Principles and Practices for a Federal Statistical Agency: Eighth Edition (2025)
Chapter: References
References
Abascal, M. A., Archie, J. C., Crawford, G. E., Naftalis, B. A., Schindler, D. J., Jones, S. C., & Stout, A. L. (2016). What you need to know about the Cybersecurity Act of 2015. Latham & Watkins. https://www.lw.com/thoughtLeadership/lw-Cybersecurity-Act-of-2015
Advisory Committee on Data for Evidence Building. (2021). Advisory Committee on Data for Evidence Building: Year 1 report. https://www.bea.gov/system/files/2021-10/acdeb-year-1-report.pdf
Advisory Committee on Data for Evidence Building. (2022). Advisory Committee on Data for Evidence Building: Year 2 report. https://www.bea.gov/system/files/2022-10/acdeb-year-2-report.pdf
American Economic Association. (2018). Principles of economic measurement. https://www.aeaweb.org/content/file?id=6847
American Statistical Association. (2022). Ethical guidelines for statistical practice. https://www.amstat.org/your-career/ethical-guidelines-for-statistical-practice
American Statistical Association. (2024). The nation’s data at risk: Meeting America’s information needs for the 21st century. https://www.amstat.org/policy-and-advocacy/the-nation’s-data-at-risk-meeting-american’s-information-needs-for-the-21st-century
An Act to Establish a Department of Education, Pub. Law 39-73, 14 Stat. 434 (1867). https://www.docsteach.org/documents/document/act-of-march-2-1867-public-law-3973-14-stat-434-which-established-the-department-of-education
Anderson, M. J. (2015). The American census: A social history (2nd ed.). Yale University Press. https://doi.org/10.12987/9780300216967
Behzad, B., Bheem, B., Elizondo, D., & Martonosi, S. (2023). Prevalence and propagation of fake news. Statistics and Public Policy, 10(1). https://doi.org/10.1080/2330443X.2023.2190368
Bohman, M. (2024). Making a difference through trusted, high-quality research and statistics. American Journal of Agricultural Economics, 106(2), 485–495. https://doi.org/https://doi.org/10.1111/ajae.12459
Bowen, C., & Snoke, J. (2023). Do no harm guide: Applying equity awareness in data privacy methods. Urban Institute. https://policycommons.net/artifacts/3525920/do-no-harm-guide/4326655/
Bowen, C. M. (2023). The autonomy gap: Response to Citro et al. and the statistical community. Statistics and Public Policy, 10(1). https://doi.org/10.1080/2330443X.2023.2221324
Budget and Accounting Procedures Act, 31 U.S.C. § 1104(d) (1950). https://www.govregs.com/uscode/expand/title31_subtitleII_chapter11_section1104#uscode_3
Bureau of Labor Statistics (BLS). (2021a). Final report of the Interagency Technical Working Group on evaluating alternative measures of poverty. U.S. Department of Labor. https://www.bls.gov/cex/itwg-report.pdf
BLS. (2021b). Report to the Office of Management and Budget: Consumer inflation measures. U.S. Department of Labor. https://www.bls.gov/evaluation/technical-recommendations-for-the-consumer-inflation-measure-best-suited-for-conducting-annual-adjustments-to-the-official-poverty-measure.pdf#:~:text=The%20ITWG%20was%20chartered%20to%3A%20%281%29%20develop%20a,the%20methodologies%20used%20in%20the%20consumer%20inflation%20measures
Cabrera, N. B., Bongartz, E. C., Dörrenbächer, N., Goebel, J., Kaluza, H., & Siegers, P. (2020). White paper on implementing the FAIR principles for data in the social, behavioural, and economic sciences. Consortium for the Social, Behavioral, Educational, and Economic Sciences, 274. https://doi.org/10.17620/02671.60
Census Bureau. (2010). Observations from the Interagency Technical Working Group on Developing a Supplemental Poverty Measure. U.S. Department of Commerce. https://www.census.gov/content/dam/Census/library/working-papers/2010/demo/SPM_Wkg-Grp.pdf
Census Bureau. (2021). Improvements to the Census Bureau’s supplemental poverty measure for 2021. U.S. Department of Commerce. https://www.census.gov/topics/income-poverty/supplemental-poverty-measure/library/working-papers/topics/potential-changes.html
Chief Financial Officers Act of 1990, Pub. L. No. 101-576, 105 Stat. 2838 (1990). https://www.congress.gov/101/statute/STATUTE-104/STATUTE-104-Pg2838.pdf
CHIPS and Science Act of 2022, Pub. L. No. 117-167, 136 Stat. 1366 (2022). https://www.congress.gov/bill/117th-congress/house-bill/4346/text
Citro, C. F. (2014). Principles and practices for a federal statistical agency: Why, what, and to what effect. Statistics and Public Policy, 1(1), 51–59. http://dx.doi.org/10.1080/2330443X.2014.912953
Citro, C. F. (2016). The U.S. federal statistical system’s past, present, and future. Annual Review of Statistics and Its Application, 3(1), 347–373. https://www.annualreviews.org/content/journals/10.1146/annurev-statistics-041715-033405
Citro, C. F., Auerbach, J., Evans, K. S., Groshen, E. L., Landefeld, J. S., Mulrow, J., Petska, T., Pierson, S., Potok, N., Rothwell, C. J., Thompson, J., Woodworth, J. L., & Wu, E. (2023). What protects the autonomy of the federal statistical agencies? An assessment of the procedures in place to protect the independence and objectivity of official U.S. statistics. Statistics and Public Policy, 10(1). https://doi.org/10.1080/2330443X.2023.2188062
Cohen, M. (2023). Discussion of “What protects the autonomy of the federal statistical agencies? An assessment of the procedures in place to protect the independence and objectivity of official U.S. statistics” by Citro et al. (2023). Statistics and Public Policy, 10(1). https://doi.org/10.1080/2330443X.2023.2244026
Commission on Evidence-Based Policymaking. (2017). The promise of evidence-based policymaking. https://bipartisanpolicy.org/wp-content/uploads/2019/03/Full-Report-The-Promise-of-Evidence-Based-Policymaking-Report-of-the-Comission-on-Evidence-based-Policymaking.pdf
Committee on National Statistics. (2024). People and publications: 1972–2023. Division of Behavioral and Social Sciences and Education. https://www.nationalacademies.org/documents/embed/link/LF2255DA3DD1C41C0A42D3BEF0989ACAECE3053A6A9B/file/D48F08611AA79D848FF6C76DDB21DF2737D47EE3883B?noSaveAs=1
Confidential Information and Statistical Efficiency Act of 2018, Pub. L. No. 115-435, 132 Stat. 5529. (2019). https://www.congress.gov/115/plaws/publ435/PLAW-115publ435.pdf
Confidential Information Protection and Statistical Efficiency Act, Pub. L. No. 107-347, H.R. 5215. (2002). https://www.congress.gov/107/bills/hr5215/BILLS-107hr5215rh.pdf
Cui, I., Ho, D. E., Martin, O., & O’Connell, A. J. (2024, forthcoming). Governing by assignment. Stanford Law School. https://dho.stanford.edu/wp-content/uploads/IPA.pdf
Cybersecurity & Infrastructure Security Agency. (2023). Einstein [archived page]. U.S. Department of Homeland Security. https://web.archive.org/web/20230716151116/https:/www.cisa.gov/einstein
Cybersecurity Information Sharing Act, Pub. Law 114-185, 130 Stat. 538 (2016). https://www.congress.gov/114/plaws/publ185/PLAW-114publ185.pdf
Czajka, J., & Strange, M. (2018). Transparency in the reporting of quality for integrated data: A review of international standards and guidelines. U.S Department of Commerce. https://www.washstat.org/presentations/20180226/20180226_Czajka.pdf#:~:text=%E2%80%A2%20Quality%20reporting%20on%20accuracy%20is
Department of Commerce. (1978a). 43 F.R. 19308. https://www.govinfo.gov/content/pkg/FR-1978-05-04/pdf/FR-1978-05-04.pdf
Department of Commerce. (1978b). 43 F.R. 19260. https://www.govinfo.gov/content/pkg/FR-1978-05-04/pdf/FR-1978-05-04.pdf
Department of Commerce. (2014). Fostering innovation, creating jobs, driving better decisions: The value of government data. https://www.commerce.gov/data-and-reports/reports/2014/07/fostering-innovation-creating-jobs-driving-better-decisions-value#:~:text=This%20report%20finds:%20Government%20data%20potentially
Duncan, J. W., & Shelton, W. C. (1978). Revolution in United States statistics, 1926–1976. U.S. Government Printing Office. https://babel.hathitrust.org/cgi/pt?id=uiug.30112052125652&seq=185
E-Government Act, Pub. Law 107-347, 116 Stat. 2899 (2002). https://www.congress.gov/107/plaws/publ347/PLAW-107publ347.pdf
European Statistical System Committee. (2017). European statistics code of practice. Publications Office of the European Union. https://ec.europa.eu/eurostat/documents/4031688/8971242/KS-02-18-142-EN-N.pdf/e7f85f07-91db-4312-8118-f729c75878c7
Evidence-Based Policymaking Commission Act of 2016, Pub. L. No. 114-140, 130 Stat. 317 (2016). https://www.govinfo.gov/content/pkg/STATUTE-130/pdf/STATUTE-130-Pg317.pdf
Excepted Service, 5 U.S.C. 2103 (1978). https://www.govinfo.gov/content/pkg/USCODE-2023-title5/pdf/USCODE-2023-title5-partIII-subpartA-chap21-sec2103.pdf
Executive Office of the President. (1933). Executive Order 6226: Providing for current encumbrance reports. https://www.presidency.ucsb.edu/documents/executive-order-6226-providing-for-current-encumbrance-reports
Executive Office of the President. (1977). Executive Order 12013: Statistical policy functions. https://www.presidency.ucsb.edu/documents/executive-order-12013-statistical-policy-functions
Executive Office of the President. (1981). Executive Order 12318: Statistical policy functions. https://www.presidency.ucsb.edu/documents/executive-order-12318-statistical-policy-functions
Executive Office of the President. (2009). M 3-9-09: Scientific integrity. https://obamawhitehouse.archives.gov/the-press-office/memorandum-heads-executive-departments-and-agencies-3-9-09
Executive Office of the President. (2023). Executive Order 14110: Safe, secure, and trustworthy development and use of artificial intelligence. https://www.govinfo.gov/content/pkg/FR-2023-11-01/pdf/2023-24283.pdf
Federal Committee on Statistical Methodology. (2001). Statistical policy working paper No. 31: Measuring and reporting sources of error in surveys. https://nces.ed.gov/FCSM/pdf/spwp31.pdf
Federal Committee on Statistical Methodology. (2020). A framework for data quality. https://nces.ed.gov/FCSM/pdf/FCSM.20.04_A_Framework_for_Data_Quality.pdf
Federal Committee on Statistical Methodology. (2022). Data protection toolkit: Report and resources on statistical disclosure limitation methodology and tiered data access (formerly ‘Statistical Policy Working Paper No. 22’). https://nces.ed.gov/fcsm/dpt
Federal Committee on Statistical Methodology. (2024). U.S. Office of Management and Budget. https://www.fcsm.gov/
Federal Information Technology Acquitision Reform Act, Pub. Law 113-291, 128 Stat. 3438 (2014). https://www.cio.gov/assets/files/FITARA%20Pub%20L%20113-291.pdf
Federal Interagency Forum on Aging-Related Statistics. (2024). https://agingstats.gov/
Federal Interagency Forum on Child and Family Statistics. (2024). https://www.childstats.gov/
Federal Policy for the Protection of Human Subjects, 45 F.R. Part 46(a). (2018). https://www.ecfr.gov/on/2018-07-19/title-45/subtitle-A/subchapter-A/part-46
Federal Reports Act, Pub. L. No. 831, 31–33 (1942). https://www.census.gov/history/pdf/Federal_Reports_Act_1942.pdf
Foundations for Evidence-Based Policymaking Act of 2018, Pub. L. No. 115-435, 132 Stat. 5529. (2019). https://www.govinfo.gov/content/pkg/PLAW-115publ435/html/PLAW-115publ435.htm
General Services Administration. (2020). Federal data strategy: Data ethics framework. https://resources.data.gov/assets/documents/fds-data-ethics-framework.pdf
Goerge, R. (2018). Barriers to accessing state data and approaches to addressing them. Annals of the American Academy of Political and Social Science, 675, 122–137. https://journals.sagepub.com/doi/pdf/10.1177/0002716217741257
Gotterbarn, D., Bruckman, A., Flick, C., Miller, K., & Wolf, M. J. (2018). ACM code of ethics: A guide for positive action. Communications of the Association for Computing Machinery, 61(1), 121–128. https://doi.org/10.1145/3173016
Government Accountability Office (GAO). (1995). Report No. GGD-95-65: Statistical Agencies: Adherence to guidelines and coordination of budgets. http://www.gao.gov/products/GGD-95-65
GAO. (2007). Bureau of Justice Statistics Report No. GAO-07-340: Quality guidelines generally followed for police-public contact surveys, but opportunities exist to help assure agency independence. http://www.gao.gov/products/GAO-07-340
GAO. (2012). Report No. GAO-12-54: Federal statistical system: Agencies can make greater use of existing data, but continued progress is needed on access and quality issues. http://www.gao.gov/products/GAO-12-54
Gravelle, H., & Rees, R. (2004). Microeconomics (3rd ed.). Pearson Education Limited. https://pure.york.ac.uk/portal/en/publications/microeconomics
Group of Eight. (2013). G8 Open Data Charter. https://www.gov.uk/government/publications/open-data-charter/g8-open-data-charter-and-technical-annex
Habermann, H., & Louis, T. A. (2020). Can the fundamental principles of official statistics and the political process co-exist? Statistical Journal of the IAOS, 36(2), 347–353. https://content.iospress.com/download/statistical-journal-of-the-iaos/sji200624?id=statistical-journal-of-the-iaos%2Fsji200624
Habermann, H., Louis, T. A., & Reeder, F. (2023). Is autonomy possible and is it a good thing? Statistics and Public Policy, 10(1). https://doi.org/10.1080/2330443X.2023.2221314
Hartman, K., Habermann, H., Harris-Kojetin, B., Jones, C., & Louis, T. (2014). Strength under pressure. Significance, 11(4), 44–47. https://click.endnote.com/viewer?doi=10.1111/J.1740-9713.2014.00769.X&route=2
Health Insurance Portability and Accountability Act, Pub. Law 104-191, 110 Stat. 1936 (1996). https://www.congress.gov/104/plaws/publ191/PLAW-104publ191.pdf
Hendriks, C. (2012). Input data quality in register based statistics: The Norwegian experience. American Statistical Association. https://ww2.amstat.org/meetings/proceedings/2012/data/assets/pdf/303710_71783.pdf
Hillygus, D. S., Nie, N. H., Prewitt, K., & Pals, H. (2006). The hard count: The political and social challenges of Census mobilization. Russell Sage Foundation. http://www.jstor.org/stable/10.7758/9781610442886
Ho, D. E., & O’Connell, A. J. (2024). Opinion: The government has a workforce crisis. One of its best-kept secrets can fix it. Washington Post. https://www.washingtonpost.com/opinions/2024/03/12/federal-government-workforce-crisis/
Hogan, H., & Steffey, D. (2014). Professional ethics for statisticians: An organizational history. https://ww2.amstat.org/meetings/proceedings/2014/data/assets/pdf/311653_87910.pdf
Hughes-Cromwick, E., & Coronado, J. (2019). The value of US government data to US business decisions. Journal of Economic Perspectives, 33(1), 131–146. https://www.aeaweb.org/articles?id=10.1257/jep.33.1.131
Information Quality Act, Pub. L. No. 106-554, 114 Stat. 2763A § 515. (2000). https://www.govinfo.gov/content/pkg/PLAW-106publ554/pdf/PLAW-106publ554.pdf
Intergovernmental Personnel Act of 1970, Pub. L. No. 91-648. (1970). https://uscode.house.gov/statutes/pl/91/648.pdf
Internal Revenue Code of 1986, Pub. L. No. 99-514, 100 Stat. 2095 § 2 § 6103. (1986). https://www.govinfo.gov/content/pkg/USCODE-2011-title26/pdf/USCODE-2011-title26-subtitleF-chap61-subchapB-sec6103.pdf
Martin, M. E. (1981). Statistical practice in bureaucracies. Journal of the American Statistical Association, 76(373), 1–8. http://www.tandfonline.com/doi/abs/10.1080/01621459.1981.10477593
Metropolitan Areas Protection and Standardization Act of 2021, Pub. L. No. 117-219, 136 Stat. 2271. (2021). https://www.congress.gov/117/plaws/publ219/PLAW-117publ219.pdf
Mirel, L. B., Singpurwalla, D., Hoppe, T., Liliedahl, E., Schmitt, R., & Weber, J. (2023). A framework for data quality: Case studies. Federal Committee on Statistical Methodology. https://www.fcsm.gov/assets/files/docs/FCSM.23.02_DQ_case_studies_FINAL.pdf
National Academies of Sciences, Engineering, and Medicine (NASEM). (2016a). Reducing respondent burden in the American Community Survey: Proceedings of a workshop. The National Academies Press. https://doi.org/10.17226/23639
NASEM. (2016b). Making eye health a population health imperative: Vision for tomorrow. The National Academies Press. https://doi.org/10.17226/23471
NASEM. (2017a). Innovations in federal statistics: Combining data sources while protecting privacy. The National Academies Press. https://doi.org/10.17226/24652
NASEM. (2017b). Improving crop estimates by integrating multiple data sources. The National Academies Press. https://doi.org/10.17226/24892
NASEM. (2017c). Federal statistics, multiple data sources, and privacy protection: Next steps. The National Academies Press. https://doi.org/10.17226/24893
NASEM. (2017d). Principles and practices for federal program evaluation: Proceedings of a workshop. The National Academies Press. https://doi.org/10.17226/24831
NASEM. (2017e). Advancing concepts and models for measuring innovation: Proceedings of a workshop. The National Academies Press. https://doi.org/10.17226/23640
NASEM. (2018a). The 2014 redesign of the survey of income and program participation: An assessment. The National Academies Press. https://doi.org/10.17226/24864
NASEM. (2018b). Measuring the 21st century science and engineering workforce population: Evolving needs. The National Academies Press. https://doi.org/10.17226/24968
NASEM. (2018c). Reengineering the Census Bureau’s annual economic surveys. The National Academies Press. https://doi.org/10.17226/25098
NASEM. (2019a). Methods to foster transparency and reproducibility of federal statistics: Proceedings of a workshop. The National Academies Press. https://doi.org/10.17226/25305
NASEM. (2019b). Improving the American Community Survey: Proceedings of a workshop. The National Academies Press. https://doi.org/10.17226/25387
NASEM. (2019c). Improving data collection and measurement of complex farms. The National Academies Press. https://doi.org/10.17226/25260
NASEM. (2020a). Measuring alternative work arrangements for research and policy. The National Academies Press. https://doi.org/10.17226/25822
NASEM. (2020b). A consumer food data system for 2030 and beyond (prepublication). The National Academies Press. https://doi.org/10.17226/25657
NASEM. (2021a). Principles and practices for a federal statistical agency: Seventh edition. The National Academies Press. https://doi.org/10.17226/25885
NASEM. (2021b). A satellite account to measure the retail transformation: Organizational, conceptual, and data foundations. The National Academies Press. https://doi.org/10.17226/26101
NASEM. (2022a). A vision and roadmap for education statistics. The National Academies Press. https://doi.org/10.17226/26392
NASEM. (2022b). Modernizing the consumer price index for the 21st century. The National Academies Press. https://doi.org/10.17226/26485
NASEM. (2022c). Measuring sex, gender identity, and sexual orientation. The National Academies Press. https://doi.org/10.17226/26424
NASEM. (2022d). Transparency in statistical information for the National Center for Science and Engineering Statistics and all federal statistical agencies. The National Academies Press. https://doi.org/10.17226/26360
NASEM. (2023a). A roadmap for disclosure avoidance in the Survey of Income and Program Participation. The National Academies Press. https://doi.org/10.17226/27169
NASEM. (2023b). Toward a 21st century national data infrastructure: Mobilizing information for the common good. The National Academies Press. https://nap.nationalacademies.org/read/26688/chapter/1
NASEM. (2023c). Toward a 21st century national data infrastructure: Enhancing survey programs by using multiple data sources. The National Academies Press. https://doi.org/10.17226/26804
NASEM. (2023d). 2020 Census data products: Demographic and housing characteristics file: Proceedings of a workshop. The National Academies Press. https://doi.org/10.17226/26727
NASEM. (2023e). An updated measure of poverty: (Re)drawing the line. The National Academies Press. https://doi.org/10.17226/26825
NASEM. (2024a). Reducing intergenerational poverty. The National Academies Press. https://doi.org/10.17226/27058
NASEM. (2024b). An integrated system of U.S. household income, wealth, and consumption data and statistics to inform policy and research. The National Academies Press. https://doi.org/10.17226/27333
NASEM. (2024c). Toward a 21st century national data infrastructure: Managing privacy and confidentiality risks with blended data. The National Academies Press. https://doi.org/10.17226/27335
National Artificial Intelligence Initiative Act, H.R. 6216. (2020). https://www.congress.gov/bill/116th-congress/house-bill/6216
National Institute of Standards and Technology. (2024). Artificial intelligence risk management framework: Generative artificial intelligence profile. U.S. Department of Commerce. https://nvlpubs.nist.gov/nistpubs/ai/NIST.AI.600-1.pdf
National Research Council (NRC). (1979). Privacy and confidentiality as factors in survey nonresponse. The National Academies Press. https://doi.org/10.17226/19845
NRC. (1984). Cognitive aspects of survey methodology: Build a bridge between disciplines. The National Academies Press. https://doi.org/10.17226/930
NRC. (1992). Principles and practices for a federal statistical agency: First edition. The National Academies Press. https://doi.org/10.17226/9043
NRC. (2001). Principles and practices for a federal statistical agency: Second edition. The National Academies Press. https://doi.org/10.17226/10057
NRC. (2005). Principles and practices for a federal statistical agency: Third edition. The National Academies Press. https://doi.org/10.17226/11252
NRC. (2009). Principles and practices for a federal statistical agency: Fourth edition. The National Academies Press. https://doi.org/10.17226/12564
NRC. (1993a). Private lives and public policies: Confidentiality and accessibility of government statistics. The National Academies Press. https://doi.org/10.17226/2122
NRC. (1993b). The future of the Survey of Income and Program Participation. The National Academies Press. https://doi.org/10.17226/2072
NRC. (1995). Measuring poverty—a new approach. The National Academies Press. https://doi.org/10.17226/4759
NRC. (1997a). The Bureau of Transportation Statistics: Priorities for the future. The National Academies Press. https://doi.org/10.17226/5809
NRC. (1997b). Assessing policies for retirement income: Needs for data, research, and models. The National Academies Press. https://doi.org/10.17226/5420
NRC. (1999). Sowing seeds of change: Informing public policy in the economic research service of USDA. The National Academies Press. https://doi.org/10.17226/6320
NRC. (2000a). Small-area income and poverty estimates: Priorities for 2000 and beyond. The National Academies Press. https://doi.org/10.17226/9957
NRC. (2000b). Small-area estimates of school-age children in poverty: Evaluation of current methodology. The National Academies Press. https://doi.org/10.17226/6427
NRC. (2003a). Survey automation: Report and workshop proceedings. The National Academies Press. https://doi.org/10.17226/10695
NRC. (2003b). Protecting participants and facilitating social and behavioral sciences research. The National Academies Press. https://doi.org/10.17226/10695
NRC. (2004a). Measuring research and development expenditures in the U.S. economy. The National Academies Press. https://doi.org/10.17226/11111
NRC. (2004b). Climate data records from environmental satellites. The National Academies Press. https://doi.org/10.17226/10944
NRC. (2004c). Reengineering the 2010 Census: Risks and challenges. The National Academies Press. https://doi.org/10.17226/10959
NRC. (2004d). The 2000 Census: Counting under adversity. The National Academies Press. https://doi.org/10.17226/10907
NRC. (2004e). Eliminating health disparities: Measurement and data needs. The National Academies Press. https://doi.org/10.17226/10979
NRC. (2005). Expanding access to research data: Reconciling risks and opportunities. The National Academies Press. https://doi.org/10.17226/11434
NRC. (2006a). Improving business statistics through interagency data sharing: Summary of a workshop. The National Academies Press. https://doi.org/10.17226/11738
NRC. (2006b). Once, only once, and in the right place: Residence rules in the decennial census. The National Academies Press. https://doi.org/10.17226/11727
NRC. (2007a). Using the American Community Survey: Benefits and challenges. The National Academies Press. https://doi.org/10.17226/11901
NRC. (2007b). Understanding business dynamics: An integrated data system for America’s future. The National Academies Press. https://doi.org/10.17226/11844
NRC. (2008a). Rebuilding the research capacity at HUD. The National Academies Press. https://doi.org/10.17226/12468
NRC. (2008b). Protecting individual privacy in the struggle against terrorists—A framework for program assessment. The National Academies Press. https://doi.org/10.17226/12452
NRC. (2008c). Using the American Community Survey for the National Science Foundation’s Science and Engineering Workforce Statistics program. The National Academies Press. https://doi.org/10.17226/12244
NRC. (2009a). Reengineering the Survey of Income and Program Participation. The National Academies Press. https://doi.org/10.17226/12715
NRC. (2009b). Ensuring the quality, credibility, and relevance of U.S. justice statistics. The National Academies Press. https://doi.org/10.17226/12671
NRC. (2009c). America’s energy future: Electricity from renewable resources: Status, prospects, and impediments. The National Academies Press. https://doi.org/10.17226/12619
NRC. (2010a). National security implications of climate change for U.S. naval forces: Letter report. The National Academies Press. https://doi.org/10.17226/12782
NRC. (2010b). Accounting for health and health care: Approaches to measuring the sources and costs of their improvement. The National Academies Press. https://doi.org/10.17226/12938
NRC. (2010c). Limiting the magnitude of future climate change. The National Academies Press. https://doi.org/10.17226/12785
NRC. (2012a). Medical care economic risk: Measuring financial vulnerability from spending on medical care. The National Academies Press. https://doi.org/10.17226/13525
NRC. (2012b). Effective tracking of building energy use: Improving the commercial buildings and residential energy consumption surveys. The National Academies Press. https://doi.org/10.17226/13360
NRC. (2013a). Review of the research program of the U.S. DRIVE Partnership: Fourth report. The National Academies Press. https://doi.org/10.17226/21725
NRC. (2013b). Nonresponse in social science surveys: A research agenda. The National Academies Press. https://doi.org/10.17226/18293
NRC. (2013c). Benefits, burdens, and prospects of the American Community Survey: Summary of a workshop. The National Academies Press. https://doi.org/10.17226/18259
NRC. (2014). Proposed revisions to the common rule for the protection of human subjects in the behavioral and social sciences. The National Academies Press. https://doi.org/doi:10.17226/18614
National Science and Technology Council. (2023). A framework for federal scientific integrity policy and practice. Scientific Integrity Framework Interagency Working Group. https://www.whitehouse.gov/wp-content/uploads/2023/01/01-2023-Framework-for-Federal-Scientific-Integrity-Policy-and-Practice.pdf
Nelson, A. (2022). Memorandum for the heads of executive departments and agencies: Ensuring free, immediate, and equitable access to federally funded research. U.S. Office of Science and Technology Policy. https://www.whitehouse.gov/wp-content/uploads/2022/08/08-2022-OSTP-Public-access-Memo.pdf
Norwood, J. L. (1975). Should those who produce statistics analyze them? How far should analysis go? An American view. Bulletin of the International Statistical Institute [Proceedings of the 40th Session], 46, 420–432. https://www.isi-web.org/
Norwood, J. L. (1995). Organizing to count: Change in the federal statistical system. The Urban Institute Press. https://catalog.princeton.edu/catalog/SCSB-3263340
Norwood, J. L. (2016). Politics and federal statistics. Statistics and Public Policy, 3(1), 1–8. http://dx.doi.org/10.1080/2330443X.2016.1241061
Office of Management and Budget (OMB). (1978). Statistical policy directive 14: Official poverty measure. https://www.census.gov/topics/income-poverty/poverty/about/history-of-the-poverty-measure/omb-stat-policy-14.html
OMB. (1985). Statistical policy directive 3: Compilation, release, and evaluation of principal federal economic indicators. 50 F.R. 38932. https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/assets/OMB/inforeg/statpolicy/dir_3_fr_09251985.pdf
OMB. (1997a). Statistical policy directive 15: Standards for maintaining, collecting, and presenting federal data on race and ethnicity. 62 F.R. 58782. https://www.gpo.gov/fdsys/pkg/FR-1997-10-30/pdf/97-28653.pdf
OMB. (1997b). Order providing for the confidentiality of statistical information. 62 F.R. 35044. https://www.govinfo.gov/content/pkg/FR-1997-06-27/pdf/FR-1997-06-27.pdf
OMB. (2002). Guidelines for ensuring and maximizing the quality, objectivity, utility, and integrity of information disseminated by federal agencies; Republication. 67 F.R. 8452. https://www.federalregister.gov/documents/2002/02/22/R2-59/guidelines-for-ensuring-and-maximizing-the-quality-objectivity-utility-and-integrity-of-information
OMB. (2005). M-05-03: Final information quality bulletin for peer review. https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/memoranda/2005/m05-03.pdf
OMB. (2006). Statistical policy directive 2: Standards and guidelines for statistical surveys. https://www.whitehouse.gov/wp-content/uploads/2021/04/standards_stat_surveys.pdf
OMB. (2007). Implementation guidance for Title V of the E-Government Act, Confidential Information Protection and Statistical Efficiency Act of 2002 (CIPSEA). 72 F.R. 33362. https://www.federalregister.gov/documents/2007/06/15/E7-11542/implementation-guidance-for-title-v-of-the-e-government-act-confidential-information-protection-and
OMB. (2008). Statistical policy directive 4: Release and dissemination of statistical products produced by federal statistical agencies. 73 F.R. 12622. https://www.gpo.gov/fdsys/pkg/FR-2008-03-07/pdf/E8-4570.pdf
OMB. (2013a). Department of Health and Human Services: Centers for Disease Control and Prevention: Statement of organization, functions, and delegations of authority. 78 F.R. 70049. https://www.govinfo.gov/content/pkg/FR-2013-11-22/pdf/2013-27088.pdf
OMB. (2013b). M-13-13: Open data policy—managing information as an asset. https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/memoranda/2013/m-13-13.pdf
OMB. (2014a). M-14-06: Guidance for providing and using administrative data for statistical purposes. https://obamawhitehouse.archives.gov/sites/default/files/omb/memoranda/2014/m-14-06.pdf
OMB. (2014b). Statistical policy directive 1: Fundamental responsibilities of federal statistical agencies and recognized statistical units. 79 F.R. 71610. https://www.federalregister.gov/documents/2014/12/02/2014-28326/statistical-policy-directive-no-1-fundamental-responsibilities-of-federal-statistical-agencies-and
OMB. (2015). M-15-15: Guidance on improving statisical activities through interagency collaboration. https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/memoranda/2015/m-15-15.pdf
OMB. (2016a). Standards for maintaining, collecting, and presenting federal data on race and ethnicity. 81 F.R. 67398. https://www.federalregister.gov/documents/2016/09/30/2016-23672/standards-for-maintaining-collecting-and-presenting-federal-data-on-race-and-ethnicity
OMB. (2016b). M-16-21: Federal source code policy: Achieving efficiency, transparency, and innovation through reusable and open source software. https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/memoranda/2016/m_16_21.pdf
OMB. (2016c). Statistical policy directive 2 (addendum): Standards and guidelines for cognitive interviews. 81 F.R. 70586. https://www.federalregister.gov/documents/2016/10/12/2016-24607/statistical-policy-directive-no-2-standards-and-guidelines-for-statistical-surveys-addendum
OMB. (2016d). Guidance on agency survey and statistical information collections—questions and answers when designing surveys for information collections. https://www.whitehouse.gov/wp-content/uploads/legacy_drupal_files/omb/assets/OMB/inforeg/pmc_survey_guidance_2006.pdf
OMB. (2016e). Statistical policy directive 4 (addendum): Release and dissemination of statistical products produced by federal statistical agencies and recognized statistical units [adding section 10, performance review]. 81 F.R. 71538. https://www.federalregister.gov/d/2016-25049
OMB. (2016f). Statistical policy directive no. 2: Standards and guidelines for statistical surveys. 81 F.R. 70586. https://www.federalregister.gov/d/2016-24607
OMB. (2017a). Statistical policy directive 10: Standard occupational classification. 82 F.R. 56271. https://www.gpo.gov/fdsys/pkg/FR-2017-11-28/pdf/2017-25622.pdf
OMB. (2017b). Proposals from the Federal Interagency Working Group for revision of the standards for maintaining, collecting, and presenting federal data on race and ethnicity. 82 F.R. 12242. https://www.federalregister.gov/documents/2017/03/01/2017-03973/proposals-from-the-federal-interagency-working-group-for-revision-of-the-standards-for-maintaining
OMB. (2019a). M-19-15: Improving implementation of the Information Quality Act. https://www.whitehouse.gov/wp-content/uploads/2019/06/M-19-18.pdf
OMB. (2019b). M-19-23: Phase 1 implementation of the Foundations for Evidence-Based Policymaking Act of 2018: Learning agendas, personnel, and planning guidance. https://www.whitehouse.gov/wp-content/uploads/2019/07/m-19-23.pdf
OMB. (2019c). M-19-18: Federal data strategy—a framework for consistency. https://www.whitehouse.gov/wp-content/uploads/2019/06/M-19-18.pdf
OMB. (2020a). M-20-12: Phase 4 implementation of the Foundations for Evidence-Based Policymaking Act of 2018: Program evaluation standards and practices. https://www.whitehouse.gov/wp-content/uploads/2020/03/M-20-12.pdf
OMB. (2020b). M-20-12 Phase 4 implementation of the Foundations for Evidence-Based Policymaking Act of 2018: Program evaluation standards and practices. https://www.whitehouse.gov/wp-content/uploads/2020/03/M-20-12.pdf
OMB. (2021a). Federal data strategy. https://strategy.data.gov/assets/docs/2021-Federal-Data-Strategy-Action-Plan.pdf
OMB. (2021b). 2020 standards for delineating core based statistical areas. 86 F.R. 37770. https://www.federalregister.gov/documents/2021/07/16/2021-15159/2020-standards-for-delineating-core-based-statistical-areas
OMB. (2022a). M-23-04: Establishment of standard application process requirements on recognized statistical agencies and units. https://www.whitehouse.gov/wp-content/uploads/2022/12/M-23-04.pdf
OMB. (2022b). North American Industry Classification System—revision for 2022; Update of Statistical Policy Directive No. 8, North American industry classification system: Classification of establishments; And elimination of Statistical Policy Directive No. 9, standard industrial classification of enterprises. 86 F.R. 72277. https://www.govinfo.gov/content/pkg/FR-2021-12-21/pdf/2021-27536.pdf
OMB. (2023a). OMB Bulletin No. 23-01: Revised delineations of metropolitan statistical areas, micropolitan statistical areas, and combined statistical areas, and guidance on uses of the delineations of these areas. https://www.whitehouse.gov/wp-content/uploads/2023/07/OMB-Bulletin-23-01.pdf
OMB. (2023b). Statistical programs of the United States government: Fiscal years 2021/2022. https://www.whitehouse.gov/wp-content/uploads/2024/02/statistical-programs-20212022.pdf
OMB. (2023c). National strategy to develop statistics for environmental economic decisions. https://www.whitehouse.gov/wp-content/uploads/2023/01/Natural-Capital-Accounting-Strategy-final.pdf
OMB. (2023d). Notice of proposed rulemaking on the fundamental responsibilities of recognized statistical agencies and units. 88 F.R. 56708. https://www.federalregister.gov/documents/2023/08/18/2023-17664/fundamental-responsibilities-of-recognized-statistical-agencies-and-units
OMB. (2023e). Initial proposals for updating OMB’s race and ethnicity statistical standards. 88 F.R. 5375. https://www.govinfo.gov/content/pkg/FR-2023-01-27/pdf/2023-01635.pdf
OMB. (2023f). Improving implementation of the Information Quality Act: Frequently asked questions. https://www.whitehouse.gov/wp-content/uploads/2023/12/FAQs-Implemention-of-the-Information-Quality-Act-final.pdf
OMB. (2024a). Analytical perspectives. https://www.whitehouse.gov/wp-content/uploads/2024/03/ap_10_statistics_fy2025.pdf
OMB. (2024b). Fundamental responsibilities of recognized statistical agencies and units. 89 F.R. 82453. https://www.federalregister.gov/documents/2024/10/11/2024-23536/fundamental-responsibilities-of-recognized-statistical-agencies-and-units
OMB. (2024c). Leveraging federal statistics to strengthen evidence-based decision-making. https://www.whitehouse.gov/wp-content/uploads/2024/03/ap_10_statistics_fy2025.pdf
OMB. (2024d). Statistical policy directive 3: Compilation, release, and evaluation of principal federal economic indicators. 89 F.R. 11873. https://www.govinfo.gov/content/pkg/FR2024-02-15/pdf/2024-02972.pdf
OMB. (2024e). Statistical officials: Highlights and achievements, 2023. https://www.whitehouse.gov/wp-content/uploads/2024/03/ap_10_supp_fy2025.pdf
OMB. (2024f). M-24-10: Advancing governance, innovation, and risk management for agency use of artificial intelligence. https://www.whitehouse.gov/wp-content/uploads/2024/03/M-24-10-Advancing-Governance-Innovation-and-Risk-Management-for-Agency-Use-of-Artificial-Intelligence.pdf
Office of Science and Technology Policy (OSTP). (2010). Scientific integrity. https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/scientific-integrity-memo-12172010.pdf
OSTP. (2013). Increasing access to the results of federally funded scientific research. https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/ostp_public_access_memo_2013.pdf
OSTP. (2022). Blueprint for an AI bill of rights. https://www.whitehouse.gov/wp-content/uploads/2022/10/Blueprint-for-an-AI-Bill-of-Rights.pdf
OSTP. (2023a). Strengthening and democratizing the U.S. artificial intelligence innovation ecosystem: An implementation plan for a national artificial intelligence research resource. https://www.ai.gov/wp-content/uploads/2023/01/NAIRR-TF-Final-Report-2023.pdf
OSTP. (2023b). Policy memorandum on scientific integrity. https://www.whitehouse.gov/wp-content/uploads/2023/06/OSTP-SCIENTIFIC-INTEGRITY-POLICY.pdf
OSTP. (2024g). Revisions to OMB’s statistical policy directive no. 15: Standards for maintaining, collecting, and presenting federal data on race and ethnicity. 89 F.R. 22182. https://www.federalregister.gov/documents/2024/03/29/2024-06469/revisions-to-ombs-statistical-policy-directive-no-15-standards-for-maintaining-collecting-and
Paperwork Reduction Act, Pub. Law 96-511, 94 Stat. 2812. (1980). https://uscode.house.gov/statutes/pl/96/511.pdf
Paperwork Reduction Act, Pub. Law 99-500, § 146. (1986).
Paperwork Reduction Act, Pub. Law 99-591, § 101 (m) 100 Stat. 3341-308, 3341-335 (1986). https://www.govinfo.gov/content/pkg/STATUTE-100/pdf/STATUTE-100-Pg3341.pdf
Paperwork Reduction Act, Pub. L. No. 104-13, 109 Stat. 163. (1995). https://www.govinfo.gov/content/pkg/PLAW-104publ13/html/PLAW-104publ13.htm
Park, J., & Tractenberg, R. E. (2023). How do ASA ethical guidelines support U.S. guidelines for official statistics? Ethics International Press. https://arxiv.org/pdf/2309.07180
Prell, M., Chapman, C., Adeshiyan, S., Fixler, D., Garin, T., Mirel, L. B., & Phipps, P. (2019). Transparent reporting for integrated data quality: Practices of seven federal statistical agencies. Federal Committee on Statistical Methodology. https://nces.ed.gov/FCSM/pdf/Transparent_Reporting_FCSM_19.01.pdf#:~:text=This%20report%20provides%20results%20from%20the
Privacy Act of 1974, Pub. L. No. 93-579, 88 Stat. 1896. (1974). https://www.govinfo.gov/content/pkg/STATUTE-88/pdf/STATUTE-88-Pg1896.pdf
Pub. Law 104-191, 110 Stat. 1936. (1996). https://www.congress.gov/104/plaws/publ191/PLAW-104publ191.pdf
Pub. Law 114-94, 130 Stat. 538. (2016). https://www.congress.gov/114/plaws/publ185/PLAW-114publ185.pdf
Reamer, A. D. (2014). Stumbling into the Great Recession: How and why GDP estimates kept economists and policymakers in the dark. The George Washington Institute of Public Policy. https://gwipp.gwu.edu/sites/g/files/zaxdzs2181/f/downloads/Reamer_GDP_Research_Note_04-25-14.pdf
Royal Statistical Society. (2014). Code of conduct. https://rss.org.uk/RSS/media/File-library/About/2019/RSS-Code-of-Conduct-2014.pdf
Ryten, J. (1990). Statistical organization criteria for inter-country comparisons and their application to Canada. Journal of Official Statistics, 6(3), 319–332. https://www.proquest.com/docview/1266811482?pq-origsite=gscholar&fromopenview=true&sourcetype=Scholarly%20Journals
Science, State, Justice, Commerce, and Related Agencies Appropriations Act, Pub. L. No. 109-108, 119 Stat. 2308. (2005). https://www.congress.gov/109/plaws/publ108/PLAW-109publ108.pdf
Temporary Assignments Under the Intergovernmental Personnel Act, 5 C.F.R. Part 334. (2024). https://www.ecfr.gov/current/title-5/chapter-I/subchapter-B/part-334
Title 42—The public health and welfare, 5137 § 1885d. (2024). https://statecodesfiles.justia.com/us/2022/title-42/chapter-16/sec-1885d/sec-1885d.pdf?ts=1722330151
Title 49—Transportation, 350 § 49 § 6302. (2024). https://statecodesfiles.justia.com/us/2018/title-49/subtitle-iii/chapter-63/sec-6302/sec-6302.pdf?ts=1588215779
Tractenberg, R. E. (2020). Concordance of professional ethical practice standards for the domain of data science: A white paper. Open Archive of the Social Sciences (SocArXiv). https://osf.io/preprints/socarxiv/p7rj2
Tractenberg, R. E. (2022a). Ethical reasoning for a data-centered world. Ethics International Press. https://ethicalreasoning.org/books/
Tractenberg, R. E. (2022b). Ethical practice in statistics and data science. Ethics International Press. https://ethicalreasoning.org/books/
Tractenberg, R. E., & Park, J. (2023). How does international guidance for statistical practice align with the ASA Ethical Guidelines? Ethics International Press. https://arxiv.org/pdf/2309.08713
Triplett, J. (1991). The federal statistical system’s response to emerging data needs. Journal of Economic and Social Measurement, 17(3-4), 155–201. https://content.iospress.com/articles/journal-of-economic-and-social-measurement/jem17-3-4-03#:~:text=The%20Federal%20Statistical%20System’s%20Response%20to
United Nations Statistical Commission. (2014). Fundamental principles of official statistics. United Nations. https://unstats.un.org/unsd/dnss/gp/FP-New-E.pdf
Voting Rights Act of 1965, Pub. L. No. 89-110. (1965). https://www.govinfo.gov/content/pkg/STATUTE-79/pdf/STATUTE-79-Pg437.pdf
Young, L. J. (2019). Agricultural crop forecasting for large geographical areas. Annual Review of Statistics and Its Application, 6, 173–196. https://doi.org/10.1146/annurev-statistics-030718-105002
Young, L. J., & Chen, L. (2022). Using small area estimation to produce official statistics. Stats, 5(3), 881–897. https://www.mdpi.com/2571-905X/5/3/51
