4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics USING ADMINISTRATIVE DATA SOURCES IN OFFICIAL STATISTICS: THE PRACTICALITIES FOR STRUCTURAL BUSINESS STATISTICS AND BURDEN REDUCTION AND SAMPLING GAINS Daliute Kavaliauskiene Head of Survey Sampling Subdivision Antanina Valiuliene Head of Enterprise Statistics Division

Initial conditions necessary for successful use of administrative data  Legal basis  Close cooperation among administrative authorities  Technical preconditions (unified data code system)  General public understanding 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics

4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics Use of administrative data  Administrative data from 110 sources are used in:  Demographic statistics  Earnings statistics  Structural business statistics  Foreign trade statistics  Short-term statistics (starting from 2007 )  Statistical Business Register  40% of statistical indicators are produced using administrative data

Institutional costs of the use of administrative data  Additional data cleaning and validation  Matching with other data (statistical or administrative)  Modelling and use of complex estimation methods  Staff qualification 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics

Quality problems related to the use of administrative data sources  Coverage  Differences in definitions  Timeliness  Accuracy (reliability) 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics

Coverage  General administrative data cover census data  Population covered by administrative system does not necessarily correspond to population of statistical interest  Examples:  Not all enterprises are VAT payers  Enterprises are free to report or not to the Labor Exchange about the job vacancies  Degree of coverage is not known at the survey planning stage 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics

Timeliness problems  Especially important when administrative data source substitutes for statistical survey 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics General problem - administrative data are not available at the time they are needed Use of incomplete data set Imputation Forecasting … Use of data of previous periods Ratio type estimation techniq ue …

Accuracy of administrative data does not correspond to statistical needs Data have erroneous values Data are correct but do not fully correspond to statistical purposes 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics Background Motivation of respondents to provide correct data to the institution Ways of solving the problem Knowledge of an administrative institution Data editing procedures Historical records, matching with other data source can be helpful Background Statistical and administrative data differ in definitions Ways of solving the problem Methodological solutions Matching with other data source

Use of administrative records for statistical purposes Advantages:  Decreased costs of statistical production  Reduced statistical response burden  Possibility to produce estimates for smaller domains 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics Disadvantages  Dependence on legislation of administrative data collection  Quality problems  Confidentiality problems

Conclusions  Administrative records provide a rich source of information but are not “cost-free”  Estimation based on combined (statistical and administrative) data can increase the quality of statistical production and reduce dependence on other institution, but it requires more methodological work and higher staff qualification  Close collaboration with the owners of administrative records and thorough knowledge of administrative data source is of a crucial importance  Practical work with administrative data highlighted the need to invest more into data editing and validation procedures 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics

Organization of the SBS survey SBS Regulation 295/2008 I-IV Annexes ENTERPRISE STATISTICS DIVISION with some exceptions V-VII Financial annexes ENTERPRISE STATISTICS DIVISION Deleted VIII Annex for business services TRANSPORT AND SERVISES STATISTICS DIVISION IX Business demography annex BUSINESS REGISTER DIVISION 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics Business Register data Sample Survey + Admin data

SBS ANNEXES I-IV  Objectives  To produce preliminary SBS data by economic activity NACE 3 digit level;  To produce final SBS data by: Economic activity (NACE 4 digit level), size classes, regions  To provide data for National Account Division: Financial indicators, production, value added, etc.  Population  Active enterprises produced goods or rendered services for market: 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics

SBS survey strategy  Preliminary results :  Sample survey – purposive-cut off statistical method is used: counted 80% of accumulated turnover and 60% of accumulated employees by NACE REV.2 activity code at 3 digit level;  Only largest state and limited liabilities companies are surveyed using statistical questionnaire F01 (~9 000 enterprises, ~6%);  Pre-filled statistical questionnaire F-01 with data of financial statements and employees; SBS preliminary results are prepared on the basis of the sample survey data and for the sub-population of individual enterprises and natural persons – data from previous reference year. 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics

SBS survey strategy (2)  Final results - census survey  All administrative sources are used at the enterprise level;  Data integration is performed using a unique enterprise identification code;  On the basis of administrative sources the frozen list of active enterprise is updated for the SBS needs; 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics Sub population 1 (Sample survey - data are obtained from SQ) Sub-population 2 (data are covered from administrative sources or estimated)

Data sources used  Administrative data (AD) as a main source (94 % of enterprises):  Annual financial statement of state and all types of limited companies (balance sheet, profit and loss account);  Annual profit tax declaration of individual enterprises (turnover, materials used, other costs, etc.);  Annual income declaration of natural persons who are engaged in an economic activity in their own right (turnover);  State social insurance fund board (SODRA) data on employment.  AD as an additional source:  VAT declaration, annual profit tax declaration of limited companies.  Statistical data sources (already existed):  STS Survey (number of hours worked by employees), Quarterly Labour Cost Survey (employees’ data). 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics

SBS survey strategy (3)  Data editing:  Before usage AD are edited using edited methods;  The editing process is automated;  Estimation and imputation:  Admin Data which only partially match with the statistical definition as well as non- existent variables are estimated using mathematical methods - the optimal model based estimation method is detected;  Non-response enterprises (AD) are estimated using the donor unit (nearest neighbour method);  Quality:  The compatibility of the integrated data is checked by logical rules;  The survey is finalised with comparability and accuracy checks of the complete SBS data base. 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics

Distribution of the main SBS survey indicators by sources 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics

Quantitative quality indicators 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics  Quality indicator reflecting the initial data quality – the share of edited items (%)

Quantitative quality indicators  Quality indicators reflecting the response rate as well as estimation and imputation level. 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics

Problems and future plans  Advantages :  The reduction of a response burden for small business.  The possibility to release statistical information by plenty of various breakdowns.  Administrative data provides good estimates for the most important variables, resulting in better accuracy.  Problems:  The scope of information in AD is not complete for SBS needs;  A lot of imputation is needed and there is a risk of introducing model assumption errors;  Dependence on Administrative sources – we have limited power to influence the AD.  Future actions:  Further monitoring and improvement of data quality;  New challenges for the implementation of the FRIBS. 4-6 September 2013, Vilnius Quality in Statistics: Administrative Data and Official Statistics