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QUALITY ASSESSMENT OF THE REGISTER-BASED SLOVENIAN CENSUS 2011. Rudi Seljak , Apolonija Flander Oblak Statistical Office of the Republic of Slovenia. The schedule of the presentation. Administrative data in the statistical process Quality assessment concepts
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QUALITY ASSESSMENT OF THE REGISTER-BASED SLOVENIAN CENSUS 2011 Rudi Seljak, Apolonija Flander Oblak Statistical Office of the Republic of Slovenia
The schedule of the presentation • Administrative data in the statistical process • Quality assessment concepts • Quality assessment and the statistics based on the administrative sources • Slovenian plans for the register based census and its quality assessment • Conclusions
Administrative data in the statistical process • Administrative data have been used in the official statistics for a long time. • Firstly the administrative data have been used mostly for the sampling frame construction and sample selection. • Later the development of the statistical theory introduced the usage of these data in the estimation process in order to improve the accuracy of the statistical results (calibration techniques). • Lately the administrative data are more and more used also as a direct data source. • Use of the administrative data as the direct data source usually causes significant changes in the statistical process.
Administrative data at the Statistical Office of the Republic of Slovenia (SORS) • SORS has a long history of the usage of the administrative data in the statistical process. • Many administrative registers that are now under maintenance of other authorities have been set-up and for some time also maintained by SORS. • Administrative data are used in many surveys as a supplementary data source (e.g. EU-SILC). • The 2002 Census of Population and Housing was still a combined one, while the next one in 2011 is already planned to be fully register-based.
Quality assessment and reporting in the ESS • The general quality assessment framework, which has been in the last decade widely accepted inside the European statistical system, is based on the definition of the six quality components. • For each component the set of standard quality indicators, which should provide the numerical assessment of the quality, was defined. • The six components are: relevance; accuracy; timeliness and punctuality; accessibility and clarity; comparability; coherence. Costs and burdens is the (seventh) additional component. • For the presentation purposes we will divide the components in two parts: the product oriented and the process oriented.
Quality components - the model Quality components Product oriented Process oriented Relevance Coherence Comparability Accuracy Timeliness and punctuality Accessibility and clarity Costs and burden
Process oriented components and the “classical“statistical process Data processing Dissemination of the statistical results Sampling frame construction, sample selection Data collection Coverage errors, sampling errors Response errors, measurement errors Processing errors Timeliness of the first results, Number of means used for the dissemination Accuracy Timeliness and punctuality, accessibility and clarity
Process oriented components and the “register-based“ statistical process Data processing Dissemination of the statistical results Sampling frame construction, sample selection Data collection Relevance of the variables, Up-to-date of the register data Matching errors, consistency errors Processing errors Timeliness of the first results, Number of means used for the dissemination Relevance Accuracy Timeliness and punctuality, accessibility and clarity
The Slovenian forthcoming census • The last, 2002 Slovenian census was already partly based on the administrative data sources. • The 2011 census is planned to be fully register-based. • The main administrative sources which will define the target population will be: • Central Population Register • e-Database of Households • Register of Dwellings • Many other data sources will be linked to the target populations in the data integration phase.
The register-based census – main obstacles • A the moment the main obstacles concerning the data sources for the register-based census are: • The Register of Dwellings is still in the establishment phase • The quality of the data in the e-Database of Households is not satisfactory (maintained by the Ministry of the Interior) since it has been just recently established. • Data on relationships among persons in the CPR are not as complete as they should be so that they would enable SORS to easily identify all relationships among persons in the families.
Census quality assessment – prior activities • Identification of the relevant administrative and statistical sources. • For each source the following information will be documented: • name of the source, • description of the source, • date of the establishment, • legal basis, • identifiers used, • system of updating, • structure • method and frequency of acceptance of the source at SORS, • data editing at SORS
Census quality assessment – the process • Registration, conversion of the identifiers, validity checks • Information of the registration of the source, evidence about the failed validity checks • consistency with the predefined range of variables in the source • Set up of the two basic target populations (persons, houses and dwellings) • Consistency with the theoretical description of the population • Detection of the duplicates
Census quality assessment – the process cont’d • Integration of the different sources • The emphasis will be on the numerical assessment of the quality • At the moment there is a lack of the standard quality indicators for this phase of the process • Two examples of the possible quality indicators: the matching rate, the relative consistency rate • Matching rate. The rate of the records, successfully matched (direct or statistical) to the reference population. • The relative consistency rate: rate of the units for which the condition |YR- YA |/ YR < p (e.g. p=0.01) is fulfilled
Census quality assessment – posterior activities • Comparability of the results. The main focus will be on the comparability with the 2002 (mostly) conventional census. • Coherence with the results of the with the results of some other, “classical” statistical surveys such as EU-SILC, LFS and HBS. • The costs and burdens will be estimated and the comparison with the previous census will be made. • At the end the comprehensive quality report which should cover all the before mentioned components will be prepared and published on the internet.
Conclusions • The movement from a conventional to a register-based statistical survey demands an adjusted approach in the data quality assessment. • The relevance of the administrative and statistical sources and the relevance of the statistical variables, derived from these sources, is the crucial component of the new approach. • The exhaustive documentation which should describe the different aspects of the incoming sources should become an important part of the quality report. • The set of standard quality indicators should be adopted for the case of register-based census.