160 likes | 278 Views
SLOVENI AN REGISTER-BASED CENSUS – administrative versus statistical approach. Danilo Dolenc Statistical Office of the Republic of Slovenia. Introduction. Slovenia is a n example of change of main census method. First step – 2002 Census. Combined method of enumeration
E N D
SLOVENIAN REGISTER-BASED CENSUS – administrative versus statistical approach Danilo Dolenc Statistical Office of the Republic of Slovenia
Introduction • Slovenia is an example of change of main census method
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)
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 usedfor statistical purposes • Dwellings • Real Estate Register • Established in 2007 by Surveying and Mapping Authority
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
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
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
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
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
Data integration - input HR data RER data DN 3 DN 4 DN 1 DN 2 BA
Data integration - output DN 3 1 HH (x1) DN 4 2 HH (x3 and x4) DN 1 Vacant DN 2 1 HH (x 2) * One-person household ** Lone father household with other persons BA
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
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
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 %
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
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