Xavier Sala-i-Martin
Columbia University
April 2009
Goal
 Estimate WDI consistent with the empirical growth
evidence (which uses GDP per capita as the mean of
each country/year distribution).
 Estimate Poverty Rates and Counts resulting from this
distribution
 Estimate Income Inequality across the world’s citizens
 Estimate welfare across the world’s citizens
 Analyze the relation between poverty and growth,
poverty and inequality
Data
 GDP Per capita (PPP-Adjusted –See Note next page).
 We usually use these data as the “mean” of each
country/year distribution of income (for example, when
we estimate growth regressions)
 Note: I decompose China and India into Rural and
Urban
 Use local surveys to get relative incomes of rural and
urban
 Apply the ratio to PWT GDP and estimate per capita
income in Rural and Urban and treat them as separate
data points (as if they were different “countries”)
 Using GDP Per Capita we know…
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
GDP Per Capita Since 1970
$10,000
$9,000
$8,000
$7,000
$6,000
$5,000
$4,000
$3,000
$2,000
$1,000
$0
GDP per Capita
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Annual Growth Rate of World Per Capita GDP
5.00%
4.00%
3.00%
2.00%
1.00%
0.00%
-1.00%
-2.00%
Growth of Per Capita GDP
Mean Growth (1.99%)
-.05
0
.05
.1
β-Non-Convergence 1970-2006
4
6
8
gdppc70l
95% CI
grgdppc7006
10
Fitted values
12
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
σ-Divergence (191 countries)
1.22
1.2
1.18
1.16
1.14
1.12
1.1
1.08
1.06
1.04
1.02
1
S.D. Log GDP per Capita
10
5
0
Frequency
15
20
Histogram Income Per Capita (countries)
4
6
8
gdppc70l
10
12
15
Frequency
10
5
0
6
7
8
gdppc80l
9
10
11
6
7
8
gdppc90l
9
10
11
0
5
10
Frequency
15
20
15
Frequency
10
5
0
6
7
8
gdppc00l
9
10
11
6
8
gdppc06l
10
12
0
5
10
Frequency
15
Adding Population Weights
4
6
8
gdppc70l
10
12
0
POP70
200000400000600000
800000
6
7
8
gdppc80l
9
10
11
0
1000000
POP80
200000400000600000
800000
6
7
8
gdppc90l
9
10
0
500000 POP90
1000000
1500000
6
7
8
gdppc00l
9
10
11
0
500000 POP00
1000000
1500000
6
7
8
gdppc06l
9
10
11
Back
0
500000 POP06
1000000
1500000
-.05
0
.05
.1
β-Non-Convergence 1970-2006
4
6
8
gdppc70l
95% CI
grgdppc7006
10
Fitted values
12
-.05
0
.05
.1
Population-Weighted
β-convergence (1970-2006)
4
6
8
gdppc70l
95% CI
grgdppc7006
10
Fitted values
12
But NA Numbers do not show Personal
Situation: Need Individual Income
Distribution
• We can use Survey Data
• Problem
• Not available for every year
• Not available for every country
• Survey means do not coincide with NA means
Surveys not available every year
 Can Interpolate Income Shares (they are slow moving
animals)
 Regression
 Near-Observation
 Cubic Interpolation
 Others
Strategy 1: (Sala-i-Martin 2006)
USA Income share of Quintile 1
USA Income share of Quintile 2
0.06
0.14
0.05
0.12
0.10
0.04
0.08
y = -0.0004x + 0.056
R2 = 0.7013
Quintile 1
Linear (Quintile 1)
Quintile 2
USA Income share of Quintile 3
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1970
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
0.00
1970
0.02
0.00
1976
0.04
0.01
1974
0.02
y = -0.0007x + 0.1218
R2 = 0.9503
0.06
1972
0.03
Linear (Quintile 2)
USA Income share of Quintile 4
0.3
0.25
0.2
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
0.2
y = -0.0007x + 0.1795
R2 = 0.8822
0.1
0.05
1998
1996
1994
Linear (Quintile 3)
1992
1990
1988
1986
1984
Quintile 3
1982
1980
1978
1976
1974
1972
1970
0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
Quintile 5
Linear (Quintile 5)
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
y = 0.002x + 0.4002
R2 = 0.9307
Quintile 4
Linear (Quintile 4)
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
0
USA Income share of Quintile 5
1970
y = -0.0002x + 0.2426
R2 = 0.1933
0.15
China Income share of Quintile 1
Quintile 1
Linear (Quintile 1)
Quintile 2
China Income share of Quintile 3
1998
1996
1994
1992
1990
1988
1986
Linear (Quintile 2)
China Income share of Quintile 4
y = -0.002x + 0.2025
R2 = 0.6571
0.25
1984
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
0
1982
0.02
1980
0.04
1978
0.06
1976
0.08
y = -0.0022x + 0.1613
R2 = 0.6646
1974
0.1
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
1972
y = -0.0021x + 0.1126
R2 = 0.6565
1970
0.12
China Income share of Quintile 2
0.35
0.3
0.2
0.25
0.15
0.2
0.15
0.1
y = -2E-05x + 0.2506
R2 = 1E-05
0.1
0.05
0.05
0
Quintile 3
Linear (Quintile 3)
Linear (Quintile 5)
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
y = 0.0063x + 0.2753
R2 = 0.661
Quintile 5
Linear (Quintile 4)
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
Quintile 4
China Income share of Quintile 5
0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
1970
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
0
India Income share of Quintile 1
0.10
0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0.00
India Income share of Quintile 2
0.14
0.12
y = 4E-05x + 0.0873
R2 = 0.0123
y = -0.0002x + 0.1294
R2 = 0.1602
0.10
0.08
0.06
0.04
0.02
Quintile 1
Linear (Quintile 1)
1998
1996
1994
1992
1990
1988
1986
1984
1982
Quintile 2
India Income share of Quintile 3
Linear (Quintile 2)
India Income share of Quintile 4
y = -0.0003x + 0.1694
R2 = 0.2915
0.2
0.18
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
1980
1978
1976
1974
1972
1970
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
0.00
0.25
0.2
y = -0.0006x + 0.2234
R2 = 0.4097
0.15
0.1
0.05
Quintile 3
Linear (Quintile 3)
Linear (Quintile 5)
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
y = 0.001x + 0.3903
R2 = 0.2291
Quintile 5
Linear (Quintile 4)
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
Quintile 4
India Income share of Quintile 5
0.5
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
1970
1998
1996
1994
1992
1990
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
0
Missing Countries
 Can approximate using neighboring countries
Strategy 2: Pinkovkiy and Sala-i-Martin
(2009)
Method: Interpolate Income Shares





Break up our sample of countries into regions(World Bank region definitions).
Interpolate the quintile shares for country-years with no data, according to the following scheme, and
in the following order:
Group I – countries with several years of distribution data
 We calculate quintile shares of years with no income distribution data that are WITHIN the
range of the set of years with data by cubic spline interpolation of the quintile share time series
for the country.
 We calculate quintile shares of years with no data that are OUTSIDE this range by assuming that
the share of each quintile rises each year after the data time series ends by beta/2^i, where i is the
number of years after the series ends, and beta is the coefficient of the slope of the OLS
regression of the data time series on a constant and on the year variable. This extrapolation
adjustment ensures that 1) the trend in the evolution of each quintile share is maintained for the
first few years after data ends, and 2) the shares eventually attain their all-time average values,
which is the best extrapolation that we could make of them for years far outside the range of our
sample.
Group II – countries with only one year of distribution data.
 We keep the single year of data, and impute the quintile shares for other years to have the same
deviations from this year as does the average quintile share time series taken over all Group I
countries in the given region, relative to the year for which we have data for the given country.
Thus, we assume that the country’s inequality dynamics are the same as those of its region, but
we use the single data point to determine the level of the country’s income distribution.
Group III – countries with no distribution data.
 We impute the average quintile share time series taken over all Group I countries in the given
region.
Method 2: Step 1: Find the σ of the
lognormal distribution using least squares
for the country/years with survey data


We now have a set of quintile shares for every country-year under consideration.
We then use the assumption that the income distribution for each country-year is lognormal to
compute the formulas for the population quintile shares of the lognormal distribution. These are
given by


i
j 1
q j     1  0.2i     , i  1,
, 4 , where qi is the quintile share of the ith quintile.
These formulas are very useful in that they express the quintile shares as functions of the scale
parameter  alone.
We then define ˆ as the value of  that minimizes the sum of squared deviations between the
sample quantities and the population.
o This least-squares method should generate a consistent, asymptotically normal
estimator of  , since the sample quintiles are consistent, asymptotically normal
estimators of the population quintiles and ˆ is an implicitly defined continuous
function of the sample quintile shares.
o Since all other estimators that we use are continuous functions of ˆ and the national
accounts means (which are assumed to be the true mean income values for the
respective country-years), all our estimators of the lognormal parameters and poverty
and inequality measures should be consistent and asymptotically normal
Step 2: Compute the resulting normal
distributions for each country-year
We then easily estimate the location parameter  of the lognormal distribution by the formula
ˆ  ln  gdp   1/ 2 ˆ 2 , where “gdp” is the national accounts mean for the country-year. We use the
lognormal distribution defined by  ˆ , ˆ  to get point estimates of the poverty and inequality measures
for the country-year, and the aggregated world distribution for each year to obtain point estimates of
the poverty and inequality measures for the world as a whole for that year.
Step 3: Estimate implied Gini coefficients for
country/years with available surveys
Step 4: Three Types of countries
 Countries with multiple surveys
 Intrapolate ginis
 Estimate location parameter as a function of sigma(Gini) for
intrapolated years and then estimate the mean with sigma and GDP
per capita
 Countries with ONE survey
 We keep the single year of data, and impute the Ginis for other years to
have the same deviations from this year as does the average Gini time series
taken over all Group I countries in the given region, relative to the year for
which we have data for the given country (ie, we assume that the country’s
inequality dynamics are the same as those of its region, but we use the
single data point to determine the level of the country’s income
distribution.)
 Countries with NO distribution data
 We impute the average Gini time series taken over all Group I
countries in the given region.
Step 5: Integrate across countries and
get the WDI
Summary of Baseline Assumptions
 We use GDP data from PWT 6.2
 Sensitivity: WB, Madison
 We break up China and India into urban and rural components, and
use POVCAL surveys for within country inequality.
 Sensitivity: China and India are treated as unitary countries
 We use piecewise cubic splines to interpolate between available survey
data, and extrapolate by horizontal projection.
 Sensitivity Interpolation: 1) nearest-neighbor interpolation, 2) linear
interpolation.
 Sensitivity Extrapolation: 1) assuming that the trends closest to the
extrapolation period in the survey data continue unabated and
extrapolating linearly using the slope of the Gini coefficient between the
last two data points, and 2) a mixture of the two methods in which we
assume the Gini coefficient to remain constant into the extrapolation
period, except if the last two years before the extrapolation period both
have true survey data.
 Lognormal distributions
 Sensitivity: 1) Gamma, 2) Weibull, 3) Optimal (Minimum Squares of
residuals), 4) Kernels
Results
China
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
Total 1970
Urban 1970
$5,000
Rural 1970
$50,000
$1/day ($312, $554)
China
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
Total 1980
Urban 1980
$5,000
Rural 1980
$50,000
$1/day ($312, $554)
China
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
Total 1990
Urban 1990
$5,000
Rural 1990
$50,000
$1/day ($312, $554)
China
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
Total 2000
Urban 2000
$5,000
Rural 2000
$50,000
$1/day ($312, $554)
China
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
Total 2006
Urban 2006
$5,000
Rural 2006
$50,000
$1/day ($312, $554)
Back
China Rural
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
Rural 1970
Rural 1980
$5,000
Rural 1990
Rural 2000
$50,000
Rural 2006
1$/day
China Urban
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
Urban 1970
Urban 1980
$5,000
Urban 1990
Urban 2000
$50,000
Urban 2006
1$/day
China Total
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
$5,000
$50,000
Total 1970
Total 1980
Total 1990
Total 2000
Total 2006
$1/day ($312 , $554 a year)
China
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
$5,000
$50,000
Total 1970
Urban 1970
Rural 1970
Total 1980
Urban 1980
Rural 1980
Total 1990
Urban 1990
Rural 1990
Total 2000
Urban 2000
Rural 2000
Total 2006
Urban 2006
Rural 2006
1$/day
India
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
Total 1970
Urban 1970
$5,000
Rural 1970
$50,000
$1/day ($312 . $554)
India
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
Total 1980
Urban 1980
$5,000
Rural 1980
$50,000
$1/day ($312 . $554)
India
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
Total 1990
Urban 1990
$5,000
Rural 1990
$50,000
$1/day ($312 . $554)
India
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
Total 2000
Urban 2000
$5,000
Rural 2000
$50,000
$1/day ($312 . $554)
India
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
Total 2006
Urban 2006
$5,000
Rural 2006
$50,000
$1/day ($312 . $554)
Back
India Urban
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
$5,000
$50,000
Urban 1970
Urban 1980
Urban 1990
Urban 2000
Urban 2006
$1/day ($312 . $554)
India Rural
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
$5,000
$50,000
Rural 1970
Rural 1980
Rural 1990
Rural 2000
Rural 2006
$1/day ($312 . $554)
India Total
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
Total 1970
$500
Total 1980
$5,000
Total 1990
Total 2000
$50,000
Total 2006
$1/day ($312 . $554)
India
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
$5,000
$50,000
Total 1970
Urban 1970
Rural 1970
Total 1980
Urban 1980
Rural 1980
Total 1990
Urban 1990
Rural 1990
Total 2000
Urban 2000
Rural 2000
Total 2006
Urban 2006
Rural 2006
$1/day ($312 . $554)
United States
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
$50
$500
$5,000
1970
$1/day ($312, $554)
$50,000
United States
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
$500
$5,000
$50,000
1970
$1/day ($312, $554)
$500,000
United States
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
$500
$5,000
$50,000
1980
$1/day ($312, $554)
$500,000
United States
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
$500
$5,000
$50,000
1990
$1/day ($312, $554)
$500,000
United States
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
$500
$5,000
$50,000
2000
$1/day ($312, $554)
$500,000
United States
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
$500
$5,000
$50,000
2006
$500,000
$1/day ($312, $554)
Back
United States
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
$500
$5,000
1970
1980
$50,000
1990
2000
2006
$500,000
$1/day ($312, $554)
Indonesia
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
$50
$500
1970
1980
$5,000
1990
2000
2006
$50,000
$1/day ($312, $554)
Brazil
4,000
3,500
3,000
2,500
2,000
1,500
1,000
500
0
$50
$500
1970
1980
$5,000
1990
2000
2006
$50,000
$1/day ($312, $554)
Brazil
2,000
1,800
1,600
1,400
1,200
1,000
800
600
400
200
0
$50
$500
1970
1980
1990
2000
2006
$1/day ($312, $554)
Brazil vs Indonesia 1970
4,000
3,500
3,000
2,500
2,000
1,500
1,000
500
0
$50
$500
Brazil
$5,000
Indonesia
$1/day ($312, $554)
$50,000
Bangladesh
4,000
3,500
3,000
2,500
2,000
1,500
1,000
500
0
$50
$500
1970
1980
$5,000
1990
2000
2006
$50,000
$1/day ($312, $554)
Bangladesh
4,000
3,500
3,000
2,500
2,000
1,500
1,000
500
0
$50
$500
1970
1980
1990
2000
2006
$1/day ($312, $554)
Nigeria
4,000
3,500
3,000
2,500
2,000
1,500
1,000
500
0
$50
$500
1970
1980
$5,000
1990
2000
2006
$50,000
$1/day ($312, $554)
Nigeria vs China 1970
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
Nigeria
$5,000
China
$1/day ($312, $554)
$50,000
Nigeria vs China 2006
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
Nigeria
$5,000
China
$1/day ($312, $554)
$50,000
Nigeria vs China 1970
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
$50
$500
Nigeria
$5,000
China
$1/day ($312, $554)
$50,000
Nigeria vs China 2006
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
$50
$500
Nigeria
$5,000
China
$1/day ($312, $554)
$50,000
Nigeria
4,000
3,500
3,000
2,500
2,000
1,500
1,000
500
0
$50
$500
1970
1980
1990
2000
2006
$1/day ($312, $554)
Nigeria
700
600
500
400
300
200
100
0
$5,000
1970
1980
1990
2000
2006
$1/day ($312, $554)
Japan
6,000
5,000
4,000
3,000
2,000
1,000
0
$50
$500
1970
1980
$5,000
1990
2000
2006
$50,000
$1/day ($312, $554)
Mexico
2,500
2,000
1,500
1,000
500
0
$50
$500
1970
1980
$5,000
1990
2000
2006
$50,000
$1/day ($312, $554)
Mexico
700
600
500
400
300
200
100
0
$50
$500
1970
1980
1990
2000
2006
$1/day ($312, $554)
USSR-FSU
12,000
10,000
8,000
6,000
4,000
2,000
0
$50
$500
$5,000
1970
$1/day ($312, $554)
$50,000
USSR-FSU
12,000
10,000
8,000
6,000
4,000
2,000
0
$50
$500
$5,000
1980
$1/day ($312, $554)
$50,000
USSR-FSU
12,000
10,000
8,000
6,000
4,000
2,000
0
$50
$500
$5,000
1990
$1/day ($312, $554)
$50,000
USSR-FSU
12,000
10,000
8,000
6,000
4,000
2,000
0
$50
$500
$5,000
2000
$1/day ($312, $554)
$50,000
USSR-FSU
12,000
10,000
8,000
6,000
4,000
2,000
0
$50
$500
$5,000
2006
$50,000
$1/day ($312, $554)
Back
USSR-FSU
12,000
10,000
8,000
6,000
4,000
2,000
0
$50
$500
1970
1980
$5,000
1990
2000
2006
$50,000
$1/day ($312, $554)
USSR-FSU
8,000
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
$300
$3,000
1970
1980
1990
2000
2006
$1/day ($312, $554)
USSR-FSU
10,000
9,000
8,000
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
$10,000
$100,000
1970
1980
1990
2000
2006
$1/day ($312, $554)
1970
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
OECD
1975
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
OECD
1980
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
OECD
1981
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
OECD
1982
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
OECD
1983
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
OECD
1984
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
OECD
1985
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
OECD
1986
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
OECD
1987
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
OECD
1988
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
OECD
1989
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
OECD
1990
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
OECD
1995
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
OECD
2000
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
OECD
2005
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
OECD
2006
50,000
45,000
40,000
35,000
30,000
25,000
20,000
15,000
10,000
5,000
0
$50
$500
SSA
EA
SA
$5,000
Latam
MENA
FSU
$50,000
EEU
HNOECD
Back
OECD
1970
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
1975
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
1980
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
1981
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
1982
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
1983
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
1984
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
1985
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
1986
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
1987
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
1988
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
1989
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
1990
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
1995
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
2000
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
2005
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
2006
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
SSA
$500
EA
SA
Latam
$5,000
MENA
FSU
$50,000
EEU
HNOECD
OECD
World
Back
World F_Normal
120,000
100,000
80,000
60,000
40,000
20,000
0
$50
$500
1970
1980
$5,000
1990
2000
$50,000
2006
$1/day ($312, $554)
World CDF Normal
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
$50
$500
1970
1980
$5,000
1990
2000
$50,000
2006
$1/day ($312, $554)
World CDF Normal
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
$50
$500
$5,000
1970
2006
$1/day ($312, $554)
$50,000
CDF Normal vs Kernel 1970
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
$50
$500
Normal 1970
$5,000
Kernel 1970
$50,000
$1/day ($312, $554)
CDF Normal vs Kernel 2006
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
$50
$500
Normal
$5,000
Kernel
$1/day ($312, $554)
$50,000
WDI Normal vs Kernel 2006
120,000.00
100,000.00
80,000.00
60,000.00
40,000.00
20,000.00
0.00
$50
$500
Normal
$5,000
Kernel
$1/day ($312, $554)
$50,000
Poverty Rates: $1/day
Poverty Rates
World Poverty Rates for Different Poverty Lines, 1970-2006
.8
Poverty Rate
.6
.4
.2
0
1970
1980
1990
year
2000
$1/Day USD 2006
$1/Day
$2/Day
$5/Day
$7.5/Day
$10/Day
2010
$3/Day
TABLE 1: Poverty Rates (percent of world population below each poverty line)
year One 2006 Dollar
$1/day
$2/day
$3/day
$5/day
$10/day
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Change 1970-2006
Change 1990-2006
% Change 1970-2006
%Change 1990-2006
0.123
0.110
0.110
0.101
0.101
0.092
0.090
0.084
0.071
0.064
0.060
0.052
0.046
0.043
0.041
0.039
0.038
0.039
0.037
0.039
0.039
0.040
0.039
0.040
0.039
0.041
0.039
0.038
0.038
0.037
0.037
0.038
0.037
0.035
0.035
0.034
0.033
0.279
0.267
0.266
0.256
0.257
0.245
0.241
0.231
0.211
0.198
0.187
0.169
0.148
0.136
0.124
0.111
0.104
0.100
0.093
0.097
0.093
0.096
0.094
0.092
0.087
0.088
0.083
0.080
0.078
0.076
0.075
0.075
0.074
0.072
0.070
0.067
0.066
0.457
0.451
0.450
0.444
0.447
0.439
0.433
0.426
0.413
0.408
0.398
0.390
0.376
0.365
0.346
0.328
0.307
0.291
0.276
0.277
0.267
0.268
0.261
0.254
0.239
0.232
0.217
0.206
0.198
0.189
0.185
0.182
0.178
0.173
0.165
0.157
0.149
0.550
0.545
0.544
0.539
0.541
0.536
0.530
0.525
0.517
0.515
0.508
0.506
0.503
0.498
0.485
0.476
0.452
0.436
0.422
0.420
0.405
0.403
0.395
0.388
0.372
0.360
0.341
0.327
0.316
0.304
0.296
0.291
0.284
0.276
0.262
0.248
0.235
0.643
0.639
0.634
0.628
0.628
0.626
0.619
0.615
0.611
0.612
0.609
0.609
0.611
0.610
0.610
0.608
0.598
0.589
0.583
0.580
0.569
0.565
0.558
0.552
0.542
0.529
0.514
0.500
0.490
0.478
0.466
0.458
0.449
0.437
0.420
0.402
0.383
0.773
0.767
0.758
0.748
0.745
0.742
0.733
0.729
0.724
0.723
0.721
0.721
0.723
0.723
0.723
0.722
0.720
0.719
0.717
0.718
0.722
0.724
0.725
0.725
0.722
0.717
0.712
0.703
0.699
0.690
0.679
0.672
0.661
0.650
0.636
0.620
0.603
-0.1
0.0
-73.19%
-14.39%
-0.2
0.0
-76.55%
-29.85%
-0.3
-0.1
-67.34%
-44.06%
-0.3
-0.2
-57.27%
-41.96%
-0.3
-0.2
-40.43%
-32.62%
-0.2
-0.1
-21.97%
-16.45%
Rates or Headcounts?
 Veil of Ignorance: Would you Prefer your children to
live in country A or B?
• (A) 1.000.000 people and 500.000 poor
(poverty rate = 50%)
• (B) 2.000.000 people and 666.666 poor
(poverty rate =33%)
 If you prefer (A), try country (C)
• (C) 500.000 people and 499.999 poor.
Poverty Counts
Poverty Counts
World Poverty Counts for Different Poverty Lines, 1970-2006
4000
3000
2000
1000
0
1970
1980
1990
year
2000
$1/Day - USD 2006
$1/Day
$2/Day
$5/Day
$7.5/Day
$10/Day
2010
$3/Day
year World Population
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Change 1970-2006
Change 1990-2006
% Change 1970-2006
%Change 1990-2006
One 2006 Dollar
Table 2: Poverty Counts (Thousands of People below each poverty line)
$1/day
$2/day
$3/day
$5/day
$10/day
3,606,646.0
3,681,281.0
3,755,533.0
3,829,299.0
3,902,750.0
3,974,246.0
4,044,943.0
4,115,778.0
4,186,440.0
4,259,927.0
4,344,658.0
4,417,978.0
4,495,735.0
4,573,770.0
4,709,259.0
4,789,305.0
4,870,966.0
4,955,597.0
5,043,809.0
5,140,045.0
5,248,769.0
5,330,761.0
5,416,449.0
5,496,619.0
5,575,946.0
5,655,997.0
5,734,735.0
5,813,939.0
5,892,413.0
5,970,596.0
6,047,572.0
6,123,042.0
6,195,291.0
6,269,550.0
6,343,710.0
6,419,510.0
6,491,237.0
444,641.3
406,738.1
411,561.0
386,184.8
395,766.0
366,514.3
365,477.5
345,794.9
296,380.5
270,530.4
260,364.0
231,865.0
205,232.3
196,646.9
194,516.9
185,695.5
184,987.2
193,838.7
185,347.3
200,383.9
202,621.8
215,331.0
213,817.3
218,595.5
217,812.4
229,781.8
224,335.3
221,095.5
225,553.7
223,743.2
225,531.3
230,941.1
230,246.5
221,618.2
220,407.7
216,642.8
214,531.8
1,007,538.0
984,720.0
999,249.8
981,950.8
1,004,700.0
975,240.6
973,105.5
951,294.7
881,817.3
842,980.0
813,840.8
748,141.5
665,976.8
622,173.4
582,329.9
532,438.8
508,050.4
495,716.2
468,115.8
496,126.5
490,153.3
511,443.2
509,414.8
507,336.5
487,109.1
500,377.3
477,813.1
466,003.8
461,732.8
453,389.5
455,322.3
459,863.0
457,918.3
450,007.8
443,006.1
433,097.9
425,216.2
1,648,511.0
1,659,322.0
1,689,943.0
1,699,996.0
1,742,651.0
1,744,393.0
1,751,912.0
1,754,359.0
1,729,552.0
1,738,154.0
1,727,627.0
1,722,229.0
1,692,197.0
1,668,643.0
1,627,128.0
1,569,960.0
1,494,990.0
1,442,980.0
1,390,318.0
1,426,302.0
1,400,471.0
1,426,305.0
1,412,927.0
1,397,167.0
1,331,746.0
1,313,307.0
1,243,264.0
1,198,167.0
1,164,305.0
1,128,356.0
1,119,703.0
1,115,204.0
1,105,123.0
1,084,718.0
1,048,866.0
1,007,580.0
968,882.9
1,983,942.0
2,007,323.0
2,041,934.0
2,062,489.0
2,110,316.0
2,130,391.0
2,145,033.0
2,161,679.0
2,165,001.0
2,195,136.0
2,207,945.0
2,235,265.0
2,259,232.0
2,277,091.0
2,285,972.0
2,280,631.0
2,200,567.0
2,158,356.0
2,126,567.0
2,156,436.0
2,125,605.0
2,148,116.0
2,139,333.0
2,133,969.0
2,074,965.0
2,036,325.0
1,957,865.0
1,899,619.0
1,859,742.0
1,813,257.0
1,791,115.0
1,780,000.0
1,762,351.0
1,727,319.0
1,664,438.0
1,594,872.0
1,525,622.0
2,320,645.0
2,352,244.0
2,381,762.0
2,405,316.0
2,451,273.0
2,486,075.0
2,503,232.0
2,532,818.0
2,559,641.0
2,606,902.0
2,645,252.0
2,691,429.0
2,745,659.0
2,790,940.0
2,870,739.0
2,910,372.0
2,913,693.0
2,921,185.0
2,938,968.0
2,979,478.0
2,985,646.0
3,010,542.0
3,019,925.0
3,036,761.0
3,019,744.0
2,992,975.0
2,949,788.0
2,907,866.0
2,889,217.0
2,851,840.0
2,818,526.0
2,806,690.0
2,783,187.0
2,740,697.0
2,664,595.0
2,579,862.0
2,488,103.0
2,786,990.0
2,823,650.0
2,847,501.0
2,865,353.0
2,906,424.0
2,949,548.0
2,964,454.0
2,999,564.0
3,029,117.0
3,078,563.0
3,130,533.0
3,185,929.0
3,251,121.0
3,304,582.0
3,404,412.0
3,459,193.0
3,507,443.0
3,562,329.0
3,616,456.0
3,692,695.0
3,787,708.0
3,861,495.0
3,929,054.0
3,984,752.0
4,023,876.0
4,056,164.0
4,080,834.0
4,089,448.0
4,120,422.0
4,121,021.0
4,105,643.0
4,113,926.0
4,097,103.0
4,073,520.0
4,033,179.0
3,981,031.0
3,913,945.0
2,884,591.0
1,242,468.0
79.98%
23.67%
-230,109.5
11,910.0
-51.75%
5.88%
-582,321.8
-64,937.1
-57.80%
-13.25%
-679,628.1
-431,588.1
-41.23%
-30.82%
-458,320.0
-599,983.0
-23.10%
-28.23%
167,458.0
-497,543.0
7.22%
-16.66%
1,126,955.0
126,237.0
40.44%
3.33%
Regional Analysis
Poverty Rates
$1/Day Poverty Rate Across Regions: 1970-2006
.6
.5
.4
.3
.2
.1
1970
1980
1990
year
East Asia
Latin America
Eastern Europe
Middle East - North Africa
2000
South Asia
Sub-Saharan Africa
USSR-FSU
2010
Counts $1/day
$1/Day Poverty Count Across Regions: 1970-2006
700
600
500
400
300
200
100
1970
1980
1990
year
East Asia
Latin America
Eastern Europe
Middle East - North Africa
2000
2010
South Asia
Sub-Saharan Africa
USSR-FSU
Poverty Rates $2/day
$2/Day Poverty Rates Across Regions: 1970-2006
.9
.8
Poverty Rate
.7
.6
.5
.4
.3
.2
.1
1970
1980
1990
year
East Asia
Latin America
Eastern Europe
Middle East - North Africa
2000
South Asia
Sub-Saharan Africa
USSR-FSU
2010
Counts $2/day
$2/Day Poverty Counts Across Regions: 1970-2006
1,000
800
600
400
200
100
1970
1980
1990
year
East Asia
Latin America
Eastern Europe
Middle East - North Africa
2000
2010
South Asia
Sub-Saharan Africa
USSR-FSU
$1/Day Poverty and Growth in Sub-Saharan Africa, 1970-2006
.45
2000
GDP per Capita
1900
.4
.35
1800
1700
1600
.3
1970
1980
1990
Year
Poverty Rate, $1/Day
2000
GDP per capita
2010
$1/Day Poverty and Growth in East Asia, 1970-2006
.6
6000
GDP per Capita
5000
.4
.2
4000
3000
2000
1000
0
1970
1980
1990
Year
Poverty Rate, $1/Day
2000
2010
GDP per capita
$1/Day Poverty and Growth in South Asia, 1970-2006
3500
.2
3000
GDP per Capita
.15
.1
2500
2000
.05
1500
0
1000
1970
1980
1990
Year
Poverty Rate, $1/Day
2000
2010
GDP per capita
$1/Day Poverty and Growth in Latin America, 1970-2006
.12
8000
.1
GDP per Capita
7000
.08
.06
6000
.04
5000
.02
1970
1980
1990
Year
Poverty Rate, $1/Day
2000
2010
GDP per capita
8.6
.02
8.4
.04
8.5
.06
rgdpch62l
.08
8.7
.1
8.8
mena
1970
1980
1990
year
POVRT_1_normal
2000
rgdpch62l
2010
$1/Day Poverty and Growth in Eastern Europe, 1970-2006
.04
9000
8000
GDP per Capita
.03
.02
7000
6000
.01
5000
0
4000
1970
1980
1990
Year
Poverty Rate, $1/Day
2000
GDP per capita
2010
$1/Day Poverty and Growth in the USSR-FSU, 1970-2006
12000
.015
10000
GDP per Capita
.02
.01
8000
.005
6000
0
4000
1970
1980
1990
Year
Poverty Rate, $1/Day
2000
2010
GDP per capita
East Asia
year
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Change 1970-2006
Change 1990-2006
South Asia Africa (SSA)
$1/day Poverty Rates
Latin
America
MENA
Eastern
Europe
FSU
OECD
0.593
0.560
0.551
0.523
0.519
0.492
0.484
0.462
0.414
0.371
0.349
0.298
0.234
0.198
0.158
0.128
0.112
0.098
0.087
0.093
0.083
0.079
0.070
0.069
0.057
0.049
0.040
0.034
0.034
0.033
0.030
0.029
0.027
0.026
0.024
0.022
0.020
0.238
0.232
0.243
0.240
0.253
0.234
0.227
0.215
0.188
0.187
0.168
0.156
0.145
0.136
0.126
0.110
0.103
0.092
0.076
0.073
0.074
0.081
0.084
0.075
0.069
0.079
0.075
0.070
0.061
0.053
0.058
0.057
0.053
0.050
0.047
0.043
0.039
0.414
0.404
0.396
0.396
0.390
0.398
0.395
0.395
0.397
0.410
0.416
0.416
0.422
0.428
0.444
0.444
0.440
0.457
0.444
0.451
0.448
0.453
0.452
0.456
0.456
0.463
0.449
0.438
0.442
0.437
0.428
0.428
0.424
0.410
0.401
0.389
0.377
0.115
0.106
0.096
0.080
0.071
0.065
0.057
0.053
0.050
0.046
0.042
0.043
0.046
0.052
0.049
0.049
0.045
0.047
0.052
0.055
0.054
0.053
0.054
0.053
0.051
0.049
0.049
0.048
0.049
0.049
0.045
0.046
0.046
0.042
0.036
0.035
0.033
0.108
0.105
0.097
0.098
0.095
0.093
0.075
0.073
0.067
0.061
0.058
0.063
0.053
0.043
0.040
0.039
0.040
0.040
0.039
0.063
0.059
0.080
0.069
0.057
0.046
0.049
0.038
0.048
0.032
0.026
0.024
0.023
0.023
0.037
0.043
0.051
0.062
0.036
0.032
0.028
0.027
0.025
0.022
0.018
0.017
0.016
0.017
0.017
0.015
0.014
0.013
0.012
0.011
0.010
0.008
0.008
0.010
0.008
0.009
0.013
0.015
0.013
0.008
0.006
0.005
0.005
0.006
0.006
0.006
0.005
0.005
0.004
0.004
0.003
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.005
0.006
0.008
0.010
0.012
0.019
0.021
0.021
0.021
0.019
0.017
0.016
0.014
0.012
0.009
0.008
0.007
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
-0.6
-0.1
-0.2
0.0
0.0
-0.1
-0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
-83.59%
-47.01%
-8.92%
-15.94%
-71.55%
-39.60%
-42.15%
5.14%
-91.40%
-59.65%
0.00%
0.00%
0.00%
0.00%
% Change 1970-2006 -96.66%
%Change 1990-2006 -76.20%
year
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Change 1970-2006
Change 1990-2006
$2/day Poverty Rates
Latin
Eastern
America
MENA
Europe
East Asia
South
Asia
Africa
(SSA)
0.805
0.790
0.783
0.767
0.766
0.755
0.748
0.737
0.714
0.692
0.676
0.657
0.619
0.585
0.525
0.485
0.430
0.390
0.360
0.364
0.333
0.317
0.289
0.278
0.239
0.206
0.171
0.143
0.135
0.131
0.119
0.112
0.108
0.102
0.093
0.083
0.074
0.599
0.591
0.604
0.600
0.616
0.592
0.584
0.566
0.538
0.543
0.518
0.502
0.488
0.476
0.457
0.431
0.415
0.392
0.359
0.348
0.343
0.357
0.356
0.337
0.319
0.323
0.307
0.292
0.265
0.231
0.232
0.225
0.214
0.201
0.185
0.165
0.148
0.658
0.650
0.641
0.642
0.636
0.644
0.642
0.641
0.641
0.652
0.657
0.656
0.661
0.667
0.680
0.678
0.674
0.681
0.673
0.673
0.670
0.673
0.681
0.686
0.687
0.693
0.680
0.672
0.673
0.672
0.671
0.669
0.666
0.654
0.647
0.635
0.623
0.257
0.244
0.226
0.202
0.186
0.174
0.160
0.153
0.146
0.137
0.128
0.130
0.135
0.147
0.141
0.141
0.134
0.136
0.147
0.152
0.152
0.151
0.151
0.149
0.146
0.144
0.142
0.140
0.142
0.141
0.134
0.137
0.138
0.129
0.116
0.112
0.106
0.288
0.285
0.268
0.270
0.266
0.266
0.228
0.226
0.214
0.200
0.195
0.213
0.195
0.172
0.163
0.162
0.160
0.158
0.155
0.192
0.182
0.205
0.190
0.174
0.158
0.165
0.147
0.175
0.149
0.138
0.134
0.131
0.131
0.156
0.160
0.165
0.168
-0.7
-0.3
-0.5
-0.2
0.0
0.0
-0.2
0.0
-75.30%
-56.87%
-5.28%
-6.96%
-58.65%
-30.29%
% Change 1970-2006 -90.86%
%Change 1990-2006 -77.91%
FSU
OECD
0.098
0.090
0.082
0.079
0.077
0.071
0.062
0.059
0.060
0.062
0.062
0.058
0.057
0.054
0.051
0.049
0.045
0.040
0.041
0.047
0.045
0.052
0.063
0.068
0.067
0.052
0.044
0.039
0.035
0.043
0.042
0.044
0.035
0.033
0.029
0.025
0.023
0.001
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.018
0.022
0.031
0.034
0.045
0.075
0.085
0.084
0.086
0.079
0.073
0.068
0.062
0.055
0.046
0.041
0.036
0.002
0.001
0.001
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
-0.1
0.0
-0.1
0.0
0.0
0.0
0.0
0.0
-41.67%
-7.59%
-76.95%
-49.70%
0.00%
0.00%
0.00%
0.00%
year
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Change 1970-2006
Change 1990-2006
$3/day Poverty Rates
Latin
Eastern
America
MENA
Europe
East Asia
South
Asia
Africa
(SSA)
0.894
0.884
0.879
0.867
0.866
0.861
0.853
0.846
0.832
0.820
0.811
0.806
0.797
0.782
0.741
0.723
0.656
0.615
0.584
0.577
0.533
0.509
0.476
0.460
0.414
0.370
0.326
0.286
0.271
0.262
0.241
0.228
0.220
0.209
0.192
0.173
0.155
0.789
0.783
0.792
0.789
0.801
0.782
0.777
0.762
0.743
0.750
0.732
0.719
0.708
0.699
0.682
0.661
0.645
0.624
0.595
0.582
0.573
0.584
0.580
0.565
0.549
0.537
0.518
0.501
0.473
0.430
0.427
0.417
0.399
0.378
0.350
0.319
0.290
0.771
0.764
0.757
0.757
0.753
0.760
0.758
0.757
0.757
0.765
0.768
0.767
0.770
0.775
0.784
0.782
0.779
0.782
0.777
0.774
0.772
0.774
0.783
0.788
0.790
0.795
0.785
0.780
0.778
0.779
0.779
0.778
0.776
0.766
0.761
0.753
0.744
0.371
0.356
0.336
0.309
0.291
0.277
0.259
0.250
0.240
0.228
0.216
0.217
0.224
0.239
0.233
0.231
0.223
0.225
0.239
0.245
0.247
0.244
0.243
0.241
0.237
0.237
0.234
0.230
0.232
0.230
0.221
0.227
0.228
0.217
0.200
0.193
0.185
0.430
0.426
0.405
0.405
0.404
0.405
0.360
0.359
0.347
0.330
0.325
0.352
0.331
0.305
0.294
0.291
0.289
0.285
0.283
0.319
0.305
0.320
0.304
0.291
0.273
0.279
0.258
0.291
0.263
0.251
0.247
0.245
0.243
0.265
0.264
0.264
0.260
-0.7
-0.4
-0.5
-0.3
0.0
0.0
-0.2
-0.1
-63.25%
-49.41%
-3.43%
-3.61%
-50.20%
-25.09%
% Change 1970-2006 -82.62%
%Change 1990-2006 -70.83%
FSU
OECD
0.177
0.159
0.144
0.132
0.131
0.120
0.107
0.103
0.103
0.106
0.107
0.102
0.103
0.100
0.096
0.093
0.087
0.080
0.081
0.093
0.095
0.107
0.123
0.133
0.135
0.119
0.106
0.097
0.090
0.104
0.099
0.103
0.086
0.081
0.073
0.065
0.058
0.009
0.007
0.005
0.003
0.002
0.002
0.001
0.001
0.001
0.001
0.001
0.001
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.036
0.048
0.069
0.073
0.099
0.147
0.164
0.161
0.163
0.152
0.140
0.131
0.121
0.109
0.095
0.086
0.076
0.007
0.005
0.003
0.003
0.002
0.002
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.000
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.001
0.000
0.000
0.000
-0.2
0.0
-0.1
0.0
0.1
0.0
0.0
0.0
-39.42%
-14.69%
-67.31%
-39.03%
0.00%
0.00%
0.00%
0.00%
year
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Change 1970-2006
Change 1990-2006
$5/day Poverty Rates
Latin
Eastern
America
MENA
Europe
East Asia
South
Asia
Africa
(SSA)
0.956
0.951
0.946
0.938
0.936
0.934
0.926
0.920
0.913
0.911
0.909
0.906
0.907
0.901
0.893
0.891
0.866
0.842
0.822
0.808
0.767
0.739
0.705
0.683
0.641
0.601
0.564
0.525
0.507
0.490
0.460
0.439
0.424
0.405
0.382
0.354
0.326
0.932
0.930
0.933
0.932
0.937
0.928
0.925
0.918
0.911
0.915
0.907
0.900
0.895
0.891
0.881
0.871
0.861
0.850
0.836
0.826
0.816
0.819
0.815
0.810
0.802
0.781
0.766
0.754
0.736
0.701
0.696
0.685
0.667
0.643
0.611
0.576
0.541
0.870
0.866
0.861
0.861
0.858
0.864
0.863
0.862
0.862
0.866
0.867
0.866
0.867
0.869
0.874
0.872
0.872
0.873
0.869
0.867
0.865
0.867
0.874
0.878
0.881
0.883
0.877
0.874
0.872
0.873
0.873
0.872
0.871
0.865
0.863
0.858
0.853
0.533
0.518
0.498
0.473
0.455
0.441
0.422
0.411
0.400
0.386
0.372
0.371
0.379
0.396
0.389
0.385
0.376
0.377
0.392
0.399
0.402
0.398
0.395
0.394
0.389
0.392
0.387
0.381
0.383
0.380
0.371
0.377
0.380
0.368
0.347
0.337
0.325
0.610
0.606
0.582
0.578
0.580
0.582
0.538
0.542
0.533
0.515
0.516
0.547
0.529
0.506
0.495
0.493
0.491
0.488
0.488
0.516
0.501
0.506
0.490
0.483
0.466
0.469
0.443
0.468
0.443
0.430
0.426
0.423
0.418
0.429
0.422
0.416
0.405
-0.6
-0.4
-0.4
-0.3
0.0
0.0
-0.2
-0.1
-42.01%
-33.76%
-2.05%
-1.46%
-38.92%
-19.12%
% Change 1970-2006 -65.90%
%Change 1990-2006 -57.52%
FSU
OECD
0.361
0.332
0.300
0.262
0.260
0.236
0.202
0.193
0.185
0.189
0.191
0.192
0.201
0.195
0.190
0.183
0.175
0.166
0.165
0.191
0.205
0.229
0.252
0.273
0.279
0.262
0.245
0.235
0.223
0.236
0.226
0.235
0.211
0.202
0.186
0.170
0.154
0.112
0.093
0.081
0.058
0.047
0.039
0.031
0.025
0.021
0.019
0.017
0.016
0.014
0.012
0.011
0.010
0.010
0.009
0.008
0.011
0.091
0.122
0.164
0.175
0.233
0.294
0.317
0.308
0.311
0.295
0.273
0.257
0.240
0.221
0.198
0.182
0.164
0.032
0.028
0.019
0.016
0.014
0.014
0.010
0.010
0.008
0.008
0.007
0.006
0.007
0.007
0.006
0.006
0.005
0.005
0.004
0.004
0.003
0.004
0.004
0.005
0.005
0.005
0.005
0.004
0.004
0.003
0.003
0.003
0.003
0.003
0.003
0.003
0.002
-0.2
-0.1
-0.2
-0.1
0.1
0.1
0.0
0.0
-33.64%
-19.18%
-57.42%
-24.79%
0.00%
0.00%
0.00%
0.00%
year
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Change 1970-2006
Change 1990-2006
$10/day Poverty Rates
Latin
Eastern
America
MENA
Europe
East Asia
South
Asia
Africa
(SSA)
0.990
0.989
0.987
0.984
0.983
0.982
0.979
0.975
0.971
0.969
0.969
0.967
0.967
0.964
0.962
0.961
0.958
0.954
0.948
0.943
0.935
0.925
0.912
0.895
0.871
0.855
0.840
0.819
0.810
0.791
0.764
0.744
0.717
0.693
0.671
0.640
0.608
0.993
0.992
0.993
0.993
0.993
0.992
0.991
0.990
0.989
0.990
0.989
0.987
0.986
0.985
0.982
0.981
0.979
0.977
0.975
0.972
0.968
0.966
0.964
0.965
0.964
0.953
0.949
0.946
0.941
0.930
0.926
0.920
0.912
0.901
0.886
0.868
0.848
0.948
0.946
0.944
0.943
0.943
0.945
0.944
0.944
0.944
0.945
0.944
0.944
0.943
0.943
0.945
0.944
0.945
0.945
0.943
0.942
0.942
0.942
0.946
0.948
0.949
0.950
0.948
0.946
0.945
0.945
0.945
0.944
0.944
0.942
0.941
0.939
0.937
0.747
0.736
0.723
0.706
0.694
0.685
0.673
0.665
0.658
0.644
0.632
0.633
0.641
0.657
0.652
0.644
0.636
0.634
0.645
0.650
0.655
0.649
0.645
0.644
0.638
0.644
0.639
0.630
0.630
0.628
0.620
0.625
0.631
0.622
0.602
0.591
0.576
0.810
0.802
0.781
0.772
0.774
0.777
0.745
0.756
0.753
0.741
0.748
0.772
0.763
0.754
0.747
0.747
0.749
0.750
0.753
0.768
0.758
0.756
0.746
0.746
0.736
0.738
0.716
0.718
0.704
0.696
0.690
0.688
0.683
0.679
0.670
0.661
0.648
-0.4
-0.3
-0.1
-0.1
0.0
0.0
-0.2
-0.1
-14.56%
-12.34%
-1.21%
-0.55%
-22.82%
-12.04%
% Change 1970-2006 -38.56%
%Change 1990-2006 -34.91%
FSU
OECD
0.702
0.680
0.646
0.606
0.584
0.550
0.506
0.481
0.461
0.461
0.475
0.487
0.505
0.488
0.470
0.459
0.443
0.429
0.424
0.489
0.526
0.570
0.588
0.589
0.592
0.565
0.547
0.535
0.524
0.525
0.512
0.518
0.497
0.483
0.459
0.436
0.410
0.650
0.610
0.580
0.512
0.472
0.435
0.394
0.360
0.329
0.320
0.299
0.281
0.261
0.239
0.222
0.214
0.204
0.198
0.175
0.187
0.287
0.351
0.420
0.464
0.539
0.582
0.605
0.588
0.593
0.572
0.540
0.514
0.488
0.459
0.426
0.402
0.373
0.177
0.165
0.137
0.120
0.115
0.116
0.097
0.092
0.080
0.078
0.071
0.068
0.072
0.070
0.065
0.061
0.057
0.054
0.047
0.043
0.040
0.039
0.040
0.046
0.044
0.041
0.039
0.037
0.034
0.031
0.028
0.029
0.029
0.028
0.025
0.025
0.023
-0.2
-0.1
-0.3
-0.1
-0.3
0.1
-0.2
0.0
-19.94%
-14.48%
-41.63%
-22.06%
0.00%
0.00%
0.00%
0.00%
Inequality
Gini Coefficient, Baseline Specification
.68
Gini
.66
.64
.62
.6
1970
1980
1990
year
2000
2010
Atkinson(0.5) Coefficient, Baseline Specification
.38
A(0.5)
.36
.34
.32
.3
1970
1980
1990
year
2000
2010
Atkinson(0.75) Coefficient, Baseline Specification
.52
A(0.75)
.5
.48
.46
.44
.42
1970
1980
1990
year
2000
2010
Atkinson(1) Coefficient, Baseline Specification
.65
A(1)
.6
.55
.5
1970
1980
1990
year
2000
2010
Atkinson(1.5) Coefficient, Baseline Specification
.76
A(1.5)
.74
.72
.7
.68
1970
1980
1990
year
2000
2010
.75
.8
.85
.9
.95
1
MLD and Theil
1970
1980
1990
year
GE_0_total_normal
2000
GE_1_total_normal
2010
Decomposable Measures
(Generalized Enthropy, GE)
GE(0) Inequality Decomposition, Baseline Specification
1
.9
.8
GE(0)
.7
.6
.5
.4
.3
.2
1970
1980
Total
Within Countries
1990
year
2000
Between Countries
2010
GE(0.25) Inequality Decomposition, Baseline Specification
.9
.8
.7
.6
.5
.4
.3
.2
1970
1980
Total
Within Countries
1990
year
2000
Between Countries
2010
GE(0.5) Inequality Decomposition, Baseline Specification
.9
.8
GE(0.5)
.7
.6
.5
.4
.3
.2
1970
1980
Total
Within Countries
1990
year
2000
Between Countries
2010
GE(1) Inequality Decomposition, Baseline Specification
.9
.8
GE(1)
.7
.6
.5
.4
.3
.2
1970
1980
Total
Within Countries
1990
year
2000
Between Countries
2010
World 75-25 Percentile Ratio
10
9
Ratio
8
7
6
5
1970
1980
1990
year
2000
2010
World 90-10 Percentile Ratio
45
Ratio
40
35
30
25
1970
1980
1990
year
2000
2010
World Indequality Indexes
Gini
Atkinson Indexes
Gini
GE(-0.5)
(MLD)
GE(0)
GE(0.25)
GE(0.5)
GE(0.75)
(Theil)
GE(1)
GE(1.5)
A(0.5)
A(0.75)
A(1)
A(1.25)
A(1.5)
0.677
0.676
0.678
0.679
0.678
0.673
0.674
0.673
0.670
0.672
0.668
0.665
0.659
0.658
0.657
0.656
0.653
0.651
0.651
0.655
0.654
0.654
0.653
0.652
0.650
0.648
0.644
0.642
0.641
0.639
0.639
0.637
0.634
0.631
0.628
0.624
0.620
1.438
1.421
1.453
1.471
1.475
1.430
1.455
1.450
1.417
1.413
1.385
1.344
1.286
1.270
1.257
1.239
1.221
1.221
1.211
1.244
1.242
1.243
1.221
1.214
1.202
1.209
1.189
1.185
1.182
1.178
1.195
1.196
1.193
1.179
1.181
1.172
1.171
1.005
0.998
1.013
1.022
1.023
0.999
1.008
1.005
0.990
0.991
0.973
0.955
0.925
0.916
0.909
0.900
0.886
0.882
0.877
0.894
0.890
0.889
0.881
0.876
0.868
0.865
0.852
0.847
0.842
0.838
0.843
0.839
0.832
0.825
0.820
0.811
0.804
0.909
0.903
0.914
0.921
0.921
0.901
0.907
0.905
0.893
0.896
0.881
0.867
0.844
0.838
0.834
0.828
0.816
0.812
0.809
0.822
0.819
0.818
0.813
0.809
0.802
0.798
0.787
0.782
0.778
0.774
0.776
0.771
0.764
0.757
0.752
0.741
0.733
0.861
0.857
0.865
0.871
0.869
0.851
0.855
0.853
0.843
0.848
0.834
0.824
0.805
0.801
0.799
0.796
0.785
0.781
0.780
0.792
0.790
0.788
0.785
0.783
0.778
0.772
0.762
0.758
0.755
0.751
0.752
0.746
0.738
0.730
0.724
0.713
0.704
0.854
0.850
0.856
0.861
0.857
0.840
0.842
0.840
0.832
0.839
0.825
0.816
0.800
0.797
0.798
0.797
0.787
0.784
0.783
0.796
0.793
0.792
0.791
0.791
0.787
0.781
0.772
0.768
0.766
0.762
0.761
0.755
0.746
0.737
0.730
0.718
0.707
0.888
0.885
0.889
0.893
0.888
0.869
0.870
0.868
0.860
0.869
0.853
0.846
0.830
0.829
0.832
0.834
0.824
0.823
0.823
0.837
0.834
0.833
0.834
0.837
0.835
0.827
0.819
0.816
0.815
0.811
0.809
0.802
0.791
0.781
0.772
0.759
0.746
1.098
1.094
1.096
1.098
1.086
1.058
1.055
1.053
1.043
1.060
1.037
1.029
1.010
1.010
1.023
1.031
1.022
1.025
1.028
1.050
1.042
1.042
1.050
1.066
1.069
1.057
1.050
1.050
1.052
1.049
1.045
1.035
1.017
1.000
0.987
0.967
0.947
0.384
0.383
0.386
0.388
0.387
0.380
0.382
0.381
0.377
0.379
0.374
0.369
0.362
0.360
0.360
0.358
0.354
0.352
0.352
0.357
0.356
0.355
0.354
0.353
0.351
0.349
0.345
0.343
0.342
0.340
0.340
0.338
0.335
0.332
0.329
0.325
0.321
0.526
0.524
0.529
0.532
0.531
0.523
0.526
0.525
0.519
0.521
0.514
0.508
0.498
0.495
0.493
0.491
0.485
0.483
0.482
0.488
0.487
0.486
0.484
0.482
0.479
0.477
0.472
0.470
0.468
0.466
0.467
0.465
0.461
0.458
0.455
0.451
0.447
0.634
0.631
0.637
0.640
0.640
0.632
0.635
0.634
0.628
0.629
0.622
0.615
0.603
0.600
0.597
0.594
0.588
0.586
0.584
0.591
0.589
0.589
0.586
0.584
0.580
0.579
0.573
0.571
0.569
0.567
0.569
0.568
0.565
0.562
0.560
0.555
0.552
0.713
0.710
0.715
0.719
0.719
0.711
0.715
0.714
0.708
0.708
0.702
0.694
0.682
0.679
0.675
0.672
0.666
0.665
0.663
0.670
0.669
0.669
0.665
0.663
0.660
0.660
0.654
0.653
0.651
0.650
0.653
0.652
0.650
0.647
0.646
0.643
0.641
0.769
0.766
0.771
0.774
0.775
0.767
0.771
0.770
0.765
0.764
0.759
0.752
0.741
0.738
0.735
0.731
0.728
0.727
0.725
0.732
0.732
0.732
0.728
0.726
0.723
0.725
0.721
0.720
0.719
0.718
0.722
0.722
0.721
0.718
0.719
0.717
0.717
Change 1970-2006
Change 1980-2006
-0.057
-0.048
-0.267
-0.214
-0.202
-0.170
-0.175
-0.147
-0.157
-0.130
-0.146
-0.117
-0.142
-0.107
-0.151
-0.090
-0.063
-0.052
-0.080
-0.068
-0.082
-0.070
-0.071
-0.060
-0.052
-0.043
Percent cut 70-06
Percent cut 80-06
-8.40%
-7.14%
-18.56%
-15.45%
-20.06%
-17.43%
-19.28%
-16.73%
-18.22%
-15.58%
-17.13%
-14.20%
-16.02%
-12.59%
-13.79%
-8.65%
-16.42%
-14.05%
-15.12%
-13.14%
-12.90%
-11.22%
-10.00%
-8.61%
-6.76%
-5.64%
Year
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Welfare
Sen Index (=Income*(1-gini))
Sen Welfare Index, Baseline Specification
3500
Sen
3000
2500
2000
1500
1970
1980
1990
year
2000
2010
Atkinson Welfare Index
 certainty equivalent for a person with a CRRA utility
with risk aversion parameter gamma of a lottery over
payoffs, in which the density is equal to the
distribution of income.
 Hence, the Atkinson welfare index is the sure income a
CRRA individual would find equivalent to the prospect
of being randomly assigned to be a person within the
community with the given distribution of income
Atkinson(0.5) Welfare Index, Baseline Specification
6000
Y(0.5)
5000
4000
3000
1970
1980
1990
year
2000
2010
Atkinson(0.75) Welfare Index, Baseline Specification
5000
Y(0.75)
4000
3000
2000
1970
1980
1990
year
2000
2010
Atkinson(1) Welfare Index, Baseline Specification
4000
Y(1)
3500
3000
2500
2000
1500
1970
1980
1990
year
2000
2010
Atkinson(1.25) Welfare Index, Baseline Specification
3500
3000
2500
2000
1500
1970
1980
1990
year
2000
2010
Atkinson(1.5) Welfare Index, Baseline Specification
3000
Y(1.5)
2500
2000
1500
1000
1970
1980
1990
year
2000
2010
WELFARE MEASURES
Gini
Sen Index
1,409.6
1,451.8
1,491.7
1,555.0
1,560.6
1,584.3
1,642.5
1,681.6
1,743.8
1,772.2
1,803.6
1,824.8
1,841.7
1,871.5
1,913.5
1,957.9
2,024.4
2,076.0
2,138.8
2,145.9
2,193.6
2,183.1
2,202.8
2,220.0
2,283.8
2,335.4
2,417.0
2,502.7
2,555.0
2,638.2
2,726.4
2,775.0
2,847.1
2,944.7
3,078.0
3,225.9
3,395.9
A(0.5)
A(0.75)
Atkinson Indexes
A(1)
A(1.25)
A(1.5)
101.662
103.130
104.654
106.967
107.072
107.577
109.562
110.853
112.786
113.868
114.620
115.148
115.368
116.247
117.570
118.891
120.703
122.161
124.002
124.503
125.884
125.548
126.050
126.432
128.083
129.379
131.345
133.532
134.798
136.853
139.157
140.210
141.796
144.010
147.036
150.179
153.786
22.970
23.175
23.339
23.615
23.623
23.733
23.961
24.129
24.402
24.537
24.663
24.769
24.859
24.986
25.168
25.351
25.600
25.787
26.019
26.047
26.217
26.181
26.260
26.319
26.534
26.690
26.949
27.212
27.369
27.613
27.862
27.988
28.175
28.436
28.777
29.141
29.543
7.375
7.408
7.427
7.465
7.465
7.487
7.515
7.540
7.584
7.604
7.626
7.647
7.669
7.690
7.718
7.747
7.784
7.810
7.843
7.842
7.865
7.861
7.874
7.884
7.915
7.934
7.971
8.006
8.027
8.058
8.087
8.103
8.126
8.160
8.201
8.246
8.294
3.328
3.334
3.336
3.342
3.342
3.346
3.350
3.354
3.362
3.366
3.369
3.374
3.379
3.382
3.387
3.392
3.398
3.401
3.407
3.406
3.409
3.408
3.411
3.412
3.417
3.420
3.425
3.430
3.433
3.438
3.441
3.443
3.446
3.451
3.456
3.462
3.468
1.937
1.938
1.939
1.940
1.940
1.940
1.941
1.942
1.943
1.944
1.945
1.946
1.947
1.947
1.948
1.949
1.950
1.950
1.951
1.951
1.952
1.951
1.952
1.952
1.953
1.953
1.954
1.955
1.955
1.956
1.956
1.957
1.957
1.958
1.959
1.959
1.960
Change 1970-2006
Change 1980-2006
1986.268
1592.353
52.124
39.166
6.573
4.880
0.919
0.668
0.141
0.099
0.023
0.016
Percent cut 70-06
Percent cut 80-06
140.91%
88.29%
51.27%
34.17%
28.62%
19.79%
12.46%
8.76%
4.22%
2.94%
1.20%
0.80%
year
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Income Equivalents
A(0.5)
Atkinson Indexes
A(0.75)
A(1)
A(1.25)
A(1.5)
$2,686
$2,763
$2,844
$2,968
$2,974
$3,002
$3,112
$3,184
$3,294
$3,356
$3,400
$3,431
$3,444
$3,496
$3,574
$3,654
$3,764
$3,854
$3,969
$4,001
$4,089
$4,067
$4,099
$4,124
$4,230
$4,315
$4,445
$4,592
$4,678
$4,820
$4,981
$5,056
$5,169
$5,330
$5,553
$5,790
$6,067
$2,067
$2,130
$2,182
$2,272
$2,274
$2,311
$2,388
$2,446
$2,542
$2,591
$2,637
$2,676
$2,709
$2,758
$2,827
$2,899
$2,999
$3,075
$3,172
$3,184
$3,257
$3,241
$3,275
$3,301
$3,396
$3,465
$3,584
$3,707
$3,782
$3,902
$4,026
$4,090
$4,187
$4,324
$4,509
$4,712
$4,945
$1,596
$1,650
$1,681
$1,745
$1,745
$1,784
$1,836
$1,882
$1,966
$2,007
$2,051
$2,095
$2,141
$2,186
$2,249
$2,314
$2,402
$2,465
$2,547
$2,546
$2,606
$2,593
$2,629
$2,654
$2,737
$2,791
$2,896
$2,998
$3,062
$3,161
$3,252
$3,303
$3,381
$3,496
$3,645
$3,813
$4,001
$1,254
$1,300
$1,318
$1,365
$1,364
$1,401
$1,435
$1,473
$1,545
$1,581
$1,620
$1,665
$1,716
$1,757
$1,812
$1,870
$1,943
$1,993
$2,063
$2,053
$2,101
$2,089
$2,126
$2,148
$2,219
$2,255
$2,346
$2,428
$2,479
$2,559
$2,623
$2,659
$2,719
$2,815
$2,928
$3,061
$3,206
$1,010
$1,049
$1,060
$1,096
$1,094
$1,127
$1,151
$1,181
$1,243
$1,274
$1,306
$1,349
$1,399
$1,434
$1,479
$1,530
$1,587
$1,622
$1,682
$1,665
$1,702
$1,690
$1,729
$1,746
$1,803
$1,823
$1,896
$1,960
$1,998
$2,060
$2,101
$2,123
$2,166
$2,248
$2,328
$2,428
$2,533
Change 1970-2006
Change 1980-2006
$3,381
$2,667
$2,878
$2,308
$2,405
$1,950
$1,952
$1,587
$1,523
$1,227
Percent cut 70-06
Percent cut 80-06
125.85%
78.45%
139.27%
87.55%
150.65%
95.09%
155.63%
97.97%
150.84%
93.98%
year
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
Sen Welfare by Region
7000
6000
5000
4000
3000
2000
1000
0
1970
1980
1990
Year
2000
2010
East Asia
South Asia
Latin America
Sub-Saharan Africa
Eastern Europe
USSR-FSU
Middle East - North Africa
World
Atkinson(2) Welfare by Region
8000
7000
6000
Y(2)
5000
4000
3000
2000
1000
0
1970
1980
1990
Year
2000
2010
East Asia
South Asia
Latin America
Sub-Saharan Africa
Eastern Europe
USSR-FSU
Middle East - North Africa
World
.05
.1
.15
.2
.25
.3
Sensitivity of Functional form:
Poverty Rates ($1/day) with Kernel, Normal,
Gamma, Adjusted Normal, Weibull distributions
1970
1980
1990
year
POVRT_1_kernels
POVRT_1_normal_adj
POVRT_1_weibull
2000
POVRT_1_normal
POVRT_1_gamma
2010
.62
.64
.66
.68
.7
Sensitivity of Functional form:
Gini with Kernel, Normal, Gamma, Weibull
distributions
1970
1980
1990
year
Gini_kernels
Gini_gamma
2000
Gini_normal
Gini_weibull
2010
.05
.1
.15
.2
.25
.3
Sensitivity of GDP Source:
Poverty Rates ($1/day) with PWT, WB, and
Maddison
1970
1980
1990
year
POVRT_1_62_1
POVRT_1_M_1
2000
POVRT_1_WB_1
2010
.62
.64
.66
.68
.7
Sensitivity of Source of GDP:
Gini with PWT, WB, and Maddison
1970
1980
1990
year
Gini_62_1
Gini_M_1
2000
Gini_WB_1
2010
.05
.1
.15
.2
.25
.3
Sensitivity of Interpolation Method:
Poverty Rates 1$/day with Nearest, Linear, Cubic and
Baseline
1970
1980
1990
year
POVRT_1_nearest
POVRT_1_cubic
2000
POVRT_1_linear
POVRT_1_baseline
2010
.62
.64
.66
.68
Sensitivity of Interpolation Method:
Gini with Nearest, Linear, Cubic and Baseline
1970
1980
1990
year
Gini_nearest
Gini_cubic
2000
Gini_linear
Gini_baseline
2010
Missreporting
 Rich don’t answer
 Poor don’t have houses
 Eliminate quintiles 1 and 3 and repeat the procedure
Survey Adjustment: Poverty
.3
.25
.2
.15
.1
.05
1970
1980
1990
year
Normal
Gamma
Weibull
2000
Normal, Adjusted
Gamma, Adjusted
Weibull, Adjusted
2010
Survey Adjustment: Gini Inequality
.68
.67
.66
Gini
.65
.64
.63
.62
.61
.6
.59
1970
1980
1990
year
Normal
Gamma
Weibull
2000
Normal, Adjusted
Gamma, Adjusted
Weibull, Adjusted
2010
The WB revised China and India
GDP (PPP)
 Following the conclusion of the International Comparisons Project (ICP) in
November 2007, the World Bank has changed its methodology with respect to
calculating country GDPs at PPP.
 This change lowered Chinese and Indian GDPs by 40% and 35% respectively
 Several criticisms have been made of this finding;
 It considers prices in urban China only (so prices are too high and real income too
low).
 Chinese GDP in 1980 is implied to be $465, and by applying the old WB growth rates,
it is $308 in 1970, which may be below the lower limit of survival
 In comparing the original and revised World Bank series, we see that the effect
of the revision was largely to multiply each country’s GDP series by a time-
invariant constant, which is the expected effect of applying the PPP
adjustments derived from the ICP to all years from 1980 to 2006.
 We nevertheless compare the poverty and inequality estimates arising from the
new WB series to our baseline estimates.
PPP Revision: Chinese Poverty
.8
.6
.4
.2
0
1970
1980
1990
year
Baseline
2000
WB PPP Revision
2010
PPP Revision: Poverty
.4
.3
.2
.1
0
1970
1980
1990
year
Baseline
2000
WB PPP Revision
2010
PPP Revision: Gini Inequality
.72
.7
.68
.66
.64
.62
1970
1980
1990
year
Baseline
2000
WB PPP Revision
2010
 END
All is not money!
 Easterlin Paradox:
 1) Within a society, rich people tend to be much happier
than poor people.
2) But, rich societies tend not to be happier than poor
societies (or not by much).
3) As countries get richer, they do not get happier (after
a given threshold)
 Implications



Economic Sociologists: Relative Income
UN: Human Development Index (as opposed to GDP)
Environmental Movement: No growth
 Problem with Easterlin Paradox:
 Old data (1974)
 No poor countries in the data set
 Gallup conducted a poll in 2006.
 Analyzed by Stevenson and Wolfers (2008)
Source: Stevenson and Wolfers (2008). Economic Growth and Subjective Well-Being: Reassessing the Easterlin
Paradox*