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Differences Between Household Income from Surveys and Registers and How These Affect the Poverty Headcount: Evidence from the Austrian SILC

Overview of attention for article published in Social Indicators Research, June 2017
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  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

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1 policy source
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Citations

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27 Dimensions

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24 Mendeley
Title
Differences Between Household Income from Surveys and Registers and How These Affect the Poverty Headcount: Evidence from the Austrian SILC
Published in
Social Indicators Research, June 2017
DOI 10.1007/s11205-017-1672-7
Pubmed ID
Authors

Stefan Angel, Richard Heuberger, Nadja Lamei

Abstract

We take advantage of the fact that for the Austrian SILC 2008-2011, two data sources are available in parallel for the same households: register-based and survey-based income data. Thus, we aim to explain which households tend to under- or over-report their household income by estimating multinomial logit and OLS models with covariates referring to the interview situation, employment status and socio-demographic household characteristics. Furthermore, we analyze source-specific differences in the distribution of household income and how these differences affect aggregate poverty indicators based on household income. The analysis reveals an increase in the cross-sectional poverty rates for 2008-2011 and the longitudinal poverty rate if register data rather than survey data are used. These changes in the poverty rate are mainly driven by differences in employment income rather than sampling weights and other income components. Regression results show a pattern of mean-reverting errors when comparing household income between the two data sources. Furthermore, differences between data sources for both under-reporting and over-reporting slightly decrease with the number of panel waves in which a household participated. Among the other variables analyzed that are related to the interview situation (mode, proxy, interview month), only the number of proxy interviews was (weakly) positively correlated with the difference between data sources, although this outcome was not robust over different model specifications.

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 29%
Student > Master 3 13%
Student > Ph. D. Student 3 13%
Student > Postgraduate 2 8%
Lecturer 1 4%
Other 4 17%
Unknown 4 17%
Readers by discipline Count As %
Social Sciences 8 33%
Economics, Econometrics and Finance 4 17%
Business, Management and Accounting 2 8%
Psychology 2 8%
Computer Science 1 4%
Other 3 13%
Unknown 4 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 December 2021.
All research outputs
#6,587,550
of 24,529,782 outputs
Outputs from Social Indicators Research
#617
of 1,849 outputs
Outputs of similar age
#98,421
of 321,759 outputs
Outputs of similar age from Social Indicators Research
#8
of 27 outputs
Altmetric has tracked 24,529,782 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 1,849 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one has gotten more attention than average, scoring higher than 66% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 321,759 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.