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

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...

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Detalles Bibliográficos
Autores principales: Brunori, Paolo, Neidhöfer, Guido
Formato: Articulo Documento de trabajo
Lenguaje:Inglés
Publicado: 2020
Materias:
Ciencias Económicas
Inequality
Opportunity
SOEP
Germany
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/92881
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-92881
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Económicas
Inequality
Opportunity
SOEP
Germany
spellingShingle Ciencias Económicas
Inequality
Opportunity
SOEP
Germany
Brunori, Paolo
Neidhöfer, Guido
The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach
topic_facet Ciencias Económicas
Inequality
Opportunity
SOEP
Germany
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.
format Articulo
Documento de trabajo
author Brunori, Paolo
Neidhöfer, Guido
author_facet Brunori, Paolo
Neidhöfer, Guido
author_sort Brunori, Paolo
title The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach
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 evolution of inequality of opportunity in germany: a machine learning approach
publishDate 2020
url http://sedici.unlp.edu.ar/handle/10915/92881
work_keys_str_mv AT brunoripaolo theevolutionofinequalityofopportunityingermanyamachinelearningapproach
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AT neidhoferguido evolutionofinequalityofopportunityingermanyamachinelearningapproach
bdutipo_str Repositorios
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