identified various factors 
that can affect costs. These include but are not limited to 
negotiations with the agency holding the data, the quality of the 
administrative data, and the ease with which they can be linked to 
other data. BLS officials said that in some cases the costs of using 
administrative data with survey data may outweigh any savings and that 
evaluation of administrative data options always requires careful 
consideration of a wide range of quality and cost issues, including 
the costs of specialized personnel and infrastructure. According to an 
FCSM study that profiled examples of successful statistical uses of 
administrative data, agencies wanting to share data also may not have 
the necessary staff, policies, or procedures. For example, negotiating 
data-sharing agreements may require significant time. Moreover, many 
key administrative datasets are held by states, further complicating 
the data-sharing process because agencies have to negotiate under 
different policies and procedures as well as work with numerous staff 
across states.

* Documentation of datasets: OMB and agency officials said that 
agencies holding administrative data do not uniformly document 
information about their datasets in a way that is always useful or 
efficient for use outside of the agency. This lack of documentation of 
datasets makes evaluating their potential for statistical uses 
challenging. For example, definitions of key variables of research 
interest or information about how frequently the agency updates the 
data may not be available. ERS officials also noted that private 
companies typically do not disclose detailed information about the 
sources of their data, making it difficult to assess their quality. As 
a result, agencies interested in using these data for statistical 
purposes may have to spend additional time and resources to understand 
the content and structure of the datasets.

* Quality of data: Agency officials and experts identified reasons why 
the quality of administrative data can vary, which can affect their 
potential use with survey data. Specifically, different agencies may 
use different systems, definitions, and time frames when collecting 
administrative data. For example, states may collect and evaluate the 
quality of data in different ways, making it complicated to aggregate 
the data across states as well as to compare state-level data. In 
addition, several factors can influence the accuracy of data reported 
in administrative data. For example, agencies that collect data for 
the purpose of program administration may be concerned with the 
accuracy of only the variables used for such purpose. Moreover, 
reporting incentives may influence data quality. For example, 
individuals may underreport income on tax forms, and program agencies 
may pay less attention to the accuracy of information collected from 
applicants when it does not affect their participation in a program.

Agencies and interagency committees have been taking numerous actions 
to address these constraints. For example, ERS, in collaboration with 
the Census Bureau, NCHS, and OMB is undertaking a pilot project to 
address data quality concerns with state-level administrative data, 
and FCSM is working on a project to clarify legal requirements for 
informed consent (see figure 3).

Figure 3: Actions Taken to Address Constraints That Hamper Greater Use 
of Administrative Data:

[Refer to PDF for image: interactive graphic] 

Directions: [Click] on the types of constraints within the graphic 
structure on the right to see descriptions and examples of selected
actions taken by agencies to address each constraint type. 

Constraint: Access: 

Statutory restrictions on data sharing. 

Description: 

Statutes may not authorize statistical uses for data collected by a 
program. 

Examples of actions taken: 

* OMB has issued guidance encouraging greater sharing of data while 
protecting privacy; and: 

* FCSM produced a document, highlighting lessons learned when 
negotiating data-sharing agreements. 

Note: See appendix IV for noninteractive breakout of all the data. 

[End of figure] 

One theme that cuts across many of these efforts, and where additional 
short-term actions could accelerate progress, is identifying ways to 
facilitate the process of deciding whether to share data among 
agencies. FCSM published a paper describing successful data-sharing 
arrangements between various federal and state agencies. One of the 
four core elements of success that FCSM identified in these 
arrangements was mutual interest, in that each participant--in 
particular the agency providing the data--evaluates a proposed data-
sharing agreement from its own perspective.[Footnote 44] On the one 
hand, agencies may share data because the linked data can benefit 
program administration, as noted earlier. On the other hand, OMB and 
agency officials noted that agencies may decide against sharing 
because perceived disadvantages, such as policy concerns and potential 
identification of weaknesses in program administration, outweigh the 
possible benefits. In such a case, an individual agency's interests 
may be at odds with the broader efficiency of the whole federal 
statistical system. As illustrated in figure 3, FCSM and agencies are 
developing tools to approach these decisions in a more standardized 
way, such as developing checklists for evaluating the quality of 
administrative data and a template for executing data-sharing 
agreements. However, these individual tools focus on particular 
aspects of data sharing--for example, the checklist focuses on data 
quality. Separately, they may not be sufficient for agencies to 
efficiently identify potential datasets with the greatest potential 
for mutual benefit and address all factors involved in the decision-
making process.

The benefits of having more-comprehensive centralized guidance could 
include greater consistency, clarification, and efficiency. A more-
comprehensive standardized framework that ties together existing tools 
with additional resources in order to cover major aspects of the data-
sharing process could bring consistency to the decision-making 
process. Similar to the checklist that FCSM is developing for agencies 
to use in evaluating data quality, the framework could include a 
template outlining a list of key questions for all agencies involved 
in the proposed data sharing, including federal and state agencies 
that hold data, to address issues such as: (1) the steps to take to 
ensure data reliability; (2) any statutory limitations on planned uses 
of the data (including confidentiality protections); (3) whether 
consent has already been obtained for additional use of the data, or 
how it will be obtained; and (4) methods to fully account for the 
costs associated with obtaining and using the data. To be 
comprehensive, such guidance would not need to be voluminous, but it 
should identify each of these major aspects of data sharing, provide 
advice to agencies, and reference any tools available to assist 
agencies during the process. It should also be kept up-to-date, 
reflecting changes in legislation or other factors that affect data 
sharing, as well as any new tools that are developed. Although such a 
framework may not lead to sharing in all cases, the framework could 
better ensure that agencies weigh the related benefits and costs in a 
more balanced, consistent, and transparent fashion. Such guidance 
could also clarify ways that agencies could resolve disagreements over 
data sharing. It could also improve efficiency, given that agency 
officials we spoke with cited examples in which it took multiple years 
to reach a resolution on data sharing, by helping agencies evaluate 
available data and determine those that have the greatest potential 
for mutual benefit.

While agencies can take steps to address some constraints on sharing 
data, in other cases only policy actions on the part of the executive 
branch or Congress can lift barriers. One of the primary examples of 
such action is Congress's enactment of CIPSEA in 2002, which 
authorized the Census Bureau to share selected business data with BLS 
and the Bureau of Economic Analysis for statistical purposes. However, 
CIPSEA is limited because the Census Bureau's business data are based 
in large part on tax data, and as a result the tax code would need to 
be amended for the Census Bureau to also share these data with other 
statistical agencies. There have been proposals to amend the tax code 
to further expand the scope and coverage of CIPSEA, but action has not 
yet been taken by Congress.[Footnote 45]

Prospects for Enhanced Use of the ACS with Other Surveys Are Mixed:

The ACS Provides Unique Coverage of the Nation's Population:

The Census Bureau's full implementation of the ACS in 2005 was a major 
change to the statistical system. The survey is unique among other 
surveys of households and individuals because of its size--the monthly 
surveys add to an annual sample of 3.54 million addresses. The ACS 
provides annual estimates of social and economic characteristics for 
all areas of the country and is a primary source of information on 
small areas, such as towns and tribal lands, down to the neighborhood 
level. The ACS covers a broad range of topics, such as housing, 
education, and employment. The information provided by the ACS was 
previously only available once a decade from the decennial census long 
form, which the ACS replaced. Users of ACS information include all 
levels of government, the private and nonprofit sectors, and 
researchers. According to the Census Bureau, ACS estimates are 
currently used to help allocate more than $400 billion in federal 
funding annually. Table 2 lists some of the key characteristics of the 
ACS.

Table 2: Key Characteristics of the ACS:

Characteristic: Response requirements; 
ACS: Responses are required by law.

Characteristic: Frequency of administration; 
ACS: Administered on a monthly basis.

Characteristic: Frequency of data products; 
ACS: Annual.

Characteristic: Reference point for data products; 
ACS: Period estimates: the period over which data are cumulated is 
determined by the population of the geographic area for which the 
estimate applies. Estimates for places with populations of more than 
65,000 represent a 1-year period; places with populations of 20,000 to 
65,000 represent 3-year periods; and places with populations smaller 
than 20,000 represent 5-year periods. 

Characteristic: Number of questions; 
ACS: 48 potential questions per person, plus 21 per housing unit[A].

Characteristic: Respondent burden; 
ACS: 38 minutes per respondent[B].

Characteristic: Sample size; 
ACS: 3.54 million addresses per year.

Characteristic: Key uses; 
ACS: Directing government funding, informing government and private-
sector decision making, and research.

Source: Census Bureau.

[A] Although there are 48 individual questions on the ACS, several 
questions only apply to respondents with certain characteristics, so 
respondents likely do not answer every question. For example, only ACS 
respondents who are female and age 15 to 50 are asked to answer a 
question about whether they have given birth in the past year.

[B] The Census Bureau estimates that the respondent burden is 38 
minutes for the questionnaire it administers to households. Its 
estimates for other interviews, such as group quarters, are different. 

[End of table] 

Agencies Use the ACS to Inform the Design of Other Surveys and Analyze 
Their Results:

Several of the ACS's characteristics lend to its appeal for use for 
other surveys, including that it produces annual estimates on a broad 
range of topics at finer geographic levels than other surveys, and 
agencies and others identified five areas of opportunity in which 
surveys can make use of ACS data and resources. Two of these areas, 
which generally rely on publicly-available ACS estimates and do not 
require changes to the survey's design or methodology, have the 
greatest potential for widespread use. The Census Bureau has provided 
users with various resources to guide their use of ACS estimates. 
These include a guide to comparing estimates, handbooks directed to 
specific types of users, training presentations, and a tutorial. The 
two areas with the most potential for use are as follows:

* Evaluating and supplementing other surveys' results: Survey 
administrators and data users can also use ACS estimates to evaluate 
information collected by other surveys. For example, survey 
administrators can use ACS information to evaluate the quality of 
responses to other surveys that include some questions that are the 
same as or similar to ACS questions. Additionally, data users and 
survey administrators can use ACS data to supplement information 
collected by other surveys. For example, a recent report based on 
analysis of ACS data describes how median earnings vary by the field 
in which people obtain their bachelor's degrees.[Footnote 46] Such 
information can complement results from other surveys. In this case, 
NCSES also produces information on earnings by degree type, based on 
information in its Scientists and Engineers Statistical Data System 
database, which contains data on people with a science or engineering 
degree and those who work in related fields. NCSES information 
collection is less frequent than ACS estimates and pertains to a more-
narrowly defined population, but allows more detailed analysis of 
issues such as how people use their college degrees at work. Together, 
these two sources of information offer more-timely and more-detailed 
information than a single source.

* Designing other surveys: There is also widespread potential to use 
ACS data to more-efficiently design other surveys. Because many of the 
topics included in the ACS are covered in more detail by other surveys 
or relate to other surveys' target populations, survey administrators 
can use ACS estimates at different demographic or geographic levels to 
stay up-to-date on changes that may affect their surveys. These 
estimates can also be used when designing and selecting a survey's 
sample. Census Bureau officials told us that, when designing a survey, 
survey administrators can use the data to guide the selection of a 
survey's sample so that it better represents individuals or households 
with certain characteristics. For example, the Survey of Income and 
Program Participation can use ACS estimates at different demographic 
or geographic levels to identify and more-efficiently sample 
geographic areas with disproportionately large numbers of low-income 
households because this is a population of interest for the survey. 
Because these data are available for small geographic areas, agencies 
can use the data when samples include more-local geographic levels.

Uses of ACS That Require Design and Methodology Changes Have Limited 
Potential:

Agencies and others identified three uses of ACS data and resources 
that, while offering potential benefits to other surveys, face such 
constraints that more widespread use is likely not possible under 
current ACS design. These uses are more intensive than the ones 
described above, in that they affect the survey's design and 
methodology or respondent burden, or both. Because the ACS has a large 
sample size and a complex methodology, there are logistical challenges 
involved in changing its design and methodology. Additionally, any 
changes that affect the survey's respondent burden also have limited 
potential, as there are already concerns about the burden that the ACS 
places on respondents. Uses with more-limited potential are as follows:

* Adding or modifying ACS content: Adding a question to the ACS or 
modifying existing questions can improve the efficiency of other 
surveys, though doing so involves trade-offs with factors such as 
respondent burden. This use of ACS could provide information that 
would inform the design of other surveys or facilitate the use of ACS 
data for another survey's sample frame. For example, NCSES worked with 
the Census Bureau to add a question to the ACS about the field in 
which respondents earned their bachelor's degrees in order to identify 
respondents that are in the target population for the National Survey 
of College Graduates. Despite the potential benefits of adding or 
modifying ACS content, adding a question to the ACS would increase 
respondent burden and have operational impacts, as it requires the 
Census Bureau to change the questionnaire design and processing and 
editing systems. If these actions result in additional pages for the 
questionnaire, it could affect costs and the response rate. Modifying 
questions poses an additional challenge because ACS estimates reflect 
multiple years of data, and a change in a question may affect the 
Census Bureau's ability to cumulate data.

* Adding supplements to the ACS: Another possible use of the ACS by 
other surveys is adding supplements to the ACS, though this use faces 
several obstacles. While the ACS currently does not include 
supplements, doing so could enable surveys to leverage the resources 
of the ACS. Other surveys, such as the Current Population Survey, 
allow other agencies or entities to sponsor supplemental surveys that 
are added on to the survey's core set of questions. According to 
officials at BLS, which sponsors the Current Population Survey, in 
their experience it costs less to add a supplement to an existing 
survey than to conduct a separate stand-alone survey. Additionally, 
the agencies sponsoring the supplements gain the benefit of the 
experience of BLS or Census staff, or both, in designing and 
implementing surveys. Although the Current Population Survey 
successfully incorporates supplements, the ACS is different in several 
key ways, and adding supplements to the ACS would involve significant 
challenges. For example, the ACS is mandatory, meaning that responses 
are required by law. Assuming a supplement to the ACS would be 
voluntary, Census Bureau officials told us that they would have to 
determine how to distinguish between the mandatory and voluntary 
sections, which would create complexity. Additionally, the Census 
Bureau processes ACS data on a yearly basis and does not have a 
process in place for producing estimates from a single month's data, 
which would be a challenge if the supplement was administered along 
with only 1 month's ACS mailout. Finally, including supplements raises 
concerns about respondent burden and respondent fatigue.[Footnote 47] 
BLS officials noted the potential of matrix sampling, in which a set 
of additional questions, as in a supplement, is added to a month of 
collection (or all months) but differs from a supplement in that it is 
only administered to a subset of the survey sample in a given 
collection period. This option could reduce burden and increase 
efficiency; however, such an option involves logistical considerations 
in administering the survey and processing the data, and adds 
complexity for analysts using the data for research.

* Creating sample frames: Using ACS data to develop sample frames for 
follow-on surveys has been identified as a potential use of ACS data, 
but several factors limit this use.[Footnote 48] This involves using 
ACS data to identify ACS respondents with certain characteristics for 
potential inclusion in a follow-on survey and requires the approval of 
the Census Bureau and OMB.[Footnote 49] At present only NCSES uses ACS 
data for this purpose. Agency officials told us that using ACS data to 
create a sample frame, as opposed to census long-form data, which they 
used previously, has improved the agency's coverage of its target 
population and has reduced costs and respondent burden.[Footnote 50] 
Another benefit of this use is expanded analysis, as agencies, under 
appropriate Title 13 restrictions, can analyze respondents' answers to 
the ACS along with responses to the follow-on surveys, and can analyze 
the characteristics (from ACS data) of those who do and do not respond 
to the follow-on survey to determine if they have different 
characteristics, which might cause bias in the survey. Surveys such as 
the National Survey of College Graduates that focus on populations 
that are costly to identify are likely to realize higher gains in 
efficiency from using ACS data for this purpose. Despite these 
benefits, opportunities for other surveys to use ACS data for this 
purpose are limited. ACS's sample size, although large compared to 
most surveys, can be too small for another survey to use for a 
sampling frame. This is especially an issue if a survey targets a rare 
population or targets members similar to those of surveys already 
drawing from the ACS for their frame, because there would be too much 
chance of drawing individuals into both follow-on surveys, and current 
policy does not allow for that. Census Bureau policy states that, when 
agencies conduct follow-on surveys, they may not contact any member of 
a household that has already responded to the ACS and also had a 
member selected for a follow-on survey. With certain households in the 
ACS excluded from potential selection, it becomes more difficult for 
other surveys to draw samples because the data no longer reflect 
respondents with certain characteristics.

In the long run, more-intensive uses of ACS data and resources may 
require difficult decisions and entail trade-offs with factors such as 
cost and respondent burden. Further, they risk affecting ACS response 
rates and overall data quality. However, redesign of the scope and 
methodology of ACS might overcome some of these constraints. After the 
release of the survey's first 5-year data products in 2010, the Census 
Bureau and others began evaluating the survey and exploring options 
for increased uses. In addition to its own evaluation of the ACS, at 
the Census Bureau's request the National Academy of Sciences is 
organizing workshops with data users to assess the survey. Also, OMB, 
in cooperation with the Census Bureau, created an ACS subcommittee of 
the ICSP with the goal of investigating trade-offs of options such as 
adding questions to the ACS and rotating questions in and out of the 
survey. If the Census Bureau changes the survey's design or 
methodology, these changes may become more feasible.

Conclusions:

To ensure the provision of high-quality, timely statistical data for 
public-and private-sector users, OMB and the agencies that make up the 
federal statistical system must continue to identify opportunities for 
efficiency in federal surveys of households and individuals. Most of 
the surveys and other information collections in our scope have 
relatively modest costs, but challenges such as declining survey 
response rates will strain available resources unless agencies find 
more-effective and less-costly ways to collect and analyze the needed 
information, while maintaining critical protections of respondents' 
privacy and confidentiality. In the long term, addressing the key 
challenges and constraints that agencies have identified will 
necessitate broader public debates and policy decisions about 
balancing trade-offs among competing values, such as quality, cost, 
timeliness, privacy, and confidentiality. In the short term, our 
review indicated that two promising avenues to sustain the progress 
that OMB and agencies are making include (1) facilitating 
collaboration and coordination among agencies and (2) combining 
existing data from both survey and administrative sources.

The federal statistical system already exhibits many collaborative 
traits and practices, in particular through projects sponsored by OMB 
and interagency committees that facilitate coordination and the 
development of new policies and tools. However, additional efforts 
could help enhance the effectiveness of these efforts. Going forward, 
it will be important for OMB to supplement existing guidance to 
clarify the range of options available to address PRA standards. 
Supplementing the guidance could increase agencies' awareness of these 
options, in particular those that were cited less frequently. At the 
same time, interagency committees could do more to improve 
accessibility and timeliness of their work products. Doing so could 
maximize the usefulness of committees' work. Additionally, OMB's 
ability to oversee and coordinate information collections across the 
government would benefit from additional steps to ensure the 
reliability of data on collections' costs and burdens. Doing so would 
also benefit users of the information, whether they access it through 
the website or though OMB reports.

Agencies identified multiple ways that combining survey and 
administrative data can improve the efficiency and quality of their 
work, and they are already pursuing such opportunities. Importantly, 
they have demonstrated that using existing datasets to supplement each 
other can add value for all agencies involved in data sharing. But 
agencies also face serious constraints to expanded uses of existing 
data. One of the more-significant barriers is the complexity of the 
process through which they make decisions about sharing data. Though 
agencies and interagency committees are working to create tools to 
facilitate parts of this process, more-comprehensive and centralized 
guidance for agencies to follow when negotiating and making decisions 
regarding data-sharing opportunities could help facilitate the process.

A standard protocol or framework could accelerate progress in this 
area by helping agencies to (1) evaluate the growing array of 
administrative data to identify those datasets that have the greatest 
potential for mutual benefit of the participating agencies, and (2) 
consider a common set of criteria and key questions when weighing the 
pros and cons of sharing data. A key benefit would be to encourage 
agencies to consider, in a uniform manner, all relevant aspects of 
these decisions, such as whether or not proposed uses would be 
consistent with applicable law, maintain confidentiality protections, 
be cost-effective, and serve to increase the broader efficiency of the 
federal statistical system.

Recommendations for Executive Action:

In order to maintain progress in maximizing the efficiency of existing 
data sources, we recommend that the Director of OMB, in consultation 
with the Chief Statistician, work with the ICSP to take the following 
four actions:

To improve the broader efficiency of the federal statistical system 
and improve communication among agencies and others,

* when OMB next updates guidance on agency survey and statistical 
information collection and dissemination methods, include additional 
details on actions agencies can take to meet requirements to identify 
duplication, to consult with persons outside of the agency, and 
address other requirements as appropriate; and:

* create new methods or enhance existing methods to improve the 
dissemination of information and resources produced by interagency 
statistical committees. For example, such enhancements could include 
increasing the timeliness and availability of information on websites 
to better capture the full range of products and identify committee 
priorities.

To increase the reliability of the information presented on the 
Reginfo.gov website and in OMB's internal system,

* implement quality-control procedures designed to identify and remedy 
any differences between cost and burden information provided on the 
website and in the related supporting statement documentation that 
underlies this information.

To accelerate progress in sharing administrative data for statistical 
purposes, where appropriate,

* develop comprehensive guidance for both statistical agencies and 
agencies that hold administrative data to use when evaluating and 
negotiating data sharing, such guidance should include key questions 
focused on issues such as statutory authority, confidentiality, cost, 
and usefulness in order to ensure agencies consider all relevant 
factors and the broader interest of the federal government.

Agency Comments and Our Evaluation:

We provided a draft of this report to the Secretaries of Commerce and 
Health and Human Services, the Director of OMB, the Commissioner of 
BLS, the Administrator of ERS, and the Director of the National 
Science Foundation for their review and comment. We received written 
comments on the draft report from the Secretary of Commerce that are 
reprinted in appendix V. We also received comments from OMB staff that 
are summarized below. The Department of Health and Human Services, 
BLS, National Science Foundation, OMB, and agencies on the ICSP also 
provided technical comments and suggestions that we incorporated as 
appropriate.

Commerce stated that our observations illuminate future opportunities 
for using administrative records within the federal statistical system 
to increase efficiency and better meet informational needs and that 
our suggested actions would enhance the ability of statistical 
agencies to realize these opportunities. Regarding our recommendation 
on standard protocols and procedures to facilitate data sharing, the 
department noted that policies and other initiatives can also play a 
role in achieving cooperation. Finally, the department noted that our 
report's acknowledgment of related concerns about the quality of 
administrative data, and the level of support and resources necessary 
to maintain a statistical and administrative data infrastructure, 
underscore the importance of our recommendations.

OMB generally agreed with our recommendations and said that the agency 
hopes to pursue these in the future. More specifically,

* OMB agreed that it is worth considering good practices for reducing 
duplication. As we suggested, OMB indicated that when its survey 
guidance is next updated it will include additional details and 
examples of actions agencies can take to identify duplication and 
consult with persons outside the agency.

* OMB said that it shared our concerns about timely and easily 
accessible dissemination of information resources produced by 
interagency statistical committees, and that our recommendation 
underscores the need for addressing this issue.

* With respect to our recommendation that OMB implement quality-
control procedures designed to identify and remedy any differences 
between cost and burden information provided on Reginfo.gov and in the 
related supporting statement documentation that underlies this 
information, OMB noted that PRA requires OMB to weigh the burdens 
imposed on the public by information collections against the 
legitimate needs of the federal agencies. OMB said that this requires 
a careful assessment of the estimates of paperwork burden that 
agencies provide to OMB as part of their information collection 
requests and, further, that these estimates are subject to public 
scrutiny and comment in Federal Register notices, in the PRA 
statements provided on information collections, and on Reginfo.gov. 
OMB pointed out that, because the burden estimates provided on 
Reginfo.gov and in the underlying supporting statements are all made 
public, discrepancies such as those found by us are public as well. 
OMB said that it will investigate and address any such discrepancies 
that are brought to its attention by GAO or any member of the public.

* Finally, OMB concurred that administrative records can be a valuable 
supplement to, though usually not a replacement for, household 
surveys. OMB believes that our recommendation to develop comprehensive 
guidance for statistical and administrative agencies to use when 
evaluating and negotiating data-sharing agreements would be 
constructive, but cautioned that this involves a very complex set of 
issues and said it will take some time to develop such guidance.

As agreed with your office, unless you publicly announce the contents 
of this report earlier, we plan no further distribution until 30 days 
from the report date. At that time, we will send copies to the 
Commissioner of the Bureau of Labor Statistics (BLS), the Director of 
the U.S. Census Bureau, the Administrator of the Economic Research 
Service (ERS), the Secretary of Health and Human Services, the 
Director of the National Science Foundation, the Director of OMB, the 
Secretary of Commerce, and the Under Secretary of Economic Affairs. In 
addition, the report will be available at no charge on the GAO website 
at [hyperlink, http://www.gao.gov].

If you or your staff have any questions concerning this report, please 
contact Robert Goldenkoff at (202) 512-2757 or goldenkoffr@gao.gov, or 
Ronald S. Fecso at (202) 512-7791 or fecsor@gao.gov. Contact points 
for our Offices of Congressional Relations and Public Affairs may be 
found on the last page of this report. Key contributors are listed in 
appendix VI.

Sincerely yours, 

Signed by: 

Robert Goldenkoff: 
Director, Strategic Issues: 

Signed by: 

Ronald S. Fecso: 
Chief Statistician: 

[End of section] 

Appendix I: Scope and Methodology: 

The objectives of this report were to (1) review the ways in which the 
Office of Management and Budget (OMB) and agencies identify 
opportunities for improvement and increased efficiency of selected 
information collections; (2) evaluate opportunities and constraints 
for the statistical agencies to use administrative data in conjunction 
with selected surveys; and (3) evaluate ways in which American 
Community Survey (ACS) data and resources can be used in selected 
surveys, and the associated benefits and constraints.

To achieve our objectives, we focused on statistical information 
collections administered to households and individuals and subject to 
the Paperwork Reduction Act (PRA), which requires OMB approval of 
certain federal data collections. Although in many cases the 
information and views provided by agencies during our review and our 
general findings may also apply to statistical information collections 
outside of our scope, such as those administered to businesses, all of 
the specific collections and surveys we reviewed were administered to 
households and individuals. The majority of the collections within our 
scope include a survey, though some also include other methods of 
information collection such as focus groups. To examine the issues 
related to our objectives, we performed case studies of five federal 
surveys: the Consumer Expenditure Surveys, sponsored by the Bureau of 
Labor Statistics; the National Health and Nutrition Examination Survey 
and the National Health Interview Survey, both sponsored by the 
National Center for Health Statistics, part of the Centers for Disease 
Control and Prevention; the National Survey of College Graduates, 
sponsored by the National Center for Science and Engineering 
Statistics, part of the National Science Foundation; and the Survey of 
Income and Program Participation, sponsored by the Census Bureau. We 
selected these surveys based on several factors, such as their size 
and cost and whether they use or have the potential to use 
administrative data or ACS data.

For the first objective, to review the ways in which OMB and agencies 
identify opportunities for improvement and increased efficiency of 
selected statistical information collections, we examined the PRA, OMB 
guidance to agencies, and prior GAO work on the federal statistical 
system.[Footnote 51] We interviewed officials at OMB and the four 
agencies that administer the case-study surveys to learn about 
coordination among agencies, efforts agencies take to identify 
improvement, and OMB's role. We also interviewed officials at the 
Department of Agriculture's Economic Research Service, which is a 
member of several interagency statistical committees and the lead 
agency for the Statistical Community of Practice and Engagement. In 
addition, we interviewed experts on the federal statistical system to 
learn about their perspectives on the efficiency of the federal 
statistical system and agency and OMB coordination. In evaluating OMB, 
agency, and interagency actions, we used as criteria the requirements 
of the PRA and practices identified in prior GAO work on agency 
collaboration.[Footnote 52]

To address the second objective, to evaluate opportunities and 
constraints for agencies to use administrative data in conjunction 
with selected surveys, we reviewed statutes that govern the sharing 
and use of administrative data, documentation from case-study surveys, 
and various papers and reports. We interviewed officials at OMB and 
experts in the field of federal statistics to learn about their 
perspectives on the current and potential uses of administrative data. 
We also interviewed officials at the Economic Research Service and the 
agencies that sponsor the case-study surveys to learn about ways in 
which their surveys use or could potentially use administrative data. 
For this objective and the third we used OMB guidance, relevant 
statutes, and prior GAO work as criteria in our evaluation.

For the third objective, to evaluate the ways in which ACS data and 
resources can be used in selected surveys, we reviewed Census Bureau 
documentation, National Science Foundation reports, prior GAO work, 
and reports issued by the Committee on National Statistics. We 
interviewed officials at the Census Bureau, which sponsors the ACS, 
and at OMB to learn about their perspectives on potential uses of the 
survey and its data. We also interviewed officials at the Economic 
Research Service and the agencies that administer the case-study 
surveys to learn about ways in which their surveys use or could 
potentially use ACS data and resources, and experts in the field of 
federal statistics to learn about their assessment of the uses and 
potential uses of the ACS.

To gain a broader perspective on the information collections in our 
scope and to inform our work across all three objectives, we obtained 
and analyzed publicly-available data from Reginfo.gov, a government 
website that provides access to information on agency requests for OMB 
approval of information collections. We used the website's search 
feature to download all of the collections that were classified as (1) 
active, meaning that they are currently approved by OMB for use by 
agencies; (2) employing statistical methods; and (3) directed to 
households and individuals. We downloaded data on all information 
collections that met these criteria from Reginfo.gov on two dates, May 
17, 2011, and September 22, 2011.

We performed more in-depth analyses of the 507 information collections 
in our May 17, 2011, download. First, we reviewed the supporting 
statements for each of these collections, and on the basis of 
information in these documents classified them according to the 
subject matter on which they focus.[Footnote 53] Next, we grouped the 
collections into categories, based on information on the sponsoring 
agency in Reginfo.gov and the supporting statements. Depending on the 
sponsoring agency, we put the collections into one of four categories: 
(1) those that are sponsored by one of the 13 principal statistical 
agencies; (2) those that are sponsored by another agency that shares a 
parent agency with one of the 13 principal statistical agencies (for 
example, agencies in the Department of Health and Human Services would 
fall into this category because it is the parent agency of the 
National Center for Health Statistics); (3) those that are not a 
principal statistical agency and do not share a parent agency with 
one; and (4) unknown, for those whose sponsoring agency we could not 
determine based on the available information. We also used the 
information in the supporting statements to determine if the 
collections included a survey component and found that 481 of the 507 
did.

We divided the 481 collections that included a survey component into 
three strata that reflect the type of sponsoring agency. Of the 481, 
we were not able to determine agency type for 7 collections so we 
dropped these records, leaving a population of 474 statistical 
information collections. The number of collections by stratum is shown 
in table 3. In order to estimate the prevalence of certain 
characteristics in this population--for example, the percentage of 
information collections for which the sponsoring agency reported steps 
taken to identify potential duplication--we drew a stratified sample 
of 106 collections. Within each stratum, we estimated the sample size 
required to yield a 95 percent confidence interval of plus or minus 14 
percent around such an estimate. For the overall population of 474, 
the approximate precision for an estimated percentage of 50 percent is 
plus or minus 8.4 percent, at the 95 percent level of confidence.

Table 3: Number of Collections, by Stratum:

Stratum: Principal statistical agency; 
Stratum population: 60; 
Sample size: 27.

Stratum: Nonstatistical agency; 
Stratum population: 139; 
Sample size: 37.

Stratum: Nonstatistical agency that shares a parent agency with a 
statistical agency; 
Stratum population: 275; 
Sample size: 42.

Stratum: Total: 
Stratum population: 474; 
Sample size: 106.

Source: GAO analysis of OMB data. 

[End of table] 

We reviewed the supporting statements of each of the information 
collections in our sample of 106, focusing on agencies' reported 
efforts to identify duplication and to consult with persons outside 
the agency to obtain their views. Because agencies follow a standard 
format in preparing supporting statements, we focused our analysis on 
the sections of the supporting statements in which OMB instructs 
agencies to include this information (sections 4 and 8, respectively, 
of section A of the supporting statement). To review agencies' 
reported actions, we used a data-collection instrument that contained 
a series of "yes-no" questions about the types of efforts reported. 
For example, we reviewed whether agencies had reported considering 
administrative data as a potential source of duplication, and whether 
agencies reported that they had consulted with other agencies when 
describing consultations outside of the agency. We did not evaluate 
whether agencies actually took the actions they reported taking. 
Estimates produced from the sample of the collections are subject to 
sampling error. We express our confidence in the precision of our 
results as a 95 percent confidence interval. This is the interval that 
would contain the actual population value for 95 percent of the 
samples we could have drawn. As a result, we are 95 percent confident 
that each of the confidence intervals in this report will include the 
true values in the study population.

We took several steps to evaluate the reliability of the data we 
accessed through the Reginfo.gov website. We interviewed OMB officials 
and reviewed documentation of the Reginfo.gov website and the 
Regulatory Information Service Center and OIRA Consolidated 
Information System,[Footnote 54] which is the system that agencies use 
to track information collection requests and that underlies 
information provided on Reginfo.gov. As part of our review of the 
subject matter of the collections in the May 17, 2011, download, we 
confirmed that the collections were within our scope. We also used the 
information in the September 22, 2011, download to evaluate the 
reliability of data on collections' cost and annual burden. To do 
this, we drew a systematic random sample of 56 (approximately 10 
percent) of the 555 collections in the download.

We found a number of inconsistencies between the cost and burden 
information available on the website and that provided in supporting 
statement documentation. According to an official at OMB, the two 
sources should match, but the supporting statement documentation is 
more accurate than that on the website. On the basis of our 
assessment, we determined that the information from the website was 
not sufficiently reliable for the purpose of describing the annual 
cost or annual burden to respondents of the collections in our scope. 
However, through this review and the other steps we took, we found 
that the other information provided on the Reginfo.gov site was 
sufficiently reliable for our other intended purposes of identifying 
the collections within our scope and obtaining information on their 
subject matter and reported actions taken to identify unnecessary 
duplication and solicit input from outside persons and entities.

Because the cost information on the Reginfo.gov website was not 
sufficiently reliable, we used cost information from the supporting 
statements of the collections in our sample to provide background 
information on the costs of the collections in our scope. In addition 
to using information from the supporting statements in our initial 
sample of 56 collections, we drew another systematic random sample of 
56 additional collections from the September download. In total, we 
obtained cost information from the supporting statements of 112 
(approximately 20 percent) of the 555 collections in our scope that 
were active as of our September 22, 2011, download.

We conducted this performance audit from December 2010 until February 
2012 in accordance with generally accepted government auditing 
standards. Those standards require that we plan and perform the audits 
to obtain sufficient, appropriate evidence to provide a reasonable 
basis for our findings and conclusions based on our audit objectives. 
We believe that the evidence obtained provides a reasonable basis for 
our findings and conclusions based on our audit objectives. 

[End of section] 

Appendix II: Description of Case-Study Surveys:

Consumer Expenditure (CE) Surveys: Quarterly Interview Survey (CEQ) 
and Diary Survey (CED):

Purpose: To collect information on expenditures and households' 
characteristics:

Sponsoring agency: Bureau of Labor Statistics (BLS):

Annual sample size (estimated): CEQ: 14,725 households;[Footnote 55] 
CED: 12,075 households[Footnote 56]. 

Annual cost to the federal government (estimated): $41.8 
million[Footnote 57]. 

Annual burden hours (estimated): CEQ: 36,033hours;[Footnote 58] CED: 
33,721 hours[Footnote 59]. 

Target population: Nationally-representative sample of the U.S. 
population[Footnote 60]. 

Uses of data: According to BLS documentation, the most important use 
of the CE Surveys is to provide expenditure data for updating the 
Consumer Price Index, the most widely used measure of inflation. 
[Footnote 61] In addition, government agencies, private companies, 
policymakers, and researchers use data from the CE Surveys in a 
variety of ways. For example, the Department of Defense uses data from 
the CE Surveys to update cost-of-living adjustments for military 
families. Congressional committees also use the data to inform 
decision making, such as the potential effect of increases in the 
minimum wage.

National Health and Nutrition Examination Survey (NHANES):

Purpose: To assess the health and nutritional status of adults and 
children in the United States:

Sponsoring agency: National Center for Health Statistics (NCHS), 
Centers for Disease Control and Prevention:

Annual sample size (estimated): 5,180 individuals[Footnote 62]; 

Annual cost to the federal government (estimated): $37.8 million 
[Footnote 63]; 

Annual burden hours (estimated): 49,626 hours[Footnote 64]; 

Target population: Nationally-representative sample of individuals of 
all ages[Footnote 65]. 

Uses of data: According to NCHS documentation, a variety of users, 
including federal agencies, research organizations, universities, 
health-care providers, and educators, use NHANES data. For example, 
the Food and Drug Administration uses NHANES data to determine whether 
changes are needed to federal regulations. In addition, use of NHANES 
data informs key decision making. For example, according to NCHS 
documentation, NHANES data on lead levels in blood were instrumental 
in developing the policy to eliminate lead from gasoline and in food 
and soft drink cans. As part of its broader data-linkage program, NCHS 
links NHANES survey data to multiple administrative datasets, such as 
the National Death Index (a centralized index of state death record 
information) and Medicare and Medicaid claims from the Centers for 
Medicare and Medicaid Services. The National Death Index linkages give 
researchers an opportunity to analyze mortality differences among 
subgroups defined using the survey information. Similarly, the 
Medicare and Medicaid claim linkages provide an opportunity to examine 
health conditions, utilization, and costs among subgroups defined 
using the survey information. Additionally, according to NCHS 
officials, NCHS is currently conducting a pilot study to link NHANES 
data on participants from Texas to administrative data on food 
assistance.

National Health Interview Survey (NHIS):

Purpose: To monitor the health of the U.S. population:

Sponsoring agency: National Center for Health Statistics (NCHS), 
Centers for Disease Control and Prevention:

Annual sample size (estimated): 35,000 households[Footnote 66]; 

Annual cost to the federal government (estimated): $32.2 million 
[Footnote 67]; 

Annual burden hours (estimated): 34,977 hours[Footnote 68]; 

Target population: Nationally-representative sample of households, 
collecting data on all members of each household[Footnote 69]. 

Uses of data: According to NCHS documentation, government agencies, 
policymakers, researchers, and academics use NHIS data for a variety 
of purposes, such as identifying health problems and evaluating health 
programs. For example, policymakers used NHIS data to shape the 
Centers for Disease Control and Prevention's cervical-cancer screening 
policy. In addition, other agencies can use the NHIS as a sample frame 
for their surveys. Lastly, as part of its broader data-linkage 
program, NCHS links NHIS survey data to multiple administrative 
datasets, including those it uses for linkages with NHANES data, such 
as the National Death Index and Medicaid and Medicare claims.

National Survey of College Graduates (NSCG):

Purpose: To provide information on the U.S stock of scientists and 
engineers:

Sponsoring agency: National Center for Science and Engineering 
Statistics, National Science Foundation:

Sample size per survey administration (estimated): 100,000 individuals:

Cost to the federal government (estimated): $13.3 million[Footnote 70]; 

Burden hours per administration (estimated): 34,792 hours[Footnote 71]; 

Target population: Individuals in the United States who have a 
bachelor's degree in science, engineering, or health, and those who 
have a degree in another field but work in science, engineering, or 
health occupation.

Uses of data: According to National Science Foundation documentation, 
information from the NSCG is used by researchers and policymakers. 
Government agencies use the data to assess available scientific and 
engineering resources and inform the development of related policies. 
Additionally, educational institutions use NSCG data to inform the 
establishment and modification of curricula, and businesses use the 
data to develop recruitment and compensation policies.

Survey of Income and Program Participation (SIPP):

Purpose: To provide information about status and principal 
determinants of individuals' and households' income and participation 
in government programs such as Social Security and Medicaid:

Sponsoring agency: Census Bureau:

Annual sample size (estimated): 45,000 households[Footnote 72]; 

Annual cost to the federal government (estimated): $50 million 
[Footnote 73]; 

Annual burden hours (estimated): 143,303 hours[Footnote 74]; 

Target population: Nationally-representative sample of households. 
[Footnote 75] All household members 15 years old or over are 
interviewed for the survey.

Uses of data: According to the Census Bureau, SIPP data are used by 
agencies such as the Department of Health and Human Services and the 
Department of Agriculture, as well as economic policymakers, Congress, 
and state and local governments, to plan and evaluate government 
social-welfare and transfer-payment programs. 

[End of section] 

Appendix III: Selected Statutes Related to Information Collection:

Selected statutes that regulate the collection and dissemination of 
information include the following.

Governmentwide Statutes:

* The Information Quality Act of 2000 requires, among other things, 
that the Office of Management and Budget (OMB) develop and issue 
guidelines that provide policy and procedural guidance for federal 
agencies for ensuring and maximizing the quality of the information 
they disseminate. These guidelines include steps designed to assure 
objectivity and utility of disseminated information. See 44 U.S.C. § 
3504(d)(1); OMB guidelines are at [hyperlink, 
http://www.whitehouse.gov/omb/info_quality_iqg_oct2002/].

* The Privacy Act of 1974, as amended, and the privacy provisions of 
the E-Government Act of 2002 specify requirements for the protection 
of personal privacy by federal agencies. The Privacy Act places 
limitations on agencies' collection, disclosure, and use of personal 
information maintained in systems of records. See 5 U.S.C. §§ 552a and 
552a note. The E-Government Act requires agencies to conduct privacy 
impact assessments that analyze how personal information is collected, 
stored, shared, and managed in a federal system. See 44 U.S.C. § 3501 
note.

* The Confidential Information Protection and Statistical Efficiency 
Act (CIPSEA) of 2002 focuses on confidentiality protection and data 
sharing. It requires that information acquired by an agency under a 
pledge of confidentiality and for exclusively statistical purposes be 
used by the agency only for such purposes and not be disclosed in 
identifiable form for any other use, except with the informed consent 
of the respondent. It also authorizes identifiable business records to 
be shared for statistical purposes among the Bureau of Economic 
Analysis, Bureau of Labor Statistics, and the Census Bureau. See 44 
U.S.C. § 3501 note.

Agency-Specific Statutes:

* Agency-specific statutes also guide federal data collection and use. 
For example, the Census Bureau conducts the census and census-related 
surveys such as the American Community Survey under Title 13 of the 
U.S. Code, which gives the Census Bureau the authority to request and 
collect information from individuals but also guarantees the 
confidentiality of these data and establishes penalties for unlawfully 
disclosing this information. Unless specifically authorized, these 
provisions preclude the Census Bureau from sharing identifiable census 
information with other agencies. See 13 U.S.C. § 9. Title 15 of the 
U.S. Code permits the Secretary of Commerce to conduct studies on 
behalf of other agencies and organizations. Identifiable data from 
surveys conducted under Title 15 authority are subject to the 
sponsoring agency's legislation and confidentiality requirements. See 
15 U.S.C. § 176a. Statutes and regulations specific to other agencies 
also affect collection and sharing of data.

* Section 6103 of the Internal Revenue Code provides that federal tax 
information is confidential and may not be disclosed except as 
specifically authorized by law.

* Section 308(d) of the Public Health Service Act requires that 
identifiable information obtained by the National Center for Health 
Statistics be used only for the purpose for which it was collected 
unless consent is obtained for another purpose, and it prohibits the 
release of identifiable information without consent.

* Other legislation such as the Family Educational Rights and Privacy 
Act, which protects the privacy of student education records, can 
affect federal data-collection efforts. See 20 U.S.C. § 1232g. 

[End of section] 

Appendix IV: Printable Interactive Graphic:

This table reproduces the information in the interactive figure 3 
earlier in this report.

Table 4: Actions Taken to Address Constraints That Hamper Greater Use 
of Administrative Data:

Constraint type: Access; 
Constraint: Statutory restrictions on data sharing; 
Description: Statutes may not authorize statistical uses for data 
collected by a program; 
Examples of actions taken: 
* OMB [the Office of Management and Budget] has issued guidance 
encouraging greater sharing of data while protecting privacy; and; 
* FCSM [the Federal Committee on Statistical Methodology] produced a 
document, highlighting lessons learned when negotiating data-sharing 
agreements. 

Constraint type: Access; 
Constraint: Consent; 
Description: Agencies may not have consent from respondents to use 
their administrative data for statistical purposes, or agencies may 
interpret the legal requirements for consent differently; 
Examples of actions taken: 
* When requesting consent to link respondents' survey data with 
administrative data, NCHS [the National Center for Health Statistics] 
has moved from asking for respondents' full Social Security numbers to 
only asking for part of their Social Security numbers (used to assure 
link quality), which has improved consent rates; and; 
* FCSM is working on a project to clarify legal requirements for 
informed consent and to examine the current practices agencies 
typically use to obtain consent. 

Constraint type: Access; 
Constraint: Costs and infrastructure; 
Description: Agencies may not have the staff, policies, procedures, 
and systems in place to share or use administrative data for 
statistical purposes; 
Examples of actions taken: 
* FCSM is completing a template for agencies to use when negotiating 
data-sharing agreements; 
* FCSM produced a document highlighting lessons learned when 
negotiating data sharing agreements; and; 
* The Census Bureau is using government and commercial administrative 
data to simulate the 2010 Census results, as well as comparing the 
quality of the Census Bureau's process for linking data from NCHS 
surveys with administrative data to NCHS's current record-linkage 
process. 

Constraint type: Quality; 
Constraint: Data documentation; 
Description: Agencies may not uniformly document information about 
administrative datasets; 
Examples of actions taken: 
* FCSM is investigating the potential for using a checklist to 
evaluate the quality of datasets, part of which focuses on 
documentation in order to assess potential for statistical uses. 

Constraint type: Quality; 
Constraint: Quality of data; 
Description: The quality of administrative data varies; 
Examples of actions taken: 
* The Census Bureau is investigating the quality of administrative 
data held by private companies; 
* FCSM and the Census Bureau are investigating the quality of 
administrative data and the potential for using a checklist to assess 
the quality of datasets; and; 
* ERS [the Economic Research Service] (in collaboration with the 
Census Bureau and NCHS) is undertaking a pilot project to address data-
quality concerns with state-level administrative data. 

Source: GAO analysis of OMB and principal statistical agency data.

Note: Data are from related documentation and interviews with 
officials at OMB and selected principal statistical agencies. 

[End of table] 

Appendix V: Comments from the Department of Commerce: 

United States Department of Commerce: 
The Secretary of Commerce: 
Washington, DC, 20230: 

February 6, 2012: 

Mr. Robert Goldenkoff: 
Director: 
Strategic Issues: 
U.S. Government Accountability Office: 
Washington, DC 20548: 

Dear Mr. Goldenkoff: 

Enclosed is the Department of Commerce's action plan in response to 
recommendations contained in the Government Accountability Office's 
final report, titled "Federal Statistical System: Agencies Can Make 
Greater Use of Existing Data, But Continued Progress is Needed on 
Access and Quality Issues" (GAO-12-54). This plan was prepared in 
accordance with the Office of Management and Budget's Circular A-50. 

Sincerely, 

Signed by: 

John E. Bryson: 

[End of letter] 

U.S. Department of Commerce Response to the United States Government 
Accountability Office (GAO) Report titled "Federal Statistical System: 
Agencies Can Make Greater Use of Existing Data, But Continued Progress 
is Needed on Access and Quality Issues" (GAO-12-54): 

The Government Accountability Office's observations illuminate future 
opportunities for using administrative records within the Federal 
statistical system to increase efficiency and better meet 
informational needs. The report also suggests several actions that 
would enhance the ability of statistical agencies to realize these 
opportunities, including expanding access to administrative records 
through statutory revisions, comprehensive decision frameworks, and 
greater information sharing, not only within the statistical system 
but also with Federal partners and the public. 

By making these recommendations, GAO elevates key concerns within the 
statistical agencies, including the degree of cooperation required 
between statistical and administrative agencies to negotiate data-
sharing agreements. Such cooperation is fundamental to expanding 
access to Federal data sources and the use of administrative records 
within the Federal system. While standard protocols and procedures 
will facilitate such cooperation, it is also important to note that 
policies and other initiatives can also play a role in achieving 
cooperation. 

Finally, the Census Bureau appreciates GAO's acknowledgment of related 
concerns about the quality of administrative data, as well as the 
level of support and resources necessary to maintain a statistical and 
administrative data infrastructure. Recognizing these concerns 
underscores the importance of GAO's recommendations regarding quality-
control procedures, information collection requirements, 
dissemination, and comprehensive guidance. 

[End of section] 

Appendix VI: GAO Contacts and Staff Acknowledgments:

GAO Contacts:

Ronald S. Fecso, (202) 512-7791 or fecsor@gao.gov:

Robert Goldenkoff, (202) 512-2757 or goldenkoffr@gao.gov:

Staff Acknowledgments:

In addition to the individuals named above, Tim Bober (Assistant 
Director), Carl Barden, Russell Burnett, Robert Gebhart, Jill Lacey, 
Andrea Levine, Jessica Nierenberg, Susan Offutt, Kathleen Padulchick, 
Tind Shepper Ryen, and Jared Sippel made key contributions to this 
report.

[End of section] 

Footnotes: 

[1] Examples of administrative data include Social Security 
Administration records, state unemployment records, medical records, 
and store loyalty-card data.

[2] The PRA is codified at 44 U.S.C. §§ 3501-3521. 

[3] For examples of our prior work, see: GAO, Federal Information 
Collection: A Reexamination of the Portfolio of Major Federal 
Household Surveys Is Needed, GAO-07-62 (Washington, D.C.: Nov. 15, 
2006); American Community Survey: Key Unresolved Issues, GAO-05-82 
(Washington, D.C.: Oct. 8, 2004). 

[4] The website is maintained by OMB and the General Services 
Administration.

[5] The Statistical Community of Practice and Engagement is an 
interagency committee that focuses on providing a collaborative 
community for agencies that focus on statistics. 

[6] GAO, Results-Oriented Government: Practices That Can Help Enhance 
and Sustain Collaboration among Federal Agencies, GAO-06-15 
(Washington, D.C.: Oct. 21, 2005).

[7] Examples of countries that have centralized statistical agencies 
include Australia, Canada, and Sweden. 

[8] The amount requested for statistical work includes requested 
funding for work done by federal agencies that have annual budgets of 
$500,000 or more for statistical work. OMB presented this information 
in Statistical Programs of the United States Government, Fiscal Year 
2011, an annual report that it prepares on statistical program 
funding. This was the most up-to-date budget information available at 
the time of our review.

[9] When decennial census costs are included, the fiscal year 2011 
budget request for the Census Bureau was $1.3 billion. 

[10] The sample of 112 collections was designed to be representative 
of the population of 555 collections in our scope that were active as 
of September 22, 2011.

[11] For example, the Committee on National Statistics publishes 
"Principles and Practices for a Federal Statistical Agency" every 4 
years in order to provide a current edition to newly appointed cabinet 
secretaries at the beginning of each presidential administration. This 
report outlines basic principles that statistical agencies should 
adhere to in order to carry out their missions effectively, as well as 
practices designed to help implement them.

[12] 44 U.S.C. § 3501 note.

[13] 44 U.S.C. § 3504.

[14] Under PRA the term "person" includes, among others, individuals, 
partnerships, associations, corporations, and state and local 
governments. 

[15] OMB, "Questions and Answers When Designing Surveys for 
Information Collections," (January 2006).

[16] Similar coordination could be fruitful for other surveys as well. 
For example, we have noted concerns about the surveys the Department 
of Labor uses for Davis-Bacon Act wage determination and have 
recommended that the department seek help from an independent 
statistical organization to ensure survey methods are sound and in 
accordance with best practices. See GAO, Davis-Bacon Act: 
Methodological Changes Needed to Improve Wage Survey, GAO-11-152 
(Washington, D.C.: March 22, 2011).

[17] Information collections' supporting statements contain a 
narrative section through which agencies describe their efforts to 
identify potential duplication. Our review focused on collections that 
were active as of May 17, 2011.

[18] These directions are provided in OMB's "Questions and Answers 
When Designing Surveys for Information Collections," and OMB Circular 
No. A-130. 

[19] OMB defines unnecessary duplication as information similar to or 
corresponding to information that could serve the agency's purposes 
and need and is already accessible to the agency. (OMB, The Paperwork 
Reduction Act of 1995: Implementing Guidance for OMB Review of Agency 
Information Collection, draft [Aug. 16, 1999]).

[20] The 95 percent confidence interval for this estimate is (68, 85).

[21] The 95 percent confidence interval for this estimate is (46, 68).

[22] The 95 percent confidence interval for this estimate is (32, 59).

[23] Twenty-four percent of collections indicated that agencies 
consulted with another entity, and 25.5 percent reported that they 
conducted literature searches. The 95 percent confidence intervals for 
these estimates are (15, 35) and (16, 37), respectively.

[24] For example, the ACS is the largest survey in our scope and is 
administered annually to 2.5 percent of households. 

[25] The 95 percent confidence interval for this estimate is (65, 83).

[26] The 95 percent confidence interval for this estimate is (46, 67).

[27] Thirty nine percent of collections indicated that agencies 
consulted with other agencies, 32 percent reported contacting 
contractors or subcontractors, and 15 percent described meeting with 
interagency or advisory committees. The 95 percent confidence 
intervals for these estimates are (30, 49), (22, 41), and (8, 25), 
respectively. 

[28] For example, we estimate that 15 percent reported soliciting 
input from data users and customers. The 95 percent confidence 
interval for this estimate is (8, 25). 

[29] Factors that facilitate interaction among agencies and between 
agencies and others in the statistical community include agency 
staff's professional involvement in committee work, movement by some 
staff to other agencies during their careers, and training 
opportunities. For example, survey methodologists work together on 
various interagency subcommittees. Plus, their professional 
development also includes attending local and other conferences at 
which papers are presented describing uses and activities related to 
surveys in other agencies. These opportunities for cross-agency 
professional knowledge transfer facilitate collaboration and the 
identification of opportunities for efficiency.

[30] The Landsat Survey collects information from professional users 
of satellite imagery to better understand the uses and applications of 
moderate-resolution satellite imagery as well as information about the 
users. 

[31] GAO-06-15.

[32] Outside of these interagency committees, there are nonfederal 
organizations, such as the Committee on National Statistics and the 
Council of Professional Associations on Federal Statistics, which 
serve as resources to identify opportunities for improving federal 
statistics.

[33] GAO-06-15.

[34] OMB staff noted that the specific program improvements are 
reflected in the President's budget. 

[35] FedStats is a website that provides access to statistical 
information produced by the federal government. In addition, it 
includes all federal agencies listed in Statistical Programs of the 
United States Government that report a certain level of expenditures 
in statistical activities.

[36] FCSM has active subcommittees looking at statistical uses of 
administrative data and privacy issues. In addition, FCSM has 
permanent working groups that discuss specific topic areas, such as 
nonresponse to household surveys. 

[37] GAO-06-15.

[38] John Gantz and David Reinsel, "Extracting Value from Chaos" 
(Framingham, Mass.: IDC Go-to-Market Services, June 2011).

[39] For the purposes of our report, we focused on the use of 
administrative data with surveys administered to households and 
individuals. However, agencies such as the Census Bureau and BLS also 
use administrative data with business surveys to produce business 
statistics. For example, by combining administrative and survey data, 
the Census Bureau produces an annual series on employment by county, 
and BLS produces its quarterly series of statistics on gross job gains 
and losses. 

[40] 7 U.S.C. § 2020(e)(8)(A)(i). The Department of Agriculture 
administers the program at the federal level through the Food and 
Nutrition Service, while state agencies administer the program at the 
state and local levels, including determination of eligibility and 
allotments.

[41] 20 U.S.C. § 1090(a)(3)(E).

[42] GAO, Record Linkage and Privacy: Issues in Creating New Federal 
Research and Statistical Information, GAO-01-126SP (Washington, D.C.: 
April 2001).

[43] Agency officials noted that, if the survey respondents who 
consent differ from those who do not consent, analysis of the linked 
files may lead to misleading or biased results. Also, the reduced 
sample size from an analysis using data for those who consent may 
increase confidence intervals for calculated estimates. 

[44] The three other core elements of success in these arrangements 
were (1) vision and support by agency leadership, (2) narrow but 
flexible goals, and (3) infrastructure.

[45] As discussed in our recent report, Taxpayer Privacy: A Guide for 
Screening and Assessing Proposals to Disclose Confidential Tax 
Information to Specific Parties for Specific Purposes (GAO-12-231SP), 
Internal Revenue Code Section 6103 provides that federal tax 
information is to be kept confidential and used to administer federal 
tax laws except as otherwise specifically authorized by law. 

[46] Anthony P. Carnevale, Jeff Strohl, and Michelle Menton, What's It 
Worth? The Economic Value of College Majors, Georgetown University 
Center on Education and the Workforce (Washington, D.C.: May 24, 2011). 

[47] Respondent fatigue occurs when respondents become tired of being 
surveyed and become more prone to refusal or the quality of their 
responses deteriorates.

[48] A follow-on survey is one that is sent to ACS respondents after 
they have completed the ACS. Census Bureau policy prohibits sending an 
ACS respondent a follow-on survey within 6 months of his or her ACS 
interview.

[49] Using ACS for sample frame development is more intensive than 
using ACS estimates to inform the design of a survey's sample frame, 
which does not involve contacting ACS respondents again. In 
determining whether a survey can use ACS data for its sample frame, 
the Census Bureau's and OMB's policy is to give priority to surveys 
that meet certain criteria, including those that could substantially 
reduce costs by doing so and those that produce estimates for 
populations that would otherwise have prohibitively expensive 
screening costs.

[50] The census long form did not include a question that asked for 
the field in which respondents received their bachelor's degree. NCSES 
used long-form data to identify respondents who had characteristics 
that made them likely to be in the survey's target population, but it 
had to screen a larger sample in order to identify those who in fact 
belonged to the target population.

[51] GAO, Federal Information Collection: A Reexamination of the 
Portfolio of Major Federal Household Surveys Is Needed, GAO-07-62 
(Washington, D.C.: Nov. 15, 2006)

[52] GAO, Results-Oriented Government: Practices That Can Help Enhance 
and Sustain Collaboration among Federal Agencies, GAO-06-15 
(Washington, D.C.: Oct. 21, 2005).

[53] Agencies include supporting statements with each request for 
approval of an information collection. These statements must follow a 
prescribed format and include specified information such as the 
circumstances that make the collection necessary and how, by whom, and 
for what purpose the information will be used.

[54] OIRA is the Office of Information and Regulatory Affairs within 
OMB.

[55] BLS estimates that 8,825 of the 14,725 households surveyed per 
quarter will complete the interviews. As a result, over the course of 
a year, BLS estimates that there will be 35,300 completed interviews.

[56] BLS estimates that 7,050 of the 12,075 households that receive 
the CED will complete the interview and diaries. Because each 
household completes two weekly diaries, BLS estimates that households 
will complete 14,100 diaries per year. 

[57] This amount reflects the approximate fiscal year 2010 cost of 
collecting, processing, reviewing, and publishing data collected 
through the CE Surveys. Survey costs vary somewhat from year to year.

[58] BLS estimates that respondents will take an average of 60 minutes 
to complete one interview survey of the CEQ. Since the CEQ is 
administered to the same sample of households four times in a year, 
the annual burden for respondents who complete all four surveys is 
roughly 4 hours. In addition, a certain number of respondents who 
complete the interview surveys are reinterviewed, a process that adds 
10 minutes to these selected respondents' burden times. 

[59] BLS estimates that respondents will take approximately 105 
minutes to complete one diary survey of the CED. In addition to the 
diary survey, respondents complete three interviews, each of which 
takes 25 minutes. Lastly, a certain number of respondents are 
reinterviewed, a process that adds 10 minutes to these selected 
respondents' burden times. 

[60] The CE Surveys are limited to the U.S. civilian, 
noninstitutionalized population, and as a result exclude certain 
segments of the population, such as active-duty military members 
living on bases and prisoners.

[61] The Consumer Price Index produces monthly data on changes in the 
prices paid by urban consumers for a representative basket of goods 
and services.

[62] Although a larger pool of respondents participates in a screener 
survey, NCHS estimates that 5,180 respondents participate in the 
screener, household interview, and physical examination. 

[63] NCHS estimates that the annual cost to the federal government of 
NHANES for fiscal year 2010 was $37.8 million, including both direct 
and reimbursable funding provided by other agencies for NCHS 
statistical services. Survey costs vary somewhat from year to year.

[64] NCHS estimates that the total annual burden for the NHANES is 
37,626 hours, including screening, household interviews, physical 
examinations, and any follow-up interviews. In addition, tests of 
procedures and special studies account for an additional 12,000 hours, 
for a total annual burden of 49,626 hours. NCHS estimates that 
respondents who participate in all aspects of the NHANES, including 
the screener survey, household interview, and physical examination, 
can expect a burden of 6.7 hours. In addition to those who complete 
all aspects of the NHANES, some respondents may only participate in 
the screener survey and be screened out of the sample, while other 
respondents may participate in the screener survey and the household 
interview but not the physical examination. NCHS includes all 
respondents at these varying levels of participation in its 
calculation of the annual burden hours. 

[65] The NHANES is limited to the U.S. civilian, noninstitutionalized 
population, and as a result excludes certain segments of the 
population, such as active-duty military members living on bases and 
prisoners.

[66] NCHS estimates that the annual sample size in 2011 is 35,000 
households, and that 87,500 individuals will participate in the 
survey. NCHS plans to increase the sample size in the future. 

[67] NCHS estimates that the annual cost to the federal government of 
NHIS for fiscal year 2010 was $32.2 million, including both direct and 
reimbursable funding provided by other agencies for NCHS statistical 
services. Survey costs vary somewhat from year to year.

[68] NCHS estimates that the total annual burden of the NHIS was 
34,977 hours for 2010 and 2011. NCHS estimates that a single 
respondent who completes all portions of the NHIS for a household can 
expect a time burden of one hour. Some respondents who complete all 
portions of the NHIS are asked to take a short reinterview survey, a 
process that adds 5 minutes to these selected respondents' burden 
times. In addition to those who complete all portions of the NHIS, 
some respondents may only participate in a screener survey and be 
screened out of the sample, which NCHS estimates takes 5 minutes per 
respondent. NCHS includes all respondents at these varying levels of 
participation in its calculation of the annual burden hours. 

[69] The NHIS is limited to the U.S. civilian, noninstitutionalized 
population, and as a result excludes certain segments of the 
population, such as active-duty military members living on bases and 
prisoners. 

[70] Survey costs vary somewhat from year to year. $13.3 million is 
the expected cost for the survey in 2012. 

[71] This estimate is based on the assumption that 83,500 individuals 
will respond to the survey and each respondent will take 25 minutes to 
complete it.

[72] The Census Bureau estimates that of the 65,300 households in its 
sample, approximately 52,900 are occupied at the time of interview and 
approximately 45,000 households are interviewed. It estimates that 
each interview yields 2.1 individual interviews, for a total of 94,500 
individual interviews per survey administration. The Census Bureau 
administered the SIPP three times to the same households in fiscal 
year 2011, and estimates that each administration generated 94,500 
interviews, for a total of 283,500 in the fiscal year.

[73] The Census Bureau estimates that the production cost for all 
parts of the SIPP in fiscal year 2011 is $50.1 million. Survey costs 
vary somewhat from year to year.

[74] The bureau estimates the total burden to respondents in fiscal 
year 2011 as 143,303 hours, which includes the time it takes 
respondents to fill out the core and topical module sections, as well 
as the reinterview of selected respondents. This estimate is based on 
the assumption that most respondents take 30 minutes to complete one 
administration of the survey. Since the SIPP was administered to the 
same sample of households three times in fiscal year 2011, the annual 
burden for most respondents was 90 minutes.

[75] The SIPP is limited to the U.S. civilian, noninstitutionalized 
population, and as a result excludes certain segments of the 
population, such as active-duty military members living on bases and 
prisoners.

[End of section] 

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