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

Publikation: Working paperForskning

Standard

The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees. / Brunori, Paolo; Hufe, Paul; Mahler, Daniel Gerszon.

2017.

Publikation: Working paperForskning

Harvard

Brunori, P, Hufe, P & Mahler, DG 2017 'The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees'. <https://www.disei.unifi.it/upload/sub/pubblicazioni/repec/pdf/wp18_2017.pdf>

APA

Brunori, P., Hufe, P., & Mahler, D. G. (2017). The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees. DISEI - Università degli Studi di Firenze - Working Papers Bind 2017 Nr. 18 https://www.disei.unifi.it/upload/sub/pubblicazioni/repec/pdf/wp18_2017.pdf

Vancouver

Brunori P, Hufe P, Mahler DG. The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees. 2017.

Author

Brunori, Paolo ; Hufe, Paul ; Mahler, Daniel Gerszon. / The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees. 2017. (DISEI - Università degli Studi di Firenze - Working Papers; Nr. 18, Bind 2017).

Bibtex

@techreport{cf2305d03e1647b7ab6f487a1b099e64,
title = "The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees",
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.",
author = "Paolo Brunori and Paul Hufe and Mahler, {Daniel Gerszon}",
year = "2017",
language = "English",
series = "DISEI - Universit{\`a} degli Studi di Firenze - Working Papers",
number = "18",
type = "WorkingPaper",

}

RIS

TY - UNPB

T1 - The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees

AU - Brunori, Paolo

AU - Hufe, Paul

AU - Mahler, Daniel Gerszon

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

M3 - Working paper

T3 - DISEI - Università degli Studi di Firenze - Working Papers

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

ER -

ID: 187243302