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Robust cross-country analysis of inequality of opportunity

Author

Listed:
  • Francesco Andreoli

    (University of Verona and LISER)

  • Alessio Fusco

    (Luxembourg Institute of Socio-Economic Research - LISER)

Abstract

International rankings of countries based on inequality of opportunity indices may not be robust vis-à-vis the specific metric adopted to measure opportunities. Indices often aggregate relevant information and neglect to control for normatively irrelevant distributional factors. This paper shows that gap curves can be estimated from crosssectional data and adopted to test hypotheses about robust cross-country comparisons of (in)equality of opportunity.

Suggested Citation

  • Francesco Andreoli & Alessio Fusco, 2019. "Robust cross-country analysis of inequality of opportunity," Working Papers 492, ECINEQ, Society for the Study of Economic Inequality.
    • Handle: RePEc:inq:inqwps:ecineq2019-492
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    File URL: http://www.ecineq.org/milano/WP/ECINEQ2019-492.pdf
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    References listed on IDEAS

    as
    1. Andreoli, Francesco & Fusco, Alessio, 2019. "Robust cross-country analysis of inequality of opportunity," Economics Letters, Elsevier, vol. 182(C), pages 86-89.
    2. Michele Raitano & Francesco Vona, 2015. "Measuring the link between intergenerational occupational mobility and earnings: evidence from eight European countries," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 13(1), pages 83-102, March.
    3. Tim Goedemé, 2013. "How much Confidence can we have in EU-SILC? Complex Sample Designs and the Standard Error of the Europe 2020 Poverty Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 110(1), pages 89-110, January.
    4. repec:hal:spmain:info:hdl:2441/4rs0hmrl0s8farskm2usmmbu0s is not listed on IDEAS
    5. Michele Raitano & Francesco Vona, 2015. "Measuring the link between intergenerational occupational mobility and earnings," SciencePo Working papers Main hal-03459992, HAL.
    6. Francesco Andreoli, 2018. "Robust Inference for Inverse Stochastic Dominance," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 146-159, January.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Paul Hufe & Andreas Peichl & Daniel Weishaar, 2022. "Lower and upper bound estimates of inequality of opportunity for emerging economies," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 58(3), pages 395-427, April.
    2. Andreoli, Francesco & Fusco, Alessio, 2019. "Robust cross-country analysis of inequality of opportunity," Economics Letters, Elsevier, vol. 182(C), pages 86-89.
    3. Brunori, Paolo & Hufe, Paul & Mahler, Daniel Gerszon, 2021. "The Roots of Inequality: Estimating Inequality of Opportunity from Regression Trees and Forests," IZA Discussion Papers 14689, Institute of Labor Economics (IZA).
    4. Radl, Jonas & Miller, Luis, 2021. "Conceptual and Methodological Considerations on Effort: An Interdisciplinary Approach," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 65(11), pages 1447-1456.
    5. Brunori, Paolo & Hufe, Paul & Mahler, Daniel, 2023. "The roots of inequality: estimating inequality of opportunity from regression trees and forests," LSE Research Online Documents on Economics 118220, London School of Economics and Political Science, LSE Library.

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    More about this item

    Keywords

    Inequality of opportunity; EU-SILC; gap curves.;
    All these keywords.

    JEL classification:

    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • J62 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Job, Occupational and Intergenerational Mobility; Promotion
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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