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Trust in official statistics – and dissemination policies and practices

11.2. Trust in official statistics – and dissemination policies and practices.

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Trust in official statistics – and dissemination policies and practices

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  1. 11.2 Trust in official statistics – and dissemination policies and practices Presentation given in Yalta, Ukraine, by Mr Jan Byfuglien, Statistics Norway,at the Joint Management Seminar on Global Assessments in September 2009, organized by UNECE, EFTA and EurostatPresented at the Training Workshop on Disseminating MDG Indicators and Statistical Information Astana, Kazakhstan, 23-25 November 2009 By Mr Petteri Baer, Regional Adviser, UNECE

  2. Introduction • Trust is a cornerstone for National Statistical institutes • Dissemination policies and practices are important elements in building the public image - and thus trust • This presentation will discuss some issues related to measurement, building – and destruction of trust

  3. Some key elements of trust and trust-building (Fellegi 2004*): • Structural factors: • Legislative basis • The position of the head • Equal access to statistical information… • Statistical factors: • Broad user dialogue and transparent programming • Professional methods, competent staff and high product quality • Respondent privacy • Professional dissemination, analysis and documentation… • Reputational factors • Transparent and user oriented dissemination policy….. * Maintaining the credibility of official statistics. Conference of European Statisticians, CES/2004/11.

  4. What makes official statistics trusted by users? (Heinrich Brüngger 2007*): • Trust in results and products of official statistics • Relevance, quality, accessibility ….. • Trust in institutions that act as producers • Integrity, professionalism, impartiality, transparency about methods and sources… • Trust in the institutional set-up for official statistics • Legal framework, professional independence, appointment/dismissal of DG *Joint EFTA/ECE/SSCU Seminar Kiev 2007

  5. Trust in public statistics should also be of vital importance for the government: The UK case*: • A survey in 2005 identified that • Only 17 per cent thought that statistics were produced without the interference from government • Only 31 per cent felt that government figures were accurate • 59 per cent thought that the government used statistics dishonestly • The most common reason for thinking statistics inaccurate was the perception that statistics was manipulated for political purposes, or that they were misrepresented by politicians and media *Monitoring and Improving Public Trust in Official Statistics: The United Kingdom example. Karen Dunnel, National Statistician, UK. OECD Committee on Statistics June 2008

  6. A model for building trust (UK)

  7. Four main strands to improve confidence (UK): • Improve communication infrastructure and capability • Develop and maintain effective relationship with opinion formers • Modernise product range • Continue to invest in quality

  8. Trust: long time to build, quickly destroyed External review Relevance User orientation Integrity Confidentiality Independence Political bias Professionalism Wrong figures Proper legal basis Misuse of microdata

  9. Trust can be quickly destroyed: • For instance by suspicion of political pressure to improve figures – such as the case in Argentina related to CPI:

  10. Break of confidentiality. The US case* • Second War Powers Act passed in 1942 authorized the release of any census (micro) data to any US Federal agency if needed ”for use in connection with the conduct of war” • Several disclosures of microdata took place, including data used for internment of Japanese • The Census Bureau since the repeal of the act in 1947, has a strong legal basis and a good record for protecting statistical confidentiality • However, the issue is still alive: • The Patriot Act after the 9/11 attack, has some similar provisions • Some citizens object to the census because of fear of misuse * Census Confidentiality under the Second War Powers Act (1942-1947). W. Seltzer & M. Anderson. 2007

  11. Credibility of statistics a concern in many countries: The China case

  12. Measurement of ’trust’: Percentage with ’very good’ or ’fairly good’ total impression of Statistics Norway.

  13. Percentage with ’very good’ or ’fairly good’ impression of openness and information of different agencies. 2008 (SSB- Statistics Norway)

  14. A potential threat to misuse of microdata: unclear borderline between official statistics and administrative data • Use of administrative data for statistical purposes is important and growing • NSIs has often had an active role in the development of administrative registers (as has been the case in Norway) • However, it is very important to ensure clear formal and practical procedures to ensure that the NSI cannot be accused of disclosing microdata: • Official statistics: Statistics produced by public authorities based on well defined principles for wide dissemination and usage (aggregated) • Administrative data: Data collection based on specific administrative laws to serve administrative purposes (often micro/individual data) • One way traffic: Micro data from administrative registers to NSI statistics – but never opposite

  15. UN Fundamental principles on trust • Bearing in mind that the essential trust of the public in official statistical information depends to a large extent on respect for the fundamental values and principles, which are the basis of any society, which seeks to understand itself and to respect the rights of its members. • 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.

  16. What measures to improve trust? • Perform surveys to understand why users don’t trust the NSI and official statistics • Avoid any suspicion of political interference: • Clear and transparent rules for preparation and release of information • Clear policy for protecting confidentiality • Systematic quality control to avoid erroneous data • Implement a clear policy of equal access to the same information to all sectors and parties of society • Supplement all figures with user-friendly documentation • Inform and train users

  17. Thanks for your attention!Any comments/questions?

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