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Lower Bounds and the Linearity Assumption in Parametric Estimations of Inequality of Opportunity

Author

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  • Hufe, Paul

    (University of Bristol)

  • Peichl, Andreas

    (Ludwig-Maximilians-Universität München)

Abstract

The consistent underestimation of inequality of opportunity has led some scholars to call into question the usefulness of such estimates. In this paper we argue that neglecting heterogeneity in the influence of circumstances across types as well as neglecting heterogeneity in type-specific effort distributions are two important sources of the downward bias in inequality of opportunity measures. Compared to the standard parametric approach of ex ante measurement of inequality of opportunity, we calculate a 50% upwards correction when accounting for both sources of heterogeneity. Therefore, taking heterogeneity across types seriously is an important step towards strengthening the policy relevance of this concept.

Suggested Citation

  • Hufe, Paul & Peichl, Andreas, 2015. "Lower Bounds and the Linearity Assumption in Parametric Estimations of Inequality of Opportunity," IZA Discussion Papers 9605, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp9605
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    References listed on IDEAS

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    1. 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.
    2. Judith Niehues & Andreas Peichl, 2014. "Upper bounds of inequality of opportunity: theory and evidence for Germany and the US," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 43(1), pages 73-99, June.
    3. Anders Björklund & Markus Jäntti & John Roemer, 2012. "Equality of opportunity and the distribution of long-run income in Sweden," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 39(2), pages 675-696, July.
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    Cited by:

    1. 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.
    2. Paolo Brunori & Vito Peragine & Laura Serlenga, 2019. "Upward and downward bias when measuring inequality of opportunity," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 52(4), pages 635-661, April.
    3. Niaz Asadullah & Alain Trannoy & Sandy Tubeuf & Gaston Yalonetzky, 2018. "Fair and unfair educational inequality in a developing country: The role of pupil’s effort," Working Papers 474, ECINEQ, Society for the Study of Economic Inequality.
    4. Vincenzo Carrieri & Apostolos Davillas & Andrew M. Jones, 2020. "A latent class approach to inequity in health using biomarker data," Health Economics, John Wiley & Sons, Ltd., vol. 29(7), pages 808-826, July.
    5. Dai, Xinchen & Li, Jing, 2021. "Inequality of opportunity in China: Evidence from pseudo panel data," China Economic Review, Elsevier, vol. 68(C).

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    More about this item

    Keywords

    equality of opportunity; type heterogeneity; parametric estimation;
    All these keywords.

    JEL classification:

    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • D3 - Microeconomics - - Distribution

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