Abstract
Despite the growing prominence of theoretical analysis of inequality of opportunity over the past twenty years, empirical work towards the normative evaluation of real-world policies has been minimal. This paper seeks to address this issue. It proposes a normative framework to model the influence of educational policy on health outcomes, grounded in Roemer’s model of equality of opportunity. We apply this model to the National Child Development Study cohort, who, since their schooling lay within the transition period of the comprehensive education reform in England and Wales, attended different types of secondary school. We use this reform in two ways: first, to evaluate the health outcomes of different educational policies under different normative principles; second, to simulate counterfactual distributions of health outcomes by neutralising the different channels through which early life circumstances influence health. Evidence on the comparative performance of the two educational systems is mixed, suggesting that the opportunity-enhancing effects of the comprehensive reform were, at best, modest in terms of adult health. For some of the health outcomes considered, this leads to a convergence between the policy recommendations made by the two ethical principles of equality of opportunity and utilitarianism, while for others, the two principles diverge in their evaluation.
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Notes
See Fleurbaey and Schokkaert (2012) for a recent review of the literature on inequality of opportunity in health.
For a more extensive application of stochastic dominance tests in the context of opportunity-enhancing policy interventions see Van de gaer et al. (2012).
Note that, since the degree of equality-of-opportunity is given by the area above the left-hand envelope of the CDFs, then within the equality of opportunity framework, what happens to the most advantaged type is of no consequence as such. This explains our focus on the least advantaged children, who were also those whose opportunities the reform tried to improve.
Under different policy regimes the left-hand envelope may change, so the most disadvantaged, at a given percentile, may change types. Nevertheless, within the equality-of-opportunity framework this does not matter. Our measure of equality-of-opportunity indicates how well the most unfairly treated are doing (i.e. those who comprise the left-hand envelope), irrespective of their identity. It does not matter who they are per se.
Data on Scotland are not used: the Scottish educational system of the 1960s and 1970s was structurally very different from the one experienced by all the other NCDS cohort-members, and comprehensive schooling was introduced earlier, preventing a legitimate comparison of types of school, educational qualifications and outcomes.
In a few cases, pupils whose grades were sufficient transferred to grammar schools or sixth form colleges to complete their A-levels.
Despite these differences, there are no significant discrepancies in observed childhood health outcomes between Conservative and Labour areas.
Although these circumstances encompass a wide range of the factors known to influence health outcomes in adulthood, we cannot claim that they capture the entirety of influences beyond individual control. In this application, however, working with more than twelve types proved to be impractical, for cell sizes quickly collapse to zero as the number of types increases. The inequality attributable to our social types should thus be seen as a lower bound for the true inequality of opportunities in health.
Jones et al. (2011) CSEs and O-level (Ordinary levels) were secondary education qualifications corresponding, typically, to 11 years of education in total; CSEs were academically less demanding than O-levels. A-levels (Advanced levels) are a qualification which typically corresponds to 13 years of education. Completion of A-levels is ordinarily a prerequisite for university admission.
Further disaggregate this information into thirteen categories, ordered according to the grades obtained and number of passes. This is not done here, since that would greatly increase the dimensionality of the model, reducing cell size, and making the empirical implementation intractable.
A richer characterization of cigarette smoking in the UK in the context of socioeconomic inequalities can be found in Balia and Jones (2011).
It should be noted that it is possible that the evaluation of SAH by individuals of different countries, or different social groups within a country, may be systematically affected by expectations, aspirations, social and cultural norms. This type of reporting heterogeneity has been extensively examined in the literature using anchoring vignettes: these are descriptions of hypothetical, but objectively defined health statuses, used to anchor and make comparable SAH valuations by different survey respondents. Vignettes are however not available in the NCDS and this issue is only tangentially related to our analyses, since we consider a other health outcomes in addition to SAH. For an application of the vignettes methodology to the analysis of health inequalities see Bago d’Uva et al. (2008).
The working paper version of this article is available at: http://www.york.ac.uk/media/economics/documents/hedg/workingpapers/13_29.pdf
It has been shown that this test is bounded and consistent [for details see Yalonetzky (2013), pp. 141–142].
Our data set and empirical strategy are not designed to provide information on the reasons behind the positive association between exposure to the comprehensive system and the prevalence of long-standing illness and of mental conditions. However, we could posit that by streaming individuals into different educational/career pathways early on, the selective system potentially alleviates anxiety associated with being a relatively disadvantaged type in a mixed pool of pupils. Our mixed findings may relate to the fact that despite being self-reported, long-standing illness and mental illness (measured using the Cornell questionnaire) are typically considered more objective than SAH.
These tables are available at: http://www.york.ac.uk/media/economics/documents/hedg/workingpapers/13_29.pdf
The full set of results for chronic illness and disability are available in the working paper version of this article (Tables 8, 9 and 10).
Evidence on this is provided in the working paper version of this article (Tables 8, 9 and 10).
Our results should be interpreted as statistical associations, since our empirical strategy and data do not allow us to rule out the possibility of unobservable factors affecting the relationship between schooling and health.
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Acknowledgments
Pedro Rosa Dias and Andrew M. Jones gratefully acknowledge funding from the Economic and Social Research Council (ESRC) under Grant reference RES-060-25-0045. We thank the Editor and two anonymous reviewers for their comments. We are also grateful for comments on earlier versions of this work from Marc Fleurbaey, Silvio Daidone, Gaston Yalonetzky and seminar participants at the University of Oxford, CORE - Louvain La Neuve, Rome—La Sapienza and University of Catania. The NCDS was supplied by the ESRC Data Archive. Responsibility for interpretation of the data, as well as any errors, is the authors’ alone.
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Jones, A.M., Roemer, J.E. & Rosa Dias, P. Equalising opportunities in health through educational policy. Soc Choice Welf 43, 521–545 (2014). https://doi.org/10.1007/s00355-014-0793-z
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DOI: https://doi.org/10.1007/s00355-014-0793-z