editing of linked micro files for statistics and research

Editing of linked micro files for statistics and research

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

Datasets and input

Administrative Data sets

Base RegistersStatistical Surveys

EnterprisesInternal DataSystems

Web-questionnaire

PaperQuestionnaire

Editing at response time

EnterprisesInternal DataSystem

Web-questionnaire

Checks and corrections interacting

with respondent

Collecting information from the prosesses

Editing using prosessinformation

Statistical Surveys

PaperQuestionnaire

Collected information from the prosesses on web-questionnaires

Editing withoutinteraction with

respondent

DynarevDynamic revision in business surveys

Data collection

Publishing

Totalpopulation

Sampled population

MetadataEnterprise accounts,other administrative data

and statistical surveys

Dynarev

Data collection

Publishing

Totalpopulation

Sampled population

MetadataEnterprise accounts,

other administrative dataand statistical surveys

Calculation-basis and rules

Checkingrules

Editing Calculating

Data sources for research

The strength of administrative data

Longitudinal databases Base registers Education Labour force Income Transfers Annual Census file Health indicators

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

Editing and imputation

Longitudinal data Base register of person Base register of business Base register of dwelling Enterprise accounts Labour Force

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 jobs 2 106 000

Editing and imputation

Annual Census micro file

Activities and source of livelihood

Micro file on generations

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

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