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

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

• Milanovic, Global inequality and its
  implications
• Lecture 10

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1. Large countries an overview
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See also Table 4
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2. Concept 1 and Concept 2 inequalities in large
countries
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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)

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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 ? between population size and growth
• But Concept 2 inequality goes up, population
  weighted divergence (since C and D become
  dissimilar)

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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.

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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

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Concept 1 Gini (unweighted inter-regional
inequality) (across nominal GDPs per capita)
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
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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
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India Real and nominal divergence
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?)
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China (1980-2000)
North to South Shandong Jiangsu Zhejiang
Fujian Guangdong
Red fast growth (1s above the mean) Yellow
average Light yellow slow (1s below the mean)
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India (1980-1999)
Maharashtra (Bombay) Karnataka (Bangalore) Tamil
Nadu (Madras)
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United States
New HampshireMassachusetts Connecticut
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Brazil
West to East Amazonas Para Mato Grosso
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Indonesia
West to East West Nusa Tenggara Jakarta/
Bali Lampung Irian Jaya
Does not include oil and gas sectors.
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Chinese provincial growth 1978-90 and 1990-00
In 1990-2000, poorer regions growing slower than
the average
Beijing, Shanghai and Tienjin not shown
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China's rural and urban mean provincial incomes
in 2000
Source from Kanbur and Zhang 26 provincial
means for rural and 26 for urban.
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Concept 2 Gini (population-weighted
inter-regional inequality)
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!
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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)

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Impact of differential population and GDP per
capita growth on Concept 2 Gini
1980-90 1980-90 1990-2000 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
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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

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Importance of population-weighted divergence
India ß and 95 confidence interval
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Economic and "political economy" convergence
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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

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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)

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3. China and India Concept 3 inequalities
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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)

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Illustration of Concepts 2 and 3 China,
inequality according to HS data
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Decomposing total inequality in China
Based on Ravallion Chen (2004), Kanbur Zhang
(2002), Milanovic (2004)
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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
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4. Role in global income distribution
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Shares of US, China and India in world GDI (in
PPP terms)
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Recall Concepts 2 calculation

• In Gini terms
• where Giindividual country Gini, pincome
  share, yi country income, pi population
  share, µoverall 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

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• As Chinas GDI pc (in PPP terms) is some 10
  times less than the USs, 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 Chinas 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.

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Mean-normalized income distances between China,
India and the US
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Contributions (in Gini points) of differences in
mean incomes between Ch, In, US to Concept 2
inequality
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• 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

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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)