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Register-Based Census 2011 in Slovenia – Some Quality Aspects Danilo Dolenc Statistical Office of the Republic of Slovenia UNECE-Eurostat Expert Group.

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Presentation on theme: "Register-Based Census 2011 in Slovenia – Some Quality Aspects Danilo Dolenc Statistical Office of the Republic of Slovenia UNECE-Eurostat Expert Group."— Presentation transcript:

1 Register-Based Census 2011 in Slovenia – Some Quality Aspects Danilo Dolenc Statistical Office of the Republic of Slovenia UNECE-Eurostat Expert Group Meeting on Censuses Using Registers, Geneva, 22-23 May 2012

2 Basic facts (1)  Fully register-based census using data from Administrative registers (5) Statistical register (1) Administrative databases (7) Statistical surveys (full coverage) (6)  Organized as a project Started in 2009 Project team consists of 6 employees  No permanent staff  No outsourcing No budget (savings around 14 mio EUR) Census considered as regular statistical survey

3 Basic facts (2)  Reference date 1 January 2011  Three (four) stages of the statistical process following the availability of sources concluded by dissemination of data: Basic demographic data (30 April 2011)  Produced quarterly Households and families (30 June 2011) Other population topics (30 December 2011)  Including occupied dwellings – preliminary data Housing (by the end of June 2012)  Delay due to the updated version of administrative data (Real Estate Register)

4 Background  Four basic registers set up by SORS far ago CPR for the first time used for statistics in 1986  Data already used in 1991 and 2002 Censuses Register of Spatial Units (address list) in 80‘s Statistical Register on Employment – from 1986  In 2002 data on occupation, industry, place of work taken over Business Register in 1976  Two missing registers available after 2002 Real Estate Register established in 2007 Household Register computerized  CPR supplemented with dwellings number Mini project of SORS and Ministry of Interior in 2010

5 Preparatory phase (1)  Analyses and evaluation Data sources Quality of data Methodological and processing solutions  Trial census carried out in 2010 - main findings Inconsistencies in Household Register  Easy to improve quality Solved by Ministry of the Interior on the basis of SORS guidelines  Detected errors should be corrected in primary source

6 Preparatory phase (2)  Missing dwelling numbers (DN) in CPR More than half of population living in multi-dwelling buildings Two main activities for improvement undertaken  Automated determination of DN on the basis of ownership and residence  49,000 letters sent to residents without DN –Response rate 75 % including returning letters by post Still 12.3 % of missing DN in input database

7 Preparatory phase (3)  Unsatisfactory quality of Real Estate Register data The main problem in whole statistical process SORS analyses sent to register keeper Public data – owners had chance to check and change data Data on ownership depends on long-lasting legal matters Re-updating of final database – selected topics

8 Linkage of data (1)  Identifiers crucial for integration of persons, households and dwellings PIN (transformed to SID before the process)  Basic identifier for most of linkage regarding persons Household number  Housekeeping concept is implemented  Not available for foreigners - 2.1% HN missing  Relation to the reference person could be considered as identifier (key for family generation) Dwelling number  The share of missing data still high – 12.3% Address  Unique identifier of every building

9 Linkage of data (2)  Statistical process almost completely automated Very complex rules for imputing key identifiers  Interface for manual editing incorporated in the statistical process Better quality – but only 1% records  Household formation of foreigners  Family formation –Multi-member households –Households without data on biological parents or spouses

10 Quality indicators - identifiers

11 Current activity status  Population aged 15+ Data integration stage

12 Imputation  Almost all missing data imputed Except occupation, industry and status in employment for persons working abroad (e. g. daily commuters)  Two main methods used Automated corrections on the basis of existing correlated data (e.g. activity status by health insurance code) Hot-deck imputation  Imputation rates – lower than in 2002 Census

13 Where should we be heading ?  Integration into social statistics Census data used for regular surveys (e.g. country ob birth of parents, immigrant background)  Coverage  Cooperation with MI to improve over-registrationover-registration  Geo-referencing Free of charge on the web – application KASPeRKASPeR  Qualty of processes and outputs Every single change of data from the input databases to the final census database is recorded Introducing manual interface for improving quality  Common tools – internal integration of IT processes

14 Over-registration  Common problem of register-based systems  Missing data on activity status used as indicator Data from 8 sources usedsources  For 1,25 % of population no evidence in any source Overestimated population groups  Foreigners with permanent residence  Working age population (30-44 years) – working abroad?  Administrative survivors (over 94 years)  Final estimation 0.9%  Very comparable with households surveys  No need for post-enumeration survey

15 Conclusion  Two main conditions for input data quality Close cooperation with register keepers  Feedback implemented in primary source Permanent use of registers  Not only for statistical purposes  In future no more ‘‘Census‘‘ but regular annual/periodical survey Every 3-4 years complete ‘‘Census‘‘ Every year education, activity, migration data Twice a year basic demographic data including citizenship  New term instead of ‘‘Census‘‘ ???

16 Thank you for your attention!


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