This document discusses measuring inequality in education attainment. It argues that absolute measures are most appropriate for cross-country comparisons and tracking changes over time. Absolute Gini coefficients can compare education inequality between countries, while gains incidence curves show growth rates across the distribution of education attainment within a country over time. Using these absolute measures reveals that relative and absolute measures sometimes yield different conclusions about changes in inequality. The document advocates for absolute measures based on the theory that education returns are proportional to absolute differences in years of schooling.

1. Which distribution of income feels more unequal to you?
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$400 $200
$600 $400
$400 $200
$800 $400
A B

2. Education, Economics, and Inequality
An absolutist approach to measuring
inequality in education attainment
Presentation to the Comparative and International
Education Society
March 6, 2016

3. Outline
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▪ Education and Economic Thought
▪ The Distribution of Education Attainment
▪ Measuring Inequality in Education
▪ Absolute Gini Coefficients (cross-country comparisons)
▪ Gains Incidence Curves (time series comparisons)
▪ Challenges
▪ Conclusion

4. History of Thought
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▪ The idea of universal basic education as an economic policy is
centuries old.
▪ Not accepted as an uncontroversial goal until much later.
▪ The economic role of education been formalized.
▪ Equitable expansion of education is a key to broad-based
growth.
▪ But what exactly does equitable expansion mean?

5. Why does the level of education matter for
individuals?
▪ Mincer (1958) models the private return to education.
▪ Present value of earnings:
▪ Equilibrium equates V(s):
▪ Bottom line: log(w(s)) = α + β*s+ Other factors.
β is the private rate of return to schooling.
▪ Implication: Proportionate differences in earnings
(relative) is linear in the difference in years of schooling
(absolute).
▪ This type of model is applied in hundreds of empirical
studies (e.g., Montenegro and Patrinos 2014).
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6. Why does the distribution of education matter for
societies?
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Equity concerns
▪ Access to basic
education is a human
right.
▪ Basic education can be
a powerful anti-poverty
instrument.
Economic efficiency
concerns
▪ Economic disparity
could restrict
cooperation so that
public goods are
underprovided and block
efficient policies
(Bardhan et al. 2000).
▪ Inequality could
necessitate distortionary
redistribution (Alesina
and Rodrik 1994).

7. Why might the bottom of the distribution be especially
important?
▪ Equity concern: self-evident.
▪ Efficiency concern: non-linearities in the education-productivity
relationship
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8. Implications for measurement of inequality
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▪ Averages (mean years of schooling, enrolment rates) are not
enough.
▪ We should track absolute inequality to compare countries,
and pay attention to how the bottom of the distribution moves
over time.
▪ With this in mind, what measures can we use to make
international and intertemporal comparisons of education
attainment?
▪ For international comparisons: Absolute Gini Coefficients.
▪ For intertemporal comparisons: Gains Incidence Curves.
▪ They find that education inequality fell in nearly every country
over. But these are relative Gini coefficients.

9. Cross-country comparisons: Gini Coefficients
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▪ Thomas et al. (2000) construct Gini coefficients for education
attainment for 85 countries between 1960 and 1990:
▪ They find that
education inequality
fell in nearly every
country over the 30
year period.
▪ But they look at
relative Gini
coefficients.
Cumulative population share
(least to most educated
Cumulativeyearsofeducationshare
Complete equality
Unequal
distribution
Gini = A/(A+B)

10. Cross-country comparisons: Gini Coefficients
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Source: presenter’s calculations
based on Barro and Lee (2010)

11. Is this distinction of practical importance?
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Mean Grade 6 completion rate
Relative gap (top/bottom quintile) Absolute gap (top-bottom quintile)
Source: Ravallion (2016)

12. Time series comparisons: GICs for Income
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▪ Chen and Ravallion (2003): track changes in the distribution of
income using a Growth Incidence Curve (GIC).
▪ GIC shows the economic growth rate at every percentile of
income.
Source: World Bank
Source: World Bank (2009)

13. Time series comparisons: GICs for Education
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▪ For education, it doesn’t matter whether you are a relativist or
absolutist with respect to income.
▪ Even if you are a relativist for education, the Mincer model implies
you must be an absolutist with respect to education.
▪ Gains Incidence Curve for Education Attainment:
▪ Source of attainment data is Filmer (2015).
▪ We can directly observe gains along the distribution of education
attainment.

14. Often relative and absolute measures yield the
same conclusion: Uganda (2000-2011)
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Source: presenter’s calculations
based on Barro and Lee (2010)

15. But sometimes they present very different pictures:
Malawi (2000-2010)
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Source: presenter’s calculations
based on Barro and Lee (2010)

16. Challenges
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▪ Shadow education system.
▪ Need to account for quality of education (education inequality
likely understated by attainment-based measures).
▪ Missing inequality between demographic groups within a
country (topic of the next presentation by EPDC), which may
be most relevant for policy design.

17. Conclusions
This supports the use of Absolute Gini Coefficients for
comparing countries or sub-populations and Gains Incidence
Curves for tracking changes over time.
How we think about the economics of education in theory has
direct practical implications for education inequality.
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If we believe in a Mincer-like model, it is most important to
track absolute inequality (regardless of whether you are an
absolutist or relativist in income terms).

18. Thank you for your attention.
▪ Milan Thomas, Associate Fellow (mthomas@r4d.org)
Contact Information
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