APPENDIX A
Legislation and Regulations That Govern Federal Statistics

This appendix summarizes the major legislation, regulations, and guidance that govern the operations of the federal statistical system as a whole, including: (1) laws on the U.S. Office of Management and Budget (OMB) authority over federal statistics; (2) OMB statistical policy directives; (3) laws and OMB guidance on surveys, statistics, and evidence building; (4) laws and guidance on confidentiality and privacy protection; (5) OMB guidance on information quality, and the federal data strategy; and (6) Interagency on Statistical Policy documents. In addition to these laws, regulations, and guidance documents, each agency is governed by additional legislation and guidance particular to its department and itself.

Most of the legislation, regulations, and guidance summarized here are issued by OMB, which plays a critical role in oversight of the federal government’s widely dispersed statistical operations. OMB’s oversight role dates to 1939, when the functions of a Central Statistical Board, created in 1933, were transferred to the then-named Bureau of the Budget (see Anderson, 2015; Duncan and Shelton, 1978; Norwood, 1995). Recent legislation and guidance address such systemwide issues as confidentiality protection and privacy of respondents, data quality (including peer review prior to dissemination), efficiency of operations, and scientific integrity and transparency.

LEGAL AUTHORITY OF OMB OVER FEDERAL STATISTICS

The Paperwork Reduction Act (PRA) of 1980 (P.L. 96-511 and codified at 44 USC 3501 and following; reauthorized and amended in 1986 by P.L. 99-500 and in 1995 by P.L. 104-13) is the legal foundation for the modern statistical coordination and management mission of OMB. It affirms OMB’s review power over federal statistical agencies and myriad other agencies throughout the federal government that collect information from individuals and organizations. This review power covers both the burden imposed by information collection and methods and practices for data collection and dissemination. The Foundations for Evidence-Based Policymaking Act of 2018 broadened this authority to include using data and statistics for evidence, and it further strengthened the role of the chief statistician.

Background: 1933–1980

The PRA’s origins trace back to Executive Order 6226, signed by Franklin D. Roosevelt in July 1933, which established a Central Statistical Board to “appraise and advise upon all schedules of all Government agencies engaged in the primary collection of statistics required in carrying out the purposes of the National Industrial Recovery Act, to review plans for tabulation and classification of such statistics, and to promote the coordination and improvement of the statistical services involved.” Members of the board were appointed by the relevant cabinet secretaries. The board was established in law for a 5-year period in 1935. Its functions were transferred to the Bureau of the Budget (itself established in 1921) in 1939, when the Budget Bureau was transferred to the Executive Office of the President.

The 1942 Federal Reports Act represented another milestone by codifying the authority for the Budget Bureau to coordinate and oversee the of federal statistical agencies. Most famously, it provided that no federal agency could collect data from 10 or more respondents without approval of the budget director. The 1950 Budget and Accounting Procedures Act (31 USC 1104(d)) further strengthened the statistical coordinating and improvement role of OMB, giving OMB authorization to promulgate regulations and orders governing statistical programs throughout the federal government.

The statistical policy function continued in the budget office in the Executive Office of the President when the Budget Bureau became OMB in 1970. However, in 1977 the statistical policy staff was split into two groups: one group remained in OMB to handle the paperwork clearance and review function for statistical agencies; the other group was moved to the U.S. Department of Commerce to address statistical policy and standards issues (Executive Order 12013, October 7, 1977).¹

Paperwork Reduction Act, 1980–Present

The overarching goal of the 1980 Paperwork Reduction Act (PRA) was to reduce the burden of filling out federal forms by businesses and individuals. It created a new Office of Information and Regulatory Affairs (OIRA) within OMB, which was charged with reducing the combined burden imposed by regulatory agencies and administrative and statistical program agencies. The PRA required OIRA to engage in long-range planning to improve federal statistical programs; review statistical budgets; coordinate government statistical functions; establish standards, classifications, and other guidelines for statistical data collection and dissemination; and evaluate statistical program performance. In furtherance of that work, Executive Order 12318 (August 21, 1981) revoked the 1977 order and moved the statistical policy office from the Department of Commerce and moved it under OIRA; the 1986 reauthorization of the PRA required the appointment of a chief statistician at OMB to carry out the statistical policy functions (100 Stat. 1783-337).² In the 1995 reauthorization and extensive revision of the PRA, the director of OMB was given broad authority over the activities of the federal statistical system, but was directed to appoint a chief statistician who is a trained and experienced professional statistician to carry out the following functions:

1. coordinate the activities of the federal statistical system to ensure (a) the efficiency and effectiveness of the system; and (b) the integrity, objectivity, impartiality, utility, and confidentiality of information collected for statistical purposes;

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¹ Seven months later, a pair of Federal Register notices (43 Federal Register 19260 and 19308) formally transferred the content of and responsibility for various regulatory circulars on federal statistical activities to the Commerce Department—at which time they were designated “statistical policy directives” for the first time.

² Consequent to congressional hearings, the Reagan administration first appointed a chief statistician in 1983.

2. ensure that budget proposals of agencies are consistent with systemwide priorities for maintaining and improving the quality of federal statistics, and prepare an annual report on statistical program funding;
3. develop and oversee the implementation of governmentwide policies, principles, standards, and guidelines concerning:
   1. statistical collection procedures and methods;
   2. statistical data classification;
   3. statistical information presentation and dissemination;
   4. timely release of statistical data; and
   5. such statistical data sources as may be required for the administration of federal programs;
4. evaluate statistical program performance and agency compliance with governmentwide policies, principles, standards and guidelines;
5. promote the sharing of information collected for statistical purposes consistent with privacy rights and confidentiality pledges; and
6. coordinate the participation of the United States in international statistical activities, including the development of comparable statistics. (44 USC 3504(e))

The law also codified the Interagency Council on Statistical Policy, which is headed by the chief statistician and consists of the heads of the major statistical programs and representatives of other statistical agencies under rotating membership. In addition, it authorizes training opportunities in statistical policy functions for employees of the federal government who serve on rotational assignments at OMB. The law also requires an annual report to Congress on the statistical programs of the U.S. government.

The Foundations for Evidence-Based Policymaking Act of 2018

The Foundations for Evidence-Based Policymaking Act of 2018 (P.L 115-345) includes three separate sections covering, respectively, Evidence Building Activities; Open Government Data; and Confidential Information Protection and Statistical Efficiency. It includes about half of the recommendations from the Commission on Evidence-Based Policymaking (2017) as well as some key provisions for federal statistics.

Under Evidence Building Activities, the Act requires that agencies develop evidence-building plans, appoint qualified evaluation officers, and appoint qualified statistical officials. It also establishes an Advisory Committee on Data for Evidence Building, which shall be chaired by the chief statistician at OMB, to recommend ways to facilitate data sharing, enable data linkages, and develop privacy-enhancing methods.

The Open Government Data Act, which is Title II of the Foundations for Evidence-Based Policymaking Act, requires agencies to make Open Data the government default for nonsensitive publicly available government data. It requires agencies to create a comprehensive data inventory and appoint qualified chief data officers. It also establishes a chief data officer council and requires the General Services Administration to host and maintain a comprehensive Federal Data Catalogue of all data assets.

The Confidential Information Protection and Statistical Efficiency Act (CIPSEA) of 2018 reauthorized the 2002 law of the same name, and codified the responsibilities of statistical agencies in units originally issued as Statistical Policy Directive No. 1 (see below). It also provides statistical agencies with broader statutory authority for accessing and using data assets of nonstatistical agencies, expands secure access to CIPSEA data assets for approved statistical purposes, including evidence and evaluation uses, and establishes a single access portal for qualified researchers to apply for the use of restricted or sensitive data (see additional information on CIPSEA below).

OMB is charged with implementing guidance for multiple sections of this law (see below).

OMB STATISTICAL POLICY DIRECTIVES

OMB issues guidance to federal agencies via “circulars,” which are expected to have a continuing effect of 2 years or more, and “bulletins,” which are more limited in their effect.³ OMB statistical standards and guidance were originally issued in this form; however, after the statistical policy function was temporarily moved to the U.S. Department of Commerce in 1977, the circulars were reissued as “statistical policy directives” (43 Federal Register 19260) so as not to cause confusion with other OMB circulars. When the statistical policy function was moved back to OMB in 1981, the statistical policy directives were transferred

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³ See https://www.whitehouse.gov/omb/information-for-agencies/circulars. [February 2021]

back to OMB. Through the years, OMB terminology has varied, with some policy documents called “directives” and others called “standards” or “classifications,” but the current OMB website has recently gone back to referring to these standards as statistical policy directives, as noted below. The process of issuing or revising a directive or standard involves expert review, agency consultation, and public comment.

Statistical Policy Directive No. 1—Fundamental Responsibilities of Federal Statistical Agencies and Recognized Statistical Units

OMB issued this statistical policy directive on December 2, 2014 (U.S. Office of Management and Budget, 2014b), and labeled it no. 1 because of its foundational importance.⁴ The directive cites relevant documents issued by OMB (e.g., other statistical policy directives) and by the Office of Science and Technology Policy, together with Principles and Practices for a Federal Statistical Agency (NRC, 2013b), the European Statistics Code of Practice (European Statistical System Committee, 2011), and the Fundamental Principles of Official Statistics (United Nations Statistical Commission, 2014), as contributing “to an integrative framework guiding the production of Federal statistics, encompassing design, collection, processing, editing, compilation, storage, analysis, release, and dissemination” (U.S. Office of Management and Budget, 2014b, p. 71611).

The directive goes on to articulate four statistical agency responsibilities: (1) produce and disseminate relevant and timely information; (2) conduct credible and accurate statistical activities; (3) conduct objective statistical activities; and (4) protect the trust of information providers by ensuring the confidentiality and exclusive statistical use of their responses. These responsibilities were codified in the Foundations for Evidence Based Policymaking Act of 2018.⁵ Importantly, the law retained the requirement that requires heads of departments to “enable, support, and facilitate statistical agencies or units in carrying out the responsibilities.”⁶

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⁴ The original Statistical Policy Directive No. 1 was Standards for Statistical Surveys. When this was revised, updated, and issued in 2006, it was referred to as Standards and Guidelines for Statistical Surveys, and was later renamed as Statistical Policy Directive No. 2, as noted below.

⁵ 44 USC 3563.

⁶ 44 USC 3563(b).

Statistical Policy Directive No. 2—Standards and Guidelines for Statistical Surveys

OMB issued a revised and updated Standards and Guidelines for Statistical Surveys in 2006 (U.S. Office of Management and Budget, 2006) but now refers to this document as Statistical Policy Directive No. 2.⁷ It includes 20 standards with one or more associated guidelines for every aspect of survey methodology from planning through data release:

1. survey planning
2. survey design
3. survey response rates
4. pretesting survey systems
5. developing sampling frames
6. required notification to potential survey respondents
7. data collection methodology
8. data editing
9. nonresponse analysis and response rate calculation
10. coding
11. data protection
12. evaluation
13. developing estimates and projections
14. analysis and report planning
15. inference and comparisons
16. review of information products
17. releasing information
18. data protection and disclosure avoidance for dissemination
19. survey documentation, and
20. documentation and release of public-use microdata.

On October 12, 2016, OMB issued a notice in the Federal Register of a final decision to add an Addendum: Standards and Guidelines for Cognitive Interviews to Directive No. 2 (U.S. Office of Management and Budget, 2016b). This addendum recognizes the important role that qualitative cognitive interviewing techniques play in the design of effective survey questions (see NRC, 1984, 2006c, Ch. 8).

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⁷ This document was a combined update and revision of the original Statistical Policy Directive No. 1, Standards for Statistical Surveys, and Statistical Policy Directive No. 2, Publication of Statistics.

Statistical Policy Directive No. 3—Compilation, Release, and Evaluation of Principal Federal Economic Indicators

OMB first issued Directive No. 3 in the 1970s and strengthened it in 1985.⁸ Its purpose is clearly stated (U.S. Office of Management and Budget, 1985, p. 38932):

Each September, OMB issues the Schedule of Release Dates for Principal Federal Economic Indicators for the calendar year.⁹ At present, the following agencies issue one or more of the 36 principal economic indicators:

• Bureau of Economic Analysis (5 indicators, including gross domestic product [GDP], personal income and outlays, corporate profits);
• Bureau of Labor Statistics (7 indicators, including the employment situation, Consumer Price Index [CPI]);
• Census Bureau (13 indicators, including new residential construction, monthly retail trade);
• Energy Information Administration (natural gas storage);
• Federal Reserve Board (2 indicators, industrial production, consumer credit);
• Foreign Agricultural Service (world agricultural production);
• National Agricultural Statistics Service (6 indicators, including agricultural prices, grain production); and

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⁸Norwood (2016) recounts the history of threats to the integrity of economic indicators that necessitated the directive’s issuance and updating.

⁹ See https://www.whitehouse.gov/wp-content/uploads/2020/09/pfei_schedule_release_dates_2021.pdf. [February 2021]

• World Agricultural Outlook Board (world agricultural supply and demand).

OMB issued a Federal Register notice on April 11, 2019, seeking comment on one aspect of this directive. The directive has required that:

OMB sought public comment on just this provision of the directive and asked:

OMB has not reported any results from this request for comment or made any changes to Directive No. 3 as of the writing of this report.

Statistical Policy Directive No. 4—Release and Dissemination of Statistical Products Produced by Federal Statistical Agencies

OMB issued Directive No. 4, which essentially covers all statistical releases other than those specified in Directive No. 3, in 2008 (U.S. Office of Management and Budget, 2008). It includes not only statistical information released in printed reports or on the Internet, but also statistical press releases, which describe or announce a statistical data product. Statistical press releases are the sole responsibility of the relevant statistical agency. Each fall statistical agencies must issue a schedule of when they expect each regular or recurring product to be released and give timely notification of any change to the published schedule.

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¹⁰Federal Register vol. 84 no. 70, p. 14684.

¹¹Federal Register vol. 84 no. 70, p. 14684.

On October 17, 2016, OMB issued a notice in the Federal Register requesting comments on a proposed addendum to Directive No. 4, which would constitute Section 10: Performance Review (U.S. Office of Management and Budget, 2016c). Comments were due December 1, 2016. As proposed, the addendum, which incorporates language from Directive No. 3, would require each statistical agency and recognized statistical unit to submit an annual performance review of the production and dissemination of its key statistical products to OMB. Key products would be defined by the agency in consultation with OMB. Reviews would address for each product (U.S. Office of Management and Budget, 2016c, 71541–71542):

OMB would include a summary of the year’s evaluations in its annual report to Congress. As of February 2021, this addendum has yet to be enacted. If enacted, it would represent the first formal process by OMB for performance review specifically of statistical products, with the exception that Directive No. 3 requires that the key economic indicators (see above) be evaluated every 3 years.

Statistical Policy Directive No. 7—Metropolitan Statistical Areas

Since the 1950s, OMB’s Metropolitan Area Classification Program has provided standards for delineating areas that are “metropolitan” in nature for use throughout the federal government. In general, such

an area has a population nucleus plus one or more adjacent communities that have a high degree of interaction with the nucleus. These areas were called “standard metropolitan areas” in the 1950 census publications. For censuses from 1960 through 2000, OMB revised as appropriate the definitional criteria for metropolitan areas before each census and, on the basis of those criteria, issued an updated list of recognized areas after each census.¹²

The definitional criteria issued before the 2000 census marked a major revision to the coverage of the program. Standards for Defining Metropolitan and Micropolitan Statistical Areas defined not only metropolitan statistical areas but also, for the first time, micropolitan areas.¹³ Metropolitan areas are those with a central urbanized core of 50,000 or more people in one or more counties; micropolitan areas are those with a central urbanized core of 10,000 or more people in one or more counties. The list of metropolitan and micropolitan areas using the 2000 criteria was initially issued in 2003 and was updated annually through 2008 by OMB on the basis of the Census Bureau’s population estimates. Two years later, OMB issued 2010 Standards for Delineating Metropolitan and Micropolitan Statistical Areas, which largely continued the criteria adopted for the 2000 standards.¹⁴ Areas based on these standards, using data from the 2010 census and the American Community Survey (ACS), were announced in 2013, and any proposed revisions are subject to public comment.

Beginning with the 2010 Census, the revision and updating process was changed to reflect the availability of needed commuting and employment information from the continuous ACS. Under the changed process, OMB will issue as often as annually a list of newly recognized areas by using Census Bureau population estimates; in addition, on the basis of ACS and census data, OMB issued revisions in 2018 and 2020, using population estimates and ACS data on commuting and employment.¹⁵ OMB requested comments on potential changes to the standards for

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¹² Issues of rural area classification were discussed at a Committee on National Statistics workshop sponsored by the Economic Research Service, U.S. Department of Agriculture, in April 2015 (NASEM, 2016a).

¹³ See 65 Federal Register 82228 (December 27, 2000). Available: https://www.federalregister.gov/d/00-32997. [February 2021]

¹⁴ See 75 Federal Register 37245. Available: https://www.federalregister.gov/d/2010-15605. [February 2021]

¹⁵ See https://www.whitehouse.gov/wp-content/uploads/2018/09/Bulletin-18-04.pdf [February 2022] https://www.whitehouse.gov/wp-content/uploads/2020/03/Bulletin-20-01.pdf. [February 2021]

delineating the 2020 Census in early 2021 (see 86 Federal Register 5263-5266). Input to the OMB decisions is provided by an interagency Metropolitan Area Standards Review Committee.

Statistical Policy Directive No. 8—North American Industry Classification System

The North American Industry Classification System (NAICS) was developed by the United States, Canada, and Mexico to provide a common, contemporary classification system for economic production activity following the enactment of the North American Free Trade Agreement (NAFTA). NAICS, which is a substantial revision of its predecessor, the Standard Industrial Classification (SIC), was first issued in 1997. (The SIC was originally issued in various sections in 1938–1940 and revised on an irregular basis between 1940 and its last iteration in 1987, and it is now being discontinued.) Interagency and country working groups (under the aegis of OMB in the United States) have the opportunity to update NAICS every 5 years for years ending in 2 and 7 so that it keeps up reasonably well with changes in the structure of industrial activity in the three countries. NAICS was most recently updated for use beginning in 2017.¹⁶ In 2020, OMB issued a Federal Register notice requesting comments on potential changes to the structure and content of NAICS for the 2022 update.¹⁷

Statistical Policy Directive No. 10—Standard Occupational Classification

The Standard Occupational Classification (SOC) is used by federal statistical agencies to classify workers into occupational categories for collecting, tabulating, and disseminating data.¹⁸ The first SOC was published in 1977 in an effort to standardize the collection of occupational data by multiple agencies. It was revised in 1980 but not universally

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¹⁶ See “North American Industry Classification System—Revision for 2017,” 81 Federal Register 52584 (August 8, 2016). Available: https://www.federalregister.gov/d/2016-18774 [February 2021]. See also “North American Industry Classification System (NAICS)—Updates for 2017,” 80 Federal Register 46480 (August 4, 2015). Available: https://www.federalregister.gov/d/2015-19022. [February 2021]

¹⁷ As a formality, comments are also being sought on the elimination of the Standard Industrial Classification of Enterprises, which has not been updated or widely adopted over the past 45 years. See Federal Register 85 FR 38: 11120-11124. Available: https://www.census.gov/eos/www/naics/federal_register_notices/notices/fr26fb20.pdf. [February 2021]

¹⁸ Available: http://www.bls.gov/soc. [February 2021]

adopted until an interagency process under the aegis of OMB further revised it in 1998 for use in the 2000 decennial census and surveys conducted in the following decade. Work to revise the 2000 SOC was completed in time for its use in 2010 for the ACS, which provides occupational data in place of the decennial census “long form” sample, and other surveys. The latest version of the SOC was issued for 2018, and it will be updated every 10 years thereafter.¹⁹

Statistical Policy Directive No. 14—Definition of Poverty for Statistical Purposes

OMB first issued standards for the statistical definition of poverty in 1969. It adopted the existing poverty thresholds (first specified by Mollie Orshansky of the Social Security Administration in 1963 and used by the Office of Economic Opportunity) for different categories of families defined by size, number of children, gender of the family head, and farm-nonfarm residences. (One change from Orshansky’s specification was that the farm thresholds were raised from 70% to 85% of the nonfarm thresholds.) For most family types, the thresholds represented the costs of a minimally adequate diet multiplied by three to allow for all other expenses.

The 1969 directive specified that the thresholds would be updated each year for the change in the Consumer Price Index (instead of the cost of the Economy Food Plan as in prior years) and compared with families’ total regular money income as measured in the Current Population Survey. The directive was promulgated as Statistical Policy Directive No. 14 in 1978, when the statistical policy function was briefly housed in the Department of Commerce (U.S. Department of Commerce, 1978); minor modifications were made to the thresholds beginning in 1982 (the nonfarm thresholds were used for all families, the thresholds for male- and female-headed families were averaged, and the largest family-size category was raised from 7 to 9 people).²⁰ No further changes have been made to the official thresholds or definition of countable resources, although major socioeconomic changes in the United States and in income support policies have made the official poverty concept increasingly unable to inform assessments of policy effectiveness for different population

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¹⁹ See https://www.govinfo.gov/content/pkg/FR-2017-11-28/pdf/2017-25622.pdf. [February 2021]

²⁰ Information on the poverty measure and current statistics are available at: https://www.census.gov/topics/income-poverty/poverty.html. [February 2021]

groups (e.g., refunds from the Earned Income Tax Credit are not counted in the resource measure).

With input from the observations of an Interagency Technical Working Group on Developing a Supplemental Poverty Measure (2010), the U.S. Census Bureau released a new supplemental poverty measure (SPM in fall of 2011 (referencing poverty in calendar 2010), using thresholds developed by the U.S. Bureau of Labor Statistics.²¹ The thresholds and definition of countable resources as money and near-money disposable income for the SPM were derived in large part from the recommendations from the report of a Committee on National Statistics panel, Measuring Poverty: A New Approach (NRC, 1995b). The SPM, which is designed to be a useful tool for policy evaluation, is issued annually, as is the official measure.

In the past 2 years, OMB has sought public comments twice on issues related to poverty measurement. In 2019, OMB sought comments on the differences among various consumer price indexes produced by the Bureau of Labor Statistics (BLS) and the Bureau of Economic Analysis (BEA) and how those differences might influence the estimation of the Official Poverty Measure. OMB reportedly received thousands of comments in response and as of the writing of this report has not reported on those comments or issued any changes.²²

In 2020 OMB requested answers to questions posed by the Interagency Technical Working Group on Evaluating Alternative Measures of Poverty, which was established by OMB in 2019. The working group issued an interim report,²³ which posed 14 specific questions in categories covering definitions, resource measures, and thresholds.²⁴ The comments were intended to inform the working group’s recommendations to OMB. As of the writing of this report, no further information has been publicly released.

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²¹ Information on the supplemental poverty measure is available at https://www.census.gov/topics/income-poverty/supplemental-poverty-measure.html. [February 2021]

²² See Federal Register vol. 84 No. 88, pages 19961-19963, May 7, 2019.

²³ See www.regulations.gov in docket number OMB-2019-0007.

²⁴ See Federal Register vol. 85 No. 31, pages 8610-8613, February 14, 2020.

Statistical Policy Directive No. 15—Standards for Maintaining, Collecting, and Presenting Federal Data on Race and Ethnicity

The first standards on this topic, issued in 1977, Race and Ethnic Standards for Federal Statistics and Administrative Reporting, specified a minimum set of racial and ethnic categories for reporting of race and ethnicity on federal surveys and in administrative records systems. It recommended either two separate questions, one on ethnicity (Hispanic or non-Hispanic) and one on race (white, black, Asian or Pacific Islander, American Indian or Alaska Native), or a combined question that included Hispanic as a category. Historically, the U.S. decennial census has included additional categories under the two-question format.

Following an intensive research, testing, and consultation process, OMB issued a revised set of standards in 1997.²⁵ The updated standards retain a two-question format, include separate categories for Asians and for Native Hawaiian and other Pacific Islanders, emphasize self-identification, and allow respondents to select more than one racial category.

The 2010 census included several experimental panels to test different strategies that incorporated alternative wording and format for the questions on race and ethnicity, including a combined race and ethnicity question. Analysis of the results led to an important finding that the combined question improved reporting.²⁶ Additional research was conducted in subsequent years, including a National Content Test in 2015 for 2020 census planning.²⁷

On September 30, 2016, OMB issued a request for comments on a “possible limited revision” of Standards for Maintaining, Collecting, and Presenting Federal Data on Race and Ethnicity.²⁸ Comments were requested within 30 days on the possibility of allowing the use of a combined race and ethnicity question, adding a “Middle Eastern or North African (MENA)” category, and some other changes in terminology. On March 1, 2017, OMB asked for comments within 60 days on the interim proposals of the Federal Interagency Working Group for Research on

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²⁵ See https://www.govinfo.gov/content/pkg/FR-1997-10-30/pdf/97-28653.pdf. [February 2021]

²⁶ See http://www.census.gov/2010census/pdf/2010_Census_Race_HO_AQE.pdf. [February 2021]

²⁷ See https://www.census.gov/programs-surveys/decennial-census/2020-census/research-testing/testing-activities/2015-census-tests/national-content-test.html. [February 2021]

²⁸ See 81 Federal Register 67398. Available: https://www.federalregister.gov/d/2016-23672. [February 2021]

Race and Ethnicity, which took account of the comments received on the September 30 notice.²⁹ However, OMB took no further action on the proposal, and the race and ethnicity questions on the 2020 Census continued to follow the 1997 standards.

OMB GUIDANCE FOR SURVEYS, FEDERAL STATISTICS, AND EVIDENCE BUILDING

PRA Implementation Guidance for Surveys and Other Agency Information Collection Activities

In January 2006, the OMB Statistical and Science Policy Office released Guidance on Agency Survey and Statistical Information Collections—Questions and Answers When Designing Surveys for Information Collections.³⁰ The guidance is a set of 81 questions and answers that attempts to demystify the OMB clearance process (required by the PRA) for surveys and other statistical information collections. Its purpose is to explain OMB’s review process, assist agencies in strengthening their supporting statements for information collection requests, and provide advice for improving information collection designs.

The Guidance covers such topics as its purpose; submission of information collection requests (ICRs, often called clearance packages) to OMB; scope of the information collection (e.g., calculation of burden hours on respondents); choice of methods; sampling; modes of data collection; questionnaire design and development; statistical standards; informing respondents about their participation and the confidentiality of their data; response rates and incentives; analysis and reporting; and studies using stated preference methods (which ask respondents about the use or nonuse value of a good in order to obtain willingness-to-pay estimates relevant to benefit or cost estimation). The Guidance includes a glossary of terms and ICR supporting statement instructions.

OMB also issued several memoranda to clarify particular interpretations and applications of the PRA to agency activities.³¹ Topics covered

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²⁹ See 82 Federal Register 12242. Available: https://www.federalregister.gov/d/2017-03973. [February 2021]

³⁰ This was updated in October 2016 (U.S. Office of Management and Budget, 2016a) to incorporate reference to the standards and guidelines for cognitive interviewing (U.S. Office of Management and Budget, 2016b).

³¹ All the memoranda can currently be found at https://obamawhitehouse.archives.gov/omb/inforeg_infocoll. [February 2021]

include an overview of PRA requirements, PRA implications of social media and web-based interactive technologies, the use of generic clearances, options for streamlining the PRA process for scientific research, a fast-track process for qualitative customer service delivery feedback, and answers to PRA questions related to challenges and prizes.

North American Product Classification System

The North American Product Classification System (NAPCS) is intended to be a comprehensive, market- or demand-based, hierarchical classification system for products or outputs (goods and services) that: (a) is not industry-of-origin based but can be linked to the NAICS industry structure; (b) is consistent across the three North American countries; and (c) promotes improvements in the identification and classification of service products across international classification systems, such as the Central Product Classification System of the United Nations NAPCS responds to the problem that a business establishment can only have one NAICS code, even though it may produce more than one product. It is also the case that the same product can be produced by more than one industry.

NAPCS has been under development since 1998, beginning with exploratory efforts to develop classifications for the services sector. At present, a version of NAPCS for 2017 is in beta testing by U.S. statistical agencies; the plan is to update NAPCS every 5 years on the same cycle as NAICS. For more information, see Economic Classification Policy Committee of the United States (2003), in which the three countries agreed that the objectives and principles articulated in sections A through C of that paper define the purposes of NAPCS and the operational guidelines for creating it.³²

2014 Guidance for Providing and Using Administrative Data for Statistical Purposes (M-14-06)

Recognizing the informational value and potential efficiencies to be achieved by using already collected federal administrative data for federal statistics, the OMB director issued M-14-06 on February 14, 2014 (U.S. Office of Management and Budget, 2014a). The intent of this memorandum is to provide agencies with “guidance for addressing the legal, policy, and operational issues that exist with respect to using

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³² See https://www.census.gov/naics/napcs/. [February 2021]

administrative data for statistical purposes.” First, it “calls for departmental and agency leadership to: (i) foster greater collaboration between program and statistical offices; (ii) develop strong data stewardship policies and practices around the statistical use of administrative data; (iii) require the documentation of quality control measures and key attributes of important administrative datasets; and (iv) require the designation of responsibilities and practices through the use of agreements amongst these offices.” Second, it “encourages Federal departments and agencies to promote the use of administrative data for statistical purposes…[while] continu[ing] to fully protect the privacy and confidentiality afforded to the individuals, businesses, and institutions providing the data.” Third, it “provides some ‘best practice’ tools, including detailed guidance on the interaction of the Privacy Act requirements and the use of administrative data for statistical purposes, as well as a model interagency agreement for…sharing data for statistical purposes.” Fourth, it “requires each department/agency to report to OMB, within 120 days…on its progress in implementing this Memorandum.”

2015 Guidance on Improving Statistical Activities Through Interagency Collaboration (M-15-15)

Issued by the administrator of the OMB Office of Information and Regulatory Affairs (OIRA) on July 8, 2015 (U.S. Office of Management and Budget, 2015), this memorandum “strongly encourages the Federal statistical agencies and units, and their parent Departments, to build interagency collaboration that will help the Federal statistical community more effectively meet the information needs of the 21st century.” The memorandum cites examples of successful interagency collaboration (including within and across departments). It also describes available tools for collaboration, such as use of the 1933 Economy Act, which authorized departments and agencies to buy goods and services from each other, and the new Category Management model for federal contracting. This model could, for example, facilitate obtaining a single license for governmentwide use of statistical software in accordance with the 2014 Federal Information Technology Acquisition Reform Act (see below).

Phase 1 Implementation of the Foundations for Evidence-Based Policymaking Act of 2018: Learning Agendas, Personnel, and Planning Guidance (M-19-23)

OMB issued memorandum M-19-23 in July 2019 to provide initial guidance to implement Phase 1 requirements from the Foundations for Evidence-Based Policymaking Act of 2018 (“Evidence Act”). For Phase 1, agencies were required to develop learning agendas, designate and develop roles and responsibilities for new personnel, and undertake planning activities.

Agencies were required to start the process of developing and implementing a multiyear learning agenda that coincides with the four-year timeframe defined for agency strategic plans and to submit them with their budget requests to OMB.

The Evidence Act created three new roles related to data and evidence. Heads of agencies were required to appoint a Chief Data Officer (CDO), an Evaluation Officer, and a Statistical Official, and to establish an agency Data Governance Body, to be chaired by the Chief Data Officer, with participation from relevant senior-level staff in agency business units, data functions, and financial management. The designated key officials are required to participate with their peers on their respective interagency councils: CDO Council, Evaluation Officer Council, and the Interagency Council on Statistical Policy (ICSP). The ICSP has existed since the late 1980s, but it was expanded by the Evidence Act to include 12 new statistical officials (heads of the current principal statistical agencies serve as statistical officials for their departments and remain on the ICSP). The CDO Council and the Evaluation Officer Councils were newly created by the law.

For planning activities, agencies were required to begin the process of developing their first Annual Evaluation Plan, including the key questions for each planned “significant” evaluation study, as well as the key information collections or acquisitions the agencies plan to begin. Agencies were also required to begin to plan how they will assess the coverage, quality, methods, effectiveness, and independence of their statistics, evaluation, research, and analysis efforts.

The Evidence Act requires each agency to develop and maintain an Open Data Plan, which, in general, shall describe the agency’s efforts to make government data open to the public. OMB also plans to issue Phase

2 Guidance to provide agencies further guidance necessary to implement the Evidence Act’s Open Data Plan requirement, which will substantively update technical aspects of operationalizing these mechanisms. Until the Phase 2 Guidance goes into effect, agencies are required to meet their existing open data obligations.

Phase 4 Implementation of the Foundations for Evidence-Based Policymaking Act of 2018: Program Evaluation Standards and Practices (M-20-14)

OMB issued Memorandum M-20-14 in March of 2020 to provide program evaluation standards to guide agencies in developing and implementing evaluation activities, evaluation policies, and the hiring and retaining of qualified staff. It also provides examples of leading practices for agencies to draw upon as they build evaluation capacity, develop policies and procedures, and carry out evaluations to support evidence-based policy making.

OMB states that evaluators need to practice and embody the following five standards in their work in order for federal evaluations to have the credibility needed for full acceptance and use:

Relevance and Utility: Federal evaluations must address questions of importance and serve the information needs of stakeholders in order to be useful. Evaluations should present findings that are actionable and available in time for use. Information should be presented in ways that are understandable and that can inform agency activities and actions.

Rigor: Federal evaluations must produce findings that federal agencies and their stakeholders can confidently rely upon, while providing clear explanations of limitations. The quality of an evaluation depends on the underlying design and methods, implementation, and how findings are interpreted and reported. Credible evaluations must be managed by qualified evaluators, and an evaluation must have the most appropriate design and methods to answer key questions.

Independence and Objectivity: Federal evaluations must be viewed as objective in order for stakeholders, experts, and the public to accept their findings. This depends on the independence and objectivity of the evaluators. The implementation of evaluation activities, including how evaluators are selected and operate, should be appropriately insulated from political and other undue influences that may affect their

objectivity, impartiality, and professional judgement. Evaluators should strive for objectivity in the planning and conduct of evaluations and in the interpretation and dissemination of findings, avoiding conflicts of interest, bias, and other partiality.

Transparency: Federal evaluation must be transparent in the planning, implementation, and reporting phases to enable accountability and help ensure that aspects of an evaluation are not tailored to generate specific findings. Decisions about the evaluation’s purpose and objectives (including internal versus public use), the range of stakeholders who will have access to details of the work and findings, the design and methods, and the timeline and strategy for releasing findings should be clearly documented before conducting the evaluation. Once evaluations are complete, comprehensive reporting of the findings should be released in a timely manner and provide sufficient detail so that others can review, interpret, or replicate/reproduce the work.

Ethics: Federal evaluations must be conducted to the highest ethical standards to protect the public and maintain public trust in the government’s efforts. Evaluations should be planned and implemented to safeguard the dignity, rights, safety, and privacy of participants and other stakeholders and affected entities. Evaluators should abide by current professional standards pertaining to treatment of participants. Evaluations should be equitable, fair, and just, and should take into account cultural and contextual factors that could influence the findings or their use.

OMB also identified leading evaluation practices to support the evaluation standards. The practices aim to provide greater specificity and detail on what may be useful when planning and implementing evaluation activities to fulfill the goals of the standards. The 10 practices are

1. Build and Maintain Evaluation Capacity
2. Use Expert Consultation Effectively
3. Establish, Implement, and Widely Disseminate an Agency Evaluation Policy
4. Pre-Specify Evaluation Design and Methods
5. Engage Key Stakeholders Meaningfully
6. Plan Dissemination Strategically
7. Take Steps to Ensure Ethical Treatment of Participants
8. Foster and Steward Data Management for Evaluation

9. Make Evaluation Data Available for Secondary Use
10. Establish and Uphold Policies and Procedures to Protect Independence and Objectivity.

OMB expects that the guidance will be implemented by (1) evaluation officers, who are expected to play a leading role in overseeing the agency’s evaluation activities and learning agenda, as well as collaborating with, shaping, and making contributions to other evidence-building functions within the agency; and (2) agency evaluators and staff in related functions who support the development and use of evaluation, using technical expertise and knowledge of evaluation methodology and these standards for evaluation and related analytic activities within federal agencies.

LAWS AND OMB GUIDANCE ON CONFIDENTIALITY AND PRIVACY PROTECTION

Protecting the confidentiality of individual information collected under a confidentiality pledge—whether from individuals, households, businesses, or other organizations—is a bedrock principle of federal statistics. Federal statistical agencies also strive to respect the privacy of individual respondents through such means as limiting the collection of information to that which is necessary for an agency’s mission. Respect for privacy has a history in federal legislation and regulation that extends back many decades; so, too, does protection of confidentiality, except that not all federal agencies were covered.³³ With the original passage of CIPSEA in 2002 (see below), a firm legislative foundation was established for confidentiality protection of statistical data governmentwide.

Privacy Act of 1974

The Privacy Act of 1974 (P.L. 93-579, as amended; codified at 5 USC 552a) is a landmark piece of legislation that grew out of concerns about the implications of computers, credit bureaus, proposals for national databanks, and the like on personal privacy. The act states in part (5 USC 552a(b)):

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³³ For example, Title 13 of the U.S. Code, providing for confidentiality protection for economic and population data collected by the U.S. Census Bureau, dates back to 1929; in contrast, the Bureau of Labor Statistics had no legal authority for its policies and practices of confidentiality protection until the passage of CIPSEA in 2002 (see NRC, 2003b, p. 119–121).

The defined conditions for disclosure of personal records without prior consent include use for statistical purposes by the Census Bureau, for statistical research or reporting when the records are to be transferred in a form that is not individually identifiable, for routine uses within a U.S. government agency, for preservation by the National Archives and Records Administration “as a record which has sufficient historical or other value to warrant its continued preservation by the United States Government,” for law enforcement purposes, for congressional investigations, and for other administrative purposes.

The Privacy Act mandates that every federal agency have in place an administrative and physical security system to prevent the unauthorized release of personal records; it also mandates that every agency publish in the Federal Register one or more system of records notices (SORNs) for newly created and revised systems of records that contain personally identifiable information as directed by OMB.³⁴ SORNs are to describe not only the records and their uses by the agency, but also procedures for storing, retrieving, accessing, retaining, and disposing of records in the system.³⁵

Federal Policy for the Protection of Human Subjects, 45 Code of Federal Regulations (CFR) 46, Subpart A (“Common Rule”), as Revised in 2017

The 1991 Common Rule regulations, promulgated by the U.S. Department of Health and Human Services (DHHS)³⁶ and signed onto by nine

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³⁴ See OMB Circular A-130, Managing Information as a Strategic Resource, Appendix II, revised 2016. Available: https://www.whitehouse.gov/sites/whitehouse.gov/files/omb/circulars/A130/a130revised.pdf. [February 2021]

³⁵ For an example of SORNs for a statistical agency, see https://www.census.gov/about/policies/privacy/sorn.html. [February 2021]

³⁶ See https://www.hhs.gov/ohrp/regulations-and-policy/regulations/common-rule/ [February 2021]. In addition to Subpart A of 45 CFR 46, DHHS and some other departments and agencies have signed onto Subparts B, C, and D, which pertain to pregnant women, human fetuses, and neonates; prisoners; and children, respectively.

other cabinet departments and seven independent agencies (in their own regulations), represent the culmination of a series of DHHS regulations dating back to the 1960s (see Practice 7 and NRC, 2003b, Ch. 3). The regulations are designed to protect individuals whom researchers wish to recruit for research studies funded by the federal government, which include surveys and other kinds of statistical data collection.³⁷

These regulations require that researchers obtain informed consent from prospective participants, minimize risks to participants, balance risks and benefits appropriately, select participants equitably, monitor data collection to ensure participant safety (where appropriate), and protect participant privacy and maintain data confidentiality (where appropriate). Institutional review boards (IRBs) at universities and other organizations and agencies, registered with DHHS, review research protocols to determine whether they qualify for exemption from or are subject to IRB review and, if the latter, whether the protocol satisfactorily adheres to the regulations. Some federal statistical agencies are required to submit data collection protocols to an IRB for approval; other agencies maintain exemption from IRB review but follow the principles and spirit of the regulations.

An Advance Notice of Proposed Rulemaking, issued in 2011, proposed changes to the Common Rule, including revisions to the provisions for confidentiality protection.³⁸ A Notice of Proposed Rulemaking, which indicated responses to the extensive comments on that advance notice, was issued in 2015; it too included a comment period.³⁹ A final rule was published January 19, 2017,⁴⁰ which took effect on January 19, 2018 (for cooperative research involving more than one institution, the effective date was January 20, 2020). Some of the changes from the 1991 version of the Common Rule are these:

• The U.S. Department of Labor became a signatory to the Common Rule; consequently, only one department that houses a federal statistical agency (U.S. Department of the Treasury) is not a signatory.

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³⁷ Of those departments with statistical units, all signed onto the Common Rule with the exception of the Departments of Labor and the Treasury.

³⁸ See 76 Federal Register 44512 (July 26, 2011). Available: https://www.federalregister.gov/d/2011-18792 [February 2021]. See also NRC (2014).

³⁹ See 80 Federal Register 53933 (September 8, 2015). Available: https://www.federalregister.gov/d/2015-21756. [February 2021]

⁴⁰ See 82 Federal Register 7149 (January 19, 2017). Available: https://www.federalregister.gov/d/2017-01058. [February 2021]

• Provisions to exempt research with human participants from IRB review were modified and enlarged and, where appropriate, IRB review is to be focused on the adequacy of confidentiality protection.
• To assist IRBs in determining the adequacy of confidentiality protection, the Secretary of DHHS, after consultation with OMB and other federal signatories, is to issue guidance on what provisions are adequate to protect the privacy of subjects and to maintain the confidentiality of data.
• Provisions are added for “broad” consent for storage, maintenance, and secondary research use of identifiable private information or biospecimens.

1997 Order Providing for the Confidentiality of Statistical Information

OMB issued this order in 1997 to bolster the confidentiality protections afforded by statistical agencies or units (as listed in the order), some of which lacked legal authority to back up their confidentiality protection.⁴¹ CIPSEA (see next section) placed confidentiality protection for statistical information on a strong legal footing across the entire federal government.

Confidential Information Protection and Statistical Efficiency Act

The Confidential Information Protection and Statistical Efficiency Act (CIPSEA) was first enacted as Title V of the E-Government Act of 2002 (P.L. 107-347) and was recodified as part of the Evidence-Based Policymaking Act of 2018 (see above). CIPSEA provides a strong statutory basis for the statistical system with regard to confidentiality protection and data sharing. CIPSEA has four parts: two original parts cover confidentiality (Part B) and data sharing (Part C; efficiency), respectively, while the other two parts include definitions and Statistical Policy Directive No. 1 (Part A), and Access to Data for Evidence (Part D; see Evidence Act above).

Part B, Confidential Information Protection. Part B of CIPSEA strengthens and extends statutory confidentiality protection for all statistical data collections of the U.S. government. Prior to CIPSEA, such

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⁴¹ See 62 Federal Register 35044 (June 27, 1997). Available: https://www.federalregister.gov/d/97-16934. [February 2021]

protection was governed by a patchwork of laws applicable to specific agencies, judicial opinions, and agencies’ practices. For all data furnished by individuals or organizations to an agency under a pledge of confidentiality for exclusively statistical purposes, Subtitle A provides that the data will be used only for statistical purposes and will not be disclosed in identifiable form to anyone not authorized by the title. It makes the knowing and willful disclosure of confidential statistical data a class E felony, with fines up to $250,000 and imprisonment for up to 5 years.

Subtitle A pertains not only to surveys, but also to collections by a federal agency for statistical purposes from nonpublic administrative records (e.g., confidential state government agency records). Data covered under Subtitle A are not subject to release under a Freedom of Information Act request.

Part C, Statistical Efficiency. Part C of CIPSEA permits the BEA, the BLS, and the Census Bureau to share individually identifiable business data for statistical purposes. The subtitle has three main purposes: (1) to reduce respondent burden on businesses; (2) to improve the comparability and accuracy of federal economic statistics by permitting these three agencies to reconcile differences among sampling frames, business classifications, and business reporting; and (3) to increase understanding of the U.S. economy and improve the accuracy of key national indicators, such as the National Income and Product Accounts.

However, this part does not authorize any new sharing among BEA, BLS, and the Census Bureau of any individually identifiable tax return data that originate from the Internal Revenue Service (IRS). This limitation currently blocks some kinds of business data sharing, such as those for sole proprietorships, which are important for improving the efficiency and quality of business data collection by statistical agencies. For tax return information, data sharing is limited to a small number of items for specified uses by a small number of specific agencies (under Title 26, Section 6103 of the U.S. Code, and associated Treasury Department regulations, as modified in the 1976 Tax Reform Act). The governing statute would have to be modified to extend sharing of tax return items to agencies not specified in the 1976 legislation. Although proposals for legislation to expand access to IRS information for limited statistical purposes have been discussed and developed through interagency discussions, they have not received necessary congressional approval.

CIPSEA Implementation Guidance. OMB originally released implementation guidance for CIPSEA in 2007 (U.S. Office of Management and Budget, 2007). The guidance covered such topics as the steps that agencies must take to protect confidential information; wording of confidentiality pledges in materials that are provided to respondents; steps that agencies must take to distinguish any data or information they collect for nonstatistical purposes and to provide proper notice to the public of such data; and ways in which agents (e.g., contractors, researchers) may be designated to use individually identifiable information for analysis and other statistical purposes and be held legally responsible for protecting the confidentiality of that information. Under the Evidence Act, OMB is charged with promulgating guidance for implementation of a process to designate statistical agencies and units.⁴² A total of 16 agencies and units are currently so recognized (see Appendix B).

Privacy Impact Assessments Required Under the E-Government Act of 2002, Section 208

Section 208 of the E-Government Act of 2002 (P.L. 107-347) requires federal agencies to conduct a privacy impact assessment whenever an agency develops or obtains information technology that handles individually identifiable information or whenever the agency initiates a new collection of individually identifiable information.⁴³ The assessment is to be made publicly available and cover topics such as what information is being collected and why, with whom the information will be shared, what provisions will be made for informed consent regarding data sharing, and how the information will be secured. Typically, privacy impact assessments cover not only privacy issues, but also confidentiality, integrity, and availability issues.⁴⁴ OMB was required to issue guidance for development of the assessments, which was done in a September 26, 2003, memorandum (M-03-22) from the OMB director to the heads of executive agencies and departments.⁴⁵

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⁴² 44 USC 3562(a).

⁴³ Section 208 also mandates that OMB lead interagency efforts to improve federal information technology and use of the Internet for government services.

⁴⁴ See, e.g., the available privacy impact assessments prepared by the Census Bureau at https://www.census.gov/about/policies/privacy/pia.html. [February 2021]

⁴⁵ See https://www.whitehouse.gov/wp-content/uploads/2017/11/203-M-03-22-OMB-Guidance-for-Implementing-the-Privacy-Provisions-of-the-E-Government-Act-of-2002-1.pdf. [February 2021]

Section 208, together with Title III, FISMA (see below), and Title V, CIPSEA (see above), of the 2002 E-Government Act are the latest in a series of laws beginning with the Privacy Act of 1974 (see above) that govern access to individual records maintained by the federal government (see also “Federal Cybersecurity Enhancement Act of 2015,” below).

Federal Information Security Management Act of 2002

The Federal Information Security Management Act (FISMA) was enacted in 2002 as Title III of the E-Government Act of 2002 (P.L. 107-347) to bolster computer and network security in the federal government and affiliated parties (such as government contractors) by mandating yearly audits.

FISMA imposes a mandatory set of processes that must be followed for all information systems used or operated by a federal agency or by a contractor or other organization on behalf of a federal agency. These processes must follow a combination of Federal Information Processing Standards documents, the special publications issued by the National Institute of Standards and Technology (SP-800 series), and other legislation pertinent to federal information systems, such as the Privacy Act of 1974 and the Health Insurance Portability and Accountability Act of 1996.

The first step is to determine what constitutes the “information system” in question. There is no direct mapping of computers to an information system; rather, an information system can be a collection of individual computers put to a common purpose and managed by the same system owner. The next step is to determine the types of information in the system and categorize each according to the magnitude of harm that would result if the system suffered a compromise of confidentiality, integrity, or availability. Succeeding steps are to develop complete system documentation, conduct a risk assessment, put appropriate controls in place to minimize risk, and arrange for an assessment and certification of the adequacy of the controls.

FISMA affects federal statistical agencies directly in that each agency must follow the FISMA procedures for its own information systems. In addition, some departments are taking the position that all information systems in a department constitute a single information system for the purposes of FISMA: those departments are taking steps to require that

statistical agencies’ information systems and personnel be incorporated into a centralized departmentwide system.

Federal Information Technology Acquisition Reform Act of 2014

The Federal Information Technology Acquisition Reform Act (FITARA) was enacted on December 19, 2014, to respond to such federal information technology (IT) challenges as duplicate IT spending among and within agencies; difficulty in understanding the cost and performance of IT investments; and inability to benchmark IT spending between federal and private-sector counterparts. FITARA has four major objectives: (1) strengthening the authority over and accountability for IT costs, performance, and security of agency chief information officers (CIOs); (2) aligning IT resources with agency missions and requirements; (3) enabling more effective planning for and execution of IT resources; and (4) providing transparency about IT resources across agencies and programs. It requires agencies (defined as cabinet departments and independent agencies) to pursue a strategy of consolidation of agency data centers, charges agency CIOs with the responsibility for implementing FITARA, and charges the U.S. Government Accountability Office with producing quarterly scorecards to assess how well agencies are meeting the FITARA objectives.

The director of OMB issued implementation guidance for FITARA, M-15-14, Management and Oversight of Federal Information Technology, on June 20, 2015.⁴⁶ This memorandum explicitly stated that agencies must implement the FITARA guidance to ensure that information acquired under a pledge of confidentiality solely for statistical purposes is used exclusively for those purposes. It also provided a “Common Baseline for IT Management,” which lays out FITARA responsibilities of CIOs and other agency officials, such as the chief financial officer and program officials. On May 4, 2016, the federal CIO and the administrator of OIRA, both in OMB, jointly issued Supplemental Guidance on the Implementation of M-15-14 “Management and Oversight of Federal Information Technology”—Applying FITARA Common Baseline to Statistical Agencies and Units (U.S. Office of Management and Budget, 2016d). This supplemental guidance posed questions for CIOs and other

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⁴⁶ See https://www.whitehouse.gov/sites/whitehouse.gov/files/omb/memoranda/2015/m-15-14.pdf. [February 2021.

officials, including statistical agency heads, to address when implementing FITARA for statistical agency programs. The questions refer to the fundamental responsibilities of federal statistical agencies outlined in Statistical Policy Directive No. 1 (see above), which include confidentiality protection and meeting deadlines for key statistics.

Federal Cybersecurity Enhancement Act of 2015

The Federal Cybersecurity Enhancement Act of 2015 is Title II, Subpart B, of the Cybersecurity Act of 2015, which was attached as a rider to the Consolidated Appropriations Act of 2016, and so became law (P.L. 114-113) when the appropriations bill was signed on December 18, 2015. The impetus for Title II, Subpart B, was the efforts of the U.S. Department of Homeland Security (DHS), dating back to 2003, to deploy systems for detection and prevention of intrusions (“hacking”) into federal government information networks (see Latham & Watkins, 2016, p. 3). As of the end of 2015, this technology, known as EINSTEIN, covered only 45 percent of federal network access points. The act requires DHS to “make [EINSTEIN] available” to all federal agencies within one year, and thereafter requires all agencies to “apply and continue to utilize the capabilities” across their networks.

The technology, currently in version E3A, has been welcomed by federal statistical agencies, but agencies initially were concerned about a DHS interpretation of the act that would allow DHS staff to monitor traffic on agency networks and follow up on actual or likely intrusions. Such surveillance by DHS staff could lead to violations of agencies’ pledges to protect the confidentiality of information provided by individual respondents for statistical purposes, which state that only statistical agency employees or sworn agents can see such information. Ultimately, DHS retained its surveillance authority, and statistical agencies modified their confidentiality pledges. As described in a Federal Register notice from the U.S. Census Bureau (other statistical agencies have issued similar notices):⁴⁷

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⁴⁷ Agency Information Collection Activities; Request for Comments; Revision of the Confidentiality Pledge Under Title 13 United States Code, Section 9, 81 Federal Register 94321 (December 23, 2016). Available: https://www.federalregister.gov/d/2016-30959. [February 2021]

The BLS led an interagency research program to test revised wording with samples of respondents, and agencies revised their pledges accordingly. As an example, the Census Bureau’s revised pledge, provided in 81 Federal Register 94321 (December 23, 2016), states:

LAWS AND GUIDANCE RELATED TO INFORMATION QUALITY AND THE FEDERAL DATA STRATEGY

Since 2000, there has been heightened interest in the Congress and the executive branch regarding the quality of scientific evidence, including federal statistics. Legislation and guidance from OMB and the Office of Science and Technology Policy (OSTP) have addressed concerns about information quality, performance evaluation, scientific integrity, and transparency.

The Information Quality Act of 2000

The Information Quality Act of 2000 (P.L. 106-554) directed OMB to issue government-wide guidelines that “provide policy and procedural guidance to Federal agencies for ensuring and maximizing the quality, objectivity, utility, and integrity of information (including statistical information) disseminated by Federal agencies.” It also required federal agencies to develop their own implementing procedures, including “administrative mechanisms allowing affected persons to seek and obtain correction of information maintained and disseminated by the agency.” After a public comment period, OMB issued governmentwide guidelines on February 22, 2002.⁴⁸

2004 OMB Final Information Quality Bulletin for Peer Review

Consistent with the Information Quality Act of 2000 (see above), OMB developed guidance for federal agencies with regard to seeking peer review of the policy-relevant scientific information an agency disseminates. After two rounds of public comment, OMB issued the Final Information Quality Bulletin for Peer Review on December 16, 2004: it requires federal agencies to conduct a peer review of “influential scientific information” before the information is released to the public.⁴⁹ “Influential scientific information” is defined as “scientific information the agency reasonably can determine will have or does have a clear and substantial impact on important public policies or private sector decisions” (U.S. Office of Management and Budget, 2005, p. 2667). The Final Information Quality Bulletin for Peer Review allows agencies discretion to select the type of peer review process most appropriate for a given scientific information product. Research reports and nonroutine collections by statistical agencies that can be considered “influential scientific information” are covered under the guidelines, but “routine statistical information released by federal statistical agencies (e.g., periodic demographic and economic statistics) and the analysis of these data to compute standard indicators and trends (e.g., unemployment and poverty rates)” are excluded (U.S. Office of Management and Budget, 2005, p. 2674).

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⁴⁸ See 67 Federal Register 8452 (February 22, 2002). Available: https://www.federalregister.gov/d/R2-59. [February 2021]

⁴⁹ See https://www.whitehouse.gov/wp-content/uploads/2017/11/2005-M-05-03-Issuance-of-OMBs-Final-Information-Quality-Bulletin-for-Peer-Review-December-16-2004.pdf. [February 2021]

Government Performance and Results Modernization Act of 2010

The Government Performance and Results Modernization Act of 2010, which supersedes the Performance Assessment Rating Tool and the Government Performance and Results Act of 1993, was signed into law on January 4, 2011.⁵⁰ It requires performance assessments of government programs for purposes of evaluating agency performance and improvement. In carrying out the provisions of the act, the director of OMB coordinates with agencies to develop the federal government performance plan. The act requires all federal agencies, with few exceptions, to establish performance indicators to be used in measuring or assessing progress toward their identified performance goals and an objective, quantifiable, and measurable means by which to compare actual program results with these established performance goals. Additionally, each agency must describe how it will ensure the accuracy and reliability of the data used, including validation of measures, data sources, required level of accuracy, data limitations, and management of those limitations.

The broad scope of agencies affected by this act, and the use of the act in making budgetary decisions based on measured achievement toward program goals, have fostered added focus among many agencies on how to collect high-quality data and produce sound government statistics with which to conduct rigorous program evaluation. The addendum to Statistical Policy Directive No. 4 (see above), issued in 2016, prescribes a program of annual performance reviews for federal statistical products.

2010 Office of Science and Technology Policy Memorandum on Scientific Integrity

In a memorandum on scientific integrity issued March 9, 2009, President Obama stated:⁵¹

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⁵⁰ See http://www.gpo.gov/fdsys/pkg/PLAW-111publ352/pdf/PLAW-111publ352.pdf. [February 2021]

⁵¹ See https://obamawhitehouse.archives.gov/the-press-office/memorandum-heads-executive-departments-and-agencies-3-9-09. [February 2021]

President Obama directed the Office of Science and Technology Policy (OSTP) to develop a strategy to ensure scientific integrity in government decision making. In response, the OSTP director issued a memorandum on December 17, 2010, that called for executive departments and agencies to develop policies to “ensure a culture of scientific integrity,” “strengthen the actual and perceived credibility of Government research,” “facilitate the free flow of scientific and technological information, consistent with privacy and classification standards,” and “establish principles for conveying scientific and technological information to the public.”⁵² The memorandum included guidance on the selection of candidates for scientific positions, independent peer review, whistleblower protections, promoting access to scientific and technological information in online open formats, and agency communications. It also provided guidance on public communications, use of federal advisory committees, professional development of government scientists and engineers, and implementation.

Each statistical agency is covered by its department’s scientific integrity policies. In addition, the principal statistical agencies developed a Statement of Commitment to Scientific Integrity that documents in a single place their response to the OSTP memorandum. The statement articulates how the Principles and Practices for a Federal Statistical Agency, Fourth Edition (NRC, 2009c), various OMB statistical policy directives and standards, and each agency’s information quality guidelines together form “the foundation for achieving and maintaining scientific integrity within and among the principal statistical agencies.”⁵³

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⁵² See https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/scientific-integrity-memo-12172010.pdf. [February 2021]

⁵³ See http://www.census.gov/content/dam/Census/about/about-the-bureau/policies_and_notices/scientificintegrity/Scientific_Integrity_Statement_of_the_Principal_Statistical_Agencies.pdf. [February 2021]

2013 Office of Science and Technology Policy Memorandum on Increasing Access to the Results of Scientific Research

On February 22, 2013, the OSTP director issued a memorandum for heads of executive departments and agencies on “Increasing Access to the Results of Federally Funded Scientific Research.”⁵⁴ Citing the importance of scientific research for driving improvements in “areas such as health, energy, the environment, agriculture, and national security,” the memorandum outlined the administration’s commitment to:

The memorandum directed federal agencies with more than $100 million in annual research and development expenditures to develop a plan “to support increased public access to the results of research funded by the Federal Government. This includes any results published in peer reviewed scholarly publications that are based on research that directly arises from Federal funds…” The memorandum further directed agencies to develop plans for ensuring archiving of and access to data underlying federally funded research and the associated documentation or metadata. It listed various topics to be covered in each agency’s plan, including that the plan be posted on the agency’s website and provide for protection of the confidentiality of individual respondents’ information.

Improving Implementation of the Information Quality Act (M-19-15)

OMB issued Memorandum M-19-15 in April of 2019 to reinforce, clarify, and interpret agency responsibilities under the Information Quality Act. The guidance provides updates for specific areas in the original guidance related to identifying influential information, peer review of influential scientific information, public access to government informa-

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⁵⁴ See https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/ostp_public_access_memo_2013.pdf. [February 2021]

tion (open data), and reuse of existing agency program data. Guidance in the last area draws from OMB Memorandum M-14-06 and includes the following updates:

• Implementation Update 2.3: Agencies should consider the potential for using existing data sources from both inside and outside the agency for statistical and research purposes, while protecting privacy and confidentiality.
• Implementation Update 2.4: When designing or improving data collection systems, departments should actively solicit comment from their statistical, research, and evaluation agencies about potential downstream uses. Agencies should describe such uses in the Information Collection Request submitted to OMB for review under the PRA.
• Implementation Update 2.5: If agencies are considering secondary analysis of data that includes personally identifiable information, the agencies should coordinate with their Senior Agency Official for Privacy to meet all privacy requirements and manage privacy risks.
• Implementation Update 2.6: Agencies should develop procedures for clearly documenting and communicating the quality of administrative data that have the potential to be used for statistical purposes

There are also several updates regarding the reproducibility of influential information and requests for correction.

Federal Data Strategy—A Framework for Consistency (M-19-18)

The Federal Data Strategy describes a 10-year vision for how the federal government will accelerate the use of data to deliver on mission, serve the public, and steward resources while protecting security, privacy, and confidentiality. OMB states that federal data is both a strategic asset and a valuable national resource that enables the government to carry out its mission and programs effectively. It provides the public with knowledge of the government, society, economy, and environment and serves as a means to ensure the accountability of government, to manage the government’s operations, and to maintain and enhance the performance of the nation’s economy, public health, and welfare. The strategy states that

appropriate access to federal data significantly enhances its value and the return on the nation’s investment in its creation.

The Federal Data Strategy comprises three components to guide federal data management and use:

• Mission Statement: The mission statement articulates the intent and core purpose of the Strategy.
• Principles: The principles serve as motivational guidelines in the areas of ethical governance, conscious design, and learning culture.
• Practices: The practices guide agencies in leveraging the value of data.

Federal Data Strategy Mission. The Mission Statement reads as follows:

Federal Data Strategy Principles. There are 10 principles in the Federal Data Strategy, which are intended to guide the development of a comprehensive data strategy:

Ethical Governance

1. Uphold ethics: Monitor and assess the implications of federal data practices for the public. Design checks and balances to protect and serve the public good.
2. Exercise responsibility: Practice effective data stewardship and governance. Employ sound data security practices, protect individual privacy, maintain promised confidentiality, and ensure appropriate access and use.
3. Promote transparency: Articulate the purposes and uses of federal data to engender public trust. Comprehensively document processes and products to inform data providers and users.

Conscious Design

4. Ensure relevance: Protect the quality and integrity of the data. Validate that data are appropriate, accurate, objective, accessible, useful, understandable, and timely.

5. Harness existing data: Identify data needs to inform priority research and policy questions; reuse data if possible and acquire additional data if needed.
6. Anticipate future uses: Create data thoughtfully, considering fitness for use by others; plan for reuse and build in interoperability from the start.
7. Demonstrate responsiveness: Improve data collection, analysis, and dissemination with ongoing input from users and stakeholders. The feedback process is cyclical; establish a baseline, gain support, collaborate, and refine continuously.

Learning Culture

8. Invest in learning: Promote a culture of continuous and collaborative learning with and about data through ongoing investment in data infrastructure and human resources.
9. Develop data leaders: Cultivate data leadership at all levels of the federal workforce by investing in training and development about the value of data for mission, service, and the public good.
10. Practice accountability: Assign responsibility, audit data practices, document and learn from results, and make needed changes.

Federal Data Strategy Practices. There are 40 practices in the Federal Data Strategy, which are intended to be sufficiently general so as to apply to all federal agencies. These practices represent aspirational goals that are intended to improve the government’s approach to data stewardship and the leveraging of data to create value. They are organized in three categories that reflect the importance of tailoring the management of data to the uses of the data:

• Building a Culture that Values Data and Promotes Public Use (Practices 1–10),
• Governing, Managing, and Protecting Data (Practices 11–26), and
• Promoting Efficient and Appropriate Data Use (Practices 27–40).

Practices 1–10 derive value by articulating data uses for agency decision-making and accountability and supporting commercialization, innovation, and public use:

1. Identify data needs to answer key agency questions.
2. Assess and balance the needs of stakeholders.

3. Champion data use.
4. Use data to guide decision-making.
5. Prepare to share.
6. Convey insights from data.
7. Use data to increase accountability.
8. Monitor and address public perceptions.
9. Connect data functions across agencies.
10. Provide resources explicitly to leverage data assets.

Practices 11–26 derive value from data by bringing leaders with diverse perspectives and expertise together to plan for using the data appropriately and responsibly:

11. Prioritize data governance.
12. Govern data to protect confidentiality and privacy.
13. Protect data integrity.
14. Convey data authenticity.
15. Assess maturity.
16. Inventory data assets.
17. Recognize the value of data assets.
18. Manage with a long view.
19. Maintain data documentation.
20. Leverage data standards.
21. Align agreements with data management requirements.
22. Identify opportunities to overcome resource obstacles.
23. Allow amendment.
24. Enhance data preservation.
25. Coordinate federal data assets.
26. Share data between state, local, and tribal governments and federal agencies.

Practices 27–40 derive value from data by providing access to data resources, promoting appropriate use of data resources, and providing guidance on approaches for data augmentation:

27. Increase capacity for data management and analysis.
28. Align quality with intended use.
29. Design data for use and re-use.

30. Communicate planned and potential uses of data.
31. Explicitly communicate allowable use.
32. Harness safe data linkage.
33. Promote wide access.
34. Diversify data access methods.
35. Review data releases for disclosure risk.
36. Leverage partnerships.
37. Leverage buying power.
38. Leverage collaborative computing platforms.
39. Support federal stakeholders.
40. Support nonfederal stakeholders.

Federal Data Strategy Action Plan. FY 2020 is the first year of the Federal Data Strategy Action Plan. The plan includes actions for individual agencies, communities of practice, and shared solutions.

Agency Actions. Six Agency Actions are identified as foundational steps to support agencies in establishing plans, processes, and priorities for better managing data assets while considering how the agency’s data assets could be leveraged to advance the agency’s mission:

Community of Practice Actions. Community of Practice Actions are taken by a specific agency or group of agencies related to a common topic, usually through an established interagency council or other existing coordinating mechanism. Community of Practice Actions seek to integrate and coordinate ongoing efforts related to existing laws, regulations, and executive orders that are particularly relevant to the strategy:

Shared Solution Actions. Shared Solution Actions are described as governmentwide data services and represent discrete pilot projects or efforts led by a single agency or existing council for the benefit of all agencies. The 10 Shared Solution Actions identified in the 2020 Action Plan are designed to provide governmentwide direction, tools, and/or services for implementing the strategy that other agencies will be able to leverage in the future:

It is anticipated that fully implementing the Federal Data Strategy will require a sustained, iterative, and systematic effort over a 10-year period. The Action Plans produced each year will be designed to identify priority actions for a given year and incrementally build on progress from year to year.

INTERAGENCY COUNCIL ON STATISTICAL POLICY DOCUMENTS

The Interagency Council on Statistical Policy (ICSP) is chaired by the chief statistician at OMB and consists of the heads of the principal statistical agencies and the statistical officials designated under the Evidence Act (see Box A-1). The ICSP creates task forces or working groups to tackle issues of interest to the federal statistical system, and these groups may

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⁵⁵ See ResearchDataGov: https://www.icpsr.umich.edu/web/pages/appfed/index.html. [February 2021]

report to the ICSP alone or may issue public reports. The ICSP issued a public statement of principles for modernizing federal statistics, which is summarized next.

2002 Federal Statistical Agency Guidelines for Ensuring and Maximizing the Quality, Objectivity, Utility, and Integrity of Disseminated Information

A few months after OMB issued implementation guidance in February 2002 for the 2000 Information Quality Act (see above), 13 principal statistical agencies issued a notice outlining a common approach to the development and provision of guidelines for ensuring and maximizing the quality, objectivity, utility, and integrity of disseminated information.⁵⁶ The notice directed people to the websites of each agency for more information and to learn how to comment on draft guidelines.

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⁵⁶ See 67 Federal Register 38467 (June 4, 2002). Available: https://www.federalregister.gov/d/02-13892. [February 2021]

Each agency then finalized its own guidelines.⁵⁷ The information quality framework developed by the agencies was followed in the 2006 revision of OMB’s standards and guidelines for statistical surveys (see Statistical Policy Directive No. 2 above).

Principles for Modernizing Production of Federal Statistics by Interagency Council on Statistical Policy⁵⁸[Summary]

Increasingly, the federal statistical system is facing challenges maintaining statistical surveys, primarily due to falling response rates and rising costs. At the same time, advances in technology and methodology are creating opportunities for statistical agencies to modernize their practices.

A shift from reliance on surveys for primary data collection to reliance on surveys as a complement to already existing data, either in-house or otherwise available to an agency, is essential to the modernization of the federal statistical system.

The use for statistical purposes of nonstatistical or integrated data—also known as blended, hybrid, or combined data—requires investment in data acquisition and development of standards. First, statistical agencies and components must be able to access alternative data sources. A second major challenge is measuring and transparently communicating the quality of statistical information derived from nonstatistical or integrated statistical and nonstatistical information. The following principles for the ICSP work on integrated data are intended to guide the FCSM and to establish priorities for research and ongoing work by statistical agencies to advance the use of nontraditional information and data to produce statistical information. The work by the ICSP and the FCSM fits more broadly under OMB’s development of a Federal Data Strategy as part of the President’s Management Agenda.

Principles for Using NonStatistical Data for Statistical Purposes:

1. Agencies should employ the highest quality reasonably obtainable sources of information, including nonstatistical data sets and derivative information in developing statistical datasets in support of mission activities.

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⁵⁷ See, e.g., https://www.census.gov/about/policies/quality/guidelines.html. [February 2021]

⁵⁸ See https://nces.ed.gov/FCSM/pdf/Principles.pdf.

2. While fully complying with confidentiality and privacy requirements, agencies should continue to make statistical information created in support of mission activities as granular and timely as practicable and widely accessible.
3. Agencies should report transparently on the quality of information they disseminate.
4. Characterization of quality should be both quantitative and qualitative, consistent with available information.
5. Judgments used in developing data sets, such as assumptions, defaults, and uncertainties, should be stated explicitly.
6. Agencies should work to adopt a common language and framework for reporting on the quality of data sets and derivative information they disseminate.

Quality is composed of multiple dimensions, each of which should be addressed in transparent public reporting:

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