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Estimating Inequality of Opportunity in More Periods Than Ever Before: The Capital Income Approach

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  • Hugo del Valle-Inclán Cruces

Abstract

The measurement of Inequality of Opportunity has attracted a lot of attention in recent years, despite of the fact that it is very limited by the scarce availability of data on family background. In this paper we propose a method to overcome this limitation, which consists of using another variable, widely available, as a proxy of socioeconomic origin: capital income. Using data of 24 European countries we first show that capital income is strongly related to parental education and occupation. Secondly, we compare the results of our approach to estimate Inequality of Opportunity (which includes a measure of capital income in the set of circumstances) to those obtained with a “standard” procedure (i.e., including parental education in the circumstances set), and conclude that our method can be employed when we do not have information on parental background. Finally, we apply it to estimate Inequality of Opportunity for the full length of the EU-SILC database, which covers every year from 2003 to 2015. To the best of our knowledge, this method allows to measure Inequality of Opportunity in more countries and periods than ever before.

Suggested Citation

  • Hugo del Valle-Inclán Cruces, 2019. "Estimating Inequality of Opportunity in More Periods Than Ever Before: The Capital Income Approach," LIS Working papers 764, LIS Cross-National Data Center in Luxembourg.
    • Handle: RePEc:lis:liswps:764
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    References listed on IDEAS

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    1. Dirk Van de gaer & Michel Martinez & Erik Schokkaert, 1998. "Measuring Intergenerational Mobility and Equality of Opportunity," Working Papers of Department of Economics, Leuven ces9810, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
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    5. John E. Roemer & Alain Trannoy, 2016. "Equality of Opportunity: Theory and Measurement," Journal of Economic Literature, American Economic Association, vol. 54(4), pages 1288-1332, December.
    6. Nicholas W Papageorge & Kevin Thom, 2020. "Genes, Education, and Labor Market Outcomes: Evidence from the Health and Retirement Study," Journal of the European Economic Association, European Economic Association, vol. 18(3), pages 1351-1399.
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    8. Bucher-Koenen, Tabea & Ziegelmeyer, Michael, 2011. "Who lost the most? Financial Literacy, Cognitive Abilities, and the Financial Crisis," MEA discussion paper series 11234, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.
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    More about this item

    JEL classification:

    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • D70 - Microeconomics - - Analysis of Collective Decision-Making - - - General
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality

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