dc.creatorBrunori, Paolo
dc.creatorNeidhöfer, Guido
dc.date2020-02-12
dc.date2020-04-06T15:09:09Z
dc.date.accessioned2023-07-14T19:10:17Z
dc.date.available2023-07-14T19:10:17Z
dc.identifierhttp://sedici.unlp.edu.ar/handle/10915/92881
dc.identifierissn:1853-0168
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7434266
dc.descriptionWe 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.
dc.descriptionCentro de Estudios Distributivos, Laborales y Sociales
dc.formatapplication/pdf
dc.languageen
dc.rightshttp://creativecommons.org/licenses/by/4.0/
dc.rightsCreative Commons Attribution 4.0 International (CC BY 4.0)
dc.subjectCiencias Económicas
dc.subjectInequality
dc.subjectOpportunity
dc.subjectSOEP
dc.subjectGermany
dc.titleThe Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach
dc.typeArticulo
dc.typeDocumento de trabajo


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