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The Evolution of Global Inequalities: the impact on politics and the - - PowerPoint PPT Presentation

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Hosted by the International Inequalities Institute The Evolution of Global Inequalities: the impact on politics and the economy Professor Branko Milanovic Senior Scholar, Luxembourg Income Study Centre Visiting Presidential Professor, Graduate

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Hosted by the International Inequalities Institute

The Evolution of Global Inequalities: the impact on politics and the economy

Professor Branko Milanovic

Senior Scholar, Luxembourg Income Study Centre Visiting Presidential Professor, Graduate Centre, City University of New York Hashtag for Twitter users: #LSEBranko

Professor Mike Savage

Chair, LSE

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Inequality in the age of globalization

Branko Milanovic Spring/Summer 2017

Branko Milanovic

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Largely based on:

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Brief structure of the talk

  • Global inequality: in the past and now
  • Technical problems of measurement
  • How the world has changed between 1988 and 2013
  • [Political implications of the changes]
  • [Kuznets waves?]
  • Issues of justice, politics and migration

Branko Milanovic

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  • 1. Global inequality: key

developments

Branko Milanovic

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Branko Milanovic

History…/the past.xls

30 35 40 45 50 55 60 65 70 75 1800 1850 1900 1950 2000 2050

Global and US Gini over two centuries

Global (BM)

Global (LM) US inequality Lahoti, Jayadev, Reddy

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La longue durée: From Karl Marx to Frantz Fanon and back to Marx?

Branko Milanovic

20 40 60 80 1850 2011 2050 Gini index Class Location Location Class Location

Location

Class Forecast

History../the_past.xls

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  • In the long‐run inequality is determined by

the spread of the technological revolutions: the West in the 19th century, Asia today

  • In the medium‐run global inequality is

determined by:

  • 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

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Branko Milanovic

Interyd\...3concepts..xls

0.40 0.45 0.50 0.55 0.60 0.65 0.70 0.75 1940 1950 1960 1970 1980 1990 2000 2010 2020

Gini

Three concepts of inter‐national income inequality, 1952‐2015

Global inequality Population‐weighted inter‐ country inequality Unweighted inter‐country inequality All in 2011 PPPs

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Branko Milanovic

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 1988 1993 1998 2003 2008 2011

Key developments, 1988‐2011

Top 1% share (left axis) Mean to median ratio (right axis)

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60 61 62 63 64 65 66 67 68 69 70 5 10 15 20 25 30 1988 1993 1998 2003 2008 2011 Global Gini Percentage of relatively poor

Axis Title

Gini and percentage of world population with income less than 1/2 global median, 1988‐2011

% ppl under 1/2 median Gini with 2011 PPPs

Summary.xls

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.2 .4 .6 .8 density

600 2100 5500 14600

log of annual PPP real income

Global income distribution in 2011 with 2011 PPPs

twoway (kdensity loginc_11_11 [w=popu] if loginc_11_11>2 & bin_year==2011, bwidth(0.2)) , legend(off) title(Global income distribution in 2011 with 2011 PPPs) xtitle(log of annual PPP real income) ytitle(density) xlabel(2.8"600" 3.3"2100" 3.74"5500" 4.2"14600", labsize(small) angle(90)) Using combine88_11.dta

10% 73% 91% 50% Median of WENAO Global mean Global median Absolute poverty

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Large gaps in mean country incomes raise two important issues

  • Political philosophy: is the “citizenship rent” morally

acceptable? Does global equality of opportunity matter?

  • Global and national politics: Migration and national welfare

state

  • (will address both at the end)

Branko Milanovic

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Different countries and income classes in global income distribution in 2008

From calcu08.dta

USA India Brazil China Russia 1 10 20 30 40 50 60 70 80 90 100 percentile of world income distribution 1 20 40 60 80 100 country percentile

Branko Milanovic

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Different countries and income classes in global income distribution in 2011

Branko Milanovic

India with 2011 income data

Final11.dta using michele_graph.do but with india consumption replaced by india income

USA Russia Brazil India 20 40 60 80 100 percentile in global income distribution 1 20 50 80 100 percentile of country's income distribution

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Netherlands Madagascar Mali Tanzania Guinea 1 10 20 30 40 50 60 70 80 90 100 percentile of world income distribution 1 20 40 60 80 100 percentile of country's income distribution

Why international aid is unlikely to involve regressive transfers?

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  • 2. Technical issues in the

measurement of global inequality

Branko Milanovic

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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 point)

Branko Milanovic

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The issue of PPPs

Branko Milanovic

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The effect of the new PPPs on countries’ GDP per capita

Branko Milanovic

EGY PAK ETH LAO BGD IND VNM UGA KHM TZA MDG NPL GMB BDI LKA YEM SLE BTN TJK GIN BLR KGZ KEN NIC THA IDN MRT PHL JOR DZA TUN MKD MNG BOL UKR RWA MLI ALB BFA BEN MAR TGO AZE SDN SDN GHA GTM GNB NER BGR MDA HTI MYS NGA CMR CIV MWI ZMB SAU OMN SEN ARM SLV SRB DOM GEO MNE TWN BIH LBR HND ECU DJI TCD PRY SWZ LSO CAF CHN KAZ PAN BWA MOZ PER MUS SUR BRN MAC BLZ FJI MDV COM TUR RUS CPV COG TTO HUN POL MEX KWT GNQ COL JAM LTU VEN NAM ZAF QAT GAB CRI LVA ARE HKG SVK SGP HRV CHL AGO EST CZE KOR MLT URY SVN PRT BRA CYP BHS GRC ESP USA ITA DEU ISR GBR IRL ISL AUT NLD BEL NZL FRA CAN LUX FIN JPN SWE DNK AUS NOR CHE

  • 50

50 100 150 gain compared to 2005 ipc--normalized by the us level 50000 100000 150000 gdppc in 2011ppp

C:\Branko\worldyd\ppp\2011_icp\define

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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

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Use of 2011 PPPs reduces global inequality by about 3 Gini points but leaves the trends the same

Branko Milanovic

58.0 60.0 62.0 64.0 66.0 68.0 70.0 72.0 74.0 1988 1993 1998 2003 2008 2011 Gini with 2011 PPPs Gini with 2005 PPPs

Using summary_data.xls

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The gap between national accounts and household surveys

Branko Milanovic

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Global Gini with different definitions of income

Branko Milanovic

60 62 64 66 68 70 72 74

1988 1993 1998 2003 2008

HH survey NA consumption GDP per capita

Summary_data.xls

Step 2 Step 1

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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 1 1.2 share of consumption in GDP 1000 10000 50000 GDP per capita in ppp

C/GDP from national accounts in year 2008

China India USA

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Step 2. No clear (weighted) relationship between survey capture and NA consumption

Branko Milanovic .2 .4 .6 .8 1 1.2 survey mean over NA consumption 1000 10000 50000 GDP 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

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The issue of top underestimation

Branko Milanovic

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Rising NAC/HS 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

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Branko Milanovic

2 4 6 8 10 12 14 16 18 20 1975 1980 1985 1990 1995 2000 2005 2010 2015

Top 1% share in US: Comparison between WTID fiscal data and factor income from LIS (both run across households/fiscal units; K gains excluded)

WTID data LIS‐CPS data

usa07_13.xls

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But the rising gap between fiscal and HS income is not universal

Branko Milanovic

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 1975 1980 1985 1990 1995 2000 2005 2010 2015

Top 1% share Norway: Comparison between WTID fiscal data and factor income from LIS (both run across households/fiscal units; K gains excluded)

WTID data LIS data

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With full adjustment (allocation to the top 10% + Pareto) Gini decline almost vanishes

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

Summary_data.xls

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  • 3. How has the world changed

between the fall of the Berlin Wall and the Great Recession

[based on joint work with Christoph Lakner]

Branko Milanovic

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Number of surveys

1988 1993 1998 2002 2005 2008 2011 Africa 14 30 24 29 32 23 30 Asia 19 26 28 26 23 27 22 E.Europe 27 22 27 25 27 27 24 LAC 19 20 22 21 18 18 18 WENAO 23 23 21 21 22 23 21 World 102 121 122 122 122 118 115

Branko Milanovic

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Population coverage

1988 1993 1998 2002 2005 2008 2011

Africa 48 76 67 77 78 78 70 Asia 93 95 94 96 94 98 96 E.Europe 99 95 100 97 93 92 87 LAC 87 92 93 96 96 97 97 WENAO 92 95 97 99 99 97 96 World 87 92 92 94 93 94 92

Non‐triviality of the omitted countries

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GDI (US dollar) coverage

1988 1993 1998 2002 2005 2008 2011 Africa 49 85 71 71 70 71 63 Asia 94 93 96 95 90 93 83

  • E. Europe

99 96 100 99 99 98 94 LAC 90 93 95 95 98 98 94 WENAO 99 96 96 100 100 97 95 World 96 95 96 98 97 95 90

Branko Milanovic

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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 180

Estimated at mean‐over‐mean

10 20 30 40 50 60 70 80 20 40 60 80 100

Real PPP income change (in percent) Percentile of global income distribution

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Branko Milanovic

From analysis horizontal quasinonanon gic pop 2do

Parts of the distribution that gained the most are dominantly from Asia, parts that stagnated are mostly from mature economies

20 30 40 50 60 70 80 90

Cumulative growth rate (%)

10 20 30 40 50 60 70 80 90 100

Share of region in ventile population (%)

.2 .4 .6 .8 1 Normalised rank in the 1988 global income distribution Asia Mature economies GIC

Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries observed in 1988 & 2008 (N=63) included.

population-weighted, including population distribution in base-year

Quasi-non-anonymous growth incidence curve (1988-2008)

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Quasi non‐anonymous growth between 1988 and 2008: real absolute per capita gains at different fractiles of the 1988 distribution

140 217 236 443 466 799 1246 1163 2218 3168 7190 22891

5000 10000 15000 20000 25000 D1 D2 D3 D4 D5 D6 D7 D8 D9 V19 P95‐99 P100 Absolute per capita real income gain between 1988 and 2008 Decile/fractile of 1988 global income distribution

Branko Milanovic

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Branko Milanovic

20 40 60 80 100 120 140 10 20 30 40 50 60 70 80 90 100

Cumulative real per capita growth in % between 1988 and 2008 Percentile of global income distribution

Real income growth over 1988‐2008 and 1988‐2011 (based on 2011 PPPs)

1988‐2011 1988‐2008

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Global income distributions in 1988 and 2011

Branko Milanovic

twoway (kdensity loginc_11_11 [w=popu] if loginc_11_11>2 & bin_year==1988, bwidth(0.14) title("Figure 3. Global income distribution in 1988 and 2011")) (kdensity loginc_11_11 [w=popu] if loginc_11_11>2 & bin_year==2011, bwidth(0.2)) , legend(off) xtitle(log of annual PPP real income) ytitle(density) text(0.78 2.5 "1988") text(0.65 3.5 "2011") xlabel(2.477"300" 3"1000" 3.477"3000" 4"10000" 4.699"50000", labsize(small) angle(90)) Using Branko\Income_inequality\final11\combine88_08_11_new.dta

1988 2011 .2 .4 .6 .8 density

300 1000 3000 10000 50000

log of annual PPP real income

Figure 3. Global income dstribution in 1988 and 2011

Emerging global “middle class” between $3 and $16

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From Christoph Lakner

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  • 4. Political implications

Branko Milanovic

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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

  • f global income distribution, and they were

also most populous

  • This led to the “elephant‐shaped” global GIC

and decreasing global inequality

Branko Milanovic

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The issues

  • Are growth (1) along the entire 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

around the 70‐80th percentile?

  • Marching of China and India through the ranks reduces

global inequality and the importance of the between‐ country component in global inequality

  • But it might “cause” increases in within‐national

inequalities (thus offsetting global inequality decline)

  • Can democracy survive if rich countries’ middle classes are

hollowed out?

Branko Milanovic

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Back to Mandeville…

  • Can something that is bad nationally

(increased inequality) be good globally (decreased inequality) ?

  • Can national vices produce global virtue?

Branko Milanovic

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Political implications

  • Possible crowding out of national middle

classes, and the creation of a global one

  • But the middle class is presumably a force for

stability when there is a political community. There is no political community at the global

  • level. What does global middle class mean?
  • Would global middle class create a global

polity?

  • Or, global plutocracy: in the longer‐term,

reversal to the pre World War I situation

Branko Milanovic

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Are we at the end of capitalism’s long “el periodo especial” or going upward the second modern era Kuznets curve?

  • Three challengers to global capitalism were beaten off in

the 20th century: depression (by reinventing gov’t), war (by marshalling resources), Communism (through Welfare State)

  • Neither of these threats is any longer present; so is this

the reason capitalism is becoming more unequal?

  • Or is the period after 1980, the second modern era

Kuznets curve driven by the technological revolution and globalization?

Branko Milanovic

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Focus on point B of the “elephant graph” (income stagnation and erosion

  • f the middle class in advanced

economies)

Branko Milanovic

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28 30 32 34 1980 1990 2000 2010 2020 year

USA

28 30 32 34 1980 1990 2000 2010 2020 year

UK

28 30 32 34 1980 1990 2000 2010 2020 year

Germany

28 30 32 34 1980 1990 2000 2010 2020 year

Canada

in percent

Income share of the middle four deciles 1980-2013

c:\branko\voter\dofils\define_variables using data_voter_checked.dta

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The middle class defined as population with income between +/‐25% of national median income (all in per capita basis; disposable income; LIS data)

27 30 35 37 33 42 43 32 34 36 40 40 45 50

10 20 30 40 50 60 USA Spain Canada * Germany UK Netherlands Finland

Percentage of population considered middle class in early 1980s and 2013

around 2013

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2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 20,000

1979 1986 1991 1994 1997 2000 2004 2007 2010 2013

US real median after‐tax household per capita income 1979‐ 2013 Average annual growth rate over the entire period: 0.5% Since 2000, zero.

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  • 5. How to think of within‐national

inequalities: Introducing the Kuznets waves

Branko Milanovic

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Kuznets waves defined

  • Kuznets saw just one curve. We now know there may be many

more.

  • Distinguish the waves in pre‐industrial and modern societies

(those with sustained increase in mean income)

  • Kuznets waves in pre‐industrial societies are visible when

plotted against time only (because mean income is stagnant)

  • Kuznets cycles in industrial societies are visible when plotted

against income per capita=> proxy for structural changes

  • Inequality waves are too complex for formal modelling =>

need to use inductive reasoning and analytic narrative

  • The waves in modern era reflect economic forces of

technological innovation and structural transformation. But also wars and policy changes.

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Malign and benign forces reducing inequality (downward portion of the Kuznets wave)

Malign Benign Societies with stagnant mean income Idiosyncratic events: wars (though destruction), epidemics, civil conflict Cultural and ideological (e.g. Christianity?) Societies with a rising mean income Wars (through destruction and higher taxation: War and Welfare), civil conflict

  • Widespread education

(reflecting changing returns)

  • Social pressure through

politics (socialism, trade unions)

  • Aging (demand for social

protection)

  • Low‐skill biased TC
  • Cultural and ideological

(pay norms?)

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From Prados de la Escosura & Alvarez-Nogal, “The rise and fall of Spain 800-1850”

Cyclical nature of the Kuznets curve: Land rental/wage ratio over the long-term in Spain, 1282-1842

20 40 60 80 100 120 140 1282 1294 1306 1318 1330 1342 1354 1366 1378 1390 1402 1414 1426 1438 1450 1462 1474 1486 1498 1510 1522 1534 1546 1558 1570 1582 1594 1606 1618 1630 1642 1654 1666 1678 1690 1702 1714 1726 1738 1750 1762 1774 1786 1798 1810 1822 1834 1846

Land rental/wage ratio Plague Wool and wine production, rising demand for land, commercial society Wars, decline of wool exports Napoleonic wars

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Kuznets curve here? No.

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From Prados de la Escosura & Alvarez‐Nogal, “The rise and fall of Spain 800‐1850”

20 40 60 80 100 120 140 10 20 30 40 50 60 70 80 90 100

Lad rent/wage ratio GDP per capita (1859‐100)

GDP per capita and rent‐wage ratio: Spain 1325‐1840

Land/wage…

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10 20 30 40 50 60 5000 10000 15000 20000 25000 30000 Gini of disposable per capita income GDP per capita (in 1990 international dollars; Maddison)

Kuznets relationship for the UK, 1688‐2014

1867 1978 1962 1993 1688 2013 1913

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10 20 30 40 50 60 5000 10000 15000 20000 25000 30000 35000 Gini of disposable per capita income GDP per capita (in 1990 international dollars; Maddison)

Kuznets relationship for the United States, 1774‐2013

1860 1929 2013 1947 1979 1774 1933

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Branko Milanovic

10 20 30 40 50 60 70 5000 10000 15000 20000 25000 30000 Gini GDP per capita (in 1990 international dollars)

The Kuznets relationship for the Netherlands, 1561‐2010

1561 1732 1962 2010 1914 1982 1808

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Downswing of Kuznets first wave and upswing of the second Kuznets wave in advanced economies

Level of maximum inequality (peak of Wave 1) Gini points (year) Level of minimum inequality (trough of Wave 1) (year) Approximate number of years of downswing

  • f the

Kuznets wave Reduction in inequality (Gini points) GDP increased (how many times) during the downswing The second Kuznets wave (increase in Gini points) United States 51 (1933) 35 (1979) 50 16 4 Strong (+8) UK 57 (1867) 27 (1978) 110 30 >4 Strong (+11) Spain 53 (1918) 31 (1985) 70 22 <5 Modest (+3) Italy 51 (1851) 30 (1983) 120 21 <9 Strong (+5) Japan 55 (1937) 31 (1981) 45 24 6 Modest (+1) Netherlands 61 (1732) 28 (1982) 250 33 7 Modest(+2)

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Table2_data.xls

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Branko Milanovic

0.05 0.1 0.15 0.2 0.25 0.3 0.35

Urban Gini Year

Urban Gini in China: 1981‐2014 (based on official household surveys)

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Where are now China and the US?

China 2013 United States 2013 GDP per capita Gini First Kuznets wave Second Kuznets wave

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What might drive the 2nd Kuznets cycle down?

  • Progressive political change (endogenous: political

demand)

  • Dissipation of innovation rents
  • Low‐skilled biased technological progress

(endogenous)

  • Reduced gap in education (but it is not a silver bullet)
  • Global income convergence: Chinese wages catch up

with American wages: the hollowing‐out process stops

  • Note that all are all endogenous

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  • 6. Issues of justice and politics
  • 1. Citizenship rent
  • 2. Migration and national welfare state
  • 3. Hollowing out of the rich countries’ middle

classes

Branko Milanovic

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Global inequality of opportunity

  • Regressing (log) average incomes of 118 countries’ percentiles

(11,800 data points) against country dummies “explains” 77%

  • f 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

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Is citizenship a rent?

  • If most of our income is determined by

citizenship, then there is little equality of

  • pportunity globally and citizenship is a rent

(unrelated to individual desert, effort)

  • Key issue: Is global equality of
  • pportunity something that we ought to

be concerned or not?

  • Does national self‐determination dispenses

with the need to worry about GEO?

Branko Milanovic

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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

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Rawls’ views on inter‐generational transmission of wealth

Group Inter‐ generational transmission of collectively acquired wealth Argument Policy Family Not acceptable Or at least to be limited Threatens equality of citizens Moderate to very high inheritance tax Nation Acceptable Affirms national self‐ determination (moral hazard) International aid

Branko Milanovic

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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

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All equal Different (as now) All equal Different (as now)

Mean country incomes Individual incomes within country

Global inequality in Real World, Rawlsian World, Convergence World…and Shangri‐La World (Theil 0; year 2011) 77 54 (all country Theils=0; all mean incomes as now) 23 (all mean incomes equalized; all country Ginis as now)

Branko Milanovic

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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

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Migration….

Branko Milanovic

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Migration: a different way to reduce global inequality and citizenship rent

  • How to view development: Development is increased

income for poor people regardless of where they live, in their countries of birth or elsewhere

  • Migration and LDC growth thus become two equivalent

instruments for development

Branko Milanovic

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Growing inter‐country income differences and migration: Key seven borders today

Branko Milanovic

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The logic of the migration argument

  • Population in rich countries enjoys the citizenship

premium

  • They are unwilling to share, and thus possibly reduce (at

least “locally”) this premium with migrants

  • Currently, the premium is full or 0 because citizenship is

(in terms of rights as well as financially) a binary variable

  • Introduce various levels of citizenship (tax discrimination
  • f migrants; obligation to return; no family etc.) to

reduce the premium

  • Temporary work
  • Doing this should make native population more

acceptant of migrants

Branko Milanovic

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Trade‐off between citizenship rights and extent of migration

Branko Milanovic

Full citizen rights Seasonal workers (almost 0 rights) Migration flow 13% of world population* * People who would like to migrate according to a world‐wide Gallup poll

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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

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Final conclusion

  • To reduce global inequality: fast growth of poor

countries + migration

  • To have migration, discriminate the migrants
  • To preserve good aspects of globalization:

reduced inequality within rich countries via equalization of human and financial assets (i.e. focus on pre‐redistribution)

Branko Milanovic

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Hosted by the International Inequalities Institute

The Evolution of Global Inequalities: the impact on politics and the economy

Professor Branko Milanovic

Senior Scholar, Luxembourg Income Study Centre Visiting Presidential Professor, Graduate Centre, City University of New York Hashtag for Twitter users: #LSEBranko

Professor Mike Savage

Chair, LSE