The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees

Paolo Brunori, Paul Hufe and Daniel Gerszon Mahler

Working Papers - Economics from Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa

Abstract: We propose a set of new methods to estimate inequality of opportunity based on conditional inference regression trees. In particular, we illustrate how these methods represent a substantial improvement over existing empirical approaches to measure inequality of opportunity. First, they minimize the risk of arbitrary and ad-hoc model selection. Second, they provide a standardized way of trading off upward and downward biases in inequality of opportunity estimations. Finally, regression trees can be graphically represented; their structure is immediate to read and easy to understand. This will make the measurement of inequality of opportunity more easily comprehensible to a large audience. These advantages are illustrated by an empirical application based on the 2011 wave of the European Union Statistics on Income and Living Conditions.

Pages: 51 pages
Date: 2017
New Economics Papers: this item is included in nep-big
References: Add references at CitEc
Citations: View citations in EconPapers (16)

Downloads: (external link)
https://www.disei.unifi.it/upload/sub/pubblicazioni/repec/pdf/wp18_2017.pdf (application/pdf)

Related works:
Working Paper: The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees (2018)
Working Paper: The roots of inequality: Estimating inequality of opportunity from regression trees (2018)
Working Paper: The roots of inequality: estimating inequality of opportunity from regression trees (2018)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:frz:wpaper:wp2017_18.rdf

Access Statistics for this paper

More papers in Working Papers - Economics from Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa Via delle Pandette 9 50127 - Firenze - Italy. Contact information at EDIRC.
Bibliographic data for series maintained by Giorgio Ricchiuti (giorgio.ricchiuti@unifi.it).