Where in the world are you?Where in the world are you?

Branko MilanovicDevelopment Research Group, World Bank

Assessing the importance of circumstance and effort in Assessing the importance of circumstance and effort in a world of different mean country incomes and (almost) a world of different mean country incomes and (almost)

no migrationno migration

Rawlsesque global “original position”

• Assume Rawls’-like veil of ignorance for all citizens of the world where two characteristics, citizenship and social class are “allocated” to each individual

• How much of one’s income position in the world will be determined by one’s location (circumstance) and how much by one’s social class (in his/her country) which is a combination of circumstance and effort

• (1) Country allocation. Two public goods: mean income of the country, and inequality (Gini).

• There is no migration: country allocation is “fate” (but “morally arbitrary” or “circumstance”)

• (2) Social class allocation. With perfect mobility (if ρ between class allocation and outcome=0) => all effort and luck. With no mobility at all, all circumstance. Real life: ρ in rich countries between 0.3 and 0.6 (circumstance between 10% and 36%; take the average of ¼).

• Country allocation determines mobility and hence also the share of circumstance vs. effort in the second element.

Motivation

• How important foir our life-chances (position in the world) is (i) country of citizenship, (ii) social class where we are born, (iii) inequality in that country

• Then, given our social class, how do mean country income and distribution interact (does their importance vary for low and high social classes).

Questions:• How much of one’s life chances will be

determined by his assignment to a given country vs. given social class?

• Does this systematically vary with social class? • How much can one improve one’s position in

world income distribution through his own effort (by climbing social ladders in his country)?

• What is equality of opportunity globally (across all individuals in the world)?

• How much of global inequality is ‘morally arbitrary’, inequality which, according to Rawls (TJ), ought to be, within each nation-state, reduced or eliminated?

Short review of the data we use

(WYD database, 2002)

Population and income coverage of the surveys (in %)

Africa Asia Latin America

E.Europe WENAO World

Population 66 96 96 97 99 92

Income 66 95 95 99 100 98

Number of surveys (countries)

24 26 21 26 21 118

Source: World Income Distribution database. Note: WENAO is Western Europe, North America and Oceania (Australia and New Zealand).Eastern Europe included all formerly Communist countries (including CIS countries).

Definitions of variables:

• Position in the world: one’s income (based on household per capita $PPP income or expenditures) percentile position in global income distribution (1 to 100)

• Social “class”: one’s income position in national income distribution (running from 1 to 20; ventiles)

• Gini and mean country income from household surveys

Inequality in the world—by countries and by social class

Source: World Income Distribution (WYD); benchmark year 2002.

Germany

Brazil

ChinaSri Lanka

India

020

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of w

orld

inco

me

dist

ribut

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0 5 10 15 20country ventile

First cut: the between-country component accounts for between 70 to 87 percent of global inequality

Global inequality between

individuals

Between-country component of global

inequality

Share of (2) in (1) (in %)

Relative mean deviation 0.517 0.450 87.0

Coefficient of variation 1.744 1.273 73.0

Standard deviation of log of incomes 1.243 0.985 79.2

Gini coefficient 0.654 0.557 85.1

Mehran measure 0.783 0.683 87.3

Piesch measure 0.590 0.493 83.6

Kakwani measure 0.356 0.273 76.8

Theil entropy measure 0.832 0.577 69.4

Theil mean log deviation 0.847 0.562 66.4

Source: World income distribution (WYD) database. All income expressed in 2002 international dollars.

Role of circumstance and effort, overall

Equation

Mean per capita income (in ln $PPP)

Gini index (in %)

“Social class” (1 to 20)

Constant

Number of observations

R2 adjusted

F value

1

22.85(0)

-125.8(0)

2220

0.60

4009(0)

2

22.22(0)

-0.34(0)

107.5(0)

2220

0.61

1073(0)

3

22.22(0)

-0.34(0)

2.78(0)

136.6(0)

2220

0.91

1138(0)

4 (all mean incomes equal)

---

-0.58(0)

4.77(0)

23.1(0)

2220

0.96

3353(0)

Explaining one’s position in the world income distribution(dependent variable: percentile in world income distribution)

• About 60% of one’s income position in the world determined by one’s location directly (pure circumstance)

• Another 30% of one’s income position determined by one’s social class (approximately 1/3 of that is pure circumstance)

=> Roughtly, some 70% of total variability in global income position “explained” by morally arbitrary features

• Citizenship premium. If mean income of country where you live increases by 10%, your position in the world goes up by 2.2 percentiles

• Trade-off. If through effort and luck you jump ahead 5 social classes (e.g. in the US, going from the median household per capita income of $14,000 to $22,000) this is equivalent to a citizenship premium of about 60% (e.g. being born in Mexico

rather than in China*)

* China is at the median (unweighted) world income

With a given social class, what is one’s global

position likely to be, and how variable will it be?

Likely outcome: Median global position as function of social class

020

40

60

80

100

media

n p

osi

tion in

the w

orld

0 5 10 15 20social class

Note: unweighted data, each country’s ventile represents one observation.

Variability: Standard deviation of one’s position in world income distribution as function of one’s social class

10

15

20

25

30

stdev

of

world p

osi

tion o

f each

soci

al c

lass

0 5 10 15 20social class

Can top and bottom social class ever intersect?

Density function of one’s position in the world as function of one’s social class

0.0

1.0

2.0

3.0

4

0 20 40 60 80 100position in world income distribution

Note: Unweighted data, each country’s ventile represents one observation.

Top social class

Bottom social class

ventile 1 2 10…. 19 20

Mean country income ($PPP)

23.4

(0)

24.9

(0)

24.01

(0)

15.91

(0)

11.74

(0)

Ventile share (% of national Y)

23.04

(0)

20.22

(0)

5.63

(0)

1.46

(0)

0.612

(0)

Constant -185.4

(0)

-196.7

(0)

-155.7

(0)

-63.2

(0)

18.3

(0)

Adj. R2 0.905 0.952 0.960 0.933 0.904

No of observations 110 110 110 110 110

F value 519

(0)

1101

(0)

1310

(0)

748.3

(0)

515.3

(0)

Explaining a person’s position in world income distribution—Explaining a person’s position in world income distribution—

given given his national social class (ventile)his national social class (ventile)

Note: Ventile share expressed in percent of total country income. Mean per capita income in $PPP per annum. p-values between brackets.

Results:

• Citizenship premium larger for low social classes than high social classes: each 10% increase in mean country income associated with 2.4 percentoile gain for the poor, and only 1.2 percentale gain for the rich.

• But how important is country’s distribution relative to mean country income (at different ventiles)?

The trade-off: if your social group’s share

increases by one standard deviation (i.e., you get

allocated a much more equal or unequal country), how

much is it worth compared to being allocated a mean-

richer country?

0

5

10

15

20

25

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Social class

Sh

are

of

tota

l in

com

e

0

1

2

3

4

5

6

7

8

Sta

nd

ard

dev

iati

on

of

ven

tile

sh

are

Average share of each ventile in national income distributions and standard deviation of that share

(globally; all in percent of total national income)

Share of total income

Not much variability in income shares

Value of one standard deviation increase in the ventile share at different points of national income distribution

(measured in terms of mean country income)

0.0

10.0

20.0

30.0

40.0

50.0

60.0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Ventile of national income distribution

Incre

ase i

n m

ean

co

un

try i

nco

me (

in %

)

• If allocated very low social class, a 1σ increase in ventile share will boost your position as much as being allocated a 50% mean-richer country (=>distribution matters)

• The same true for very high social classes: distribution matters

• But in the middle, an increase of 1σ does not really mean much (the shares of the middle ventiles are fairly constant across countries)

The equivalent citizenship premium

Conclusion

• Citizenship premium. Given social class, mean country income matters the most for low social classes and its importance decreases monotonically as social class goes up

• But country’s distribution (measured by equivalent country premium) is very important for low social classes and top social classes, and does not matter for the middle

The bottom line

• For low social classes, both mean country income and distribution matter

• For high social classes, distribution matters quite a lot, mean country income less

• For the middle, only mean country income matters

Go back to Rawls and contrast global

inequality to what he would have found

reasonable

Rawls on Concept 1 and Concept 3 inequality

• Neither of them matters• Concept 1 (divergence) is irrelevant if countries have

liberal institutions; it may be relevant for liberal vs. burdened societies

• Irrelevance rooted in two key assumptions: (i) political institutions of liberalism are what matters; (ii) acquisition of wealth immaterial

• Concept 3 is similarly irrelevant once the background conditions of justice exist in all societies

• But Concept 0 (within-national) inequality matters because the difference principle applies within each people

• In Gini terms:

LppyypG j

n

ij

iij

n

i

n

i

iii

)1

1

Go back to our definition of global inequality

Rawls would insist of the minimization of each individual Gini (Gi) so that Term 1 (within-inequality) would be minimized. But differences in mean incomes between the countries can take any value. Term 2 (between inequality) could be very high.

And this is exactly what we observe in real life. Term 2 accounts for 85% of global Gini.

Term 1 Term 2

Global inequality under different scenarios

Gini

Current (2002) global inequality 64.2

Inequality if everybody in a country had mean income of his/her country (the between component = “Rawlsian inequality”)

55.1

Inequality if all mean incomes become equalized (the between component disappeared; both πs and the overlap would change)

37.5

All mean incomes equal; all indivudual incomes equal

0

All equal Different (as now)

All equal 0 55.1 (all country Ginis=0)

Different (as now)

37.5 (all country Ginis as now; πs change)

64.2

Mean country incomes

Individual incomes within country

Global Ginis in different worlds

Composition of global inequality changed: from being mostly due to “class” (within-national), today it is mostly due to “location” (where people live; between-national)

0

10

20

30

40

50

60

70

80

90

1870 2000

C lass

Location

Location

Class

1870

2000

Source: Bourguignon and Morrisson (2002) and Milanovic (2005)

Some Country ComparisonsSome Country Comparisons

Position span National Gini Average position (rank) of

individuals

Position (rank) of the person with country’s

mean income

Countries with the largest position span (>=95)

Colombia 98 58.7 56.1 76

Brazil 98 59.0 58.3 77

Kampuchea 97 73.0 29.4 60

Paraguay 96 54.4 55.6 73

Nicaragua 96 59.0 46.7 67

Panama 95 56.1 51.6 71

Countries with the smallest position span (<25)

Luxembourg 16 30.1 95.2 98

Denmark 21 23.9 92.1 94

Norway 22 27.4 92.6 95

Finland 23 26.7 89.2 91

Other selected countries

USA 38 39.9 90.9 96

United Kingdom 58 37.4 87.2 92

Russia 64 36.9 63.9 71

Nigeria 65 41.8 16.4 19

India 66 27.9 30.1 34

Indonesia 69 34.3 33.4 41

China 81 41.6 49.1 63

Position span and national Gini Coefficient

Low global position of low social classes in the UK

Source: WYD database for the benchmark year 2002.

UK

Spain

Germany

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Position curves for urban areas in China and India, year 2002

Source: WYD data for the benchmark year 2002.

China-urban

India-urban

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Position curves for urban and rural areas in India, year 2002

Source: WYD data for the benchmark year 2002.

India-rural

India-urban

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Same income at the top, vastly different incomes elsewhere: Hungary, Ukraine and Peru

Source: WYD data for the benchmark year 2002.

Hungary

PeruUkraine

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0 5 10 15 20social class

Two among most unequal countries in the world; yet different position of

the middle class: Brazil and South Africa, 2002

Brazil

South Africa

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Similarity between Russia and urban China

Source: WYD database for the benchmark year 2002.

China-urban

Brazil

Russia

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dist

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0 5 10 15 20social class