The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees and Forests
Paolo Brunori (),
Paul Hufe () and
Daniel Gerszon Mahler ()
Additional contact information
Paolo Brunori: London School of Economics
Paul Hufe: University of Bristol
Daniel Gerszon Mahler: World Bank
No 14689, IZA Discussion Papers from Institute of Labor Economics (IZA)
In this paper we propose the use of machine learning methods to estimate inequality of opportunity. We illustrate how our proposed methods—conditional inference regression trees and forests—represent a substantial improvement over existing estimation approaches. First, they reduce the risk of ad-hoc model selection. Second, they establish estimation models by trading off upward and downward bias in inequality of opportunity estimates. The advantages of regression trees and forests are illustrated by an empirical application for a cross-section of 31 European countries. We show that arbitrary model selection may lead to significant biases in inequality of opportunity estimates relative to our preferred method. These biases are reflected in both point estimates and country rankings. Our results illustrate the practical importance of leveraging machine learning algorithms to avoid giving misleading information about the level of inequality of opportunity in different societies to policymakers and the general public.
Keywords: equality of opportunity; machine learning; random forests (search for similar items in EconPapers)
JEL-codes: C38 D31 D63 (search for similar items in EconPapers)
Pages: 84 pages
New Economics Papers: this item is included in nep-big, nep-cmp, nep-isf and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:iza:izadps:dp14689
Ordering information: This working paper can be ordered from
IZA, Margard Ody, P.O. Box 7240, D-53072 Bonn, Germany
Access Statistics for this paper
More papers in IZA Discussion Papers from Institute of Labor Economics (IZA) IZA, P.O. Box 7240, D-53072 Bonn, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Holger Hinte ().