Application of the EU-SILC 2011 data module “intergenerational transmission of disadvantage” to robust analysis of inequality of opportunity
This data article describes the original data, the sample selection process and the variables used in Andreoli and Fusco (Andreoli and Fusco, 2019) to estimate gap curves for a sample of European countries. Raw data are from 2011 roaster of EU-SILC, cross-sectional sample of module “intergenerationa...
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doaj-4354e4d2dda04508babd3f053bc2be7e2020-11-25T02:15:20ZengElsevierData in Brief2352-34092019-08-0125Application of the EU-SILC 2011 data module “intergenerational transmission of disadvantage” to robust analysis of inequality of opportunityFrancesco Andreoli0Alessio Fusco1Department of Economics, University of Verona, Via Cantarane 24, 37129, Verona, Italy; Luxembourg Institute of Socio-Economic Research – LISER, 10 Porte des Sciences, L-4366, Esch-sur-Alzette, Luxembourg; Corresponding author. Department of Economics, University of Verona, Via Cantarane 24, 37129, Verona, Italy.Luxembourg Institute of Socio-Economic Research – LISER, 10 Porte des Sciences, L-4366, Esch-sur-Alzette, LuxembourgThis data article describes the original data, the sample selection process and the variables used in Andreoli and Fusco (Andreoli and Fusco, 2019) to estimate gap curves for a sample of European countries. Raw data are from 2011 roaster of EU-SILC, cross-sectional sample of module “intergenerational transmission of disadvantage”. This article reports descriptive statistics of the using sample. It also discusses the algorithm adopted to estimate the main effects and details the content of additional Stata files stored on the online repository. These additional files contain raw estimates from bootstrapped samples, which form the basis for estimating gap curves and their variance-covariance matrices. The data article also reports representations of gap curves for all 16 selected countries. Keywords: Inequality, Survey data, Intergenerational, Cohort, Earnings, Gap curves, Europehttp://www.sciencedirect.com/science/article/pii/S2352340919306559 |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Francesco Andreoli Alessio Fusco |
spellingShingle |
Francesco Andreoli Alessio Fusco Application of the EU-SILC 2011 data module “intergenerational transmission of disadvantage” to robust analysis of inequality of opportunity Data in Brief |
author_facet |
Francesco Andreoli Alessio Fusco |
author_sort |
Francesco Andreoli |
title |
Application of the EU-SILC 2011 data module “intergenerational transmission of disadvantage” to robust analysis of inequality of opportunity |
title_short |
Application of the EU-SILC 2011 data module “intergenerational transmission of disadvantage” to robust analysis of inequality of opportunity |
title_full |
Application of the EU-SILC 2011 data module “intergenerational transmission of disadvantage” to robust analysis of inequality of opportunity |
title_fullStr |
Application of the EU-SILC 2011 data module “intergenerational transmission of disadvantage” to robust analysis of inequality of opportunity |
title_full_unstemmed |
Application of the EU-SILC 2011 data module “intergenerational transmission of disadvantage” to robust analysis of inequality of opportunity |
title_sort |
application of the eu-silc 2011 data module “intergenerational transmission of disadvantage” to robust analysis of inequality of opportunity |
publisher |
Elsevier |
series |
Data in Brief |
issn |
2352-3409 |
publishDate |
2019-08-01 |
description |
This data article describes the original data, the sample selection process and the variables used in Andreoli and Fusco (Andreoli and Fusco, 2019) to estimate gap curves for a sample of European countries. Raw data are from 2011 roaster of EU-SILC, cross-sectional sample of module “intergenerational transmission of disadvantage”. This article reports descriptive statistics of the using sample. It also discusses the algorithm adopted to estimate the main effects and details the content of additional Stata files stored on the online repository. These additional files contain raw estimates from bootstrapped samples, which form the basis for estimating gap curves and their variance-covariance matrices. The data article also reports representations of gap curves for all 16 selected countries. Keywords: Inequality, Survey data, Intergenerational, Cohort, Earnings, Gap curves, Europe |
url |
http://www.sciencedirect.com/science/article/pii/S2352340919306559 |
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