Perfect equality = O < G < 1 = Perfect inequality 4% 20% A B G = A/(A+B)

Perfect equality = O < G < 1 = Perfect inequality

4%

20%

20%

AABB

G = A/(A+B)G = A/(A+B)

World Development Report 2006: Equity and Development


Gini coefficients in the world

http://en.wikipedia.org/wiki/Image:World_Map_Gini_coefficient.png

http://en.wikipedia.org/wiki/Image:World_Map_Gini_coefficient_Legend.png


Wage ratios

Wage

20% 20%

W80W20

W80

W20

WR =

Acemoglu, Daron “Technical Change, Inequality, and the Labor Market” Journal of Economic Literature, March 2002

Wages rising at upper tail, Wages rising at upper tail, falling at lower tail falling at lower tail


Residual inequality: wage Residual inequality: wage differences holding differences holding constant education, constant education, experienceexperience

W = βX + e; X = vector of measured skills; e = residual

Wage dispersion: ratio of the 90th percentile to the 10th percentile wage

1980-1984

1995-1999

Δ 1999-1980

Australia 2.88 2.94 0.06

Finland 2.49 2.36 -0.13

France 3.18 3.07 -0.11

Germany 2.88 2.87 -0.01

Japan 3.08 2.99 -0.09

Netherlands 2.47 2.85 0.38

New Zealand 2.89 3.28 0.39

Sweden 2.01 2.23 0.22

UK 3.09 3.45 0.36

USA 3.91 4.59 0.68

Source: OECD Employment Outlook, 2004

Stylized facts regarding earnings inequality

1) Inequality has been increasing steadily in the U.S. since the 1980s for both men and women

2)Inequality has been rising in other industrialized economies

3) Until 1980, inequality had been rising across countries

4) Conclusions are not sensitive to measure of inequality used

Rising inequality not due to gender discriminationRising inequality not due to gender discrimination

Source: Bureau of Labor Statistics

Rising inequality not due to Rising inequality not due to race discriminationrace discrimination

Source: Bureau of Labor Statistics

Ratio of Women's to Men's Hourly Earnings by Country, 1970-2002Source: Blau, Ferber, and Winkler, The Economics of Women, Men and Work 2006.

0.5

0.55

0.6

0.65

0.7

0.75

0.8

0.85

0.9

0.95

1970 1975 1980 1985 1990 1995 2000 2005

Year

Rat

io

Australia

France

Germany

Norway

Sweden

UK

USA


5) Women are gaining relative to men

6) Minorities gained relative to whites before the 1980s, but relative earnings for minorities stabilized thereafter

7) Wage inequality between women increased, as did wage inequality between men

8) Residual inequality began to increase for both men and women in the 1970s

Relative wages of males 25-54 versus males 20-24, 1973-1998

0.8

0.9

1

1.1

1.2

1.3

1.4

1970 1975 1980 1985 1990 1995 2000

Year

Ratio (1973=1)

CANADA

JAPAN

FRANCE

USA

UK

Estimated Returns to Schooling Relative to High School Graduates: 1976-1998

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

1976 1981 1986 1991 1996

Bachelor's Degree Recipients

Post Graduate education



9) There have been coincident increases in returns to schooling over that period

10) There have been rising returns to experience over that time frame

11) Young college graduates have gained the most, especially in the 1990s

12) Rising returns to college even as relative supply has increased tremendously

Econ 1 Test

Has to be a demand side reason for

Rising relative employmentRising relative wages

Cause must be common across industrialized economies


Demand for

Price of

Physical Capital

Numbers of Workers

Human Capital per Worker

Physical Capital -0.45 1.07 -0.11

Numbers of Workers

0.66 -1.44 0.15

Human Capital per Worker

-0.15 0.35 -0.13

Red: Complements; Blue: Substitutes

Note: Based on share-weighted elasticities of substitution reported in Table 6 of Huang. Hallam, Orazem and Paterno, "Empirical Tests of Efficiency Wage Models."Economica 65 (February 1998):125-143.

Estimated own and cross price elasticities between capital, labor and human capital per worker


ln(WR)= β0 + β1* NR + β2* r + e

WR= relative college to high school wage

NR = relative weeks worked of college educated to high school educated

r = relative price of equipment capital

Stop here

Other issues

Economic policy to limit inequality and labor market performance

Tax and Transfer policies and inequality

Inequality within occupations

Scatterplot of Changes in wage dispersion and unemployment rates, 1990-2000

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

-6 -4 -2 0 2 4 6 8

Change in unemployment rate

Ch

ang

e in

90-

10 w

age

rati

o

France

UK

New ZealandUSA

Netherlands

Finland

Sweden

Japan

Germany

Australia

Tradeoff between rising inequality Tradeoff between rising inequality and employment stabilityand employment stability

Weinberg, Daniel. Alternative Measures of Income Poverty and. the Anti-poverty Effects of Taxes and Transfers www.welfareacademy.org/pubs/poverty/Weinberg_Alt_Measures.pdf

http://www.welfareacademy.org/pubs/poverty/Weinberg_Alt_Measures.pdf



http://www.census.gov/hhes/www/poverty/effect2004/effectofgovtandt2004.pdf

http://www.census.gov/hhes/www/poverty/effect2004/effectofgovtandt2004.pdf

Buckley, John. “Rankings of Full-Time Occupations, by Earnings, 2000.” Monthly Labor Review 125 (March 2002): 46-57.

Buckley, John. “Rankings of Full-Time Occupations, by Earnings, 2000.” Monthly Labor Review 125 (March 2002): 46-57.

CPS: Current Population Survey

MINT: Social Security Administration data

B. Bosworth, G. Burtless and C. Sahn “The Trend in Lifetime Earnings Inequality and Its Impact on the Distribution of Retirement Income” August 2001

Restricted to Full-time workers

All workers

CPS: Current Population Survey

MINT: Social Security Administration data

B. Bosworth, G. Burtless and C. Sahn “The Trend in Lifetime Earnings Inequality and Its Impact on the Distribution of Retirement Income” August 2001

Economic Freedom Index

High

Medium

Low

Returns to Education and Experience among Full-Time, Year-Round Workers, Selected Ages, 1975–2003 (in 2003 dollars)

Documents

Perfect equality = O < G < 1 = Perfect inequality 4% 20% A B G = A/(A+B)