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Longitudinal Weights for Flow Estimates

This presentation discusses the longitudinal dimension of the Austrian LFS, bias analysis, imputation, and weighting methods used for the production of transitions and flow estimates. It highlights the differences between mobile and immobile persons and outlines the preferred weighting option for bias reduction.

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Longitudinal Weights for Flow Estimates

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  1. Longitudinal Weights for the Production of Transitions and Flow Estimates Katrin Baumgartner Angelika Meraner Alexander Kowarik Statistics Austria Rome 16 May 2014 9th Workshop on Labour Force Survey Methodology

  2. Introduction • Longitudinal Dimension of the Austrian LFS • Bias Analysis • Imputation • Weighting • Summary

  3. Longitudinal Dimension ofthe Austrian LFS • Is not in focus so far • Depends on the survey design • Only available for a subset of LFS sample • Every quarter: exchange of 1/5 of the survey • Household stays 5 consecutive quarters in the survey

  4. Longitudinal Dimension of the Austrian LFS • Cross sectional point of view: quarter consists of 5 waves (rotation numbers) • Longitudinal point of view: a rotation number appears in 5 quarters • Q-Q-Changes: approximately 4/5 of the LFS sample can be used • Y-Y-Changes: approximately 1/5 of the LFS sample can be used

  5. Longitudinal Analysis Can be based on different subsamples: • One removes all incomplete cases for the flow analysis, i.e. flows are based on the subsample of persons who are successfully surveyed in both quarters, q(t) and q(t+1) (immobile persons). • All persons who are successfully surveyed in one quarter, q(t) or q(t+1) and do not regularly rotate in or out, are used (mobile + immobile persons). Potentially missing information of the second q(t+1) and first quarter q(t) respectively is imputed.

  6. Bias Analysis Are thereanydifferencesbetween mobile and immobile persons in their sociodemographic structure? • Linking to administrative datafrom Central Population Register • Information of mobile personsisonlyavailableforonequarter: first q(t) orsecond q(t+1).

  7. Bias Analysis (Q1 2012)

  8. Bias Analysis (Q1 2012)

  9. Bias Analysis (Q1 2012) S.: Microcensus-LFS 2012 Q1 2012. – Unweighted sample population in Q4 2011 and Q1 2012 (aged 15 to 64). Register labour status for mobile and immobile persons with administrative identifier (bPK).

  10. Bias Analysis – Flows (Q4 2011 + Q1 2012) S.: Microcensus-LFS 2012– Unweighted sample population in Q4 2011 and Q1 2012 (aged 15 to 64). Register labour status for mobile and immobile persons with administrative identifier (bPK).

  11. Imputation Proportions of imputed missing values for longitudinal data sets:

  12. Imputation Random hot deck imputation of important labour market characteristics

  13. Weighting: Longitudinal Weights

  14. Weighting: Longitudinal Weights Two versions of weights: • Reducing the bias: not calibrating against the ILO labour market status • Providing consistency between stocks and flows: additionally calibrating against the ILO labour market status (LMS adj) Key figures for ILO labour market status stem from published quarterly results of the microcensus-> projected data

  15. Weights 1: Reducing the bias Base weights calibrated against marginal totals for q(t) and q(t+1) consecutively • Population by NUTS-2 region, sex and age • Population by NUTS-2 region and nationality • Weights corresponding to people born, deceased, immigrated or emigrated in q(t) are calibrated against the natural population change and the migration statistics

  16. Weights 2: Consistency of stocks and flows Base weights calibrated against marginal totals for q(t) and q(t+1) consecutively • Population by NUTS-2 region, sex and age • Population by NUTS-2 region and nationality • Population by nationality, sex, age and ILO labour status • Weights corresponding to people born, deceased, immigrated or emigrated in q(t) are calibrated against the natural population change and the migration statistics

  17. Comparison Comparison of weighting options 1 and 2 for cross-sectional data Q4 2011 of population living in private households aged 15-64 without persons doing their military or civilian service according to ILO labour status.

  18. Comparison Comparison of weighting options 1 and 2 for flows corresponding to longitudinal data comprising Q4 2011 and Q4 2012, i.e. the population living in private households at both time points, aged 15-64 and not doing their military or civilian service according to ILO labour status.

  19. Summary • Obvious differences between immobile and mobile persons for demographic characteristics and administrative labourstatus • Random hot deck imputation of missing data • Longitudinal concept incorporated • Use of administrative labour status • Weighting option 1 preferred • Bias reducing • Not adjusted to ILO Labour Market Status -> not providing consistency between stocks and flows

  20. Please address queries to: Katrin Baumgartner Angelika Meraner Alexander Kowarik Contact information: Guglgasse 13, 1110 Vienna phone: +43 (1) 71128-7211 katrin.baumgartner@statistik.gv.at Thank you very much for your attention

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