The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach

Autores
Brunori, Paolo; Neidhöfer, Guido
Año de publicación
2020
Idioma
inglés
Tipo de recurso
documento de trabajo
Estado
versión enviada
Descripción
We show that measures of inequality of opportunity (IOP) fully consistent with Roemer (1998)'s IOP theory can be straightforwardly estimated by adopting a machine learning approach, and apply our novel method to analyse the development of IOP in Germany during the last three decades. Hereby, we take advantage of information contained in 25 waves of the Socio-Economic Panel. Our analysis shows that in Germany IOP declined immediately after reuni cation, increased in the rst decade of the century, and slightly declined again after 2010. Over the entire period, at the top of the distribution we always nd individuals that resided in West-Germany before the fall of the Berlin Wall, whose fathers had a high occupational position, and whose mothers had a high educational degree. East-German residents in 1989, with low educated parents, persistently qualify at the bottom.
Centro de Estudios Distributivos, Laborales y Sociales
Materia
Ciencias Económicas
Inequality
Opportunity
SOEP
Germany
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/92881

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spelling The Evolution of Inequality of Opportunity in Germany: A Machine Learning ApproachBrunori, PaoloNeidhöfer, GuidoCiencias EconómicasInequalityOpportunitySOEPGermanyWe show that measures of inequality of opportunity (IOP) fully consistent with Roemer (1998)'s IOP theory can be straightforwardly estimated by adopting a machine learning approach, and apply our novel method to analyse the development of IOP in Germany during the last three decades. Hereby, we take advantage of information contained in 25 waves of the Socio-Economic Panel. Our analysis shows that in Germany IOP declined immediately after reuni cation, increased in the rst decade of the century, and slightly declined again after 2010. Over the entire period, at the top of the distribution we always nd individuals that resided in West-Germany before the fall of the Berlin Wall, whose fathers had a high occupational position, and whose mothers had a high educational degree. East-German residents in 1989, with low educated parents, persistently qualify at the bottom.Centro de Estudios Distributivos, Laborales y Sociales2020-02-12info:eu-repo/semantics/workingPaperinfo:eu-repo/semantics/submittedVersionDocumento de trabajohttp://purl.org/coar/resource_type/c_8042info:ar-repo/semantics/documentoDeTrabajoapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/92881enginfo:eu-repo/semantics/altIdentifier/issn/1853-0168info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:51:28Zoai:sedici.unlp.edu.ar:10915/92881Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:51:28.95SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach
title The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach
spellingShingle The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach
Brunori, Paolo
Ciencias Económicas
Inequality
Opportunity
SOEP
Germany
title_short The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach
title_full The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach
title_fullStr The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach
title_full_unstemmed The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach
title_sort The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach
dc.creator.none.fl_str_mv Brunori, Paolo
Neidhöfer, Guido
author Brunori, Paolo
author_facet Brunori, Paolo
Neidhöfer, Guido
author_role author
author2 Neidhöfer, Guido
author2_role author
dc.subject.none.fl_str_mv Ciencias Económicas
Inequality
Opportunity
SOEP
Germany
topic Ciencias Económicas
Inequality
Opportunity
SOEP
Germany
dc.description.none.fl_txt_mv We show that measures of inequality of opportunity (IOP) fully consistent with Roemer (1998)'s IOP theory can be straightforwardly estimated by adopting a machine learning approach, and apply our novel method to analyse the development of IOP in Germany during the last three decades. Hereby, we take advantage of information contained in 25 waves of the Socio-Economic Panel. Our analysis shows that in Germany IOP declined immediately after reuni cation, increased in the rst decade of the century, and slightly declined again after 2010. Over the entire period, at the top of the distribution we always nd individuals that resided in West-Germany before the fall of the Berlin Wall, whose fathers had a high occupational position, and whose mothers had a high educational degree. East-German residents in 1989, with low educated parents, persistently qualify at the bottom.
Centro de Estudios Distributivos, Laborales y Sociales
description We show that measures of inequality of opportunity (IOP) fully consistent with Roemer (1998)'s IOP theory can be straightforwardly estimated by adopting a machine learning approach, and apply our novel method to analyse the development of IOP in Germany during the last three decades. Hereby, we take advantage of information contained in 25 waves of the Socio-Economic Panel. Our analysis shows that in Germany IOP declined immediately after reuni cation, increased in the rst decade of the century, and slightly declined again after 2010. Over the entire period, at the top of the distribution we always nd individuals that resided in West-Germany before the fall of the Berlin Wall, whose fathers had a high occupational position, and whose mothers had a high educational degree. East-German residents in 1989, with low educated parents, persistently qualify at the bottom.
publishDate 2020
dc.date.none.fl_str_mv 2020-02-12
dc.type.none.fl_str_mv info:eu-repo/semantics/workingPaper
info:eu-repo/semantics/submittedVersion
Documento de trabajo
http://purl.org/coar/resource_type/c_8042
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dc.language.none.fl_str_mv eng
language eng
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Creative Commons Attribution 4.0 International (CC BY 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
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