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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Main Authors: Francesco Andreoli, Alessio Fusco
Format: Article
Language:English
Published: Elsevier 2019-08-01
Series:Data in Brief
Online Access:http://www.sciencedirect.com/science/article/pii/S2352340919306559
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spelling 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
collection 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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