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Principles and Practices for a Federal Statistical Agency: Seventh Edition (2021)

Chapter: APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics

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Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
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APPENDIX C
Some International Frameworks and Guidance Relevant for Federal Statistics

National statistical offices around the world face many of the same issues as federal statistical agencies. Although the United States participates in a wide variety international statistical work, including through the United Nations Statistical Commission and the Organisation for Economic and Co-operation and Development Statistics and Data Directorate, the decentralized nature of the U.S. federal statistical system has often meant that many staff and even entire agencies or programs in the system are unaware of relevant international work. This Appendix is intended to provide a general introduction to some key resources developed by international entities that could be useful for federal statistical agencies.

UNITED NATIONS FUNDAMENTAL PRINCIPLES OF OFFICIAL STATISTICS

The United Nations Statistics Division website notes that the need for a set of principles governing official statistics became apparent at the end of the 1980s when countries in Central Europe began to change from centrally planned economies to market-oriented democracies. It was essential to ensure that national statistical systems in such countries would be able to produce appropriate and reliable data that adhered to certain professional and scientific standards.

The Conference of European Statisticians developed and adopted the Fundamental Principles of Official Statistics in 1991, and these were subsequently adopted by the United Nations Statistical Commission in 1994

Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×

as the United Nations Fundamental Principles of Official Statistics. In 2014, the U.N. General Assembly endorsed the following Fundamental Principles of Official Statistics:78

Principle 1. Official statistics provide an indispensable element in the information system of a democratic society, serving the Government, the economy and the public with data about the economic, demographic, social and environmental situation. To this end, official statistics that meet the test of practical utility are to be compiled and made available on an impartial basis by official statistical agencies to honor citizens’ entitlement to public information.

Principle 2. To retain trust in official statistics, the statistical agencies need to decide according to strictly professional considerations, including scientific principles and professional ethics, on the methods and procedures for the collection, processing, storage and presentation of statistical data.

Principle 3. To facilitate a correct interpretation of the data, the statistical agencies are to present information according to scientific standards on the sources, methods and procedures of the statistics.

Principle 4. The statistical agencies are entitled to comment on erroneous interpretation and misuse of statistics.

Principle 5. Data for statistical purposes may be drawn from all types of sources, be they statistical surveys or administrative records. Statistical agencies are to choose the source with regard to quality, timeliness, costs and the burden on respondents.

Principle 6. Individual data collected by statistical agencies for statistical compilation, whether they refer to natural or legal persons, are to be strictly confidential and used exclusively for statistical purposes.

___________________

78 See https://unstats.un.org/fpos/. [February 2021]

Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×

Principle 7. The laws, regulations and measures under which the statistical systems operate are to be made public.

Principle 8. Coordination among statistical agencies within countries is essential to achieve consistency and efficiency in the statistical system.

Principle 9. The use by statistical agencies in each country of international concepts, classifications and methods promotes the consistency and efficiency of statistical systems at all official levels.

Principle 10. Bilateral and multilateral cooperation in statistics contributes to the improvement of systems of official statistics in all countries.

In 2015, the U.N. Statistical Commission issued implementation guidelines for the Fundamental Principles.79 These guidelines list several actions or activities that a statistical agency is advised to take into account when aiming to improve the practical and effective implementation of a certain principle or when developing a certain principle further. Concrete as well as practice-orientated examples (good practices) complement these recommended actions. Part II of the implementation guidelines contains recommendations on how to ensure a high level of independence for national statistical systems. These guidelines differentiate between various forms of independence (such as institutional, professional, and scientific independence) and recommend good practices in order to ensure independence.

THE COMMON QUALITY FRAMEWORK OF THE EUROPEAN STATISTICAL SYSTEM

The common quality framework of the European Statistical System is composed of the European Statistics Code of Practice, the Quality Assurance Framework of the European Statistical System, and general quality management principles (such as continuous interaction with users, commitment of leadership, partnership, staff satisfaction, continuous improvement, integration and harmonization). The European Statistics Code of Practice is the cornerstone of the common quality framework

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79 See https://unstats.un.org/fpos/implementation/. [February 2021]

Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×

of the European Statistical System. It is a self-regulatory instrument and is based on 16 principles covering the institutional environment, statistical processes, and statistical outputs.80 A set of indicators of best practices and standards for each of the principles provides guidance and reference for reviewing the implementation of the Code of Practice, increasing transparency within the European Statistical System.

Institutional Environment

Institutional and organizational factors have a significant influence on the effectiveness and credibility of a statistical authority developing, producing, and disseminating European statistics. The relevant principles are professional independence, coordination and cooperation, mandate for data collection, adequacy of resources, quality commitment, statistical confidentiality, impartiality, and objectivity.

Principle 1: Professional Independence. Professional independence of statistical authorities from other policy, regulatory or administrative departments and bodies, as well as from private sector operators, ensures the credibility of European Statistics.

Principle 1b: Coordination and Cooperation. National Statistical Institutes and Eurostat ensure the coordination of all activities for the development, production, and dissemination of European Statistics at the level of the national statistical system and the European Statistical System, respectively. Statistical authorities actively cooperate within the partnership of the European Statistical System, so as to ensure the development, production and dissemination of European statistics.

Principle 2: Mandate for Data Collection and Access to Data. Statistical authorities have a clear legal mandate to collect and access information from multiple data sources

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80 European Statistics Code of Practice: https://ec.europa.eu/eurostat/web/products-catalogues/-/KS-02-18-142. [February 2021]

Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×

for European statistical purposes. Administrations, enterprises and households, and the public at large may be compelled by law to allow access to or deliver data for European statistical purposes at the request of statistical authorities.

Principle 3: Adequacy of Resources. The resources available to statistical authorities are sufficient to meet European Statistics requirements.

Principle 4: Commitment to Quality. Statistical authorities are committed to quality. They systematically and regularly identify strengths and weaknesses to continuously improve process and output quality.

Principle 5: Statistical Confidentiality and Data Protection. The privacy of data providers, the confidentiality of the information they provide, its use only for statistical purposes, and the security of data are absolutely guaranteed.

Principle 6: Impartiality and Objectivity. Statistical authorities develop, produce, and disseminate European Statistics respecting scientific independence and in an objective, professional, and transparent manner in which all users are treated equitably.

Statistical Processes

European and other international standards, guidelines, and good practices are fully observed in the statistical processes used by the statistical authorities to develop, produce, and disseminate European Statistics, while constantly striving for innovation. The credibility of the statistics is enhanced by a reputation for good management and efficiency. The relevant principles are sound methodology, appropriate statistical procedures, non-excessive burden on respondents, and cost effectiveness.

Principle 7: Sound Methodology. Sound Methodology underpins quality statistics. This requires adequate tools, procedures, and expertise.

Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×

Principle 8: Appropriate Statistical Procedures. Appropriate statistical procedures implemented throughout the statistical processes underpin quality statistics.

Principle 9: Non-excessive Burden on Respondents. The response burden is proportionate to the needs of the users and is not excessive for respondents. The statistical authorities monitor the response burden and set targets for its reduction over time.

Principle 10: Cost effectiveness. Resources are used effectively.

Statistical Output

Available statistics meet users’ needs. Statistics comply with the European quality standards and serve the needs of European institutions, governments, research institutions, business concerns, and the public generally. Output quality is measured by the extent to which the statistics are relevant, accurate and reliable, timely, coherent, comparable across regions and countries, and readily accessible by users, i.e., the Principles of Statistical Output.

Principle 11: Relevance. European Statistics meet the needs of users.

Principle 12: Accuracy and Reliability. European Statistics accurately and reliably portray reality.

Principle 13: Timeliness and Punctuality. European Statistics are released in a timely and punctual manner.

Principle 14: Coherence and Comparability. European Statistics are consistent internally, over time and comparable between regions and countries; it is possible to combine and make joint use of related data from different data sources.

Principle 15: Accessibility and Clarity. European Statistics are presented in a clear and understandable form, released in a suitable and convenient manner, available and accessible on an impartial basis with supporting metadata and guidance. [pages 4-54]

Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×

QUALITY FRAMEWORK FOR OECD STATISTICAL ACTIVITIES

Quality Dimensions

The OECD Quality Framework has four elements:

  1. A definition of quality and its dimensions;
  2. A procedure for assuring the quality of proposed new statistical activities;
  3. A procedure for evaluating the quality of existing statistical activities on a regular basis; and
  4. A set of broad principles on which OECD statistical activities are to be conducted and quality guidelines covering all phases of the statistical production process.81

Quality

Quality is defined as “fitness for use” in terms of user needs. This definition is broader than has been customarily used in the past when quality was equated with accuracy. It is now generally recognized that there are other important dimensions. Even if data is accurate, they cannot be said to be of good quality if they are produced too late to be useful, or cannot be easily accessed, or appear to conflict with other data. Thus, quality is viewed as a multifaceted concept. The quality characteristics of most importance depend on user perspectives, needs and priorities, which vary across groups of users.

Relevance

The relevance of data products is a qualitative assessment of the value contributed by these data. Value is characterized by the degree to which the data serve to address the purposes for which they are sought by users. It depends upon both the coverage of the required topics and the use of appropriate concepts. Value is further characterized by the merit of users’ purposes in terms of the OECD mandate, the agreements with member countries, and the opportunity costs of producing the data.

___________________

81 See http://www.oecd.org/sdd/qualityframeworkforoecdstatisticalactivities.htm. [February 2021]

Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×

Accuracy

The accuracy of data products is the degree to which the data correctly estimate or describe the quantities or characteristics they are designed to measure. Accuracy refers to the closeness between the values provided and the (unknown) true values. Accuracy has many attributes, and in practical terms there is no single aggregate or overall measure of it. Of necessity these attributes are typically measured or described in terms of the error, or the potential significance of error, introduced through individual sources.

Credibility

The credibility of data products refers to the confidence that users place in those products based simply on their image of the data producer, i.e., the brand image. The confidence of users is built over time. One important aspect is trust in the objectivity of the data. This implies that the data are perceived to be produced professionally in accordance with appropriate statistical standards and that policies and practices are transparent. For example, data are not manipulated nor their release timed in response to political pressure.

Timeliness

The timeliness of data products reflects the length of time between their availability and the event or phenomenon they describe, but considered in the context of the time period that permits the information to be of value and still acted upon. The concept applies equally to short-term or structural data; the only difference is the timeframe.

Accessibility

The accessibility of data products reflects how readily the data can be located and accessed from within OECD data holdings. The range of different users leads to such considerations as multiple dissemination formats and selective presentation of metadata. Thus, accessibility

Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×

includes the suitability of the form in which the data are available, the media of dissemination, and the availability of metadata and user support services. It also includes the affordability of the data to users in relation to their value to them and whether the user has reasonable opportunity to know that the data are available and how to access them.

Interpretability

The interpretability of data products reflects the ease with which the user may understand and properly use and analyze the data. The adequacy of the definitions of concepts, target populations, variables, and terminology underlying the data, and the information describing the limitations of the data, if any, largely determines the degree of interpretability.

Coherence

The coherence of data products reflects the degree to which they are logically connected and mutually consistent. Coherence implies that the same term should not be used without explanation for different concepts or data items; that different terms should not be used without explanation for the same concept or data item; and that variations in methodology that might affect data values should not be made without explanation. Coherence in its loosest sense implies that the data are “at least reconcilable.” For example, if two data series purporting to cover the same phenomena differ, the differences in time of recording, valuation, and coverage should be identified so that the series can be reconciled. Coherence has four important subdimensions: within a dataset, across datasets, over time, and across countries.

Cost-efficiency

The cost-efficiency with which a product is produced is a measure of the costs and provider burden relative to the output. Provider burden is a cost that happens to be borne by the provider, but is a cost nevertheless. Whilst

Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×

the OECD does not regard cost-efficiency as a dimension of quality, it is a factor that must be taken into account in any analysis of quality as it can affect quality in all dimensions. If a product can be produced more efficiently with the same quality, then resources released can be used to improve the quality of that product or other products.

Core Values for OECD Statistics

The main principles of OECD statistical activities are as follows:82

  1. OECD statistics are compiled and made available on an impartial basis. OECD statistics are produced according to strictly professional considerations, including scientific principles and professional ethics with regard to methods and procedures used for the collection, processing, storage and dissemination of statistical data.
  2. The OECD presents statistical information according to scientific standards on the sources, methods, and procedures adopted to produce its statistics.
  3. Individual data collected by the OECD for statistical compilation are considered to be strictly confidential and used exclusively for statistical purposes. Specific measures are taken to ensure the full protection of confidential data from any potential disclosure.
  4. Internal rules and measures under which the OECD statistical system operates are made public.
  5. The OECD is committed to carrying out its statistical activities in co-ordination with national statistical agencies and with other international organisations.
  6. The OECD is committed to developing bilateral and multilateral co-operation in statistics in order to contribute to the development of systems of official statistics in all countries.
  7. Within the constraints of resource availability, OECD data products are of the best possible overall quality

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82 Taken from http://www.oecd.org/sdd/qualityframeworkforoecdstatisticalactivities.htm. [February 2021]

Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×

    in terms of each of the seven quality dimensions outlined in the Organisation’s Quality Framework. Effort involved in assuring quality is commensurate with the scale of the statistical activity, the purpose of the activity and its frequency (i.e. whether it is intended to be repeated regularly or occasionally, or is one-off). [pages 6-12]

U.K. CODE OF PRACTICE FOR STATISTICS83

The framework for the U.K. Code of Practice for Statistics is based on three pillars:

  • Trustworthiness is about having confidence in the people and organizations that produce statistics and data.
  • Quality is about using data and methods that produce assured statistics.
  • Value is about producing statistics that support society’s needs for information.

Each pillar contains a number of principles and detailed practices that apply when producing and releasing official statistics.

Trustworthiness: Confidence in the people and organisations that produce statistics and data

Trustworthiness is a product of the people, systems and processes within organizations that enable and support the production of statistics and data. Trustworthiness comes from the organization that produces statistics and data being well led, well managed and open, and the people who work there being impartial and skilled in what they do.

T1: Honesty and integrity: People in organizations that release statistics should be truthful, impartial and independent, and meet consistent standards of behavior that reflect the wider public good.

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83 Taken from https://www.statisticsauthority.gov.uk/code-of-practice/the-code/. [February 2021]

Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×

T2: Independent decision making and leadership: Organizations should assign a Chief Statistician/Head of Profession for Statistics who upholds and advocates the standards of the Code, strives to improve statistics and data for the public good, and challenges their inappropriate use.

T3: Orderly release: Organizations should commit to releasing their statistics in an open and transparent manner that promotes public confidence.

T4: Transparent processes and management: Organizations should have effective business processes and appropriate resources to support their statistical functions and be open about their plans, priorities and progress.

T5: Professional capability: People producing statistics should be appropriately skilled, trained and supported in their roles and professional development.

T6: Data governance: Organizations should look after people’s information securely and manage data in ways that are consistent with relevant legislation and serve the public good.

Quality: Data and methods that produce assured statistics

Quality means that statistics fit their intended uses, are based on appropriate data and methods, and are not materially misleading. Quality requires skilled professional judgement about collecting, preparing, analyzing and publishing statistics and data in ways that meet the needs of people who want to use the statistics.

Q1: Suitable data sources: Statistics should be based on the most appropriate data to meet intended uses. The impact of any data limitations for use should be assessed, minimized, and explained.

Q2: Sound methods: Producers of statistics and data should use the best available methods and recognised standards, and be open about their decisions.

Q3: Assured quality: Producers of statistics and data should explain clearly how they assure themselves that statistics and data are accurate, reliable, coherent, and timely.

Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×

Value: Statistics that support society’s needs for information

Value means that the statistics and data are useful, easy to access, remain relevant, and support understanding of important issues. Value includes improving existing statistics and creating new ones through discussion and collaboration with stakeholders, and being responsible and efficient in the collection, sharing and use of statistical information.

V1: Relevance to users: Users of statistics and data should be at the center of statistical production; their needs should be understood, their views sought and acted on, and their use of statistics supported.

V2: Accessibility: Statistics and data should be equally available to all, not given to some people before others. They should be published at a sufficient level of detail and remain publicly available.

V3: Clarity and insight: Statistics and data should be presented clearly, explained meaningfully, and provide authoritative insights that serve the public good.

V4: Innovation and improvement: Statistics producers should be creative and motivated to improve statistics and data, recognizing the potential to harness technological advances for the development of all parts of the production and dissemination process.

V5: Efficiency and proportionality: Statistics and data should be published in forms that enable their reuse. Producers should use existing data wherever possible and only ask for more where justified. [pages 17-23]

GENERIC STATISTICAL BUSINESS PROCESS MODEL

The Generic Statistical Business Process Model (GSBPM) of the United Nations Economic Commission for Europe was first developed in 2008 and most recently updated in 2019 (version 5.1). The model is designed to enable statistical agencies to describe production processes in a coherent

Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×

way, compare processes within and among organizations, and make better decisions on production systems and allocation of resources.84 The GSBPM (shown in Figure C-1) describes and defines the set of business processes needed to produce official statistics. It provides a standard framework and harmonized terminology to help statistical organizations modernize their statistical production processes, as well as to share methods and components. The GSBPM can also be used for integrating data and metadata standards, as a template for process documentation, for harmonizing statistical computing infrastructures, and to provide a framework for process quality assessment and improvement.85

___________________

84 See UNECE High-Level Group for the Modernisation of Official Statistics (2013).

85 For more information, see: https://statswiki.unece.org/display/GSBPM/GSBPM+v5.1 [February 2021].

Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×
Image
FIGURE C-1 Generic Statistical Business Process Model.
SOURCE: United Nations Economic Commission for Europe (UNECE), on behalf of the international statistical community. Version 5.1 January 2019 Available: https://statswiki.unece.org/display/GSBPM/Generic+Statistical+Business+Process+Model.
Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×

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Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×
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Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×
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×
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×
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×
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×
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×
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×
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Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×
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×
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×
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Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
×
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Suggested Citation:"APPENDIX C: Some International Frameworks and Guidance Relevant for Federal Statistics." National Academies of Sciences, Engineering, and Medicine. 2021. Principles and Practices for a Federal Statistical Agency: Seventh Edition. Washington, DC: The National Academies Press. doi: 10.17226/25885.
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Government statistics are widely used to inform decisions by policymakers, program administrators, businesses and other organizations as well as households and the general public. Principles and Practices for a Federal Statistical Agency, Seventh Edition will assist statistical agencies and units, as well as other agencies engaged in statistical activities, to carry out their responsibilities to provide accurate, timely, relevant, and objective information for public and policy use. This report will also inform legislative and executive branch decision makers, data users, and others about the characteristics of statistical agencies that enable them to serve the public good.

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