Post on 11-May-2020
Trends in global income inequality and their political
implications
Branko Milanovic LIS Center; Graduate School City University of New York
Autumn 2014
Branko Milanovic
A. National inequalities mostly increased
Branko Milanovic
Ginis in the late 1980s and around now
1985-90 After 2008
Change
Average Gini 36.3 38.8 +2.5
Pop-weighted Gini
33.9 37.3 +3.4
GDP-weighted Gini
32.2 36.4 +4.2
Countries with higher Ginis
32.0 36.2 +4.5
Countries with lower Ginis
42.8 39.5 -3.3
From final-complete3.dta and key_variables_calcul2.do (lines 2 and 3; rest from AlltheGinis)
Branko Milanovic
Ginis in the late 1980s and around now
twoway (scatter bbb aaa if year==2000, mlabel(contcod) msize(vlarge)) (function y=x, range(20 60) legend(off) xtitle(Gini between 1985 and 1990) ytitle(Gini after 2008)) using allginis.dta
Branko Milanovic
ARG
ARM
AUS
AUT
AZE
BELBEL
BGD
BGR
BLR
BOLBOLBOL
BRA
CAN
CHL
CHN
CIV
COL
CRI
CZE
DEUDEUDEU
DNK
DOMECU
ESPESPESTESTEST
FINFINFIN
FRA
GBR
GEO
GRC
GTMHND
HRV
HUN
IDN
IND
IRL
IRNISR
ITAITA
JOR
JPN
KAZ
KGZ
KOR
LKALKA
LTU
LVA
MDA
MEXMEXMEX
MKD
MLI
MRT
MYSNGA
NLD
NOR
PAK
PAN
PER
PHL
POL
PRT
ROU
RUS
SGPSLVSLV
SVKSVN
SWE
THA
TJK
TUR
TWNTWN
UGAUGA
UKR
URY
USAUSA
VEN
20
30
40
50
60
70
Gin
i afte
r 2
00
8
20 30 40 50 60Gini between 1985 and 1990
Ginis in 1988 and 2008 (population-weighted countries)
From twenty_years/… key_variables_calcul3.do
Branko Milanovic
RUS
IND-U
MEX
BRA
NGA
IND-R
USA
CHN-U
CHN-R
20
30
40
50
60
Gin
i in
200
8
20 30 40 50 60Gini in 1988
Convergence of countries’ Ginis: an empirical observation without theoretical explanation
Branko Milanovic
ARG
AUSBEL
BGD
BGR
BHS
BOL BRA
BRB
CAN
CHLCHN
COL
CRI
CZE
DEUDNK
DOM
ECU
EGY
ESP
FIN
FJI
FRA
GAB
GBR
GRC
GTM
HKG
HND
HUN
IDNIND
IRL
IRNISR
ITA
JAM
JPN
KOR LKA
MEX
MYS
NLD
NOR
NPL
NZL
PAK
PAN
PER
PHL
POL
PRI
PRT
SDN
SGP
SLE
SLV
SWE
SYC
THA
TTOTUN
TUR
TWN
TZA
USA
VEN
ZMB
-20
-10
01
02
0
chan
ge
in G
ini a
fter
19
80
20 30 40 50 60average country Giniall before 1980
twoway (scatter change_gini gini_pre1980 if nvals==1, mlabel(contcod)) (lfit change_gini gini_pre1980, yline(0, lpattern(dash)) ytitle(change in Gini after 1980) legend(off)) Using Allthe Ginis.dta
Market, gross and disposable income Ginis in the US and Germany
Branko Milanovic
.25
.3.3
5.4
.45
.5
1970 1980 1990 2000 2010year
USA
.25
.3.3
5.4
.45
.5
1970 1980 1990 2000 2010year
Germany
Define_variables.do using data_voter_checked.dta
Issues raised by growing national inequalities
• Social separatism of the rich
• Hollowing out of the middle classes
• Inequality as one of the causes of the global financial crisis
• Perception of inequality outstrips real increase because of globalization, role of social media and political (crony) capitalism (example of Egypt)
• Hidden assets of the rich
Branko Milanovic
Some long-term examples set in the Kuznets framework
Branko Milanovic
38.0
40.0
42.0
44.0
46.0
48.0
50.0
1929 1939 1949 1959 1969 1979 1989 1999 2009
Inequality (Gini) in the USA 1929-2009 (gross income across households)
From ydisrt/us_and_uk.xls
Kuznets and Piketty “frames”
0
10
20
30
40
50
60
70
1600 1650 1700 1750 1800 1850 1900 1950 2000 2050
Ginis for England/UK and the United States in a very long run
England/UK
USA
From uk_and_usa.xls
11
Contemporary examples of Brazil and China: moving on the descending portion of the Kuznets
curve China, 1967-2007
twoway (scatter Giniall lngdpppp if contcod=="CHN" & year>1960, connect(l) ylabel(40(10)60)
xtitle(2000 6000 12000) ytitle(Gini) xtitle(ln GDP per capita)) (qfit Giniall lngdpppp if
contcod=="CHN" & year>1960, lwidth(thick))
From gdppppreg4.dta
twoway (scatter Giniall lngdpppp if contcod=="BRA", connect(l) ylabel(40(10)60) xtitle(2000
6000 12000) ytitle(Gini) xtitle(ln GDP per capita)) (qfit Giniall lngdpppp if contcod=="BRA",
lwidth(thick))
From gdppppreg4.dta
12
Brazil 1960-2010
40
50
60
Gin
i
7.5 8 8.5 9 9.5ln GDP per capita
updated Giniall Fitted values
40
50
60
Gin
i
5 6 7 8 9ln GDP per capita
updated Giniall lowess Giniall lngdpppp
B. Between national inequalities remained very high even if
decreasing
Branko Milanovic
From defines.do in interyd
Distribution of people by income of the country where they live: emptiness in the middle (year 2013; 2011 PPPs)
India, Indonesia
Brazil, Mexico, RussiaW.Europe, Japan USA
China
01
02
03
0
Pe
rcen
t
0 10000 20000 30000 40000 50000GDP per capita in 2005 PPP
Different countries and income classes in global income distribution in 2008
From calcu08.dta
USA
India
Brazil
China
Russia
1
10
2
0
30
4
0
50
6
0
70
8
0
90
1
00
p
erc
en
tile
of w
orl
d in
co
me
dis
trib
utio
n
1 20 40 60 80 100 country percentile
Branko Milanovic
Denmark
Mozambique
Mali
Tanzania
Uganda1
10
20
30
40
50
60
70
80
90
100
perc
entile
of w
orl
d in
com
e d
istr
ibutio
n
1 5 10 15 20country ventile
Branko Milanovic
2 2 2 2 2 2
3 3
5
6
7 7
9 9
12
0
2
4
6
8
10
12
14
CYP DEU IRL KOR NLD TWN FRA NOR GBR JPN CAN LUX CHE SGP USA
Countries with more than 1% of their population in top global percentile (above $PPP 72,000 per capita in 2008 prices)
From summary_data.xls
C. Global inequality is the product of within- and between-county
inequalities How did it change in the last 60 years?
Branko Milanovic
Essentially, global inequality is determined by three forces
• What happens to within-country income distributions?
• Is there a catching up of poor countries?
• Are mean incomes of populous & large countries (China, India) growing faster or slower that the rich world?
Branko Milanovic
Global and international inequality after World War II
Branko Milanovic
Concept2: 1960-1980 from Bourguignon & Morrisson
Defines.do using gdppppreg5.dta
Concept 2
Concept 1
Concept 3
.45
.55
.65
.75
Gin
i coe
ffic
ien
t
1950 1960 1970 1980 1990 2000 2010year
Concept 2 inequality with 2011 PPPs and without China and India
Branko Milanovic Defines.do using gdppppreg5.dta
Without India and China
Without China
all countries
.45
.5.5
5.6
.65
Gin
i coe
ffic
ien
t in
pe
rcen
t
1940 1960 1980 2000 2020year
47
Population coverage
1988 1993 1998 2002 2005 2008 2011
Africa 48 76 67 77 78 78 71
Asia 93 95 94 96 94 98 89
E.Europe 99 95 100 97 93 92 87
LAC 87 92 93 96 96 97 97
WENAO 92 95 97 99 99 97 95
World 87 92 92 94 93 94 88
Non-triviality of the omitted countries (Maddison vs. WDI) Branko Milanovic
Three important technical issues in the measurement of global inequality
• The ever-changing PPPs in particular for populous countries like China and India
• The increasing discrepancy between GDP per capita and HS means, or more importantly consumption per capita and HS means
• Inadequate coverage of top 1% (related also to the previous point0
Branko Milanovic
The issue of PPPs
Branko Milanovic
The effect of the new PPPs on countries’ GDP per capita (compared to the US level)
Branko Milanovic
EGYPAK
ETH
LAO
BGD
IND
VNM
UGAKHM
TZA
MDG
NPL
GMB
BDI
LKA
YEM
SLEBTN
TJK
GINBLR
KGZKEN
NIC
THA
IDN
MRT
PHL
JOR
DZA
TUNMKD
MNG
BOLUKR
RWA
MLI
ALBBFA
BEN
MAR
TGO
AZE
SDNSDN
GHA
GTM
GNB
NER
BGR
MDA
HTI MYSNGA
CMR
CIV
MWI
ZMBSAU
OMN
SEN ARMSLV SRB
DOMGEO MNE
TWN
BIH
LBR
HND ECU
DJI
TCD
PRYSWZLSO
CAF
CHN
KAZ
PAN
BWA
MOZ
PER MUS
SUR
BRN
MAC
BLZ
FJI
MDV
COM
TUR
RUS
CPV
COG
TTOHUN
POLMEX
KWT
GNQ
COLJAM
LTU
VEN
NAM
ZAF
QAT
GABCRI
LVA
ARE
HKGSVK
SGP
HRV
CHLAGO
EST
CZEKOR
MLTURY
SVNPRT
BRA
CYP
BHS
GRCESP USAITA
DEUISR
GBR
IRLISL
AUTNLDBEL
NZLFRA
CAN
LUX
FIN
JPNSWE
DNKAUS
NORCHE
-50
05
01
00
150
gain
com
pare
d t
o 2
005
ipc--
norm
aliz
ed b
y th
e u
s leve
l
50000 100000150000gdppc in 2011ppp
C:\Branko\worldyd\ppp\2011_icp\define
The effect of new PPPs Country GDP per capita
increase (in %) GDP per capita increase population-weighted (in %)
Indonesia 90 ---
Pakistan 66 ---
Russia 35 ---
India 26 ---
China 17 ---
Africa 23 32
Asia 48 33
Latin America 13 17
Eastern Europe 16 24
WENAO 3 2
Global income inequality using nominal dollars
From two_concepts_exrate.do using Global_new5.dta
Concept 2
Concept 1
Concept 3
.55
.6.6
5.7
.75
.8.8
5
Gin
i coe
ffic
ien
t
1970 1980 1990 2000 2010Year
63
The gap between national accounts and household surveys
Branko Milanovic
Both the level and change: Use of GDP per capita gives a lower lever and a faster decrease of global inequality
Branko Milanovic Defines.do based on gdppppreg5.dta
usual Concept 2
GDPs pc countries in HS sample
HS means--countries in HS sample
.45
.5.5
5.6
.65
Gin
i
1990 1995 2000 2005 2010 2015year
How global inequality changes with different definitions of income
62
63
64
65
66
67
68
69
70
71
72
Global inequality
GDP ppp
Consumption
Survey mean
Step 1
Branko Milanovic
Step 2
Step 1 driven by low consumption shares in China and India (although on an unweighted base C/GDP decreases with GDP)
Branko Milanovic
twoway scatter cons_gdp gdpppp if group==1 & cons_gdp<1.4 [w=totpop], xscale(log) xtitle(GDP per capita in ppp) xlabel(1000 10000 50000) ytitle(share of consumption in GDP) title(C/GDP from national accounts in year 2008) using final08,dta
.2.4
.6.8
11
.2
sh
are
of con
sum
ption
in G
DP
1000 10000 50000GDP per capita in ppp
C/GDP from national accounts in year 2008
China
India
USA
Step 2. No clear (weighted) relationship between survey capture and NA consumption
Branko Milanovic
.2.4
.6.8
11
.2
su
rvey m
ea
n o
ve
r N
A c
onsu
mptio
n
1000 10000 50000GDP per capita in ppp
survey mean/consumption from national account in year 2008
twoway scatter scale2 gdpppp if group==1 & scale2<1.5 [w=totpop], xscale(log) xtitle(GDP per capita in ppp) xlabel(1000 10000 50000) ytitle(survey mean over NA consumption) title(survey mean/consumption from national account in year 2008)
India
China
USA
The issue of top underestimation
Branko Milanovic
Rising HS/NA gap and top underestimation
• If these two problems are really just one & the same problem.
• Assign the entire positive (NA consumption – HS mean) gap to national top deciles
• Use Pareto interpolation to “elongate” the distribution
• No a priori guarantee that global Gini will increase
Branko Milanovic
Gini: accounting for missing top incomes
1988 1993 1998 2003 2008
Surveys only
72.5 71.8 71.9 71.9 69.6
NAC instead of survey mean
71.5 70.5 70.6 70.7 67.6
NAC with Pareto
71.8 70.8 71.0 71.1 68.0
NAC with top-heavy Pareto
76.3 76.1 77.2 78.1 75.9
Branko Milanovic
The results of various adjustments
• Replacing HS survey mean with private consumption from NA reduces Gini by 1 to 2 points
• Elongating such a distribution (that is, without changing the consumption mean) adds less than ½ Gini point
• But doing the top-heavy adjustment (NA-HS gap ascribed to top 10% only) adds between 5 and 7 Gini points
• It also almost eliminates the decrease in global Gini between 1988 and 2008
Branko Milanovic
How Global Gini in 2008 changes with different adjustments
Branko Milanovic
-4
-2
0
2
4
6
8
10
Increase in global Gini with each “marginal”adjustment
Allocate the gap proportionally along each national income distributions
Allocate the gap proportionately and add a Pareto “elongation”
Allocate the gap to top 10% and add Pareto “elongation”
With full adjustment (allocation to the top 10% + Pareto) Gini decline almost fully disappears
Branko Milanovic
Survey data only
64
66
68
70
72
74
76
78
80
1988 1993 1998 2003 2008
Top-heavy allocation of the gap + Pareto adjustment
D. How has the world changed between the fall of the Berlin Wall and
the Great Recession
Branko Milanovic
Real income growth at various percentiles of global income distribution, 1988-2008 (in 2005 PPPs)
From twenty_years\final\summary_data
X“US lower middle class”
X “China’s middle class”
Branko Milanovic
$PPP2
$PPP4.5 $PPP12
$PPP 110
Estimated at mean-over-mean
0
10
20
30
40
50
60
70
80
0 20 40 60 80 100
Re
al P
PP
inco
me
ch
ange
(in
pe
rce
nt)
Percentile of global income distribution
-20
-10
0
10
20
30
40
50
60
70
80
90
0 10 20 30 40 50 60 70 80 90 100
Re
al P
PP
inco
me
ch
ange
(in
pe
rce
nt)
Percentile of global income distribution
Real income gains (in $PPP) at different percentile of global income distribution 1988-2008
Without China
World
Quasi non-anonymous GIC: Average growth rate 1988-2008 for different percentiles of the 1988 global income distribution
Branko Milanovic
Growth incidence curve (1988-2008) estimated at percentiles of the income distribution
Branko Milanovic
mean growth
02
04
06
08
0
cu
mula
tive
re
al g
row
th r
ate
betw
een
198
8 a
nd 2
008
2 10 20 30 40 50 60 70 80 90 95 100percentile of global income distribution
Using my_graphs.do Mean-on-mean
0 0 1 1 1 1 1 2 2 2 3 3 4 5 4
1 3
5
10
25 27
0
5
10
15
20
25
305
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
99
10
0
Dis
trib
uti
on
(in
pe
rce
nt)
of
gain
ventile/percentile of global income distribution
Distribution of the global absolute gains in income, 1988-2008: more than ½ of the gains went to the top 5%
From summary_data.xls
Branko Milanovic
500
5000
1988 1993 1998 2003 2008 2011
An
nu
al p
er
cap
ita
afte
r-ta
x in
com
e in
in
tern
atio
nal
do
llars
US 2nd decile
Chinese 8th urban decile
From summary_data.xls
Global income distributions in 1988 and 2008
twoway (kdensity logRRinc [w=pop] if logRRinc>2 & bin_year==2008 & keep==1 & mysample==1) (kdensity logRRinc [w=pop] if logRRinc>2 & bin_year==1988 & keep==1 & mysample==1, legend(off) xtitle(log of annual PPP real income) ytitle(density) text(0.95 2.5 "1988") text(0.85 3 "2008")) Or using adding_xlabel.do; always using final_complete7.dta
1988
20080
.2.4
.6.8
1
den
sity
300
100
0
300
0
600
0
100
00
300
00
500
00
100
00
0
log of annual PPP real income
Emerging global “middle class” between $3 and $16
Branko Milanovic
Increasing gains for the rich with a widening urban-rural gap
Urban and rural China Urban and rural Indonesia
170
180
190
200
210
220
co
mbin
ed r
ea
l_g
row
th 1
and
2
1 2 3 4 5 6 7 8 9 10decile
200
250
300
350
400
450
co
mbin
ed r
ea
l_g
row
th 1
and
2
1 2 3 4 5 6 7 8 9 10decile
From key_variables_calcul2.do
Branko Milanovic
urban
rural
urban
rural
E. Issues of justice and politics
1. Citizenship rent 2. Migration
3. Hollowing out of the middle classes
Branko Milanovic
Global inequality of opportunity
• Regressing (log) average incomes of 118 countries’ percentiles (11,800 data points) against country dummies “explains” 77% of variability of income percentiles
• Where you live is the most important determinant of your income; for 97% of people in the world: birth=citizenship.
• Citizenship rent.
Branko Milanovic
Is citizenship a rent?
• If most of our income is determined by citizenship, then there is little equality of opportunity globally and citizenship is a rent (unrelated to individual desert, effort)
• Key issue: Is global equality of opportunity something that we ought to be concerned or not?
• Does national self-determination dispenses with the need to worry about GEO?
Branko Milanovic
The logic of the argument
• Citizenship is a morally-arbitrary circumstance, independent of individual effort
• It can be regarded as a rent (shared by all members of a community)
• Are citizenship rents globally acceptable or not?
• Political philosophy arguments pro (social contract; statist theory; self-determination) and contra (cosmopolitan approach)
Branko Milanovic
The Rawlsian world
• For Rawls, global optimum distribution of income is simply a sum of national optimal income distributions
• Why Rawlsian world will remain unequal?
Branko Milanovic
All equal Different (as
now)
All equal
Different (as
now)
Mean country incomes
Individual incomes within country
Global Ginis in Real World, Rawlsian World, Convergence World…and Shangri-La World (Theil 0; year 2008)
98
68 (all country Ginis=0)
30 (all mean incomes same; all country Ginis as now)
0
Branko Milanovic
Conclusion
• Working on equalization of within-national inequalities will not be sufficient to significantly reduce global inequality
• Faster growth of poorer countries is key and also…
Branko Milanovic
Migration: a different way to reduce global inequality and citizenship rent
• A new view of development: Development is increased income for poor people regardless of where they are, in their countries of birth or elsewhere
• Migration and LDC growth thus become the two equivalent instruments for development
Branko Milanovic
A migrant point of view: trade-off between country’s mean income and its inequality
Branko Milanovic
0
2
4
6
8
10
12
14
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Pe
rce
nt
of
inco
me
Ventile
How much is one Gini point change worth in terms of mean country income?
Decrease in Gini
Increase
in Gini
From interyd..\ventil_vs_country.xls
Political issue: Global vs. national level
• Our income and employment is increasingly determined by global forces
• But political decision-making still takes place at the level of the nation-state
• If stagnation of income of rich countries’ middle classes continues, will they continue to support globalization?
• Two dangers: populism and plutocracy
• To avert both, need for within-national redistributions: those who lose have to be helped
Branko Milanovic
Final conclusion
• To reduce global inequality: fast growth of poor countries + migration
• To preserve good aspects of globalization: redistribution within rich countries
Branko Milanovic
Additional slides
Branko Milanovic
H. Global inequality over the long-run of history
Branko Milanovic
Global income inequality, 1820-2008 (Source: Bourguignon-Morrisson and Milanovic; 1990 PPPs )
Theil
Gini
02
04
06
08
01
00
1820 1860 1900 1940 1980 2020year
twoway (scatter Gini year, c(l) xlabel(1820(40)2020) ylabel(0(20)100) msize(vlarge) clwidth(thick)) (scatter Theil year, c(l) msize(large) legend(off) text(90 2010 "Theil") text(70 2010 "Gini"))
Branko Milanovic
Branko Milanovic
0
10
20
30
40
50
60
70
1800 1850 1900 1950 2000 2050
Per
cen
tage
sh
are
of
glo
bal
inco
me
Year
Shares of global income received by top 10% and bottom 60% of world population
Top 10% (B-M data)
Top 10% (L-M data)
Bottom 60% (B-M data)
Bottom 60% (L-M data)
A non-Marxist world
• Over the long run, decreasing importance of within-country inequalities despite some reversal in the last quarter century
• Increasing importance of between-country inequalities (but with some hopeful signs in the last five years, before the current crisis),
• Global division between countries more than between classes
Branko Milanovic
Composition of global inequality changed: from being mostly due to “class” (within-national), today it is mostly
due to “location” (where people live)
Based on Bourguignon-Morrisson (2002), Maddison data, and Milanovic (2005) From thepast.xls
Branko Milanovic 0
20
40
60
80
100
1870 2008
Th
eil
0 in
de
x (
me
an
lo
g d
evia
tio
n)
Class
Location
Location
Class
Branko Milanovic
0
10
20
30
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60
70
80
90
1800 1850 1900 1950 2000 2050
Bet
wee
n c
om
po
nen
t, in
per
cen
t
Year
Share of the between component in global Theil (0)
B-M data
L-M data
Very high but decreasing importance of location in global inequality
From thepast.xls under c:\history