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Role of editing and imputation in integration of sources for structural business statistics. Svein Gåsemyr, Statistics Norway Svein Nordbotten, University of Bergen. Contents of paper. Data sources for business statistics Methods for integration of sources - PowerPoint PPT Presentation
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Role of editing and imputation in integration of sources for
structural business statistics
Svein Gåsemyr, Statistics NorwaySvein Nordbotten, University of Bergen
Contents of paper
• Data sources for business statistics
• Methods for integration of sources
• Use of standard models for processes
• The need to measure quality of linked files
• Work to be done
Interaction of sources and modules
• The statistical business register
• The database to coordinate samples
• The micro file of statistical surveys
• The database of available data
• The menu of data editing imputation and estimation
Data sources to be integrated for business statistics by ISEE
Administrative business registers that are affiliated to the Legal Unit Register
• Employer Register
• Business Enterprise Register
• Value Add Tax Register
• Tax register of business enterprises and self-employed
Enterprises and establishment of manufacturing industry
• Complex enterprises 1086– Establishments 1 768
• Single enterprises 19 416
Establishment by sources
• A. Census survey 2 096
• B. In sample and selected 1 251
• C. In sample and not selected 1 092
• D. Small complex establishment 319
• E. Establishment excluded 16 426
Methods for integration
• Linkage at unit level
• Editing of a single source and linked files
• Estimation by mass imputation
Process errors in integrated records
• Errors due to incomplete registers
• Linking errors
• Observation errors
• Errors made during editing
• Imputation errors
Units identification in 2 registersUnits in register 1: Not
existing
Incorrectly existing
Existing with incorrect ID
Existing with correct ID
Sum
Units in register 2:
Not existing in register 00 01 02 03 0.
Incorrectly existing 10 11 12 13 1.
Existing with incorrect ID 20 21 22 23 2.
Existing correct 30 31 32 33 3.
Sum .0 .1 .2 .3 ..
Statistical quality indicators
• Process accuracy – Statistical accuracy• Quality of administrative data• A single source• A linked file of 2 sources• A linked file of a large number of sources• A small evaluation sample• Deviation between processes data value
and the correct value
Work to be done
• Improve the system for unit identification
• Develop the standard processing system
• Evaluation by controlled experiments
• Designing suitable evaluation samples
• Use of process data for process design