Small Area Estimation 1 -Small area estimation problem 2 - Estimation for domains - Direct estimators – estimation for planned domains 3 – Coefficient of Variation and Minimum level of precision 4- Estimation for unplanned domains and/or where the sample size is not enough for the minimum level of precision – Indirect estimators
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Small Area Estimation - Small Area methods for ...
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Comparison Between Direct,SyntheticandCompositeEstimator
Empirical comparison of small area estimation methods for the Italian Labor Force Survey (LFS)
• Performance of small area estimators are studied by simulating sample selection from 1981 Population Census.
• Samples are 400samplereplicates (h),each ofidentical sizeoftheLFSsampledrawn following the LFS design (two stages with stratication)
• Design-based properties of the estimators: verification of itsBias and calculation of the CV of the estimator
Tzavidis,Salvati,Marchetti(MOOC2020)
Comparison Between Direct,SyntheticandCompositeEstimator
Empirical comparison of small area estimation methods for the Italian Labor Force Survey (LFS)
• Activepopulation,aged 15-64- annual averages - According tothedefinitions ofthe InternationalLabour Organisation (ILO)forthepurposes ofthelabour marketstatistics people areclassified as employed,unemployed andeconomicallyinactive.Theeconomically active population is thesumofemployed andunemployed persons.Inactive persons arethose who,during thereference week,were neither employed nor unemployed.
• Example - 14Health ServiceAreas (HSA)oftheFriuliVeneziaGiuliaRegion areconsidered tobesmallareas
• Yi – true mean ofthey variable inthedomain i (HSA)– annual average ofactivepopulation (known fromtheCensus)
Tzavidis,Salvati,Marchetti(MOOC2020)
Comparison Between Direct,SyntheticandCompositeEstimator
Comparison Between Direct,SyntheticandCompositeEstimator