1. SLOVENIAN REGISTER-BASED CENSUS – administrative versus statistical approach Danilo Dolenc Statistical Office of the Republic of Slovenia

2. Introduction  Slovenia is an example of change of main census method

3. First step – 2002 Census  Combined method of enumeration Register based (data on persons only)  About 10 administrative and statistical sources have been used  Pre-printed questionnaires  10 topics entirely taken from registers (not included in questionnaire) Complete field enumeration (dwellings, households, persons – only data not available in sources)

4. Next step – new sources  Three main administrative sources Persons  CPR – available since 1986 Households  Household Register (electronic form since 2007) –Paper forms exit before – but not used for statistical purposes Dwellings  Real Estate Register –Established in 2007 by Surveying and Mapping Authority

5. Sources by topic (1)  About 30 sources are identified POPULATION TOPICS  Central Population Register  Register of Foreigners  2002 Census  Statistical demographic surveys on birth and migration Identificators: SID* and BA_DN** * SID – statistical identificator (substitute for PIN) ** BA – building address DN - dwelling number

6. Sources by topic (2)  ACTIVITY  Statistical Register on Employment  Business Register  Unemployment Register  Statistical survey on students  Statistical survey on scholarship  Income Tax Register  Database on Beneficiaries of Pensions  Social and Health Security database  Database on Social Benefits Identificator: SID

7. Sources by topic (3)  EDUCATION  Statistical Register on Employment  Unemployment database  Statistical survey on students  Statistical survey on scholarship  Statistical survey on graduates, master’s and doctoral graduates  2002 Census  General and vocational matura examination database  Chamber’s examination databases Identificator: SID

8. Sources by topic (4)  HOUSEHOLD TOPICS  Household Register (HR) –Based on statement made by household member(s)  DWELLING TOPICS  Real Estate Register (RER) –Will be also used for taxation in the future Identificators: SID and BA_DN

9. Household Register  Relevant data Dwelling number (DN) (running number in the scope of address - BA) - also in RER and CPR Household number (HN) (running number in the scope of address - BA) - only in HR Relation to the reference person of household  The main advantage Possibility of direct derivation of household composition / type of family for the most persons  Housekeeping concept

10. DN 3DN 4 DN 1 DN 2 BA DNHNRELATION 31Mother 43Reference person 22Child 44Grandchild 44Child 22Reference person 31 22Wife 44Reference person BA Data integration - input RER data HR data

11. DN 3 1 HH (x1) DN 4 2 HH (x3 and x4) DN 1 Vacant DN 2 1 HH (x 2) BA HH ID RELATIONFAMILY TYPE x1Reference personHusband-wife with children x1Wife x1Child x2Reference personLone mother x2Mother X3Reference person- * X4Reference personLone father ** X4Son x4Grandchild Data integration - output * One-person household ** Lone father household with other persons

12. Households quality assessment  Administrative obstacles Legislation  Household data only for permanent residence Statistical concepts versus administrative ones  Definition of usual residence  No data on collective households Inconsistency of source data  Relation to reference person and age  Relation to reference person and marital status Incompleteness of source data  Missing data on dwelling number

13. Households quality assessment  Statistical obstacles Recently established source  Not used for statistical purposes yet Complexity of relations in households  Multi-family households Comparability of the results to previous censuses or current field surveys  New concept/definition of household  Underestimation of consensual unions ‘’Broken’’ households  No reference person  Reference person is under certain age

14. Results of test database  Direct derivation of household/family types Simple rules – 80 % Complex criteria – 6 %  Reasons for non-derivation Records without household number – 4 % Records without relation to RP – 2 % Records with unknown relation to RP – 7 % Fault records - only 1 %

15. Improvement of the process  Introduction of quality indicators Measuring every change of input data  Use of statistical methods Setting up households Distinguish institutional households Consensual unions

16. Conclusion  Structural changes of size of household and types of families are expected Huge increase of one-person households  Focus on developing statistical methods  Improving quality in close coopeation with administrative source Feedback in aggregate form Common interest