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Imputation in EU-SILC survey

Imputation in EU-SILC survey. Andris Fisenko and Vita Kozirkova Central Statistical Bureau of Latvia. EU-SILC. "EU Statistics on Income and Living Conditions (EU-SILC)". This survey is conducted in all countries of the European Union. Variables. Total housing cost

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Imputation in EU-SILC survey

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  1. Imputation in EU-SILC survey Andris Fisenko and Vita KozirkovaCentral Statistical Bureau of Latvia

  2. EU-SILC "EU Statistics on Income and Living Conditions (EU-SILC)". This survey is conducted in all countries of the European Union.

  3. Variables • Total housing cost • Family/Children related allowances • Social exclusion • Housing allowances • Income received by people aged under 16 • Regular taxes on wealth • Regular inter-household cash transfer paid • Regular inter-household cash transfer received • Other

  4. Structure • Housholds level • Income per year is asked. • If refusal, then ask average and how often. • If answer is “ I don’t know” then IMPUTATION • Personal level • Differences for persons level • Average in one time or interval.

  5. Imputation methods • RMV (Replace Missing Values) • Hot deck & Cold deck • Mean/Median imputation • Nearest Neighbour • Regression • Other

  6. SPSS RMV- 1

  7. RMV - results

  8. Cold-deck • Does not bring new information • Very good benchmarking method • There is not data from the past • Method will be analysed in the future

  9. Random donor (Hot-deck) • The donor is chosen randomly within same group • Random overall imputation is not sensible • But random donor within imputation classes (or clusters, groups, ..) is important method

  10. Random donor (Hot-deck) • Firstly, the data is divided into homogenous sub groups by a a suitable method, e.g. easily sorting into categories by some explanatory variable. Secondly, the donors are chosen randomly within these new groups. • Many clustering methods are using the idea of nearest neighbours when determining a new grouping of the data.

  11. Multiple imputation • Creates m imputed data sets. • Hot deck+Multiple imputation

  12. Some results

  13. Some results

  14. What's next • Software • Linear regression • Auxiliary information from • State Revenue Service • State Social Insurance Agency • Regional governments • Banks

  15. Thank you for your attention!!!

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