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Economic theory and practical lessons for measuring equal opportunities

November 21, 2015
High Level Expert Group Workshop on Inequality of Opportunity January 2015 Paris OECD

High-Level Expert Group, January 2015, Paris

I’ve written a working paper based upon a presentation I made in January 2015 to a workshop on “Inequality of Opportunity” held by the High-Level Expert Group on the Measurement of Economic Performance and Social Progress. The OECD, which was one of the organizations co-hosting the workshop, is currently reviewing the paper for publication.

You can download the current draft here, and I’d invite any comments before it is finalized and officially released.

You can view the workshop agenda and all the presentations here. The broader program of the Expert Group, which includes the development of “distributional National Accounts”—national accounting that recognizes inequality and the distribution of income—can be found at this link.

What follows for quick reference is the introduction of my paper. If you have a chance to read the whole thing and have some thoughts to make it better, feel free to include your suggestions in the comment section at the end of this post, or email them to me.

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The use of the word “practical” in the title of this memorandum should not necessarily be interpreted as “feasible. Some of the suggestions I make for the development of a set of statistics appropriate for the measurement of equality of opportunity certainly are feasible, and while some can be introduced and used almost immediately, others can only be put into practice over a longer horizon and may well require a commitment of human and financial resources. “Practical” lessons are those that can in principle be put into practice, but also those that are grounded in our understanding of the theory of intergenerational mobility and equality of opportunity.

Theory, of course, rarely if ever gives direct guidance to empirical analysis and public policy. I draw two threads from economic theory, and pull them as long as I possibly can to inform specific recommendations for policy makers concerned with the measurement and monitoring of equality of opportunity in the rich countries, without hopefully splitting them from the fabric of logical and well articulated thought. These threads of thought lead to three suggestions:

  1. Use data appropriate for the country at hand—and indeed where possible promote the development and use of new data, whether those associated with the administration of the income tax and other government programs, survey data supplemented with retrospective questions, or linked survey and administrative data—to estimate summary measures of intergenerational mobility. These statistics include:

(a) the intergenerational earnings elasticity, which can be thought of as a complement to cross-sectional indicators of inequality like the GINI coefficient, and the intergenerational correlation in income ranks

(b) intergenerational income transition matrices, which depict the degree and direction of child mobility according to each parental rank

  1. Develop measures of absolute mobility, and in particular develop a poverty line based upon the monetary resources associated with discrete changes in the lack of upward mobility for children whose parents are in the lower part of the income distribution. Publish on a regular basis the headcount ratio of children living in families with less than this level of monetary resources.
  1. Make full use of the Programme for International Student Assessment (PISA) and expand its scope to include young children

(a) regularly publish a host of appropriate statistics associated with important skills and competencies of the 16 year old children surveyed in these data in a way that is framed by the theory of equality of opportunity

(b) move forward in implementing the original vision of a PISA for young children—say those five or six years of age, children at the cusp of starting primary school—by developing appropriate measures of skills and competencies that can be measured across countries, and including them—along with measures of family background—in repeatedly administered cross sectional surveys across all the countries currently included in PISA.

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