Digging at the Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees
Paolo Brunori, Paul Hufe, Daniel Gerzson Mahler.
We propose a new method to estimate inequality of opportunity based on conditional inference regression trees. In particular, we illustrate how the method represents a substantial improvement over existing empirical approaches to measure inequality of opportunity. First, regression trees minimize the risk of arbitrary and ad-hoc model specification. Second, they take into account and control for the risk of model overfitting. Third, regression trees can be graphically represented; their structure is immediate to read and easy to understand. Finally, random forests, which build upon regression trees, can be constructed to improve predictive performance. These advantages are illustrated by an empirical application based on the 2011 wave of the European Union Statistics on Income and Living Conditions.
Presented by:
Paolo Brunori, University of Florence & University of Bari
Date & time:
20 Nov 2017 16:00 pm - 20 Nov 2017 17:30 pm
Venue:
ISER Large Seminar Room, 2N2 4.16
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