Estimation of Employment for Cities, Towns and Rural Districts. Workshop of BNU Network on Survey Statistics Tallinn, August 25 – 28, 2014. Olha Lysa Ptoukha Institute for Demography and Social Studies, National Academy of Science of Ukraine Kyiv, Ukraine. Task.
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Workshop of BNU Network on Survey Statistics
Tallinn, August 25 – 28, 2014
PtoukhaInstitute for Demography and Social Studies,
National Academy of Science of Ukraine
To estimate the employment rate for cities, towns and rural districts (administrative territorial units - ATU) of Ukraine based on the annual LFS dataset
Data Sources Districts
Survey description Districts
I. Direct estimation Districts
– Districtscomposite estimate;
– direct estimate;
– weighting coefficientII. Microlevel Model
1) Gender: M– male;
2) Type of area:
3) Age grope:
A_2 –25–29 years old;
A_3 –30–34 years old;
A_4– 35–39 years old;
A_5 –40–44 years old;
A_6 –45–49 years old;
A_7 –50–54 years old;
A_8 –55–59 years old;
A_9– 60–69 years old.
Composition between regression and direct estimates:
– Districts composite estimate for ATU;
– composite estimate based on microlevel model for ATU;
– direct estimate for region what includes the estimated ATU;
– composite estimate for ATU from previous survey(year);
– weighting coefficientsIII. Multilevel Composite Estimator
Proposed approach based on multilevel composite two-stage estimation.
Results of implementation in a simulation show improvement in accuracy of employment rate estimates for the cities, towns and rural districts. The RRMSE of estimates of ATUs was reduced by 45% on average.
Using a microlevel model decreases variation between estimates of employment rate in ATUs
We can obtain estimates for ATUs that are not in the sample.