The Roots of Inequality Estimating Inequality of Opportunity from Regression Trees
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 minimiz...
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| Other Authors: | , |
| Format: | eBook |
| Language: | English |
| Published: |
Washington, D.C
The World Bank
2018
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| Series: | World Bank E-Library Archive
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| Online Access: | |
| Collection: | World Bank E-Library Archive - Collection details see MPG.ReNa |
| Summary: | 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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| Physical Description: | 35 pages |