1. UNECE Seminar on New Frontiers for Statistical Data Collection, Geneva
A quality monitoring system for statistics based on administrative data
Manuela Lenk
Statistics Austria
Registers, Classifications and Methods Division
31st Oct.– 2nd Nov. 2012
UNECE Seminar on New Frontiers for Statistical Data Collection, Geneva

2. Register-based census in Austria
First register-based census in Austria 2011
Full census, no sampling
Census topics
Population census, housing census, census of enterprises and their local units of employment
Data availability
On municipality level
Geo-Codes
Statistical databases
Interactive maps

3. Quality assessment of the census
Application of a quality framework
The framework is independent from data processing, allowing the application on other statistical projects
Data processes can be evaluated without influencing them
Three stages of quality evaluation
Raw data
Registers provided by the data holders
Central Database (CDB)
Combined information from the registers
Data is merged by a unique key
Final Data Pool (FDP)
Final data including imputations

4. Quality framework - Overview

5. Quality assessment on register level I
Calculation of quality indicators
Each attribute in each register gets a quality between 0 and 1
Quality calculation is based on 3 so-called hyperdimensions
HD Documentation
Focuses on factors which possibly predetermine data quality
Realized by a questionnaire which is filled out in accordance with the data authority
Questions are weighted by their impact on data quality
Quality indicator:
maximum obtainable score
obtained score

6. Quality assessment on register level II
HD Pre-processing
Detection of formal errors, like missing primary keys, out-of-range values and item non-response
Usable records are calculated by the subtraction of erroneous records from total records
Quality indicator:
HD External Source
The accuracy of the data is checked
Comparison with existing representative surveys
total number of records
usable records
total number of linked records
number of consistent values

7. Quality framework - Overview

8. Quality assessment of the CDB and FDP
SEX_Reg3
SEX_Reg2
SEX_Reg1
Unique Attributes
Attribute exists in only one register, directly transferred to the CDB (e.g. highest level of education)
Multiple Attributes
Attribute exists in more than one register, combined in the CDB using certain decision rules (e.g demographic attributes)
Derived Attributes
Attribute is created based on other attributes (e.g. type of commuter)
Multiple Attribute
Attrib1
Attrib2
Derived Attribute

9. Quality assessment of unique attributes
The highest level of education (EDU) is delivered by one single register. The quality indicator is derived by the three hyperdimensions.
There are still missing values (with quality=0) that decrease the quality indicator in the CDB.
After imputations of missing values, we assess the quality indicator of the attribute EDU in the Final Data Pool.

10. Quality assessment of multiple attributes
SEX is available in two registers. The attribute is evaluated in both data sources with the three hyperdimensions.
Does the information differ between the two data sources? Which register should we believe in? Dempster-Shafer theory takes uncertainty, consistency and conflict into account.

11. Quality assessment of derived attributes
There is no information on current activity status (CAS) or commuters (COM) in the raw data. We derive the information for CAS from two other attributes in two data sources.
We obtain the required information for COM from the already derived attribute CAS. Thus, the quality indicator of both attributes is equal.
Imputations are applied on CAS. The imputed values are transferred to the COM attribute by the same derivation process already done in the CDB.

12. Usability of the results
Raw data
Which register delivers a certain attribute with the highest quality indicator?
Is there a register with a below-average quality for all delivered attributes?
Is the quality indicator of a certain attribute worse than in the last delivery?
Census Database
Is there any advancement of data quality by the use of multiple data sources?
Comparison with prior censuses – plausibility checks
Final Data Pool
Comparison of attributes for further advancement
Comparison of census generations over time
RAW
CDB
FDP

13. Further Information
Austrian Journal of Statistics, Volume 39 (2010), Number 4
Statistica Neerlandica, Volume 66 (2012), Issue 1
ESSnet on Data Integration 2011, Madrid
ISI World Statistics Congress STS50 - Methods and quality of administrative data used in a census 2011, Dublin
NTTS Conference 2011, Brussels
UNECE/Eurostat Expert Group Meeting on Register-Based Censuses 2010, The Hague
European Conference on Quality in Official Statistics 2010, Helsinki
European Conference on Quality in Official Statistics, June 2012

14. A quality monitoring system for statistics based on administrative data
Please address queries to:
Manuela Lenk
Register based census
Contact information:
Guglgasse 13, 1110 Vienna
phone: +43 (1)
fax: +43 (1)
UNECE Seminar on New Frontiers for Statistical Data Collection, Geneva