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The roots of inequality : estimating inequality of opportunity from regression trees

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  • Brunori,Paolo
  • Hufe,Paul
  • Mahler,Daniel Gerszon

Abstract

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.

Suggested Citation

  • Brunori,Paolo & Hufe,Paul & Mahler,Daniel Gerszon, 2018. "The roots of inequality : estimating inequality of opportunity from regression trees," Policy Research Working Paper Series 8349, The World Bank.
  • Handle: RePEc:wbk:wbrwps:8349
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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