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221013 ||| eng |
| 100 |
1 |
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|a Brunori, Paolo
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| 245 |
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|a The Roots of Inequality
|h Elektronische Ressource
|b Estimating Inequality of Opportunity from Regression Trees
|c Brunori, Paolo
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| 260 |
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|a Washington, D.C
|b The World Bank
|c 2018
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| 300 |
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|a 35 pages
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| 700 |
1 |
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|a Mahler, Daniel Gerszon
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| 700 |
1 |
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|a Brunori, Paolo
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| 700 |
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|a Hufe, Paul
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b WOBA
|a World Bank E-Library Archive
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| 490 |
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|a World Bank E-Library Archive
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| 028 |
5 |
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|a 10.1596/1813-9450-8349
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| 856 |
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|u http://elibrary.worldbank.org/doi/book/10.1596/1813-9450-8349
|x Verlag
|3 Volltext
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| 082 |
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|a 330
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| 520 |
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|a This paper proposes a set of new methods to estimate inequality of opportunity based on conditional inference regression trees. It illustrates how these methods represent a substantial improvement over existing empirical approaches to measure inequality of opportunity. First, the new methods minimize the risk of arbitrary and ad hoc model selection. Second, they provide a standardized way to trade 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
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