Model based estimation of indicators of poverty and social exclusion
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www.statistik.at We provide information
Model based estimation of indicators of poverty and social exclusion
Thomas GlaserStatistics Austria
Directorate Social Statistics
European Conference on Quality in official Statistics
5th June 2014
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Overview
o Europe 2020 indicators: Break in time series
o Data basis for modelling: EU-SILC 2011
o Different modelling variants
o Application of modelled register data effect toEU-SILC 2008-2010
o Conclusions and outlook
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Register based household income
o Usage of register from EU-SILC 2012 onwards
o Results in a break in time series for income based Europe 2020 indicatorso At-risk-of-poverty: AROP(REG)
o At-risk-of-poverty or social exclusion: AROPE(REG)
o Data from income registers also availablefor EU-SILC 2011
o Revision of time series 2008-2012 desired
o No income register data for 2008-2010 available yet
o Model based register household income as solution
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Choice of models: Variant 1
o Direct estimation of indicators
o Likelihood of AROP(REG) and AROPE(REG) estimated by logistic regressions
o Estimate of indicators: mean value of estimated probabilities on personal level
o Advantage:
o Direct estimation of indicators
o Disadvantages:
o Possibility of inconsistent estimates of indicators
o Only moderate model fit
o Underestimation of AROP(REG) and AROPE(REG)
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Choice of models: Variant 2
o Estimation of register based household income HINC(REG)
o Linear regression: Natural log of HINC(REG) as dependent variable
o Estimation of indicators o Equivalised income from with interview based data
o Calculation of AROP(REG) and AROPE(REG)
o Advantages: o Consistent indicators
o Estimates of household income on sample level
o Very good model fit (R2=89%)
o Disadvantages: o Loss of variance due to regression
o Underestimation of AROP(REG) and AROPE(REG)
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Choice of models: Variant 2a
o Addition of iid N(0,σ2) stochastic error terms to estimates resulting from linear regression in variant 2
o Advantages:
o Compensation of tendency towards the mean
o Estimated HINC(REG) distribution similar to HINC(REG)
o Estimates close to actual AROP(REG) and AROPE(REG) (EU-SILC 2011)
o Disadvantage:
o Additional variance contains no additional information on structure of household income
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Choice of models: Variant 3
o Estimation of difference HINC - HINC(REG)
o Two step modelling
o 1) Classification of relevant difference (discriminant analysis)
o 2) Linear regression similar to variant 2 for difference
o Estimated difference is added to HINC
o Advantages:
o Explicit estimation of register data effect
o Disadvantages:
o Overestimation of AROP(REG) and AROPE(REG)
o Low model fit
o Errors of two modelling steps
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Weighting
o Calibration incorporates register income data
o Additional modelling step for estimated weights in every variant would be necessary
o All models fitted without weights
o Characteristics relevant for weighting are also predictors in the models
o Marginal differences weighted – unweighted
o OLS most efficient for linear regression
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Chosen model
o Variant 2a: Estimation of register based household income including iid N(0,σ2) stochastic error terms
o More advantages than disadvantages
o Easy application
o Coefficients from regression and stochastic error terms were applied to interview based data of EU-SILC 2008-2010
o Socio-economic structure reflected in predictor variables for each year can be incorporated in estimation
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Register and interview based time series
Source: Statistics Austria, EU-SILC 2008-2012 (interview and register income data).
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2008 2009 2010 2011 2012
in %
AROP
AROP(REG)
AROPE
AROPE(REG)
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Conclusions and outlook
o Unbroken time series of Europe 2020 indicators for EU-SILC 2008-2012 achieved
o Europe 2020 targets can be measured from 2008 onwards with register based indicators
o Next task: recalculation of register based household income for EU-SILC 2008-2010
o Revision of EU-SILC micro-data 2008-2011 until 09/2014
o Publication of revised time-series 2008-2013 in autumn/winter 2014
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www.statistik.at slide 12 | 5th June 2014
Please address queries to:Thomas Glaser
Contact information:Guglgasse 13, 1110 Vienna
Thank you for your attention!