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Inequality in the age of globalization Annual Research Conference Brussels, 20 November 2017 Lecture in Honor of Anthony A. Atkinson Branko Milanovic Branko Milanovic Copyright rests with the author. All rights reserved

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Page 1: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

Inequality in the age of globalization

Annual Research Conference Brussels, 20 November 2017

Lecture in Honor of Anthony A. Atkinson

Branko Milanovic

Branko Milanovic Copyright rests with the author. All rights reserved

Page 2: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

Largely based on:

2

Page 3: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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]

• [Issues of justice, politics and migration]

Branko Milanovic

Page 4: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

1. Global inequality: key developments

Branko Milanovic

Page 5: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

30

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75

80

1800 1850 1900 1950 2000 2050

Gin

i in

dex

Year

Estimated global income inequality over the past two centuries, 1820-2013 (using 2011 PPPs)

IR and the rise of the

WW1 and the Great

WW2 and US dominance

The rise of Asia

Page 6: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Branko Milanovic

0

20

40

60

80

1850 2011 2050

Gin

i in

de

x

Class

Location

Location

Class

Location

Location

Class

Forecast

History../the_past.xls

Page 7: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

• 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

Page 8: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

Branko Milanovic

pop-weighted international inequality

unweighted international inequality

global inequality

adjusted global inequality

.4.5

.6.7

.8

Gin

i coe

ffic

ien

t

1950 1960 1970 1980 1990 2000 2010year

Three concepts of international/global inequality

Using gdpppppreg8.dta

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60

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0

5

10

15

20

25

30

1988 1993 1998 2003 2008 2011

Glo

bal

Gin

i

Perc

enta

ge o

f re

lati

vely

po

or

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

Page 10: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 11: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

perc

entile

of w

orld

incom

e d

istr

ibution

1 20 40 60 80 100 country percentile

Branko Milanovic

Page 12: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

02

04

06

08

01

00

perc

entile

in

glo

ba

l in

com

e d

istr

ibutio

n

1 20 50 80 100percentile of country's income distribution

Page 13: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

Netherlands

Madagascar

Mali

Tanzania

Guinea

11

02

03

04

05

06

07

08

09

01

00

perc

entile

of w

orl

d in

com

e d

istr

ibutio

n

1 20 40 60 80 100percentile of country's income distribution

Why international aid is unlikely to involve regressive transfers?

Page 14: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

2. Technical issues in the measurement of global inequality

Branko Milanovic

Page 15: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 16: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

The issue of top underestimation

Branko Milanovic

Page 17: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 18: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

Branko Milanovic

0

2

4

6

8

10

12

14

16

18

20

1975 1980 1985 1990 1995 2000 2005 2010 2015

WTID data

LIS-CPS data

usa07_13.xls

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

Page 19: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 20: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 21: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 22: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 23: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 24: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 25: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

0

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0 20 40 60 80 100

Re

al P

PP

inco

me

ch

ange

(in

pe

rce

nt)

Percentile of global income distribution

Page 26: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

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Cu

mula

tive

gro

wth

ra

te (

%)

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Sh

are

of

regio

n in

ve

ntile

pop

ula

tio

n (

%)

0 .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)

Page 27: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

0

5000

10000

15000

20000

25000

D1 D2 D3 D4 D5 D6 D7 D8 D9 V19 P95-99 P100

Ab

solu

te p

er

cap

ita

real

inco

me

gai

n b

etw

ee

n

19

88

an

d 2

00

8

Decile/fractile of 1988 global income distribution

Branko Milanovic

Page 28: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

Branko Milanovic

0

20

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100

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140

0 10 20 30 40 50 60 70 80 90 100

Cu

mu

lati

ve r

eal p

er c

apit

a gr

ow

th in

% b

etw

een

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88

an

d 2

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8

Percentile of global income distribution

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

1988-2011

1988-2008

Page 29: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

Asian median

rich countries' poor

05

01

00

150

200

cu

mula

tive

grow

th

0 20 40 60 80 1001988 percentile

kernel = epanechnikov, degree = 0, bandwidth = 3

in percent; Lakner-MIlanovic data

Cumulative quasi non-anonymous rate of growth 1988-2008

05

01

00

150

200

cu

mula

tive

grow

th

0 5 10 15 201970 ventile

kernel = epanechnikov, degree = 0, bandwidth = .8

in percent; Bourguignon-Morrisson data

Cumulative quasi non-anonymous rate of growth 1970-1992

Page 30: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

0.2

.4.6

.8

den

sity

300

100

0

300

0

100

00

500

00

log of annual PPP real income

Figure 3. Global income dstribution in 1988 and 2011

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

Page 31: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

4. Political implications

Branko Milanovic

Page 32: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

The issues • Are growth (1) along the entire Chinese income distribution

and (2) stagnation around the median in the rich world 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

Page 33: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

Back to Mandeville…

• Can something that is bad nationally (increased inequality) be good globally (decreased inequality)?

• Can national vices produce global virtue?

Branko Milanovic

Page 34: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 35: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 36: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

Focus on point B of the “elephant graph”

(income stagnation and erosion of the middle class in advanced

economies)

Branko Milanovic

Page 37: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

28

30

32

34

1980 1990 2000 2010 2020year

USA

28

30

32

34

1980 1990 2000 2010 2020year

UK

28

30

32

34

1980 1990 2000 2010 2020year

Germany

28

30

32

34

1980 1990 2000 2010 2020year

Canada

in percent

Income share of the middle four deciles 1980-2013

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

Page 38: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

0 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

Page 39: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

5. 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

Page 40: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 41: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 42: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 43: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 44: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 45: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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)

0

Branko Milanovic

Page 46: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 47: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

Migration….

Branko Milanovic

Page 48: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Page 49: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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

Branko Milanovic

Page 50: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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 of 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

Page 51: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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*

0

* People who would like to migrate according to a world-wide Gallup poll

Page 52: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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 and asset equalization: those who lose have to be helped =>

Page 53: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

Why tools from the 20th century will not work?

• Education in quantitative sense will have much less of a “bang for a buck” and will not by itself reduce the skill premium

• Trade unions are on the decline because the nature of work, in service-oriented and globalized economy has changes

• Increases in taxation of current income are unlikely because the trust in the government is less

• New transfers cannot be financed; aging of the population and anti-migrant feelings further limit what can be done

• And one unlikely danger: more meritocratic capitalism where top wage earners are also top K earners (and the reverse)

Page 54: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

What could possibly be done?

• Improved quality of education and much easier access to education for all—that is, investing for stronger public education rather than the opposite trend of ever stronger private education

• Deconcentraton of ownership and income from capital through the use of tax incentives; a long and arduous process

• Employee-stock ownership plans

• Higher taxation of inheritance (not current income)

• Change in the rules re. financing of political campaigns (especially in the United States)

Page 55: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

0,60

0,58

0,57

0,56

0,56

0,55

0,53

0,52

0,52

0,51

0,51

0,50

0,47

0,47

0,40

0,38

0 0,1 0,2 0,3 0,4 0,5 0,6 0,7

IRL

GBR

DEU

ESP

USA

FRA

ITA

CAN

AUS

FIN

NLD

DNK

JPN

NOR

TWN

KOR

Gini of household per capita labor income around 2013

US_87_13_datarevised.xls

Page 56: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

Ginis of K and L income in the US and the UK

0,4

0,5

0,6

0,7

0,8

0,9

1,0

1970 1980 1990 2000 2010 2020

Gini coefficients of capital and labor income: US 1974-2013 Capital

Labo

0,4

0,5

0,6

0,7

0,8

0,9

1,0

1960 1970 1980 1990 2000 2010 2020

Gin

i co

effi

cie

nt

Year

UK income inequality 1969-2013

Capital

Labor

Page 57: Inequality in the age of globalization · Solid line shows predicted value from kernel-weighted local polynomial regression (bw=0.05, epanechnikov, cube polynomial). Only countries

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