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

54 Pages Posted: 9 Apr 2020

See all articles by Paolo Brunori

Paolo Brunori

University of Florence

Guido Neidhöfer

ZEW – Leibniz Centre for European Economic Research

Date Written: 2020

Abstract

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 reunication, increased in the first decade of the century, and slightly declined again after 2010. Over the entire period, at the top of the distribution we always find 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.

Keywords: Inequality, Opportunity, SOEP, Germany.

JEL Classification: D63, D30, D31

Suggested Citation

Brunori, Paolo and Neidhöfer, Guido, The Evolution of Inequality of Opportunity in Germany: A Machine Learning Approach (2020). ZEW - Centre for European Economic Research Discussion Paper No. 20-013, Available at SSRN: https://ssrn.com/abstract=3570385 or http://dx.doi.org/10.2139/ssrn.3570385

Paolo Brunori (Contact Author)

University of Florence ( email )

Piazza di San Marco, 4
Florence, 50121
Italy

Guido Neidhöfer

ZEW – Leibniz Centre for European Economic Research ( email )

P.O. Box 10 34 43
L 7,1
D-68034 Mannheim, 68034
Germany

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