1. The Importance of Building Trust in Official Statistics Consultation Mission on Promoting the activity and Creating a positive image of the Ukrainian State Statistical bodies Kiev, Ukraine 9 – 12 December 2014 Petteri Baer, Marketing Manager, Statistics Finland Courtesy to Jan Byfuglien, Statistics Norway, Yalta, Ukraine 2008

2. Finnish stereotype of a statistician Produces figures on something that is not important Really many theoretical concepts and indexes, out of touch with reality, focus on methodologies Statistics is related to history - has nothing relevant to say about the present Says nothing or, if does, denies it in the next sentence “Small lies, big lies, statistics” Kiev 9-12 December 2014

3. Without trust in statistical information Official Statistics is not worth much anything Trust is a cornerstone for National Statistical institutes Trust should be secured by good legislation Dissemination policies and practices are important elements in building the public image - and thus trust Broad dissemination policies Official statistics is not only for governmental institutions! Good presentation skills are important abilities for any staff member of the SSSU who is presenting, introducing or training different audiences about statistical information Petteri BaerKiev 9-12 December 2014

4. Trust: long time to build, quickly destroyed Proper legal basis Professionalism Independence Integrity Relevance Confidentiality External review User orientation Political bias Wrong figures Misuse of microdata Petteri BaerKiev 9-12 December 2014

5. Tust can be quickly destroyed... really quickly Recent examples: Argentina, Greece... Some others... Petteri BaerKiev 9-12 December 2014

6. Trust in public statistics should be of vital importance also 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 Kiev 9-12 December 2014 Petteri Baer

7. 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 Kiev 9-12 December 2014 Petteri Baer

8. Credibility of statistics is a concern in many countries - The China case Kiev 9-12 December 2014 Petteri Baer

9. A potential threat to misuse of microdata: Unclear borderline between official statistics and administrative data can be distortive 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 all the Nordic countries) 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 the opposite ; Only specific exceptions for scientific research Kiev 9-12 December 2014 Petteri Baer

10. United Nations 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. Petteri BaerKiev 9-12 December 2014

11. What makes official statistics trusted by users? By Heinrich Bruengger in a seminar in Kiev, 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 the Director General / the Head / the Chairman of the Statistical Agency * Joint EFTA/ECE/SSCU Seminar Kiev 2007 Kiev 9-12 December 2014 Petteri Baer

12. Some key elements of trust and trust-building A good summary by Ivan Fellegi, Head of Statistics Canada, at the Conference of European Statisticians, 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. Kiev 9-12 December 2014 Petteri Baer

13. 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 Kiev 9-12 December 2014 Petteri Baer

14. Challenges arising from the operational environment of Statistical Agencies Meeting user demands of statistical products and services Responding to increasing competition from other providers of statistics Modernisation of statistical production and services Increasing competition for qualified performers in the labour market Kiev 9-12 December 2014

15. Why is Quality Management important? Understanding the aims and goals of the organization is important Understanding one’s own role is important Motivation in work is a decisive factor of success It is the combined efforts of the organization and the individual, which brings results Kiev 9-12 December 2014

16. User demands – the basic ones User friendly Easily accessible Understandable and clear Focused on the essentials With visual presentations Politically neutral Balanced Petteri BaerKiev 9-12 December 2014

17. User friendly statistical services …can be established only through interaction with users Interaction with real users Not with solely our imagination on them Not only governmental users Not only the ones we by tradition are mainly used to Kiev 9-12 December 2014

18. Often it is not easy, especially if different divisions work in silos - and behave as that would be ideal Petteri BaerKiev 9-12 December 2014

19. But – that’s already another story Thank you for your attention Remember: Only used statistics are useful statistics petteri.baer@stat.fi www.stat.fi A learning Customer Relationship Kiev 9-12 December 2014