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Using administrative registers in sample surveys

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16 diapositives · 336 Views · Oct 03, 2014

This paper presented at the European Conference on Quality in Official Statistics explores the use of administrative data in sample surveys conducted by Statistics Estonia. It highlights the stages where administrative registers contribute, such as survey frame establishment, sample design, and questionnaire pre-filling. Furthermore, it discusses statistical categories like the Statistical Business Register and Population Register, the significance of good-quality data in ensuring the reliability of survey results, and the ongoing efforts to improve the integration and use of administrative sources.

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  1. Using administrative registers in sample surveys European Conference on Quality in Official Statistics 3-–6 May 2010 Kaja Sõstra Statistics Estonia

  2. Outline • Administrative data are used during different stages of sample survey: • establishing the survey frame • sample design • pre-filling of survey questionnaire • calculating weights • imputation • small area estimation

  3. Examples of sample surveys and frames in Statistics Estonia

  4. Statistical registers • Statistics Estonia has two main statistical registers based mainly on administrative sources: • Statistical business register • Commercial register • Register of taxable persons • other registers • Statistical register of agricultural holdings • Register of agricultural support and land parcels • Register of taxable persons

  5. Sample design (1) • Samples for surveys of economical units are selected every year in November • Administrative data is used for • Stratification (economic activity, size class) • Sample allocation (turnover, number of employees) • Detection of outliers

  6. Sample selection (2) • Samples for household surveys are selected in the end of each year by Population Register • Statistics Estonia gives conditions for • establishing frame (age limits), • stratification (sex, age, place of residence), • sample size by stratas • Sample is drawn using stratified systematic sampling • Sample information is periodically updated by Population Register (deaths, migration)

  7. Problems with frames • Lack of data for establishing correct frame • Immigrant population includes persons who´s parents were born abroad. Data about parents was missing for about 80% of persons • Data about institutions is missing • Incorrect contact information in Population Register – incorrect addresses cause high nonresponse and increase cost of fieldwork

  8. Pre-filling of questionnaires • New development in Statistics Estonia • Decreases response burden, saves time of respondent • Mainly the data from previous period of the same survey is used • New developments for using administrative data: • annual bookkeeping reports for SBS from Commercial register • Data of agricultural support and land parcels

  9. Calculation weights • Calculation weights consists of three steps • Design weight • Nonresponse adjustment weight • Calibration weight • Administrative data is used during all steps

  10. Nonresponse adjustment • Nonresponse is increasing problem in household surveys • Usually only administrative data is known for nonrespondents • Response probability is estimated for every household or person • Design weight is adjusted according to estimated response probability

  11. Response rates by age and sex % 100 80 60 40 20 0 15-64 65-74 75-84 15-64 65-74 75-84 Male Female Average Harju and Rapla county

  12. Population size and survey estimates by age group, males Thousand 60 50 40 30 20 10 0 15-19 40-44 45-49 50-54 65-69 70-74 75-79 80-84 20-24 25-29 30-34 35-39 55-59 60-64 Population size Estimated number of persons

  13. Calibration • Calibration of weights is a final step of weighting in all household surveys • First trial to calibrate weights of agricultural survey has done • Calibration groups in labour force survey: • Sex x 5-year age group (24 groups) • Place of residence (15 counties and capital) • Place of residence (urban, rural) • Nationality (Estonian, non-Estonian)

  14. Imputation • Administrative data is used for cold-deck imputation • Surveys of economic units: • VAT, social insurance, annual bookkeeping reports • Household surveys • personal income tax for imputation income variables

  15. Conclusions • Good quality of administrative registers is important to ensure quality of sample surveys • There are plans to increase use of administrative data for sample surveys in Statistics Estonia • Establishing statistical population register • Pre-filling of questionnaires • Collecting part of data from registers • Continuous development and updating administrative registers and cooperation is important for improving quality of all statistical activities

  16. Thank you • for your attention!