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Inequality trends in the world Common forces, idiosyncrasies and measurement errors

Francois BourguignonParis School of Economics

Economic Research Forum, Cairo, March 2014

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Outline

1. A tour d'horizon of inequality changes around the world

2. Common forces, idiosyncratic factors, or measurement errors?

3. Conclusion

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1. A 'tour d'horizon' of inequality changes around the world

Crucial data warning

• Various definitions of inequality do not show the same evolution of inequality over time

• Income distribution data are not always fully comparable across countries and even over time

• Serious improvement in developed countries over the recent past; yet, things are still imperfect

• Considerable progress still to be made in most developing countries, including in MENA.

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a) Inequality trends in developed countries

i. Gini coefficient: equivalized disposable incomes: 1985-2008, (OECD database)

ii. Share of top 5% in income before taxes and transfers (Top incomes data base)

iii. GDP-share of labor (National accounts)

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i) Change in inequality of equivalized income in selected OECD countries

0.2

0.22

0.24

0.26

0.28

0.3

0.32

0.34

0.36

0.38

0.4

Mid 80s cA 1990 Mid 90s ca 2000 mid 2000s Latest year

Gin

i coe

ffici

ent

Evolution of Gini coefficient in selected developed counries : 1985-2008

USA

UK

Canada

Source: OECD income inequality data base

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Change in inequality of equivalized income in selected OECD countries

0.2

0.22

0.24

0.26

0.28

0.3

0.32

0.34

0.36

0.38

0.4

Mid 80s cA 1990 Mid 90s ca 2000 mid 2000s Latest year

Gin

i coe

ffici

ent

Evolution of Gini coefficient in selected developed counries : 1985-2008

USA

UK

Canada

Germany

Netherlands

Source: OECD income inequality data base

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Change in inequality of equivalized income in selected OECD countries

0.2

0.22

0.24

0.26

0.28

0.3

0.32

0.34

0.36

0.38

0.4

Mid 80s cA 1990 Mid 90s ca 2000 mid 2000s Latest year

Gin

i coe

ffici

ent

Evolution of Gini coefficient in selected developed counries : 1985-2008

USA

UK

Canada

SwedenGermany

Netherlands

Source: OECD income inequality data base

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Change in inequality of equivalized income in selected OECD countries

0.2

0.22

0.24

0.26

0.28

0.3

0.32

0.34

0.36

0.38

0.4

Mid 80s cA 1990 Mid 90s ca 2000 mid 2000s Latest year

Gin

i coe

ffici

ent

Evolution of Gini coefficient in selected developed counries : 1985-2008

USA

UK

Canada

SwedenGermany

Netherlands

France

Source: OECD income inequality data base

9Source: Oecd, disposable income per CU

i) Overall change mid 1980s-late 2000s

-6 -4 -2 0 2 4 6 8

Ireland

Greece

Spain

France

Belgium

Austria

Denmark

Norway

Canada

Italy

Germany

USA

Sweden

Israel

Finland

Japan

UK

NewZealand

Netherlands

Selected OECD countries: overall change in Gini coefficient mid-1980s to 2008

Series1

ii) Top (market) incomes in selected developed countries: 1910-2010

10Source: Top incomes

0

5

10

15

20

25

30

35

40

1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Per c

ents

Year

Share of top 5% income in total income: 1920-2009, selected developed countries

USA

UK

France

Sweden

Japan

Source: Top incomes

iii) The falling GDP-share of labor in selected OECD countries

0.5

0.55

0.6

0.65

0.7

0.75

0.8

1985 1990 1995 2000 2005 2010

Per

cen

t

Year

Labor share in GDP, selected OECD countries, 1985-2011

France

Germany

Italy

UK

USA

Japan

11Source: Oecd

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b) Inequality trends in developing and emerging countries

i. Gini coefficient: disposable income (or consumption expenditures) per capita : Povcal database (World Bank)

ii. Share of top 1% in income before taxes and transfers, (Top incomes)

iii. GDP-share of labor

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i) Gini coefficient of income/consumption per capita: Asian developing countries

20

25

30

35

40

45

50

55

60

65

Bangladesh China total India rural India urban Indonesia Pakistan Philipines Thailand Vietnam

Mid 80s

cA 1990

Mid 90s

ca 2000

mid 2000s

Latest year

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i) Gini coefficient of income/consumption per capita: Sub-Saharan African countries

20

25

30

35

40

45

50

55

60

65

Mid 80s

cA 1990

Mid 90s

ca 2000

mid 2000s

Latest year

1520

25

30

35

40

45

50

55

60

65

Egypt Iran Jordan Morroco Tunisia Turkey Yemen

Mid 80s

cA 1990

Mid 90s

ca 2000

mid 2000s

Latest year

i) Gini coefficient of income/consumption per capita: surprising stability in MENA

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i) Gini coefficient of income/consumption per capita: the inverted U in South American countries

20

25

30

35

40

45

50

55

60

65

Argentina (urban)

Bolivia Brazil Chile Colombia Ecuador Mexico Peru Uruguay Venezuela

Mid 80s

cA 1990

Mid 90s

ca 2000

mid 2000s

Latest year

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ii) Top (market) incomes in a few selected emerging countries : 1910-2010

0

5

10

15

20

25

30

1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Per c

ents

Year

Share of top 1% income in total income: 1920-2009, selected emerging countries

Sth AfricaArgentina

India

China

Indonesia

Colombia

Source: Top Incomes

Mauritius

Source: Top Incomes

iii) The GDP-share of labor in selected developing countries

18Source: UN National Accounts

15

20

25

30

35

40

45

50

55

60

1994 1996 1998 2000 2002 2004 2006 2008 2010 2012

Labo

r sha

re (%

)

Year

Labor share in Non-Financial Corporations' value added: selected developing countries : 1994-2011

China

Tunisia

Morocco

MexicoIndia

Egypt

Brazil

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General lessons from the 'tour d'horizon'

• High income countries: strong common unequalizing trend, very much due to the top of the distribution over the last one or two decades

• Middle and low income countries: No clear common trend in MICs or LICs where data are available but:– Unequalizing trends among several Asian globalizers, among

African countries with the most reliable data, in Latin America until 2000, and in transition countries

– Clear trend reversal in LAC in the 2000s– Surprising relative stability in MENA

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A key question

Why the common unequalizing forces that seem to be present in developed countries do not produce the same effect in most developing and emerging countries?

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2. Common forces, idiosyncrasy, … or measurement errors?

• Common factors are the forces of globalisation, even though they may have different effects on different countries

• Idiosyncratic factors are:– Country specific exogenous changes in their economic

environment (development and sectoral reallocation of factors, business cycle, demography, natural resource discoveries, commodity prices, …)

– Policies affecting , directly or indirectly, the distribution of income, wealth, human capital or the way markets function

• Observed changes in inequality result from the (complex) combination of all these factors

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The distributional forces of globalizationDeveloped countries

Middle and low Income

Trade: Expansion (Manuf) Commodity prices

UN (S,K)??

Mostly UN but heterog.?? (Ag/Non Ag)

Technical progress: Skill bias "Economies of scale"

UN (S,K)UN (TS, K)

UN (S,K)UN (TS, K)

Factor mobility: FDI Skilled and top-skilled labor Unskilled labor

UN (K)EQ (U,S, K)UN (S, K)

EQ (U, S)UN (TS)EQ (U)

Financial flows UN (K) ?? Macro instability

UN/EQ = Un/Equalizing; In brackets : benefiting groups ; U(nskilled), S(killed)Top Skilled (TS), Capital (K)

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Could there be serious measurement errors?

• Inequality rise in developed countries very much due to the top• But the top is very imperfectly observed, especially in developing

countries!• Could it be that income distribution statistics in many countries

simply miss the rise in inequality? • Also, considerable heterogeneity of the inequality data: are we

looking at the right ones?• How come big changes in rK/Y are not accompanied by big

changes in distribution?• Why such stability in MENA despite big shocks over the last 30

years (not to mention the very recent years)?

0.200

0.250

0.300

0.350

0.400

0.450

0.500

0.550

0.600

1958 1968 1978 1988 1998 2008

Gin

i coe

ffici

ent

Year

Egypt: Evolution of inequality in consumption expenditure per capita according to various sources (Gini): 1959-2010

WIDER

POVCAL

WYD

Data from "All the Ginis"

Gini series are not always consistent

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Conclusion: caution with the the lamppost!

• Desperate need for better data:– How to extend the Top Incomes data base ?– How to improve surveys or to combine them with tax records

• The top income correction can drastically modify the evaluation of inequality changes (Alveredo)

• Existing data are probably correct for poverty measurements much less so for inequality

• For inequality, aren't we looking for our keys under the lamppost - i.e. in the light of househod surveys?

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It is not totally dark around the lamppost!

• True inequality which and the inequality that we believe for understanding development may be elsewhere in many countries:– Profits unreported in surveys– Embezzlement of natural resources rents ..– …

• Together with household survey Ginis, shouldn't we look to a battery of other indicators:– Ratio mean income survey/National Accounts– Labor share in NFCs– GDP share of household income in National Accounts,..

• Imprecise indicators, yes, .. but more accurate

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THANK YOU

In summary, a hugely important research priority!

The "UUG" hypothesis

• Inequality rose in a majority of developed countries, after decades of stability

• Analogous rise in a number of emerging countries during the same period…

• Hence, the 'universally unequalizing globalization' (UUG) hypothesis: "Globalization, the major economic force affecting all economies in the

world, is reshaping national economies and causing more inequality everywhere "

• As between inequality falls: is between country inequality in the world being replaced by within-country inequality?

Ing 28

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An unequalizing world?

• UUG does not fully fit the evidence, as illustrated in the last 10 years by Latin American countries where inequality actually fell… or by the relative stability in MENA

• But it underscores a major point:After decades of near stability the distribution of income is changing, in one direction or the other, in many countries!

• Important to understand the common forces behind these changes as well as idiosyncratic factors that can enhance or on the contrary check them.