Transcript Chapter 10

Chapter 10
Growth, Poverty, and Income
Distribution: Some Basic Facts
© Pierre-Richard Agénor
The World Bank
1



A Long-Run Perspective
Some Simple Arithmetic
Some Basic Facts
2
Key Motivation in the Study of Economic Growth:
 Observation that average annual growth rates vary
substantially across countries.
 Conventional neoclassical theory (attributing growth
to technological progress) has proved incapable of
explaining the wide disparities in per capita output
growth rates across countries.
3
A Long-Run Perspective
4
Facts:
 Highest per capita growth rates since 1820
concentrated in those countries that were already
the most prosperous in the early nineteenth century
(Maddison, 1995).
 Overall pattern suggests convergence in income
per capita levels over the very long run among most
advanced industrial countries, but significant
divergence between rich and poor countries over
time.
 From 1870 to 1990, the ratio of per capita incomes
between the richest and poorest countries
increased by a factor of five (Pritchett, 1997).
5


Large disparities in growth behavior within the
developing world, both across countries and over
time.
From 1973-92 average growth rates per annum:
 -1.7% in Ethiopia and Peru.
 6.9% in South Korea.
6
Some Simple Arithmetic
7


Growth and Standards of Living
How Fast Do Economies Catch Up?
8
Growth and Standards of Living

Small differences in output growth between countries
result in large differences in standards of livings over
long periods.
Consider the U.S. and India:
 Income per capita in 1992: $21,558 in the U.S.,
$1,348 in India (measured in 1990 U.S. dollars);
 Apply annual growth rate of 1.8% in the U.S. and
1.2% in India for the next two centuries (based on
observed growth rates for 1913-92);
9

By 2100, per capita income will have reached
$21,558(1.018)108 = $148,036 (U.S),
$1,348(1.012)108 = $4,889 (India).

India’s income per person, as a percentage of
U.S. income per person, will have fallen to 3.3%
in 2100 from 6.3% in 1992. U.S. per capita
income will have risen by a factor of 7 while
India’s level will have risen by only a factor of
3.63. .
10
How Fast Do Economies Catch Up?

Question: Using the growth rates from the last
example, how long will it take each country to double
per capita income?
 For India, doubling income in N years requires that
yN = 21,348 = 1,348(1.012)N
so that,
2 = (1.012)N
and,
N = ln2/ln(1.012)  58.11.
11

For the U.S., the same calculation yields,
N = ln2/ln(1.018)  38.5.
Another question:
 India's objective now is to attain a per capita income
that is equal to 30% of the level of the United States
by 2100. By how much should India grow per year?
US (y IN) denote per capita income in the
 Let y0
0
United States (India) in the year 1992, and gUS =
0.018 and gIN the average growth rate over the
period 1913-92 for each country.
12

Since it takes 108 years to reach 2100 beginning
in 1992, the value of gIN that is to be calculated is
the solution of,
0.3y0US(1.018)108 = y0IN(1 + gIN)108.
Solving for gIN, the target growth rate of output
must be about 3.3% per annum---almost three
times the level observed during the period 191392.
 If India grows by a slightly lower number, 3.0%
per annum, in the year 2100 its per capita income
will be only about 22% of the U.S. level.

13
Some Basic Facts
14
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Output Growth, Factor Inputs, and Population
Saving, Investment, and Growth
Poverty and Growth
Inequality, Growth and Development
Trade, Inflation, and Financial Deepening
15
Output growth, Factor Inputs
and Population



Fact 1. Output per worker (or average labor
productivity) tends to grow over time, albeit at
widely different rates across countries.
Fact 2. The rate of growth of factor inputs (capital
and labor) does not fully account for the rate of
growth of output.
Fact 3. The mean growth rate of output is unrelated
to the initial level of per capita income across
countries (Figure 10.1).
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20
Saving, Investment, and Growth
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
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See figure 10.4.
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27
Poverty and Growth
Two indicators typically used to measure poverty:
 poverty headcount index: measures the proportion
of individuals or households earning less than a given
absolute level of income;
 poverty gap: average shortfall of the income of the
poor with respect to the poverty line, multiplied by the
headcount ratio.
28




Ravallion and Chen (1997) used both types of
indicators and arrived at the following results
(Figure 10.6):
incidence of poverty in developing countries,
measured by headcount index, fell between 1987
and 1993, from 31% to 29%;
depth of poverty (average distance below the
poverty line), changed little;
rural poor are still poorer than urban poor;
differences across regions; poverty incidence fell in
East Asia, South Asia and the MENA region and
rose in Eastern and Central Europe, Latin America,
and sub-Saharan Africa.
29
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
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Fact 7. Durable reductions in poverty rates require
maintaining sustained rates of economic growth
over time. See Figure 10.7.
Other factors important; Agénor (1999) suggested that
inflation has a significant effect on the poor.
Figure 10.8.
Londoño and Székely have suggested that, at least in
Latin America, poverty is strongly associated with a
skewed distribution of income.
Other important variables are access to education,
health services and employment opportunities, and
the degree of urbanization.
31
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.
Inequality, Growth, and Development

Three indicators of income inequality:
 Share of the top to the bottom income deciles or
quintiles--only attaches weight to the two tails of the
income distribution.
 Gini Coefficient.
 Theil Inequality Index is decomposed into two
terms: one that captures inequality due to
differences between groups, and another that
captures inequality within groups.
36
Gini coefficient:
 Derived from the Lorenz curve which displays
cumulative share of total income received by
cumulative shares of the population.
 Measures the area between the Lorenz curve for a
population and the line of perfect equality; it varies
between 0 (maximum equality) and unity (maximum
inequality). See Figure 10.9.
37
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38
Evidence on Growth and Income Distribution
 Data does not show clear pattern between the rate
of growth of income per capita in developing
countries and two measures of income inequality:
the ratio of the share of the richest 20% to the share
of the poorest 20%, and the Gini coeficient. See
Figure 10.10.
39
Ratiofncmesharoftiges20%tolwes20%
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40
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41

Link between inequality, the pattern of growth,
and development:
Kuznets hypothesis: income inequality increases
in the early stages of development and then
decreases.
 Inverted-U shape reflects view that economic
development involves a transition from a lowproductivity, agrarian economy to a highproductivity, industrial economy.
 Industrial incomes, distributed less equally than
agricultural incomes, become more important
during industrialization, leading to greater
inequality.
42
Industry then takes over, average incomes rise,
earnings differentials fall.
 Growth is first unequalizing, then equalizing.
Early evidence broadly confirmed inverted-U patter
with inequality lowest in low-income and high income
countries and highest in middle-income countries.
Recent studies (Bruno, Ravallion, and Squire, 1998
and Fishlow, 1995) have failed to corroborate this
result.
Fact 8: The link between income inequality and
growth appears to be non-linear, but there remains
some controversy about the nature and robustness
of this relationship.




43
Education Inequality and Income Distribution
 Psacharopoulos et al. (1995) and Londoño and
Székely (1997) suggest strong relationship between
educational inequality and income inequality.
 Lipton and Ravallion suggest that the relationship is
nonlinear:
 During first phases of growth in education, income
inequality actually rises; for example, an increase
from 1 to 2 years of education is typically
associated with a 3 -point increase in the Gini
coefficient.
44
Turning point arises when work force attains
between 5 and 6 years of education. e.g. on
passing from 6 to 7 years, Gini falls by .5 point,
from 9 to 10 years, Gini falls by 2 points.
Other Factors and Income Distribution
Cardoso et al. (1995) identified inflation and
unemployment as determinants of income inequality
in Brazil during the 1980s.
Relationship between inflation and income
inequality as nonlinear (Bulir, 1998); inflation
reduction from very high levels reduces income
inequality while further reductions towards very low
levels bring on negligible improvements.



45
Trade, Inflation, Financial Deepening





Fact 9: export and import volume growth both
positively related output growth. evidence on
correlation between openness and growth less robust.
Figure 10.11.
Figure 10.12.
Fact 10: inflation-growth relationship; negative and
nonlinear,
 key for advocating macroeconomic stability;
 nonlinear: reductions in inflation from a low (high)
base have negligible (significant) impacts on
growth.
Figure 10.13.
46
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Fact 11: financial system development is
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Figure 10.14.
51
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