A presentation at the International Labor OrganizationUnited NationsGeneva, Switzerland

April 16, 2012

byJames K. Galbraith

Inequality and InstabilityA Study of the World Economy Just Before

the Great Crisis

“Kepler undertook to draw a curve through the places of Mars, and his greatest service to science was in impressing on men's minds that this was the thing to be done if they wished to improve astronomy; that they were not to content themselves with inquiring whether one system of epicycles was better than another, but that they were to sit down to the figures and find out what the curve, in truth was.”

-- Charles Sanders Peirce (1877)

A research initiative since ~1996 Emphasis on accurate measurement Global and national coverage 60 working papers; six books 15 data sets on-line Highly ranked in Google under “Inequality” Supported by the Ford Foundation

The University of Texas Inequality Project

DK Observations1 - 1011 - 2021 - 3031 - 4041 - 50

7000 0 7000 14000 Miles

N

EW

S

Number of Observations Per Country, 1950-1997

Deininger and Squire: Data Set of Choice?

Version of D&S used by Dollar and Kraay, “Growth is good for the poor.”

Gin

i coe

ffici

ent

GBR LUX NLD DEU SWE NOR GRC ITA IRL AUS

BEL ESP FIN CAN DNK NZL JPN USA PRT FRA

20

30

40

50

1961

19791985

1965

1975

1966

1963

19511967

1976

1962

1973

1974

1962

1974

1947

1973

1973

1969

1956

1991

1992 19851989

1991

1991

1984

1991

19921992 1991

1990

1988 1990

1991

1991

19871991

1990

1984

Deininger & Squire: Inequality Measures for the OECD

Countries ranked by average value, first and last dates shown

Trends of Inequality in the Deininger-Squire Data Set

D&

S G

ini

Non-OECD vs OECD

Non-OECD OECD

1963 1968 1973 1978 1983 1988 1993 1998

25

35

45

55

T p R R p R T

Tn

r r

j jj

m

j jj

m

j j

jj

ii g

i

j

1 1

1

log

log

pn

njj

A brief review of the Theil Statistic:

n ~ employment; ~ average income; j ~ subscript denoting group

The “Between-Groups Component”

R jj

Within-Group Inequality

Weighted Sum of Within-GroupsComponents

r yi i j

Table 2. Distribution of UTIP-UNIDO Inequality Measures

Year East

Asia & Pacific

East & Central

Asia

Latin & Central America

Middle East & North Africa

North America

South Asia

Sub-Saharan Africa

Western Europe

Total

Country 19 24 28 7 2 8 38 19 145

1960s 49 52 75 62 14 25 83 113 473 1970s 118 80 162 102 20 46 205 183 916 1980s 142 93 192 96 20 64 198 190 995 1990s 125 161 162 97 19 43 147 173 927 2000s 21 40 10 20 4 9 18 19 141

Total 455 426 601 377 77 187 651 678 3,452

The UTIP-UNIDO TheilMeasure of Inequality

SWE

DNK

CZE

NLD

NOR

FIN

POL

DEU

AUS

HKG

LUX

TWN

FRA

SVK

ITA

GBR

AUT

HUN

CAN

KOR

BEL

USA

ESP

MEX

MYS

GRC

CRI

SGP

COL

JPN

PRT

IRL

ARG

VEN

PHL

CHL

BRA

BOL

IDN

THA

IND

PER

-.05

0.0

5.1

.15

UT

IP-U

NID

O I

nequ

ality

0 10 20 30 40Rank by mean of Theil

* Bar indicates 1 standard deviation across years** Cross line indicates overall mean

China: Contributions to inequality by Province

Beijing

Contributions to a Theil T-Statistic, measured across provinces

4/16/12

ImpoverishedFar Below AverageBelow AverageLow low NeutralLow NeutralNeutralHigh NeutralAbove AverageProsperousWealthy

Contribution of European Provinces in Inequality Across the European continent, late 1990s.

China

Brazil

Korea

Denmark

USA

Kuwait

Inequality

Income

A Stylized “Augmented Kuznets Curve”

Inequality in the world economy is dominated by a common trend, with turning points around 1971, 1980, 2000

The most-likely explanation is changing global financial regimes.

Key Global Finding

Brown: Very large decreases in inequality; more than 8 percent per year.

Red Moderate decreases in inequality. Pink: Slight Decreases. Light Blue: No Change or Slight increases Medium Blue: Large Increases -- Greater than 3 percent per

year. Dark Blue: Very Large Increases -- Greater than 20 percent per

year.

Global Movement of Inequality

1963 to 1969

1970 to 1976

The oil boom: inequality declines in the producing states, but rises in the industrial oil-consuming countries, led by the United States.

1977 to 1983

1981 to 1987

… the Age of DebtNote the exceptions to rising inequality are mainly India and China, neither affected by the debt crisis…

1984 to 1990

1988 to 1994

The age of globalization…Now the largest increases in inequality in are the post-communist states; an exception is in booming Southeast Asia, before 1997…

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

Debt Crisis

End of BrettonWoods

9/11

“Concept 4” Inequality: The Common Movement of Inequality Measured within Countries, Across Time

Note: The vertical axis represents the time element in a two-way fixed effects panel regression, across the panel of country-year observations. Vertical scale is log(T) units. Source: Kum 2008.

Milanovic Concept 1

Profit Share in OECD

The Super Bubble

UTI

P-U

NID

O L

og(T

)

Non-OECD vs. OECD

Non-OECD OECD

1963 1968 1973 1978 1983 1988 19931998-4.5

-4

-3.5

-3

-2.5

UTI

P-U

NID

O L

og(T

)

Non-OECD vs. OECD

Non-OECD OECD

1963 1968 1973 1978 1983 1988 19931998

-4.5

-4

-3.5

-3

-2.5

(Actual Values) (After Global Effect Removed)

Note: Bands indicate two standard deviations of country observations within each year shown. OECD and non-OECD countries shown separately. Vertical scale is log(T) units. Source: Galbraith and Kum, 2003.

What would have happened without the Global Element?

This broad picture of the world economy from the standpoint of inequality measure suggests that the “super-bubble” was also, for most of the world’s population, a “super-crisis.”

The super-bubble came to a peak in 2000-20001.

The period since then was marked in the United States by efforts to keep the bubble going, in part through aggressive efforts to relax standards, which may be described as the growth of a “predator state.”

This led to the corruption of the financial markets whose collapse produced the great crisis.

Pay inequality in the US depends mainly on economic conditions, especially the unemployment rate.

Income inequality in the US depends mainly on the stock market, and is driven by top-level incomes in highly concentrated small areas.

For example: Manhattan, Silicon Valley in the 1990s, Washington DC in the 2000s

Key US Findings

.0 2

.0 3

.0 4

.0 5

.0 6

.0 7

.0 8

.0 9

.1 0

.1 1

.0 1 0

.0 1 2

.0 1 4

.0 1 6

.0 1 8

.0 2 0

.0 2 2

.0 2 4

.0 2 6

.0 2 8

55 60 65 70 75 80 8 5 9 0 95 00 05

Unemployment rate (left)Inequality of manufacturing pay (Theil index, right)

US Pay Inequality and Unemployment, 1952-2005

Inequality measured on earnings across industries in manufacturing, monthly data; recessions entered in gray.

4

4.5

5

5.5

6

6.5

7

7.5

8

8.5

9

0.015

0.02

0.025

0.03

0.035

0.04

0.045

1 9 6 9 1 9 7 0 1 9 7 1 1 9 7 2 1 9 7 3 1 9 7 4 1 9 7 5 1 9 7 6 1 9 7 7 1 9 7 8 1 9 7 9 1 9 8 0 1 9 8 1 1 9 8 2 1 9 8 3 1 9 8 4 1 9 8 5 1 9 8 6 1 9 8 7 1 9 8 8 1 9 8 9 1 9 9 0 1 9 9 1 1 9 9 2 1 9 9 3 1 9 9 4 1 9 9 5 1 9 9 6 1 9 9 7 1 9 9 8 1 9 9 9 2 0 0 0 2 0 0 1 2 0 0 2 2 0 0 3 2 0 0 4 2 0 0 5

N a t ur al L o g o f N a s d a q M on t hly C lo s e

B e t w ee n

- C o u nt y I n c om e I n eq u alit y

- T h eil's T S t a tis ti c ( 1y r la g )

US Income Inequality and the NASDAQ, 1969-2006

Income inequality measured between counties, from tax data

Tax Reform Act

Internet Bubble

InequalityLog of NASDAQ

4

4.5

5

5.5

6

6.5

7

7.5

8

8.5

9

0.015

0.02

0.025

0.03

0.035

0.04

0.045

1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005

Nat

ura

l Log

of N

asd

aq M

onth

ly C

lose

Bet

wee

n-C

oun

ty In

com

e In

equ

alit

y -T

hei

l's T

Sta

tist

ic (

1yr

lag)

U.S. Income Inequality Between Counties 1969 – 2005 Plotted Against the NASDAQ Composite, with Three Counterfactual Scenarios of Inequality Growth from 1994 – 2000

Without Manhattan

Without Silicon ValleyWithoutTop 15

Income Inequality in the United States, 1969-2009Measured Between Counties

1969

1972

1975

1978

1981

1984

1987

1990

1993

1996

1999

2002

2005

2008

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

0.016

0.018

0.020

Calculation by Amin Shams

Contribution of Each County to Income Inequality, Late 2000s

Contribution to inequality is presented as shading and as height above or below the zero plane. Calculation and map by Amin Shams.

Contribution of each Municipality to Inequality in Brazil

Contribution to inequality is presented as shading and as height above or below the zero plane. Calculation and map by Laura Spagnolo.

Further Research Results

Inequality and Unemployment Inequality and Political Regime Types Inequality and Voting: Participation Inequality and Voting: Outcomes Extent of wage flexibility in Europe Declining Inequality in Latin America Contribution of Financial Sectors to

Inequality

Needs Going Forward...

Staff regular updating of data sets Fill historical and geographic gaps Extend the record back in time Mapping Software Tools Spreading the Word.

Oxford University Press, 2012

For more information: