Inequality of Opportunity: Theory and Measurement: Volume 19

Individuals are completely responsible for their outcomes (income, utility, health and so on) and, therefore, total inequality is due to individual responsible choices. This view has been challenged by philosophers and economists for the last three decades since the magnum opus by John Rawls (1971). These authors have argued that individuals are only responsible for their own efforts, and, therefore, people should be compensated for a variety of circumstances beyond their control. The meritocracy approach rejects the existence of circumstances and, in accordance with this, considers that total inequality is due to inequality of effort. On the contrary, the equality of opportunity approach recognizes the existence of factors that affect individuals and over which they have no control. For the former approach, the relevant equilizandum is individual freedom of access to education, positions and jobs. For the latter approach, the relevant equilizandum is the set of available opportunities to acquire those attributes required to compete for a position or job.

Purpose – In this chapter we discuss to what extent some of the measures of inequality of opportunity (IOp hereafter) proposed in the literature meet the reward and the compensation principles.

Methodology – We study the direct unfairness and fairness gap measures proposed by Fleurbaey and Schokkaert (2009) and the ex ante and the ex post measures proposed by Checchi and Peragine (2010). As all the measures violate at least one of the principles, we propose a framework in order to quantify, for each solution, the violations of the property that it does not fully satisfy and we formulate the problem of choosing the measure that minimizes the violations of the principle not fully satisfied.

Findings – This procedure is shown to be able to rationalize some of the existing measures of opportunity inequality and to obtain new measures of IOp.

Purpose – The aim of this chapter is to analyze the measurement error due to partial observability of circumstances, given the current methodologies used to capture the inequality of opportunity.

Methodology – We limit our analysis to the case in which IOp is measured by using an inequality index and evaluated according to the ex ante and the ex post approaches proposed by Checchi and Peragine (2010). Both approaches rely on the use of two hypothetical distributions obtained by standardizing and smoothing processes so that in one of them all inequalities are due to effort and in the other they are all caused by individuals circumstances. The impact of a change in the observability of circumstances has been analyzed directly in the first case (ex ante approach) and indirectly in the second (ex post approach). Hence, in the latter results are obtained by using a decomposable inequality index, while in the first case the result holds for any Lorenz consistent inequality index.

Findings – We have shown that, in both cases, we can only identify a lower bound of opportunity inequality, and the results obtained when measuring IOp with the two approaches are biased in the same direction.

Originality – The idea that inequality of opportunity, as it is generally measured, is only a lower bound of the real inequality of opportunity has already been hinted in Peragine (2004a), Fleurbaey (2008, Chap. 9), and Ferreira and Gignoux (2011). We attempt to bring this intuition to complete fruition in this chapter by providing clear and distinct demonstrations of this result for both the ex ante and the ex post approach for measuring IOp.

Purpose – This chapter aims at proposing a methodology for evaluating long-term income distributions according to the equality of opportunity principle.

Approach – We refer to the concept that there is equality of opportunity if the value of the set of opportunities is the same for all individuals, regardless of their circumstances. This approach partitions the population into types, that is, groups of individuals with the same set of circumstances. The type-specific outcome distribution is interpreted as the opportunity set of individuals with the same circumstances. We propose partial and complete rankings on long-term type-specific distributions. Accordingly, these rankings capture inequality between types, and are neutral to inequality within types.

Findings – We show the relationship between long-run and short-run inequality of opportunity and that this relationship can be interpreted in terms of intragenerational mobility. We also show that mobility can act as an equalizer of opportunities when the accounting period is extended.

Originality – The contribution of this work is twofold. First, we develop a decomposition of some measures of long-term inequality of opportunity into measures of short-term inequality of opportunity, applied to distributions, which neutralize the effect of effort on individual income, and may be employed to explain eventual differences arising from an analysis based on the intertemporal context. Second, we propose an index to measure intragenerational mobility and show how it can be interpreted as long-term EOp. Our measure captures only that part of reranking due to the equalization of opportunities over time.

Purpose – We propose applying Reardon's approach to the measurement of ordinal segregation to the study of inequality in life chances in the case of ordinal variables. We also propose additional measures of inequality in life chances in such a case.

Methodology – We state the desirable properties of measures of inequality in life chances when the variable under study is ordinal and check which properties are fulfilled by the various indices examined in this chapter.

Findings – All the indices defined in this chapter seem suitable for the analysis of inequality in life chances with ordinal variables but we found some trade-off between indices fulfilling the population composition invariance and those fulfilling the group replication invariance.

Originality – Besides extending the indices suggested by Reardon to the study of inequality of life chances, we propose, to analyze this issue, two additional sets of indices based on the notion of distributional dissimilarity.

Purpose – The concept of equality of opportunity (EOp) goes back to Roemer (1993, 1998) who argues that a society should guarantee its members equal access to advantage regardless of their circumstances, while holding them responsible for turning that access into actual advantage by the application of effort. First, this chapter investigates how family background influences income acquisition in 17 European countries. Second, it particularly scrutinizes how governments affect EOp through redistributive policies.

Methodology – We apply two different methods in order to measure EOp: the Gini opportunity index defined by Lefranc et al. (2008) and a parametric estimation method. Effective redistribution is measured via income concepts at different stages of the tax-and-transfer schemes.

Findings – We find clear country clustering in terms of EOp for Nordic, Continental European, and Anglo-Saxon countries. For Eastern Europe our results are less definitive. By examining the impact of redistributive policies in the countries under analysis, it can be concluded that both taxes and transfers reduce inequality of opportunity (IOp), with social benefits typically playing a key role. Furthermore, the equalizing impacts of the tax-benefit system on IOp differ substantially from the ones observed in the traditional notion of inequality of outcomes.

Originality – We systematically compare two approaches used to identify the extent of EOp. Our results reveal that both methods yield rather robust country rankings for various circumstance sets. Furthermore, the impact of tax-benefit policies on EOp is rarely addressed in the existing literature. We contribute by focusing on effective redistribution directly related to different income concepts.

Purpose – We analyze equality of opportunity for earnings acquisition in France between 1973 and 1993 defining individual circumstances by parental earnings. We compare two different definitions of circumstances. In the first one they are measured by the father's earnings level, in the second one by the father's rank in the earnings distribution.

Methodology – First we use stochastic dominance tools. Then we decompose the evolution of inequality of opportunity using the mean logarithmic deviation and the results of regressions of descendants’ earnings on their parents’ earnings.

Findings – Inequality of opportunity has remained stable when conditioning on the earnings level of the father, whereas it has diminished when conditioning on his rank in the earnings distribution. The former result is explained by the stable intergenerational earnings elasticity. The latter by the decreasing wage inequality in the previous generation.

Originality – Our analysis emphasizes that the assessment of equality of opportunity and its evolution is very sensitive to the partition of circumstances used. Moreover, it stresses the complementarity between the discrete and the continuous approaches for measuring inequality of opportunity.

Purpose – We attempt to incorporate the effect of changes in circumstances over time, which are usually approximated by parental education or occupation. We claim that the relative level of parental schooling is a better measure than the absolute level of education since parents' circumstances change dramatically in a society where schooling patterns change rapidly.

Methodology – We control for parental cohorts of education for a given father's age. We also test the sensitivity of the results under the ex post and the ex ante approaches.

Findings – We find that the cohort effect is generally negative. We also provide some insights into the differences between the ex ante and the ex post approaches and investigate the convergence of both methodologies as the number of tranches, tends toward one.

Originality – Besides including parents' education changes over time, we illustrate that for Chile in 2009, the ex ante approach increases the level of inequality of opportunity compare to the ex post approach.

Purpose – This chapter investigates vulnerability to poverty in the Republic of Haiti.

Methodology – We use a hierarchical modeling technique to allow the assessment and decomposition of vulnerability to poverty by exploiting the short-panel structure of nested data in a cross section.

Originality – Specifically, a three-level hierarchical model with a partially Bayesian restricted maximum likelihood is used in the estimation procedure. This is novel in this literature.

Findings – The decomposition method adopted in this chapter reveals that vulnerability in the Republic of Haiti is largely a rural phenomenon and is correlated negatively with schooling. The results also disclose the lack of equality in various aspects of circumstances or opportunities, including education, as the salient factor determining the status and level of vulnerability of households. Most importantly, among the different shocks affecting household's income, it is found that meso-level shocks are in general far more important than covariate shocks. This finding points to some interesting policy implications in terms of decentralizing policies and delegating more powers and providing better means to local governments to enhance household resilience to shocks and to alleviate their vulnerability to poverty.

Purpose – Our ultimate goal is to characterize three methodological issues. First, compare the relative performance of alternative estimation methods for long time series, second, estimate the degree of correlation between effort and circumstances, and, third, decompose total inequality into inequality of opportunity and inequality of effort according to an ideal tree.

Methodology – We estimate parametrically and nonparametrically the ex-ante inequality of opportunity in the United States between 1969 and 2007. The degree of correlation between effort and circumstances is computed following the proposal in Björklund et al. (2011). In addition, we decompose total inequality based on an ideal tree with three levels of disaggregation by applying the natural decomposition of the squared coefficient of variation and the Nested Shapley value.

Findings – We find significant differences between the nonparametric and parametric approaches. In particular, our results reveal that considering cross-effects between circumstances may be relevant. Moreover, the degree of correlation between effort and circumstances which has significantly increased over the period 1969 and 2007 in the United States, explains between 5% and 20% of total IO. In addition, race is the main circumstance during the 1970s and 1980s, accounting for more than 50% of the direct IO, while parental education take the lead in the last two decades.

Originality – We modify the parametric specification by considering cross-effects between circumstances. We estimate the degree of correlation between effort and circumstances for long time series. We decompose total inequality according to a three-level hierarchical model.