1. United NationsUnited Nations Economic Commission for Europe Statistical Division Results of survey on organization of data collection in National Statistical Offices of participating countries Fiona Willis-Núñez

2. Presenter's Name - UNECE Statistical Division Slide 2 Summary of responses  27 completed responses  representing NSOs or National Banks of 24 countries 3 other organizations

3. Presenter's Name - UNECE Statistical Division Slide 3 Outline  Current use of data sources  Organizational structure for data collection  Legal framework for data collection  Future directions

4. Presenter's Name - UNECE Statistical Division Slide 4 CURRENT USE OF DATA SOURCES I.

5. Presenter's Name - UNECE Statistical Division Slide 5 Proportions of surveys based on each main type of data source  Based fully on admin data: average 22%  Based partially and indirectly on admin data: average 46%.  Based partially and directly on admin data: 23%  But- terminology: what is a survey?

6. Presenter's Name - UNECE Statistical Division Slide 6 Extent to which response burden is taken into account in collection activities  Burden on individuals and households: 9 responses, of which 7 ‘very large extent’ and 2 ‘very small extent’ (no intermediate answers)  Burden on businesses: 13 responses, all of which ‘very great extent’.

7. Presenter's Name - UNECE Statistical Division Slide 7 Channels of admin data  Most common answer: tax data  Also: Business, health, school, electoral, crime, unemployment, vehicles, banking transaction, vital events…… Food safety, milk market, The lucky ones: all governmental sources!

8. Presenter's Name - UNECE Statistical Division Slide 8

9. Presenter's Name - UNECE Statistical Division Slide 9 Mixed mode collection  Very wide range: from none (Mexico) to almost all (Netherlands)  Most common: census  Wide range of approaches to quality checking: sample surveys, cross validation with other sources, experimental and pilot studies

10. Presenter's Name - UNECE Statistical Division Slide 10 ORGANIZATIONAL STRUCTURE FOR DATA COLLECTION II.

11. Presenter's Name - UNECE Statistical Division Slide 11 Position of data collection  11 of 23: highly centralised  9 partially centralised;  3 (Mexico, Germany and the United States Bureau of Labor Statistics) highly decentralised.

12. Presenter's Name - UNECE Statistical Division Slide 12  12 of 23 respondent organizations have experienced recent changes  4 others envisage future changes  Changes tend towards consolidation but last thing to change is the social/business distinction

13. Presenter's Name - UNECE Statistical Division Slide 13 Functional distinction between individual/hh data collection and business data collection  8 of 24: conducted by the same organizational unit.  5: distinction but with some degree of overlap.  10: conducted by entirely separate organizational units.

14. Presenter's Name - UNECE Statistical Division Slide 14 LEGAL FRAMEWORK FOR DATA COLLECTION III.

15. Presenter's Name - UNECE Statistical Division Slide 15  12 of the 24 respondent organizations have strong legal provisions for access to administrative data.  10 have partial provisions.  Only 2 (Israel and the USDA NASS) reported that they do not have legal provision for such access.

16. Presenter's Name - UNECE Statistical Division Slide 16 Commercial sources  11 of 23 responses, yes  6 no  6 don’t know or n/a  Examples: Land line register, geographic location codes, various sources for price info, accounting data

17. Presenter's Name - UNECE Statistical Division Slide 17 Industrial sources  Only 5 yes, plus two experimenting or planning to do so in future  Credit card and mobile phone data  Few countries have separate specific legal provisions for access to commercial & industrial sources. Either general laws on statistics, or individual commercial contracts

18. Presenter's Name - UNECE Statistical Division Slide 18 FUTURE DIRECTIONS IV.

19. Presenter's Name - UNECE Statistical Division Slide 19 Main challenges  Almost universal: Response rates Budgetary pressures  Also common: Staff costs, training & retention Legal obstacles Technical challenges in exploiting admin sources, automation, etc.

20. Presenter's Name - UNECE Statistical Division Slide 20 Main advantages  Almost everyone who responded: strong legal provisions  Reputation, goodwill  Existence of registers

21. Presenter's Name - UNECE Statistical Division Slide 21  ‘If the Conference of European Statisticians decides to undertake further work on this theme, what topics would you propose for such work to address?'

22. Presenter's Name - UNECE Statistical Division Slide 22 Modes and methods Mode effects (several respondents) Mixed-mode collection (several respondents); impacts of mixed modes on quality and on funding Use of the Internet (several respondents), e.g. for social and business surveys Respondent management, including non-response and reduced response rates Replacement of direct collections with new administrative sources Conceptual issues in the use of big data 'Virtual call centres' Responsive design for data collection New collection tools (e.g., use of a single collection tool for both respondents and interviewers)

23. Presenter's Name - UNECE Statistical Division Slide 23 Organizational and legal aspects Experiences with formal data collection units or 'sub-organizations' for collection of all survey data Management and organizational issues Rationalization of data collection Field work management Coping with budget restrictions Implications of forthcoming EU data protection legislation Speeding up the processes between collection and publication Legal issues surrounding use of big data Defining data collection: deciding which processes belong to the realm of collection when modelling business processes Working with other data collectors, publishers and providers