Presentation by Francois Bourguignon (Paris School of Economics) at the ERF 20th Annual Conference - Cairo, 22 March 2014

1. Inequality trends in the world
Common forces, idiosyncrasies and
measurement errors
Francois Bourguignon
Paris School of Economics
Economic Research Forum, Cairo, March 2014
1

2. Outline
1. A tour d'horizon of inequality changes around the
world
2. Common forces, idiosyncratic factors, or
measurement errors?
3. Conclusion
2

3. 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.
3

4. 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)
4

5. i) Change in inequality of equivalized income in
selected OECD countries
50.2
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 ca2000 mid 2000s Latest year
Ginicoefficient
Evolution of Gini coefficient in selected developed counries : 1985-2008
USA
UK
Canada
Source:OECDincome inequality data base

6. Change in inequality of equivalized income in
selected OECD countries
60.2
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 ca2000 mid 2000s Latest year
Ginicoefficient
Evolution of Gini coefficient in selected developed counries : 1985-2008
USA
UK
Canada
Germany
Netherlands
Source:OECDincome inequality data base

7. Change in inequality of equivalized income in
selected OECD countries
70.2
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 ca2000 mid 2000s Latest year
Ginicoefficient
Evolution of Gini coefficient in selected developed counries : 1985-2008
USA
UK
Canada
Sweden
Germany
Netherlands
Source:OECDincome inequality data base

8. Change in inequality of equivalized income in
selected OECD countries
80.2
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 ca2000 mid 2000s Latest year
Ginicoefficient
Evolution of Gini coefficient in selected developed counries : 1985-2008
USA
UK
Canada
Sweden
Germany
Netherlands
France
Source:OECDincome inequality data base

9. 9
Source: 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

10. 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
Percents
Year
Share of top 5% income in total income: 1920-2009, selected developed
countries
USA
UK
France
Sweden
Japan
Source: Top incomes

11. 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
Percent
Year
Labor share in GDP, selected OECD countries, 1985-2011
France
Germany
Italy
UK
USA
Japan
11
Source: Oecd

12. 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
12

13. i) Gini coefficient of income/consumption per
capita: Asian developing countries
1320
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
ca2000
mid 2000s
Latest year

14. i) Gini coefficient of income/consumption per
capita: Sub-Saharan African countries
14
20
25
30
35
40
45
50
55
60
65
Mid 80s
cA 1990
Mid 90s
ca2000
mid 2000s
Latest year

15. 20
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
15

16. i) Gini coefficient of income/consumption per capita:
the inverted U in South American countries
16
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
ca2000
mid 2000s
Latest year

17. ii) Top (market) incomes in a few selected
emerging countries : 1910-2010
170
5
10
15
20
25
30
1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Percents
Year
Share of top 1% income in total income: 1920-2009, selected emerging
countries
Sth Africa
Argentina
India
China
Indonesia
Colombia
Source:Top Incomes
Mauritius
Source: Top Incomes

18. iii) The GDP-share of labor in selected
developing countries
18
Source: UN National Accounts
15
20
25
30
35
40
45
50
55
60
1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
Laborshare(%)
Year
Labor share in Non-Financial Corporations'value added: selected developing
countries: 1994-2011
China
Tunisia
Morocco
Mexico
India
Egypt
Brazil

19. 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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20. 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?
20

21. 2. Common forces, idiosyncrasy, … or
measurement errors?
21
• 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

22. The distributional forces of globalization
Developed
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
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UN/EQ = Un/Equalizing; In brackets : benefiting groups ; U(nskilled), S(killed)
Top Skilled (TS), Capital (K)

23. 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)?
23

24. 0.200
0.250
0.300
0.350
0.400
0.450
0.500
0.550
0.600
1958 1968 1978 1988 1998 2008
Ginicoefficient
Year
Egypt: Evolution of inequality in consumption expenditure per capita
accordingto various sources (Gini): 1959-2010
WIDER
POVCAL
WYD
Data from "All the Ginis"
Gini series are not always consistent

25. 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?
25

26. 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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27. THANK YOU
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In summary, a hugely important research priority!

28. 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

29. 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.
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