Global growth and inequality changes:
From the fall of the Berlin Wall to the fall of Wall Street (1988‐2008) Branko Milanovic Growth Commission Conference New York, November 2012 All based on fotrpogge.xls and final_complete2.dta
Real income growth at various percentiles of global income distribution, 1988‐2008 (in 2005 PPPs) 80
Real PPP income change 1988‐2008
70
60
50
40
30
20
10
0 5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
Percentile of income distribution
80
85
90
95
99
100
Global Lorenz curves in 1988 and 2008 100
80
60
40
20
2008
1988
0 0
20
40
60
80
100
Shape of global growth vs. US growth 90
80
World, 1988‐2008
70 Real PPP income change 1988‐2008
United States, 1990‐2008
60
50
40
30
20
10
0 5
10
15
20
25
30
35
40
45
50
55
60
65
Percentile of income distribution
70
75
80
85
90
95
99
100
US pattern is not unusual: in most countries increasing gains for the rich
120
PHL
1
2
3
4
5
6 decile
7
8
9
10
MEX
co m bine d rea l_ g row th 1 a nd 2 1 00 1 50 2 00 2 50
combined real_grow th 1 and 2 130 140 150
BGD
3 00
Mexico and Colombia
COL
50
160
Philippines and Bangladesh
1
2
3
4
5
6 decile
7
8
9
10
Increasing gains for the rich with a widening urban‐rural gap Urban and rural Indonesia
170
2 00
c o m b in e d re a l_ g ro w th 1 a n d 2 180 190 200 210
co m bine d rea l_ grow th 1 a nd 2 2 50 3 00 3 50 4 00
220
4 50
Urban and rural China
1
2
3
4
5
6 decile
From key_variables_calcul2.do
7
8
9
10
1
2
3
4
5
6 decile
7
8
9
10
Average real growth (in $PPP) across country deciles (population‐weighted) Real $PPP growth 1988‐2008, in percent, by decile 120
100
population‐weighted Real growth
80
60
40
20
0 1
2
3
4
5
6
Income decile
7
8
9
10
The contradiction of inequality changes during Globalization II • Most countries displayed an upward sloping GIC (US, China, India urban, Indonesia…) • Perception that the rich are doing better than anybody else (true) • But growth rates of countries are uneven; those that grew the fastest were in the lower middle of global income distribution, and they were also most populous • This led to the humped (more exactly, reclining S) shape of the global GIC
The issues • Are growth along (1) Chinese income distribution and (2) stagnation around the median in the rich world as well as stagnation across most of income distribution in E. Europe and LAC, related? • In other words, is the hump in middle related to the dip round the 70‐80th percentile? • Marching of China and India through the ranks reduces global inequality and the importance of the between‐ component in global inequality • But it might “cause” increases in within‐national inequalities (thus offsetting global inequality decline) • Implications for the citizenship premium & migration
real incom e level of the m edian in 2008 with 1998=100 50 100 150 200 250 300
Positive association between income growth at the median and initial (1988) Gini (unweighted data) CHN-U
IRL AZE
CHL GTM HND
CHN-R GBR UKRHUN SVN RUS
IDN-R
THA
IDN-U KOR PAK
SGP UGA
MYS NLD DOM CRI TUR ESP ITA CAN PER FRA NOR CYPPRT MRT ISR LKA IND-U BEL PHL BGD FIN LTU SWE IND-R USA ECU SLV EGY GRC JPN DNK CZE EST DEU KGZ POL MAR BOL ARG AUT SVK JOR URY VEN CIV PRY NGA LVA ROU BGR
20
30
40 Gini in 1988
50
BRA
PAN
COL MEX
60
twoway (scatter real_growth bb if bin_year==2008 & group==5 & keep==1, mlabel(contcod) xtitle(Gini in 1988) ytitle(real income level of the median in 2008 with 1998=100)) (lowess real_growth bb if bin_year==2008 & group==5 & keep==1, Using complete_final2.dta
real income level of the median in 2008 with 1998=100 50 100 150 200 250 300
Weak association between income growth at the median and initial (1988) GDP per capita (unweighted data)
SWZ MLI CAF
IRL
VNM NER UGA BFA
BDI
HNDGTM
AZE
CHL GBR
THA
SGP UKR
HUN KOR PAK BRAMYS SVN NLD DOM CRI RUS TUR ESP ITACAN GIN PER FRA NOR KHM MRT CYP PRT ISR LKA PAN LAO PHL BEL BGD ZAF LTU FIN SWE USA ECU SLV EGY LUX GRC JPN DNK DEU EST CZE CHE KGZ MAR BOL POL ARG AUT COL SVK JOR URY ZMB VEN CIV MDG MEX PRY NGA LVA TZA KEN ROU BGR
1000
5000 GDPPPP in 1988
20000
twoway (scatter real_growth dd if bin_year==2008 & group==5 & keep==1, mlabel(contcod) xtitle(GDPPPP in 1988) ytitle(real income level of the median in 2008 with 1998=100)) (lowess real_growth dd if bin_year==2008 & group==5 & keep==1, legend(off) lwidth(thick) xscale(log) xlabel(1000 5000 20000)) Using final_complete2
1000
decile inc in 2005 PPP USD 3000 10000
20000
Income levels of Chinese urban and US median (fifth) decile, 1988‐2008
1990
1995
2000 benchmark year
2005
2010
twoway (scatter RRinc bin_year if group==6 & contcod=="CHN‐U" & keep==1 & mysample==1, msize(vlarge) lwidth(thick) connect(l)) (scatter RRinc bin_year if group==5 & contcod=="USA" & keep==1 & mysample==1, msize(vlarge) lwidth(thick) udsng \final_complete2.dta
according to RRinc and mysample==1 60 70 80 90
100
Global percentile position of US median and Chinese urban middle decile 93
93
92
93
93
66 62 58
50
54 52
1990
1995
2000 benchmark year
2005
2010
twoway (scatter percentile bin_year if group==6 & contcod=="CHN‐U" & keep==1 & mysample==1, msize(vlarge) lwidth(thick) connect(l) mlabel(percentile)) (scatter percentile bin_year if group==5 & contcod=="USA" & keep==1 & mysample==1, msize(vlarge) lwidth(thick) connect(l) mlabel(percentile)), legend(off) ylabel(50(10)100)
Unweighted pooled regression (dep. var: ln real income level in 2008 with 1988=100) Fifth decile
Top decile
Gini in 1988
0.010 (0.013)
0.010 (0.015)
0.008 (0.03)
0.008 (0.03)
Ln GDP per capita in 1988 Population
0.075 (0.09)
0.075 (0,09)
0.07 (0.10)
0.07 (0.10)
0.001 (0.90)
0.004 (0.55)
R2
0.10
0.10
0.06
0.09
N
67
67
67
67
Coefficient on the Gini in FE regression of real income growth by decile 1988‐2008 Coefficient on Gini
First decile Second decile Third decile
Eighth decile
Ninth decile Tenth decile
‐8.59 ‐2.35
P‐value
0.00 0.003
‐1.19
0.12
‐0.53
0.48
0.00
0.99
0.45
0.56
0.98
0.22
1.59
0.06
2.30 4.23
for num 1/10: xtreg real_growth gini gdpppp pop if keep==1 & group==X, fe Usimg final_complete2dta
0.007 0.000
