econometric approaches to measuring child inequalities in mena

Econometric approaches to measuring child inequalities in MENA International Experts Conference, UNICEF

Rabat, Morocco 22-23 May 2012 Nadia Belhaj Hassine

[email protected]

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Inequality & Equity Inequality of outcomes along economic dimensions Inequality of outcomes along non-economic

dimensionsInequality of opportunity: A parametric approachInequality of opportunity: A non-parametric approach

Presentation Outlines

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Inequality:

Focus is on how equal is the distribution of some economic and non economic dimensions of welfare (ex-post realization)

Equity (or Inequality of Opportunity):

Focus is on the ex-ante potential to achieve welfare outcome.Usual measures of inequality (Gini, Theil etc.) fail to capture deeper layers of inequality that may account for the sense of unfairness in Arab countries where the level of inequality is moderate. Understanding the sources of inequality is important for devising policies that address its underlying causes, especially the role of unequal opportunities.

Inequality & Equity

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Child inequalities can be measured along income,

wealth or expenditures of the household:Define & harmonize the well-being indicator: Inequality

measures are sensitive to the items included in the

expenditure aggregates: apples need to be compared to

apples.

Adjust for HH composition: equivalence of scaleAdjust for spatial and temporal price differences

Inequality of Outcomes Along Economic Dimensions

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Lorenz CurveGini IndexGeneral Entropy: GE(0), GE(1), GE(2)GE indices are decomposable into within group and between group measures of inequalityk groups in a population (identified by location, education, gender , etc.)

within between ϕ(k) is the proportion of the population in group kμk is the mean income of group kGE(k;θ) is the GE index of group k

is the GE index of the population if each member of group k was assigned income μk

Common tools to measuring inequality

GE() (k)k

k1

K

GE(k; )G E ( )

G E ()

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Inequality Determinants

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Standard decomposition techniques identify potential determinants of

inequality …and lay the foundation for deeper analysis.

An important limitation of summary measures of inequality and standard

decomposition techniques is that they provide little information

regarding what happens where in the distribution.

Inequality Determinants

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Use the Recentered Influence Function (RIF) regression by

Firpo, Fortin, Lemieux (2010) to decompose the welfare

gaps at different quantiles of the unconditional distribution

into the part explained by the difference in the distributions of

observed household characteristics (between regions,

urban-rural, over time etc.) and the part that is explained by

the difference in the distributions of returns to these

characteristics.

These components are then further decomposed to identify the

specific characteristics which contribute to widening the

welfare gap.

Unconditional Quantile Regression Decomposition

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The procedure is carried out in two stages:

1. Construct a counterfactual distribution of rural log well-being (the distribution that would have prevailed if rural HH have received the same returns to their characteristics as urban ones): F(y* X∣ U, βR)

y is log well being, X is the distribution of covariates, and β is the marginal effect of X on quantile qτ (returns) at the various quantiles.

• Use the kernel smoothing technique to estimate urban and rural log-welfare

distributions and compute welfare gap at each quantile

• Estimate the RIF unconditional quantile regressions for urban, rural and counterfactual welfare distributions:

• (Yk ; τ ) = X k k k= u,r

• (Yk ; τ ) is the RIF estimate for the τ th quantile,


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2. Decomposition:

τ (YU)− τ (YR) = X U U -X R U + X R U -X R R = (X U -X R U + X R (U -R)• The first term is the is the endowment effect: the contribution of the

HH characteristics to the welfare gap at the τ th quantile; the second is the return effect: the contribution of the difference in returns to the urban–rural gap

• the endowment effect and the return effect can be further decomposed into the contribution of individual explanatory variables to identify the specific characteristics, differentiated across Rural and Urban HH, which lead to the widening of welfare gap.

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Expenditures and summary measures of inequality ($PPP Cst 2004)

Food Expenditure Expend. Food & Non Durables Total Expenditure Mean Median Gini Theil Mean Median Gini Theil Mean Median Gini TheilEgypt

2000 49.42 42.03 0.26 0.12 93.93 71.87 0.33 0.23 104.69 80.22 0.34 0.242005 51.18 44.24 0.26 0.12 94.05 74.8 0.32 0.2 107.71 85.57 0.32 0.22009 40.72 35.7 0.26 0.12 85.43 69.28 0.31 0.19 101.23 80.93 0.31 0.2

Iraq 2007 47.06 39.92 0.31 0.17 101.1 80.08 0.36 0.23 148.82 114.58 0.37 0.26

Jordan 2006 62.53 51.89 0.33 0.21 156.42 123.71 0.34 0.21 196.39 151.4 0.36 0.242008 66.91 56.27 0.31 0.17 158.19 126.75 0.33 0.19 195.87 153.04 0.34 0.21

Libya 2003 52.08 43.32 0.32 0.19 99.95 84.49 0.31 0.18 136.5 114.43 0.31 0.17

Mauritania 2000 44.12 34.33 0.39 0.28 53.59 40.35 0.41 0.31 55.26 41.38 0.41 0.322004 94.77 59.79 0.48 0.46 118.72 80.32 0.45 0.4 121.48 81.32 0.45 0.41

Palestine 1996 43.71 37.88 0.29 0.15 107.3 87.22 0.35 0.22 134.3 106.2 0.35 0.232009 43.18 35.88 0.32 0.19 121.5 94.83 0.36 0.24 151.5 114.1 0.38 0.26

Syria 1997 51.79 43.99 0.29 0.15 83.27 68.42 0.32 0.19 83.67 68.72 0.32 0.192004 80.55 65.27 0.33 0.19 144.6 108.5 0.38 0.27 165.5 126.6 0.36 0.25

Tunisia 2005 72.72 60.56 0.33 0.21 162.6 120.1 0.41 0.3 210.5 153.4 0.41 0.33

Yemen 1998 49.69 41.71 0.33 0.18 90.1 74.51 0.33 0.2 102.3 77.5 0.38 0.282006 33.02 27.47 0.33 0.2 66.57 50.55 0.38 0.32 78.27 55.27 0.42 0.43

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Standard Decomposition by HH attributes Education Gender Age Emp.stat. Fam. type Marital Region Urban/RuralEgypt

2000 27.00% 0.10% 0.80% 1.30% 18.30% 0.80% 26.50% 20.50%2004/5 24.30% 0.60% 2.00% 1.80% 19.40% 1.90% 22.00% 18.00%2008/9 23.20% 0.40% 1.90% 2.10% 19.80% 0.90% 19.90% 17.70%

Iraq 2007 4.40% 0.10% 0.20% 1.90% 16.20% 0.70% 19.40% 8.50%

Jordan 2002 17.40% 0.60% 3.80% 2.50% 23.60% 2.00% 9.70% 2.50%2008 15.40% 1.00% 6.90% 6.20% 24.60% 2.10% 11.90% 3.40%

Libya 2003 2.10% 1.00% 4.10% 0.10% 29.70% 2.10% 0.90% 0.30%

Mauritania 2004 4.10% 0.10% 1.20% 1.00% 9.70% 0.20% 0.40% 0.60%

Palestine 1996 8.10% 0.20% 0.60% 2.70% 19.80% 1.30% 7.30% 11.80%2009 5.80% 0.70% 4.30% 3.60% 18.90% 1.70% 4.50% 0.60%

Syria 1997 3.10% 0.40% 1.50% 1.30% 14.90% 0.90% 0.70% 0.80%2004 4.70% 3.40% 4.40% 6.00% 26.40% 6.90% 4.40% 6.00%

Tunisia 2005 22.20% 0.10% 0.70% 2.20% 8.80% 11.50%

Yemen 1998 9.40% 0.00% 1.10% 1.50% 11.70% 0.30% 12.60% 11.60%2006 7.30% 0.30% 0.40% 0.40% 8.50% 0.90% 7.00% 10.60%

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Education, family type and regional location of the HH are the most important determinants of overall inequality.

Slight decline over time of the importance of Head educational attainment as a determinant of inequality

Signs of income convergence between urban and rural areas and across regions in Egypt and Yemen.

The evaluation of between groups inequality against the maximum benchmark proposed by Elbers et al. 2007 confirm the consistency of these results.

Between-Groups Decomposition

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Confidence interval / endowment effect Confidence interval /returns effect Endowment effect Returns effect

Returns effects and endowment effects by Area for Egypt 2000

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Returns effects and endowment effects by Area for Egypt 2009


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• Dominance of endowments effects: welfare gap is caused primarily by the fact that urban households have superior characteristics

• Endowment effects and returns effects are both larger at higher quantiles, resulting in a larger urban–rural gap at higher quantiles.

• The Gap decreased over time except for the lowest quantile. The returns effects increased over time while the endowments effects decreased.


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Returns effects and endowment effects by Region for Egypt 2000

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Returns effects and endowment effects by Region for Egypt 2009

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Returns effects and endowment effects by Area for Syria 2004

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Returns effects and endowment effects by Area for Syria 1997

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Returns effects and endowment effects by Region for Iraq 2007

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Returns effects and endowment effects by Area for Iraq 2007

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Differences in characteristics such as hhsize, source of income and % of child under 14 matter the most important for lowest quantiles, while differences in educational attainment and experience matter much more for those who are well off.

The gap due to differences in educational attainment is decreasing over time while the gap due the returns to education is widening:

Urban markets are now paying more for educational and experience attributes than rural markets would.


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Regional differences in HH characteristics matter more than differences in returns to those characteristics at the bottom of the distribution

At the higher quantiles the welfare gap is caused primarily by the differences in returns, to those characteristics even though Metropolitan HH have superior characteristics.

Convergence of welfare levels between Metropolitan and the other regions despite an increase in the magnitude of the returns effects (returns to education particularly)


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Non-Economic Welfare• Inequality measures can be applied to non-economic

outcomes– Health: Anthropometric measures of child nutrition:

• Weight-for-Height (W/H)• Height-for-Age (H/A)• Weight-for-Age (W/A)

– Education:• Years of schooling• Test scores

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Standardizing the Measures

• Comparison is with distribution in ref. pop. for individuals of same sex and age (in months) or height

• Three ways of comparing to ref. population:– z-score (std. deviation score): difference between value of

indicator and median of reference population divided by std. deviation of reference pop.

– Percent of Median: ratio of value of indicator and median value for ref. pop.

– Percentile rank: rank position of individual on reference distribution expressed as percent of group the individual equals or exceeds

• All three standardized measured are calculated in DHS

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Standardized Indicators

• z-score is preferred:– Allows for calculation of means and std. dev. Of

populations and sub-population, which cannot be done using percentiles

– Changes at the extremes will not be necessarily reflected in changes in percentiles

– Percent of median does not correct for the variability in the reference population

• Criteria for malnourishment when using z-scores– z-score of -2 or lower (two standard deviations below

the reference median) is typical cutoff

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Health Inequality Measures

• Mean health indicator by quintile of an economic welfare measure– Grouped measure of health disparity

• Concentration Curves– Captures how the distribution of the health

variable relates to the distribution of a variable measuring living standards, which ranks individuals from poorest to richest

• Concentration Indices

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Inequality of Education

• Two main measures of education inequality– Standard deviation of schooling measures the

absolute deviation– Education Gini measures relative inequality

• The measure can be used to examine inequality in attainment (years of schooling), financing or enrollment.

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Education Gini• Just like the calculation of any Gini, education Gini can be

calculated as follows if individual data on educational attainment is available

But if only grouped data is available, then

Where pi , pj are the prop. of pop. with level of schooling i, j.yi, yj are the years of schooling for levels i and j

Gini 12n2

y i y jj1

n

i1

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Gini 12

pi p j y i y jj 1

M

i1

M

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Parametric Approaches to Measuring Inequality of Opportunity

(Roemer 1998)

Outcome (income, education, status…)

Outside the individual control

Inequality due to circumstances: Inequality of opportunity

Effort

Individual responsible choices

Inequality due to effort

Circumstances(race, gender, parents background, region of birth..)

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Simulate the reduction in overall inequality that would be attained if circumstance were equalized. The difference between the observed and the counterfactual inequality is interpreted as a measure of inequality of opportunity.

Bourguignon, Ferreira and Menedez (2007)

Methodology

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The empirical model

The earnings function can be specified in the following log-linear form :

iiii vECy )ln(

iii Cy )ln(

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• The counterfactual distribution is obtained by replacing yi with its estimated value, from the reduce form: ii Cy ˆˆexp~

The empirical model

where I(F) is the inequality measures (Gini, Theil, ..) defined on the outcome distribution.

yFI

yFIyFII

~~

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Total Partial Effects

Total IOP Opp. share Gender Moth.Edu. Fath.Edu. Bir Reg.

2006

Rural 0.404*** 0.030*** 0.075*** 0.006 0.004 0.003 0.031***

(0.061) (0.004) (0.014) (0.035) (0.004) (0.007) (0.003)

Urban 0.423*** 0.086*** 0.203*** 0.060*** 0.050*** 0.063*** 0.046***

(0.028) (0.008) (0.020) (0.010) (0.010) (0.008) (0.009)

Men 0.412*** 0.067*** 0.162*** 0.027** 0.053*** 0.032***

(0.031) (0.007) (0.016) (0.009) (0.012) (0.008)

Women 0.445*** 0.097*** 0.219*** 0.009 0.006 0.005

(0.069) (0.010) (0.039) (0.009) (0.009) (0.010)

Age 29 0.345*** 0.043*** 0.126*** 0.006 0.031 0.018 0.007

(0.042) (0.012) (0.026) (0.018) (0.028) (0.015) (0.013)

Age 44 0.453*** 0.049* 0.108* 0.053* 0.049** 0.065*** 0.052***

(0.047) (0.020) (0.049) (0.021) (0.018) (0.013) (0.010)

Age 45+ 0.381*** 0.032** 0.083** 0.011 0.010 0.020 0.015

(0.047) (0.010) (0.028) (0.008) (0.011) (0.017) (0.012)

Total 0.423*** 0.064*** 0.151*** 0.010 0.018* 0.034*** 0.024**

(0.030) (0.012) (0.029) (0.012) (0.008) (0.008) (0.008)

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1988 1998 2006

parametric CI/parametric

Inequality of opportunity share

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Table1. IOP Math Score 2007

Math Score 2007

GE(2) GINI

Total Within Between IOP_res Total Within Between IOP_res

Algeria 0.00926*** 0.00861*** 0.000655*** 0.0699*** 0.0769*** 0.0741*** 0.0202*** 0.0358***

Bahrain 0.0189*** 0.0145*** 0.00446*** 0.235*** 0.111*** 0.0963*** 0.0528*** 0.129***

Palestine 0.0320*** 0.0240*** 0.00835*** 0.253*** 0.144*** 0.124*** 0.0717*** 0.139***

Iran 0.0212*** 0.0142*** 0.00638*** 0.333*** 0.116*** 0.0948*** 0.0645*** 0.185***

Jordan 0.0260*** 0.0194*** 0.00871*** 0.254*** 0.130*** 0.112*** 0.0732*** 0.141***

Kuwait 0.0197*** 0.0152*** 0.00479*** 0.230*** 0.112*** 0.0986*** 0.0545*** 0.123***

Lebanon 0.0111*** 0.00700*** 0.00453*** 0.370*** 0.0850*** 0.0667*** 0.0545*** 0.215***

Morocco 0.0184*** 0.0146*** 0.00425*** 0.205*** 0.109*** 0.0970*** 0.0498*** 0.112***

Oman 0.0277*** 0.0202*** 0.00791*** 0.272*** 0.134*** 0.114*** 0.0706*** 0.150***

Qatar 0.0388*** 0.0263*** 0.0125*** 0.323*** 0.156*** 0.128*** 0.0890*** 0.178***

Saudi Arabia 0.0216*** 0.0156*** 0.00588*** 0.280*** 0.118*** 0.0995*** 0.0612*** 0.155***

Syria 0.0175*** 0.0134*** 0.00444*** 0.236*** 0.106*** 0.0921*** 0.0534*** 0.131***

Tunisia 0.0105*** 0.00775*** 0.00275*** 0.262*** 0.0821*** 0.0704*** 0.0417*** 0.143***

Turkey 0.0306*** 0.0187*** 0.0112*** 0.388*** 0.140*** 0.109*** 0.0839*** 0.219***

Egypt 0.0267*** 0.0178*** 0.00880*** 0.333*** 0.132*** 0.107*** 0.0750*** 0.188***

Dubai 0.0216*** 0.0132*** 0.00929*** 0.387*** 0.118*** 0.0917*** 0.0772*** 0.222***

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GE(

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Algeria Morocco Kuwait Bahrain Syria Palestine Jordan Tunisia Oman S.Arabia Qatar Iran Egypt Lebanon Dubai Turkey

Total Girl

Boy CI/Total

CI/Girl CI/Boy

Math Scores (parametric)Share of Inequality of Opportunity TIMSS 2007

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Total Inequality

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econometric approaches to measuring child inequalities in mena

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