IDEAS home Printed from https://ideas.repec.org/p/ces/ifowps/_252.html
   My bibliography  Save this paper

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

Author

Listed:
  • Paolo Brunori
  • Paul Hufe

    ()

  • Gerszon Daniel Mahler

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 in equality 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.

Suggested Citation

  • Paolo Brunori & Paul Hufe & Gerszon Daniel Mahler, 2018. "The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees," ifo Working Paper Series 252, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
  • Handle: RePEc:ces:ifowps:_252
    as

    Download full text from publisher

    File URL: http://www.cesifo-group.de/DocDL/wp-2018-252-brunori-hufe-mahler-estimating-inequality.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Paolo Brunori & Vito Peragine & Laura Serlenga, 2016. "Upward and downward bias when measuring inequality of opportunity," SERIES 05-2016, Dipartimento di Economia e Finanza - Università degli Studi di Bari "Aldo Moro", revised Sep 2016.
    2. Francisco H. G. Ferreira & Jérémie Gignoux, 2011. "The Measurement Of Inequality Of Opportunity: Theory And An Application To Latin America," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 57(4), pages 622-657, December.
    3. Nicolas Pistolesi, 2009. "Inequality of opportunity in the land of opportunities, 1968–2001," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 7(4), pages 411-433, December.
    4. repec:spr:sochwe:v:49:y:2017:i:3:d:10.1007_s00355-017-1044-x is not listed on IDEAS
    5. Alain Trannoy & Sandy Tubeuf & Florence Jusot & Marion Devaux, 2010. "Inequality of opportunities in health in France: a first pass," Health Economics, John Wiley & Sons, Ltd., vol. 19(8), pages 921-938, August.
    6. Daniele Checchi & Vito Peragine, 2010. "Inequality of opportunity in Italy," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 8(4), pages 429-450, December.
    7. Marc Fleurbaey & Vito Peragine, 2013. "Ex Ante Versus Ex Post Equality of Opportunity," Economica, London School of Economics and Political Science, vol. 80(317), pages 118-130, January.
    8. Lefranc, Arnaud & Pistolesi, Nicolas & Trannoy, Alain, 2009. "Equality of opportunity and luck: Definitions and testable conditions, with an application to income in France," Journal of Public Economics, Elsevier, vol. 93(11-12), pages 1189-1207, December.
    9. repec:aea:jecper:v:31:y:2017:i:2:p:87-106 is not listed on IDEAS
    10. Cowell, Frank A & Victoria-Feser, Maria-Pia, 1996. "Robustness Properties of Inequality Measures," Econometrica, Econometric Society, vol. 64(1), pages 77-101, January.
    11. Fleurbaey, Marc, 2012. "Fairness, Responsibility, and Welfare," OUP Catalogue, Oxford University Press, number 9780199653591.
    12. García, Jorge Luis & Heckman, James J. & Ziff, Anna, 2017. "Gender Differences in the Benefits of an Influential Early Childhood Program," IZA Discussion Papers 10758, Institute for the Study of Labor (IZA).
    13. Fleurbaey Marc, 1995. "Three Solutions for the Compensation Problem," Journal of Economic Theory, Elsevier, vol. 65(2), pages 505-521, April.
    14. Veruska Oppedisano & Gilberto Turati, 2015. "What are the causes of educational inequality and of its evolution over time in Europe? Evidence from PISA," Education Economics, Taylor & Francis Journals, vol. 23(1), pages 3-24, February.
    15. repec:dau:papers:123456789/268 is not listed on IDEAS
    16. Paul Hufe & Andreas Peichl & John Roemer & Martin Ungerer, 2017. "Inequality of income acquisition: the role of childhood circumstances," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 49(3), pages 499-544, December.
    17. Paolo Li Donni & Juan Rodríguez & Pedro Rosa Dias, 2015. "Empirical definition of social types in the analysis of inequality of opportunity: a latent classes approach," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 44(3), pages 673-701, March.
    18. Francisco H.G. Ferreira & Jérémie Gignoux, 2011. "The Measurement of Inequality of Inequality of Opportunity: Theory and an Application to Latin America," Post-Print halshs-00754503, HAL.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. repec:ces:ifosdt:v:71:y:2018:i:05:p:18-22 is not listed on IDEAS

    More about this item

    Keywords

    Equality of opportunity; machine learning; random forests.;

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ifowps:_252. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Klaus Wohlrabe). General contact details of provider: http://edirc.repec.org/data/ifooode.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.