The role of large countries (China and India in particular)

Milanovic, “Global inequality and its implications”

Lecture 10

1. Large countries: an overview

Population in 2000 (in m)

Land area in 2000 (in m

sq.km)

China 1271 9.3 Undefined

India 1033 3.0 Union

United States 283 9.2 Federation

Indonesia 213 1.8 Unitary state

Brazil 172 8.5 Federation

Russia 144 16.9 Federation

Pakistan 141 0.8 Federation

Bangladesh 133 1.3 Unitary state

Nigeria 130 0.9 Federation

Japan 127 0.4 Unitary state

China India USA Brazil Idn

Period 78-01 80-00 77-01 85-01 83-01

Regions 27/30 14/25 50/50 26/26 26/26

Pop. coverage

99 92 100 99 100

Richest Shanghai (22)

Mahar. (3)

Conn. (42)

S Paulo (9)

E. Kalim (14)

Poorest Guizhou (1.6)

Bihar (0.7)

W. Virg (20)

Maranhao (1.3)

E Nusa T (1.1)

Ratio rich

to poor

13.6

4.4

2.1

7.0

12.5

See also Table 4

2. Concept 1 and Concept 2 inequalities in large countries

Three concepts of inequality

• Concept 1: unweighted inequality of regions (or countries) useful for study of convergence (is growth faster in poorer regions?)

• Concept 2: population weighted inequality of regions (countries); "feeling" of inequality, particularly if there are regional cleavages. Also proxy to...

• Concept 3: inequality between individuals in a country (or world)

Example: population weighted divergence

• 2 rich and small regions, A and B• 2 poor and populous regions, C and D• A and C grow fast, B and D slowly, then• no change (or small change) in Concept 1

inequality, no income convergence.• no ρ between population size and growth• But Concept 2 inequality goes up,

population weighted divergence (since C and D become dissimilar)

Why it matters?• Concept 1. An economic question. Will

there be convergence if L,K, goods move relatively freely (compared to impediments that exist between countries)

• Concept 2. A social question. What is the "feeling" of inequality/exclusion (particularly if there are ethnic/religious cleavages). Threat to national cohesion.

The data we use• Regional GDPs per capita

• Concept 1 & 2 inequality calculated across nominal and real GDP per capita; overestimate of inequality (some regional redistribution; price levels higher in richer regions)

• Also in PPPs 95

)95,78(,$95,,, *PPP

DDY

jtji

)r(1*Y tj,i,d1,78,tj,i,

Concept 1 Gini (unweighted inter-regional inequality) (across nominal GDPs per capita)

0.000

0.100

0.200

0.300

0.400

Years

Gini

Brazil

China

India

USA

Indonesia

Highest regional inequality in China; lowest in the US (despite having 50 units)

China: regional convergence in the '80s

India & Indon. regional divergence throughout

US: regional convergence since early 80's

Provincial mean-normalized incomes in 1980 and 2000 (mean is unweighhted all-China mean)

0

1

2

3

4

5

6

0 1 2 3 4 5 6

1980

20

00

Shanghai

Beijing

TianjinZhejiang

Jiansu

0.20

0.24

0.28

0.32

0.36

0.40

1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

nominals

reals

China: Concept 1 Gini inequality in nominal and real terms

No real convergence: no systematic difference in real growth rates btw. the provinces

Between 1978 and 1990 prices rose faster in poorer regions

India: Real and nominal divergence

0.0

0.1

0.1

0.2

0.2

0.3

1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

nominals

reals

Nominal and real inequality rise step in step up to about 1991

Since then nominal divergence stops while real continues

Price catch-up of poorer provinces (better integrated domestic market?)

China (1980-2000)

Red: fast growth (1σ above the mean)

Yellow: average

Light yellow: slow (1σ below the mean)

North to SouthShandongJiangsuZhejiang FujianGuangdong

India (1980-1999)

Maharashtra (Bombay)Karnataka (Bangalore)Tamil Nadu (Madras)

United States

New HampshireMassachusetts Connecticut

Brazil

West to EastAmazonasParaMato Grosso

Indonesia

Does not include oil and gas sectors.

West to EastWest Nusa TenggaraJakarta/ BaliLampungIrian Jaya

Chinese provincial growth 1978-90 and 1990-005

79

11av

erag

e gro

wth

rate

of GD

P pe

r cap

ita 19

78-9

0

300 500 700 900 1100 1300GDP per capita in 1978

57

911

aver

age

grow

th ra

te o

f GDP

per

cap

ita 1

990-

00

800 1300 1800 2300 2800GDP per capita in 1990

In 1990-2000, poorer regions growing slower than the averageBeijing, Shanghai and Tienjin not shown

China's rural and urban mean provincial incomes in 2000

Source: from Kanbur and Zhang; 26 provincial means for rural and 26 for urban.

kden

sity

gdp

ppp

0 5000 10000 15000 20000 25000GDP per capita in 95 PPP

rural urban

Concept 2 Gini (population-weighted inter-regional inequality)

0.000

0.100

0.200

0.300

0.400

Years

Gini

Brazil

China

India

USA

Indonesia

1990's: Increasing Concept 2 inequality in the three Asian countries

Highest inequality in Brazil. If all people in each state had the same income, Gini would be still more than 30. In the United States less than 10!

What drives Concept 2 inequality?

• Different population growth rates by region

• Correlation between growth rates and population size (do more populous states grow faster implications for the productivity view of growth; poverty reduction)

Impact of differential population and GDP per capita growth on Concept 2 Gini

1980-90 1990-2000

Diff. Population

effect

Diff. Growth effect

Population effect

Diff. Growth effect

USA 0 +1.8 +0.1 -0.6

China 0 -2.9 +0.4 +2.6

India 0 +1.3 0 +2.5

Brazil +0.1 -0.4 0 -3.0

Indon. -0.8 +0.3 -0.1 +1.1

Results (for Concept 2 inequality)

• Differential population growth not important

• Growth disequalizing in India throughout

• China: differential growth rates equalizing in 1980-90, then disequalizing in 1990-2000

Importance of population-weighted divergence

Pop Y in 1980 Growth1980-200

Mahar 95 1300 60

UP 170 680 15

Bihar 107 512 0-0.04

0.00

0.04

0.08

0.12

1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999

Years

Beta

value

India: β and 95% confidence interval

Economic and "political economy" convergenceReal incomes Nominal incomes

Concept 1 Are growth ratesnegatively relatedto intial realincome?

Are pricesmoving the sameway in poor andrich regions?

Concept 2 (Basically)convergenceamong the subsetof populousregions

Are pricesmoving the sameway in poor andrich populousregions?

Conclusions• Asia: increasing regional inequality in the

1990's (India and China; not Indonesia)• Concept 2 increases important for national

cohesion (India and China)• Growth disequalizing; higher income level

equalizing; no evidence that nation-wide openness positively related to Concept 2 inequality

• Populous states’ outcomes diverge in both India and China

Complexity of the process

• In both China and India, a process directly opposite to what we observe at global level

• In China & India: Concept 1 inequality going down, Concept 2 inequality up

• World: Concept 1 inequality up, Concept 2 inequality down (and the latter solely due to high average growth of China & India)

3. China and India Concept 3 inequalities

China: Inequality according to HS data

• Increase in Concept 3 between 1980 and 2000 about 14 Gini points (according to Ravallion and Chen)

• Explained by rising differences between mean provincial incomes (~8 Gini points),

• rising differences urban and rural areas (~2 Gini points)

• rising differences within urban and rural areas (another 3 Gini points)

Illustration of Concepts 2 and 3: China, inequality according to HS data

0

0.1

0.2

0.3

0.4

0.5

1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

Concept 2: provinces only (from K-ZH, BM calcul)

Concept 2: provinces and U/R (from K-Zh)

Concept 3: from Ravallion and Chen

Inequality within urban and urban areas (10%)

Urban/rural inequality (35%)

Inequality between provinces (55%)

Decomposing total inequality in China

0.00

0.10

0.20

0.30

0.40

0.50

Inequality between provinces

Rural/urban inequality

Other inequality

1980 2000

Gini = 44

Gini = 31

Based on Ravallion & Chen (2004), Kanbur & Zhang (2002), Milanovic (2004)

China and India compared (Gini points)

China 2000 India 1997

Inequality between provinces/states

24 22

Rural-urban inequality 13 7

Inequality within R/U areas

7 9

Total inequality 44 38

Urban-rural ratio 3.1-1 1.8-1

From IndiaChina.xls file; China: based on HBS data; India based on state GDIs, italics: estimates

4. Role in global income distribution

Shares of US, China and India in world GDI (in $PPP terms)

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

40.0

45.0

United States

China

India

• In Gini terms:

• where Gi=individual country Gini, π=income share, yi = country income, pi = population share, μ=overall mean income, n = number of countries

• For each pair of countries depends on the mean-normalized gap between their per capita incomes and population shares

Recall Concepts 2 calculation:

j

n

i

n

ij

ij pipyy

)(1

• As China’s GDI pc (in $PPP terms) is some 10 times less than the US’s, if China grows at 10% per annum, US needs to grow only 1% to keep the numerator the same.

• Then, only if world mean income grows, will the China-US contribution to international ineqaulity go down.

• Almost all of China’s contribution to reduced Concept 2 inequality comes from its catching up of other countrieds (not the United States); and (as we shall see below) only 2/3 of it is due to growth.

Mean-normalized income distances between China, India and the US

0.0

1.0

2.0

3.0

4.0

5.0

1965 1978 2000

US-ChinaUS-India

China-india

Contributions (in Gini points) of differences in mean incomes between Ch, In, US to Concept 2 inequality

0

2

4

6

8

10

12

1965 1978 2000

China-US

US-India

India-China

• About 20% of Concept 2 inequality explained by the “triangle”

• US-China mean-normalized GDI per capita gap decreased from 4.5 to 4 (btw. 1965 and 2000)

• Gini contribution of US-China decreased 6.3 to 4.2 points (over the same period)

• Between 1978 (reforms in China) and 2000, more than 1/3 of the China decrease to Concept 2 inequality due to the population effect (↓ share of world population; from 24% to 22%)

• Difference between China and India adds to global inequality

China component in Concept 2 inequality

1978 2000 Change

Concept 2 inequality 59.4 53.4 -6.0

China component 20.9 16.1 -4.8

China economy component (if pop. share at 1978 level)

20.9 17.8 -3.1

China population component (if GDI pc relative to the world at 1978 level)

20.9 19.2 -1.7

Memo: Mean-normalized distance to the US

4.25 4.0

Source: Jiang Zhiyong (2005)