The fifth edition of Principles and Practices for a Federal Statistical Agency from the National Research Council’s Committee on National Statistics (CNSTAT) was publicly released May 8. P&P (as it is known) describes four fundamental principles and recommends 13 practices that best position a federal statistical agency to provide accurate and credible statistical information to policymakers and the public.
The four principles are the following:
- Relevance to policy issues
- Credibility among data users
- Trust among data providers
- Independence from political and other undue external influence
The practices include a clearly defined and well-accepted mission, necessary authority to protect independence, continual development of more useful data, openness about sources and limitations of the data provided, wide dissemination of data, cooperation with data users, respect for the privacy and autonomy of data providers, protection of the confidentiality of data providers’ information, an active research program, professional advancement of staff, a strong internal and external evaluation program, and coordination and collaboration with other statistical agencies. P&P is revised every four years so it is current at the beginning of each presidential administration and reflects changes in laws and regulations.
The report stresses the importance of producing transparent data, independent from political and other undue external influence, and making these data easily accessible. The report also emphasizes that statistical agencies need to actively seek new ways of acquiring information, such as from administrative records and credible Internet sources that may provide timely, cost-effective information. Read more about the CNSTAT project to produce the fifth edition and access a “highlights” leaflet. Read the full text of the fifth edition, which is available for download in PDF.
openness about sources and limitations of the data provided,: this point i feel are not applied very well, and its very important for the user. And most be a compromise: be always caring about how to do in a better way the entire statistic process. Always be in a meeting about reflextion on what had made and which will be the correctives.