1. Editing of linked micro files for statistics and research

2. Data sources Background information for editing Creating linked files Employee jobs Confidentiality and privacy

3. Datasets and input Administrative Data sets Base Registers Statistical Surveys Enterprises Internal Data Systems Web- questionnaire Paper Questionnaire

4. Editing at response time Enterprises Internal Data System Web- questionnaire Checks and corrections interacting with respondent Collecting information from the prosesses

5. Editing using prosessinformation Statistical Surveys Paper Questionnaire Collected information from the prosesses on web-questionnaires Editing without interaction with respondent

6. Dynarev Dynamic revision in business surveys Data collection Publishing Total population Sampled population Metadata Enterprise accounts, other administrative data and statistical surveys

7. Dynarev Data collection Publishing Total population Sampled population Metadata Enterprise accounts, other administrative data and statistical surveys Calculation- basis and rules Checking rules Editing Calculating

8. Data sources for research The strength of administrative data Longitudinal databases Base registers Education Labour force Income Transfers Annual Census file Health indicators

9. Infrastructure for creating linked files The advantage of use of linked files Base registers and official ID numbers Consistency control Creation of linked files - centralisation

10. Editing and imputation Longitudinal data Base register of person Base register of business Base register of dwelling Enterprise accounts Labour Force

11. Employee jobs by source Norway Two sources A = Tax Agency B = Social Security Jobs in A and B 1 911 000 Jobs only in A 169 000 Jobs only in B 26 000 Total employee jobs2 106 000

12. Editing and imputation Annual Census micro file Activities and source of livelihood Micro file on generations

13. Editing and imputation of linked files for administrative purposes E-government – a variable should be reported only once A new agency to reduce number of persons not in the labour force 2 400 000 in Labour Force 700 000 not in LF Editing and imputation by documented corrections

14. Confidentiality and privacy Administrative data are often sensitive Data Inspectorate Classification Identifiable – ID number De-identified – ID number removed Anonymised – not possible to link to other sources