DEC Course on Poverty and Inequality Analysis Module 7: Evaluating the Distributional and Poverty Impacts of Economy-wid

1. DEC Course on Poverty and Inequality AnalysisModule 7: Evaluating the Distributional and Poverty Impacts of Economy-wide Policies Session IV: Inequality of Opportunity as a Social Evaluation Criterion Francisco H. G. Ferreira

2. Plan of the Session • Motivation: Why measure inequality of opportunity? • Existing empirical literature • A conceptual framework • Measurement in practice • Data • Scalar measures of inequality of opportunity • For labor earnings • For household income per capita • For household consumption per capita • Opportunity-deprivation profiles • The Equitable Development Policy • Conclusions

3. 1. Motivation (i) • Amartya Sen’s Tanner Lectures (1980) question: “Equality of what?” • Modern theories of social justice want to move beyond the distribution-neutral, sum-based approach of utilitarianism. • Desire to place some value on “equality”. • But are outcomes, such as incomes, the appropriate space? • What role for individual effort and responsibility? • Are all inequalities unjust? ”We know that equality of individual ability has never existed and never will, but we do insist that equality of opportunity still must be sought” (Franklin D. Roosevelt, second inaugural address.)

4. 1. Motivation (ii) • Equality of opportunity is a normatively appealing concept. Many philosophers (and politicians) increasingly see it as the appropriate “currency of egalitarian justice”. • Dworkin (1981):What is Equality? Part 1: Equality of Welfare; Part 2: Equality of Resources”, Philos. Public Affairs, 10, pp.185-246; 283-345. • Arneson (1989): “Equality of Opportunity for Welfare”, Philosophical Studies, 56, pp.77-93. • Cohen (1989): “On the Currency of Egalitarian Justice”, Ethics, 99, pp.906-944. • Roemer (1998):Equality of Opportunity, (Cambridge, MA: Harvard University Press) • Sen (1985):Commodities and Capabilities, (Amsterdam: North Holland)

5. 1. Motivation (iii) • Economists have also become interested. John Roemer (1998) suggested an influential definition, based on the distinction between “circumstances” and “efforts” among the determinants of individual advantage. • Circumstances are morally-irrelevant, pre-determined factors over which individuals have no control. • Equality of opportunity is attained when advantage is distributed independently of circumstances. “According to the opportunity egalitarian ethics, economic inequalities due to factors beyond the individual responsibility are inequitable and [should] be compensated by society, whereas inequalities due to personal responsibility are equitable, and not to be compensated” (Peragine, 2004, p.11)

6. A non-income example of unequal opportunities: the distribution of survival probabilities by parental education Source: WDR 2006.

7. Motivation (iv) • The concept may also: • Help policymakers identify groups that are excluded from the opportunity to achieve their full potential in society. • Help us understand differences in intrinsic attitudes towards inequality. • Help shed new light on the inconclusive debate on the relationship between inequality and growth. Source: World Value Survey (1999-2000) conducted by the Inter-university Consortium for Political and Social Research, based at the University of Michigan. The question asked representative samples of people in 69 countries to place their views on a scale from 1 to 10, where 1 implied agreement with the statement that “Incomes should be made more equal,” and 10 implied agreement with the statement that “We need larger income differences as incentives for individual effort” (Inglehart and others 2004).

8. 2. Existing Empirical Literature (i) • Problem:How is one to measure inequality of opportunities? • The literature is very much in its infancy. • Bourguignon, Ferreira and Menéndez (2007) • Bourguignon, Ferreira and Walton (2007) • Checchi and Peragine (2005) • Ferreira and Gignoux (2008) • Lefranc, Pistolesi and Trannoy (2008) • Paes de Barros et al. (2008) • Roemer et. al. (2003) • van de Gaer, Schokkaert and Martinez (2001) • Foster and Shneyerov (2000) • Elbers, Lanjouw, Mistiaen and Özler (2008) • Vast literature on intergenerational mobility is also related.

9. 2. Existing Empirical Literature (ii) • We will focus here on the approach followed by BFM and FG, which is based on a re-interpretation of standard inequality decompositions. • Defined so as to be consistent with Roemer’s (1998) definition of equality of opportunity. • Using parametric and non-parametric methods, and a variety of indices and welfare concepts, in search of robustness. • Should be interpreted as yielding a lower-bound on inequality of opportunity for each particular “advantage”.

10. 3. Conceptual framework (i) Let a particular advantage be a function of a vector of circumstance variables, a vector of effort variables, and a random term: y = f(C, E, u) (1) Circumstances are (economically) exogenous by definition, but efforts are not: yi = f(C, E(C, v), u) (2) Equality of opportunity: which will generally require: (i) (ii)

11. 3. Conceptual framework (ii)An illustration: distributions of per capita consumption conditional on mother’s educational attainment in five Latin American countries.

12. 3. Conceptual framework (iii)A second illustration: distributions of per capita consumption conditional on ethnicity in five Latin American countries.

13. 3. Conceptual Framework (iv) • Advantage being distributed independently of all circumstances implies that, in expectation, between-group inequality in a partition by all circumstance variables should be zero. • This suggests, two plausible measures of inequality of opportunity: Then

14. 4. Measurement in Practice (i) • But is not a uniquely defined concept. It varies with: • Specific inequality index • Path of the decomposition • Which gives rise to two alternative indices • Estimation procedure

15. 4. Measurement in Practice (ii) • It may be axiomatically desirable to choose I() such that • The only inequality index anchored by the arithmetic mean which satisfies this property (as well as the transfer principle) is E(0). (Foster and Shneyerov, 2000) • To see why other members of the Generalized Entropy class do not satisfy it, note that: For α≠0, changes in relative means affect not only IB, but also weights in IW.

16. 4. Measurement in Practice (iii) • Imposing path-independence: • Eliminates multiplicity of scalar measures and decomposition paths with one stroke, focusing attention on a unique scalar I.Op. measure. • But estimation procedure still matters, since most samples are too small for reliable fully non-parametric estimation.

17. 4. Measurement in Practice (iv) • The obvious alternative to use data more efficiently is a parametric approach. This requires estimating a specific model for • Following Bourguignon et al. (2007), we use a log-linear approximation: • If one is only interested in the overall effect of circumstances, estimating the reduced form is sufficient: • The PStD is then simulated as: • The PSmD is simulated as: where

18. 4. Measurement in Practice (v) • This gives rise to two parametric indices which are analogous to the non-parametric measures previously defined: • Non-parametric estimation of is very data-intensive. With six circumstances, three of which with three categories, there are 216 possible cells in the partition. As cell size declines, sampling variance on becomes problematically large. • The parametric approach allows for partial measures of inequality of opportunity due to individual circumstances:

19. 4. Measurement in Practice (vi) • This effectively leaves us with two estimates of the unique path-independent, Roemer-consistent inequality of opportunity index. • Interpretation • Omitted circumstances can only lead to a finer partitioning of {yik}, which can not reduce, but may increase measure. • Similarly for the parametric method, is proportional to the R2 of the regression. Recall that • Implication (i): these indices are lower bound estimates of inequality of opportunity • Implication (ii): if omitted variables are thought to be a significant problem, causal attribution to specific variables is unwarranted.

20. 5. Data (i)

21. 5. Data (ii)The circumstance variables

22. 5. Data (iii) • Comparability caveats • Consumption data not available for Brazil. • Father’s occupation data not available for Colombia and Peru. • Household income and consumption data adjusted for spatial price differences in Ecuador, Guatemala, Panama and Peru (but not in Brazil or Colombia). • Imputed rents for owner-occupied housing included in income and consumption aggregates everywhere, except in Brazil. • Reference period for earnings of the self-employed vary somewhat across surveys.

23. 6. Scalar Measures of Inequality of Opportunity (iii)

24. 6. Scalar Measures of Inequality of Opportunity (iv)

25. 6. Scalar Measures of Inequality of Opportunity (v)

26. 6. Scalar Measures of Inequality of Opportunity (v)

27. 7. Opportunity-deprivation profiles (i) “The rate of economic development should be taken to be the rate at which the mean advantage level of the worst-off types grows over time. […] I look forward to a future number of the WDR that carries out the computation, across countries, of this new definition of economic development” (p.243). Roemer, John E. (2006): “Review Essay, ‘The 2006 world development report: Equity and development”, Journal of Economic Inequality (4): 233-244

28. 7. Opportunity-deprivation profiles (ii) Roemer’s types are groups such that: An opportunity profile is a ranking of types, in ascending order of some criterion to measure the opportunity sets. An appealing, but partial, ranking is provided by (first or second-order) stochastic dominance. For a complete ordering, need to rank Fk(y) by some other indicator, moment or quantile. We use the type’s mean advantage. An opportunity-deprivation profile is a subset of the opportunity profile below some arbitrary threshold in the ranking criterion. We use p = 10%

29. 7. Opportunity-deprivation profiles (iii) The Brazilian profile, by income per capita

30. 7. Opportunity-deprivation profiles (iv)

31. 7. Opportunity-deprivation profiles (v)

32. 7. Opportunity-deprivation profiles (vii):Opportunity for education in Turkey The highly disadvantaged group encompasses girls in rural areas of the East region whose mother has no education and is a non-Turkish native speaker living in a household with six children or more; it encompasses 1.0% of the population of 6-24 years-old. The highly advantaged group encompasses boys in urban areas of the Center region whose mother has some education and is a Turkish native speaker living in a household with one or two children; it encompasses 2.5% of the population of 6-24 years-old Source: Ferreira and Gignoux, forthcoming.

33. 8. The Equitable Development Policy (i): • At a general (and somewhat abstract) level, one could think of the equitable development policy problem as: • The choice of policies from a feasible set so as to maximize the future stream of ‘advantage’ for the most disadvantaged type, subject to a no-deprivation constraint and to a feasibility constraint. Source: Bourguignon, Ferreira and Walton, JEI 2007.

34. 8. The Equitable Development Policy (ii): • ‘Deconstructing’ the equitable development policy problem: “Growth matters” Permissible Policy Set: Technical feasibility and social acceptability Poverty eradication as a ‘constraint’. “Rawlsian” criterion. All weight on the least advantaged. Source: Bourguignon, Ferreira and Walton, JEI 2007.

35. 8. The Equitable Development Policy (iii): • Questions for this course: • Should economy-wide policies be assessed not only in terms of their impacts on (outcome) poverty and inequality, but also in terms of their impacts on inequality of opportunity? • Might policies even be designed (and ex-ante evaluated) with a view to improving the welfare of the worst-off types? • Dynamically, is there any evidence of inequality traps? • Persistence of group-based disadvantage.

36. 9. Concluding Remarks (i) • If one adopts Roemer’s definition of inequality of opportunity, it is possible to measure it empirically, for a given set of observed circumstance variables. • All methods are essentially variants of a within/between-group decomposition, implemented either non-parametrically or parametrically. • Parametric and non-parametric approaches are complementary: the former is less data intensive, and allows for partial analysis; the latter is more flexible (makes no functional form assumptions). • In Latin America, inequality of economic opportunity: • ranges from 17% to 34% for earnings. • Ranges from 23% to 35% for income per capita. • ranges from 24% to 50% for consumption per capita. • Estimates are consistent with higher IOp for permanent income.

37. 9. Concluding Remarks (ii) • Family background variables (particularly mother’s education) are the most important circumstance variables in LAC. • But spatial differences and ethnicity are very important in Guatemala and Panama. • Opportunity-deprivation profiles • Rank types by mean outcome in opportunity set. • Permit identifying key circumstance markers for deprivation and exclusion • Different from poverty profiles • And in an informative way (about “mobility at the bottom”, “traps”) • In Latin America, ethnicity and family background are powerful predictors of opportunity-deprivation.