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 70 Real PPP income change 1988 2008 60 50 40 30 20 10 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 99 100 Percentile of income distribution
Global Lorenz curves in 1988 and 2008 100 80 60 40 20 0 2008 1988 0 20 40 60 80 100
Shape of global growth vs. US growth 90 80 World, 1988 2008 70 United States, 1990 2008 Real PPP income change 1988 2008 60 50 40 30 20 10 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 99 100 Percentile of income distribution
US pattern is not unusual: in most countries increasing gains for the rich Philippines and Bangladesh Mexico and Colombia 50 100 150 200 250 300 combined real_growth 1 and 2 BGD 120 130 140 150 160 combined real_growth 1 and 2 1 2 3 4 5 6 7 8 9 10 decile PHL MEX COL 1 2 3 4 5 6 7 8 9 10 decile
Increasing gains for the rich with a widening urban rural gap Urban and rural China Urban and rural Indonesia 200 250 300 350 400 450 combined real_growth 1 and 2 170 180 190 200 210 220 combined real_growth 1 and 2 1 2 3 4 5 6 7 8 9 10 decile 1 2 3 4 5 6 7 8 9 10 decile From key_variables_calcul2.do
Average real growth (in $PPP) across country deciles (population weighted) 120 Real $PPP growth 1988 2008, in percent, by decile 100 80 population weighted Real growth 60 40 20 0 1 2 3 4 5 6 7 8 9 10 Income decile
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 80 th percentile? Marching of China and India through the ranks reduces global inequality and the importance of the betweencomponent in global inequality But it might cause increases in within national inequalities (thus offsetting global inequality decline) Implications for the citizenship premium & migration
Positive association between income growth at the median and initial (1988) Gini (unweighted data) real income level of the median in 2008 with 1998=100 50 100 150 200 250 300 CHN-U IRL AZE CHN-R GBR THA SGP UKR IDN-U HUN IDN-R PAK KOR UGA MYS SVN RUS NLD CRI DOM ESP TUR CAN ITA PER NOR CYP FRA PRT FIN BEL BGD IND-U ISR MRT LKA LTU SWE IND-R PHL USA ECU EGY CZE JPN EST DNK GRC SLV KGZ DEU AUT POL MAR BOL ARG SVK JOR URY VEN CIV PRY NGA LVA BGR ROU CHL HND GTM BRA PAN COL MEX 20 30 40 50 60 Gini in 1988 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
Weak association between income growth at the median and initial (1988) GDP per capita (unweighted data) real income level of the median in 2008 with 1998=100 50 100 150 200 250 300 BDI MLI CAF VNM SWZ AZE HNDGTM THA CHL GBR SGP NER UGA UKR BFA PAK HUN KOR BRAMYS DOM CRI RUS SVN NLD TUR ESP GIN PER ITA CAN KHM MRT CYP FRA BGD LAO LKA PRT NOR ISR PHL ZAF PAN FIN BEL ECU LTU SWEUSA EGY SLV GRC CZE JPN LUX BOL EST DEU DNK KGZ MAR CHE COL ARG POL AUT ZMB JOR URY SVK VEN MDG CIV PRY MEX NGA LVA TZA KEN BGR ROU 1000 5000 20000 GDPPPP in 1988 IRL 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
Income levels of Chinese urban and US median (fifth) decile, 1988 2008 decile inc in 2005 PPP USD 1000 3000 10000 20000 1990 1995 2000 2005 2010 benchmark year 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
Global percentile position of US median and Chinese urban middle decile according to RRinc and mysample==1 50 60 70 80 90 100 93 52 92 54 93 93 93 66 62 58 1990 1995 2000 2005 2010 benchmark year 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 Ln GDP per capita in 1988 0.010 (0.013) 0.075 (0.09) 0.010 (0.015) 0.075 (0,09) Population 0.001 (0.90) 0.008 (0.03) 0.07 (0.10) 0.008 (0.03) 0.07 (0.10) 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 P value First decile 8.59 0.00 Second decile 2.35 0.003 Third decile 1.19 0.12 0.53 0.48 0.00 0.99 0.45 0.56 0.98 0.22 Eighth decile 1.59 0.06 Ninth decile 2.30 0.007 Tenth decile 4.23 0.000 for num 1/10: xtreg real_growth gini gdpppp pop if keep==1 & group==x, fe Usimg final_complete2dta