1 / 15

Improving of Household Sample Surveys Data Quality on Base of Statistical Matching Approaches

Improving of Household Sample Surveys Data Quality on Base of Statistical Matching Approaches. Ganna Tereshchenko Institute for Demography and Social Research, Kyiv, Ukraine. The European Conference on Quality in Official Statistics Rome, 8-11 July 2008.

pegeen
Télécharger la présentation

Improving of Household Sample Surveys Data Quality on Base of Statistical Matching Approaches

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Improving of Household Sample Surveys Data Quality on Base of Statistical Matching Approaches Ganna Tereshchenko Institute for Demography and Social Research, Kyiv, Ukraine The European Conference on Quality in Official Statistics Rome, 8-11 July 2008

  2. Measurement of Employment and Unemployment Main source isThe State Sample Survey of Economic Activity of Population(LFS): • is conducted by State Statistics Committee of Ukraine by ILO methodology, according to international standards • population in the age of 15–70 yearsis surveyed • is conducted since 1995: in 1995–1998 once a year, in 1999–2003 – quarterly, since 2004 – monthly • LFS samplecover all regions of Ukraine by type of settlements: urban area (cities, towns) and rural area • size of monthly LFS sample is 32,5 thousands of surveyed households

  3. Reliability of unemployment rate annual estimates

  4. Improvement of reliability of LFS indicator estimates for rural areabased on statistical matching approach • Using of two probability stratified two stage samples: sample of LFS and sample of household agricultural activity survey (AAS) • Sample design in AAS is differ from LFS: In AAS households are selected in the second stage with probability proportionally to their area of agricultural allotment, in LFS – on base of the procedure of systematic selection • The size of monthly LFS sample in the rural area makes approximately 3,6 thousand households • The size of AAS sample of households which have to be interviewed under LFS questionnaire is 7,4 thousand households • Total size of monthly sample for interview under LFS questionnaire in the rural area due to AAS has increased three times and is equal to11,1 thousand households

  5. Rates of employment and unemployment by regions of Ukraine, February, 2007

  6. Composite estimation

  7. Calculation of optimal weights coefficients and where – standard error of estimate of employed population number on LFS sample; – standard error of estimate of employed population number on AAS sample; – standard error of estimate of unemployed population number on LFS sample; – standard error of estimate of unemployed population number on AAS sample, is the bias of estimate of number of employed population by data of AAS, calculated as average of biases for current and the two previous months, is the bias of estimate of number of unemployed population by data of AAS, calculated as average of biases for current and the two previous months.

  8. Calculation of coefficients for adjustment of the resulted employed and unemployed persons weights in rural area On the first stage value of is calculated for employed and unemployed persons in rural area by the formula: The corrected statistical weights of employed and unemployed persons in rural area of each region are calculated by the formula:

  9. Calculation of coefficients for adjustment of the resulted economically inactive persons weights in rural area On the second stage value of is calculated for economically inactive persons in rural area for each region by the formula: where – total number of able-bodied population in rural area of region, calculated on external data; – estimate of employed population number on LFS sample in view of corrected statistical weights ; – estimate of employed population number on AAS sample in view of corrected statistical weights ; – estimate of unemployed population number on LFS sample in view of corrected statistical weights ; – estimate of employed population number on AAS sample in view of corrected statistical weights ; – estimate of economically inactive population number on LFSP sample in view of corrected statistical weights ; – estimate of economically inactive population number on AAS sample in view of corrected statistical weights

  10. Reliability of employment rate monthly estimates in rural area before and after statistical matching of the LFS data, February, 2007

  11. Reliability of unemployment rate monthly estimates in rural area before and after statistical matching of the LFS data, February, 2007

  12. Potential problem with comparability of unemployment rate estimates by regions Share of incomparable estimates where – number of regions

  13. Relative efficiency of matching procedure by regions, February, 2007

  14. Conclusions • Statistical matching of the labour force survey data, received on samples with different design has allowed improving the reliability level of employment and unemployment indicators estimation in rural area. • At the same time there is a potential problem with providing of data comparability • It is necessary to take into account that the volume of the information for processing grows and estimation procedures are complicated

  15. Thank you for attention! Ganna Tereshchenko Institute for Demography and Social Research of National Academy of Sciences of Ukraine Kyiv, Ukraine a_tereschenko@ukr.net

More Related