Transcript Moving to Concept 2

International inequality
(Concepts 1 and 2)
Milanovic, “Global inequality and
its implications”
Lectures 3-5
Definitions
Three concepts of inequality defined
Concept 1 inequality
Concept 2 inequality
Concept 3 (global) inequalty
Definitions
Different types of inequality
Individuals in:
Countries
World
Countries in:
The usual within-country
distributions
(e.g. inequality in the US is
greater than in Sweden)
-----
Global income distribution:
distribution of persons in the
world
(comparable prices)
Distribution of countries’
GDP per capita
(rich vs. poor countries; are
the poor countries catching up
or not;
the convergence literature)
(comparable prices)
What world inequality are we talking about?
Comparison between the three concepts of inequality
Main source of
data
Unit of
observation
Welfare
concept
National
currency
conversion
Within-country
distribution
(inequality)
Concept 1:
unweighted
inter-national
inequality
National
accounts
Country
GDP or GNP
per capita
Concept 2:
weighted international
inequality
National
accounts
Country
(weighted by its
population)
GDP or GNP
per capita
Concept 3:
“true” world
inequality
Household
surveys
Individual
Mean per capita
disposable
income or
expenditures
Market exchange rate or PPP exchange rate (but
different PPP concepts used)
Ignored
Ignored
Included
Concept 1 inequality,
1950-2000
Inequality between
countries
Coverage: number of countries and share of world population
160
Number of countries or coverage of world population
140
Number of countries included
120
Coverage of world population (in %)
100
80
60
40
20
0
19
50
19
52
54
19
6
5
19
19
58
19
60
19
62
19
64
19
66
19
68
19
70
19
72
19
74
6
7
19
Year
19
78
19
80
19
82
19
84
19
86
19
88
19
90
92
19
19
94
19
96
19
98
About 140 countries included; about 6200 country/year GDPs
almost 100 percent of world population and world GDP (in
current dollars)
current countries projected backward (NEW)
 SIMA World Bank data used to get benchmark 1995 $PPP
GDP per capita; then these GDP per capita projected backward
and forward using countries’ real growth rates (78% of data
from WB sources; others mostly from national SYs; some from
PennWorld Tables, UN sources)
Convergence and divergence
• Unconditional or σ convergence (original studies
by Baumol for OECD countries based on
Maddison data). All countries end up with the
same steady-state equilibirum level (NCGT).
• Slower growth of richer countries as MPK falls
and they get closer to technological frontier
(technology is freely available to all)
• Conditional or β convergence (Barro with human
capital only). Growth regressions; based also on
endogeneous (“new”) growth theory; each
country ends with its own steady-state
equilibrium
• Endogeneous growth in response increasing
returns to scale (no ↓ MPs), monopolistic
competition (no free competition), and no free
diffusion of technology (all key neoclassical
assumptions abandoned), role of policies and
institutions important
• Noted: Lucas paradox: capital flows from rich to
rich countries; mean country incomes diverge
• But β convergence compatible with greater
dispersal of growth rates and incomes
• Often meaningless: if Ethiopia had education
level and institutions of the US, it would grow
faster than the US! (These factors are
concommitant with high income, not
independent of it.)
State steady level of income
y*  Ae gt [ s /( n  g    
• Depends on A = initial technology but also resource
enbdowment, clisate, institutions etc, g = technological
progress, s = savings (investment) rate, n = population
or labor growth rate, g = rate of technological
progress, δ = depreciation, α = share of labor in total
output
• In unconditional convergence, all economies the same,
β<0 even if no other RHS variable
• Or economies differ only if one or more of these
parameters differ. Some of the parameters to be
included on the RHS. And find out if β is negative then.
• But do not forget about A!
Panel approach : heterogeneity of
countries
• Allow for country-fixed effect (contained in A);
large differences in technology (A): variables like
institutions, climate etc. which are in countrty
fixed effect influence income level (not sufficient
to use K, L)
• Instrument for A; since A is “kitchen-sink” variable
can be instrumented by almost any variable
• If both A and g differ, no convergence
• If parameter heterogeneity (Pasaran & Binder);
no sense to talk about crss-country regressions
which constrain the parameters (even in
panelds)
The bottom line
• σ convergence among rich countries since WW2
and possibly earlier; at least in terms of wagerates (Williamson), and even during the Interwar yesrs (Milanovic, Restat)
• σ divergence for the world recently, but also
historically, since the Industrial revolution
• σ or unconditional divergence is the same as
increase in Concept 1 inequality (Gini instead of
st. deviation of logs)
Going back to the 1978-2000
outcome:
• Middle income countries declined (Latin
America, EEurope/former USSR)
• China and India pulled ahead
• Africa’s position deteriorated further
• Developed world pulled ahead
• World growth rate decreased by about 1 %
(compared to the 1960-78 period)
Different way to look at world
growth rates
1960-1980
1980-2000
Unweighted (each country
counts the same)
2.9
0.8
Percentage negative
23
33
China
2.7
8.2
India
1.2
3.6
Population-weighted
3.0
3.2
World
2.6
1.6
Annual per capita growth rates
1980-2002
Mean
Median
Percentage
negative
“Old OECD”
1.9
2.0
17
Middle
income
countries
LLDC
1.0
1.8
33
0.1
0.8
43
Growth over 1980-2002 period as function of
initial (1980) income
Distribution of population (in %; year 2000)
according to how country did over 1980-2000
Africa
Asia
WENAO
LLDC
Big time
winners
(>58%)
Winners
13
90
7
26
34
7
93
27
Losers
44
3
0
38
Big time
losers
(>20%)
9
0
0
9
100
100
100
100
Total
The Four Worlds
Define four worlds:
• First World: The West and its offshoots
• Take the poorest country of the First World
(e.g. Portugal)
• Second world (the contenders): all those
less than 1/3 poorer than Portugal.
• Third world: all those 1/3 and 2/3 of the
poorest rich country.
• Fourth world: more than 2/3 below
Portugal.
The border countries and their GDP per
capita levels (in $PPP, 1995 prices)
1960
1978
2000
Greece (13821)
Barbados
(13297)
Malaysia (9887)
Slovak (8595)
Egypt (4630)
Bulgaria (4313)
First to
second
Portugal (3205)
Croatia (3085)
Second to
third
Haiti (2139)
Malaysia (2120)
Portugal (7993)
Puerto Rico
(7662)
Armenia (5294)
Fiji (5156)
Third to
fourth
Nigeria (1080)
Madagascar
(1031)
Guyana (2728)
Cote d’Ivoire
(2649)
Overall upward and downward mobility
1960-78 and 1978-2000
1978-2000
1960-78
Four Worlds 1960
Four Worlds 2003
Four worlds in 1960 and 2003
1960
2003
Number of % of
Number of % of
countries population countries population
First
41
26
27
16
Second
22
12
7
2
Third
39
13
29
37
Fourth
25
49
72
46
Poorer than during Carter
Parts of Africa where 2000 GDI per capita
is less than in 1980 (350m people )
US GDI per
capita in the
meantime
increased 50%
Poorer than during J.F. Kennedy
Parts of Africa where 2000 GDI per capita
is less than in 1963 (180m people )
US GDI per
capita in the
meantime
doubled
Why Concept 1 inequality
matters
• Are poor countries catching up as we would
expect from theory?
• Are similar policies producing the same effects
or not? (Rodrik: convergence of policies,
divergence of outcomes). Why?
• Migration issues
• Countries are not only interchangeable
individuals (random assortments of individuals);
they are cultures. Divergence in outcomes is
elimination of some cultures. Perhaps it’s good,
perhaps not.
3500
Transition countries: continued output
divergence despite policy convergence
4
3000
5
st dev. of gdpppp per capita
6
standard deviation of all EBRD indicators
2500
2
2000
3
standard deviation of GDI per capita
1990
1995
2000
Year...
twoway (line EBRD_sd year) (line gdpppp_sd year, yaxis(2)), legend(off) text(6.2 1997 "standard deviation of all
> EBRD indicators") text(3.5 2000 "standard deviation of GDI per capita")
2005
LAC countries: continued output divergence
despite policy convergence
8.00
4
St deviation of the Lora reform indexindicator
7.00
3.9
6.00
3.8
5.00
3.7
4.00
3.6
St. deviation of GDI per capita
3.00
3.5
2.00
3.4
1.00
3.3
0.00
3.2
1985-1988
1988-1991
1992-1994
1995-1997
1998-1999
The two periods of international growth
Period
Mean
(unweighted)
incomes: “Rest
against West”
Regional homogeneity
1960-1978
Rest catching up Strong divergence in Asia &
Africa; divergence in
EEurope/FSU; mild
convergence in WENAO
and LAC
1978-2000
All falling behind
except Asia
Continued strong
divergence in Africa, joined
by EEurope; mild
divergence in Asia & LAC;
continued convergence in
WENAO only
Concept 2 inequality,
1950-2000
Moving to Concept 2: its relevance
and irrelevance
• Once we have Concepts 1 & 3, Concept 2
is redundant.
• But we have imperfect grasp of Concept 3
inequality => Concept 2 provides a check
on “true” inequality (its lower bound)
• We use it to approximate “true” inequality.
Think, at the limit, of each individual being
a country
Year
20
00
19
98
19
96
19
94
19
92
19
90
19
88
19
86
19
84
19
82
19
80
19
78
19
76
19
74
19
72
19
70
19
68
19
66
19
64
19
62
19
60
19
58
19
56
19
54
19
52
19
50
Gini index
The mother of all inequality
disputes
0.700
Global inequality
0.600
Populationweighted
0.500
Unweighted
0.400
How are Concepts 2 and 3 related?
• In Gini terms:
n
n
1
i1 Gi pii   i
n
 y  y ) p p  L
j
i
i j
j i
• where Gi=individual country Gini, π=income share, yi
= country income, pi = popul. share, μ=overall mean
income, n = number of countries
• In Theil:
n
n
 p Ti   p ln
i
i 1
i
i 

yi
Inequality between population-weighted countries
According to Concept 2, there is convergence among countries…
0.780
0.740
0.700
Theil
0.660
0.620
0.580
Gini
0.540
19
50
19
52
19
54
19
56
19
58
19
60
19
62
19
64
19
66
19
68
19
70
19
72
19
74
19
76
19
78
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
0.500
20
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
19
00
98
96
94
92
90
88
86
84
82
80
78
76
74
72
70
68
66
64
62
60
58
56
54
52
50
Gini coefficient
...or maybe there is not
0.600
World
0.560
World without
China
0.520
0.480
World without India and China
0.440
0.400
Alternative Concept 2
calculations
• Alternative growth rates for China (official-World
Bank, Maddison, Penn World Tables)
• Breaking China, India, US, Indonesia and Brazil
into states/provinces (but redistribution within
nations)
• Breaking China into rural and urban parts
(Kanbur-Zhang data set)
• What PPP to use (Geary-Khamis, EKS, Afriat)
Implied China’s GDP per capita in different years
According to different sources
PWT 6.1
Maddison
1952
568
627
World
Bank
262
1960
662
785
497
1966
773
879
534
1978
899
1142
754
1988
1703
2119
1676
1999
3319
3803
3867
2000
3642
na
4144
Concept 2 inequality for different
versions of China’s GDP per capita
0.5800
World Bank
0.5600
Penn World
Tables
Maddison
0.5200
0.5000
0.4800
98
96
94
92
90
88
86
84
82
80
00
20
19
19
19
19
19
19
19
19
19
78
Years
19
74
72
70
68
66
64
62
60
58
56
54
52
76
19
19
19
19
19
19
19
19
19
19
19
19
19
19
50
0.4600
19
Gini
0.5400
…and breaking China and India into their provinces/states.
Inter-national population-weighted inequality:
with China and India replaced by their provinces and states
65.0
60.0
Countries and regions of
China (R/U) and India
Countries and regions of China
and India
Gini index
55.0
Countries only
50.0
45.0
40.0
1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
Year
How much has Concept 2
inequality changed (Gini points;
1985-00)?
Whole
countries
ChIIBus by
states + whole
countries
R/U for China
World Bank
data
-3.3
Maddison
data
-1.9
-4.0
-2.3
-3.3
-1.9
.4
Distribution of people according to income of
country where they live (ln GDPPPP pc;
countries/provinces/states/R-U China, 1980-00
1980
.2
0
.1
kdensity lngdp
.3
2000
6
7
8
9
10
x
kdensity lngdp
kdensity lngdp
twoway (kdensity lngdp [w=popu] if Dgrand2==1 & year==1980 & lngdp<11)
11
.0001
0
.00005
kdensity gdpppp
.00015
Distribution of people according to income of
country where they live (GDPPPP pc; countries
only 1980-2000
0
10000
20000
30000
40000
x
kdensity gdpppp
kdensity gdpppp
50000
.3
.2
.1
0
kdensitylngdp
.4
.5
From one to two poles?
Concept 2 inequality in 1955
and 2000
6
7
8
x
kdensity lngdp
9
10
11
kdensity lngdp
twoway (kdensity lngdp [w=popu] if Dcont==1 & year==1955 & lngdp<11) (kdensity
Concept 2 between
1980 and 2000
Contributes to decline Reverses decline
(equilibrating factors)
(disequilibrating
factors)
• Inclusion of
provinces/states of
• Higher (old) income
China, India, Brazil,
level in China
Indonesia, US (even if
(Maddison) 1.5 points
many within
• Inclusion of
themselves are
rural/urban break up
diverging!) 0.5 point
of China 0.5 points
Result: we shave off half of the Concept 2 decline