INDEX OF
SEGREGATION
Are Jobs Gender, Race, or
Ethnically Blind?
REVIEW
We Have determined the following
– Under Pure Competition and under the
assumption of homogenous workers
– Firms will hire workers to maximize profits
• i.e. MR=MC
• Or equivalently, where w = MRP
• Where MRP = P*MPL
Discrimination
Hence, if there workers were indeed
homogenous and they received different
wages then that would imply there was
discrimination
However, if workers are not
homogenous than different wages alone
would not necessarily imply
discrimination
Discrimination
If there is disparity in wages
Then the question is why?
There are three sources that may
account for wages disparities (or
discrimination):
– Non-Market Discrimination
– Past-Employer Discrimination
– Current Employer Discrimination
Non-Market Discrimination
Lower Productivity due to training
(schooling, etc)
Geographical (more blacks in the
South)
Different preferences in terms of
Labor/Leisure
Other
Past-Employer Discrimination
Past Discriminating Hiring Practices
Followed with Mouth to Mouth Hiring
Practices
Current Employer Discrimination
Prejudice
Consumer Preferences
Other
First Source:
Non-Market Discrimination
Do individuals on average take on
different jobs based on personal
characteristics such as gender, race, or
ethnicity
If so, that may in part explain the
difference in wage differentials
U.S. MEDIAN EARNINGS BY GENDER
AND RACE/ETHNICITY, YEAR-ROUND
FULL-TIME WORKERS, 2001
Table 8.1 p. 277
WOMEN’S
EARNINGS AS
WOMEN($) MEN($) PERCENTAGE OF
MEN’S EARNINGS
ALL 29,215 38,275 76.3
WHITE 29,930 39,834 75.1
BLACK 26,595 31,351 84.8
HISPANIC 21,493 25,083 85.7
ASIA/PACIFIC
ISLANDER 30,685 41,853 73.3
FEMALE/MALE MEDIAN ANNUAL
EARNINGS RATIO, U.S. YEAR-ROUND
FULL-TIME WORKERS
Figure 8.1, p. 278
85%
80%
75%
70%
65%
60%
55%
50%
1960 1970 1980 1990 2000
FEMALE/MALE HOURLY WAGE
RATIOSBY AGE GROUP AND YEAR
Table 8.2, p. 280
WAGE RATIO (%)
AGE RANGE
1978 1988 1998
18-24 82.4 93.0 94.2
25-34 70.3 82.8 85.0
35-44 58.9 68.7 76.1
45-54 58.2 64.7 71.6
FEMALE/MALE HOURLY WAGE
RATIOSBY AGE GROUP AND YEAR
Table 8.2, p. 280
AGE RANGE WAGE RATIO (%)
1978-1988 1988-1998
ACROSS COHORT
18-24
25-34 - 10.6 1.2
35-44 - 12.5 2.3
45-54 - 9.8 7.4
- 6.6 6.8
WITHIN COHORT
18-24
25-34 - -2.4 -9.2
35-44 - -1.6 -6.7
45-54 - 5.8 2.9
- 2.9 4.5
FEMALE/MALE MEDIAN ANNUAL
EARNINGS RATIO BY EDUCATION
LEVEL, 2001
Figure 8.2, p. 282
DOCTORATE
75.1%
PROF. DEGREE
60.3%
MASTER'S DEGREE
72.2%
BAC. DEGREE
75.1%
A. DEGREE
74.9%
HS GRAD
73.4%
$75,000
$50-74,999
$35-49,999
MEN
$25-34,999
WOMEN
$20-24,999
$10-19,999
0, the Fi = 0 and
vice versa.
Duncan Segregation Index
Mi and Fi are the percentage of the
individuals in a given group (M or F) that
are working in job category i.
Consequently,
n n
M
i 1
i 1, and F 1
i 1
i
Duncan Segregation Index: An
Example
Romance Hot Dog Mimes
Novelist Venders
88
74 55
Women 4 15 81
Men 70 40 7
Duncan Segregation Index: An
Example
3 mi f i 3
S 0.5 0.5 M i Fi
i 1 m f i 1
m1 f1 m2 f2 m3 f3
0.5
m f m f m f
70 4 40 15 7 81
0.5
117 100 117 100 117 100
Duncan Segregation Index: An
Example
S 0.5 0.5983 0.04 0.3419 0.15 0.0598 0.81
0.5 0.5583 0.1919 0.7502
0.5 0.5583 0.1919 0.7502
0.5 .5004
1
.7502
or
S 75.02%
Duncan Segregation Index: An
Example
That means that you need to move 75%
of the workers to obtain equal
distribution of Employment
That is 75% of women would have to
change jobs for the employment
distribution be the same
Duncan Segregation Index: An
Example
Romance Hot Dog Mimes
Novelist Venders 13 (88)
130 (74) 74 (55)
Women 56=4+52 34=15+19 6=81-75
Men 70 40 7
Duncan Segregation Index: An
Example
Duncan Index therefore states that 75%
of women need to change job to obtain
evenly distributed workplace
However, one big draw back: the
workforce in the different sectors much
change
For instance, there would now be 130
romance novelist instead of 74, etc.
IP Segregation Index
The second segregation index is the IP
segregation index.
n
I 1
T (1 a)m
i 1
i a fi
m
where T m f , and a
T
IP Segregation Index: An
Example
Romance Hot Dog Mimes
Novelist Venders
88
74 55
Women 4 15 81
Men 70 40 7
IP Segregation Index: An
Example
1 3 117 177
IP 1
217 i 1
Mi
217
Fi
217
1 3
IP .460829 mi .53917 fi
217 i 1
IP
1
.460829 70 .53917 4 .460829 40 .53917 15 .460829 81 .53917 7
217
IP
1
30.10138 10.34562 40.447
217
IP
1
80.89401
217
IP .372783
Duncan Segregation Index: An
Example
Romance Hot Dog Mimes
Novelist Venders
88
74 55
Women 34 25 41
Men 40 30 47
Duncan Segregation Index
A-20. Employed persons by occupation, race, and sex
Aug. Aug.
2000 2000 Aggregate Disaggregate
TOTAL
Men Women
Total, 16 years and over (thousands) 73,299 62,302
Percent. 100 100
Managerial and professional specialty 28 32.4 4.4
Executive, administrative, and managerial 14.6 14.3 0.3
Professional specialty 13.3 18.1 4.8
Technical, sales, and administrative support 19.6 39.7 20.1
Technicians and related support 2.9 3.6 0.7
Sales occupations 11.4 12.9 1.5
Administrative support, including clerical 5.4 23.3 17.9
Service occupations 9.5 17.6 8.1
Private household 0.1 1 0.9
Protective service 2.6 0.8 1.8
Service, except private household and protective 6.9 15.8 8.9
Precision production, craft, and repair 19.2 2 17.2 17.2
Operators, fabricators, and laborers 19.5 7.1 12.4
Machine operators, assemblers, and inspectors 6.1 4.5 1.6
Transportation and material moving occupations 7.2 0.8 6.4
Handlers, equipment cleaners, helpers, and laborers 6.3 1.7 4.6
Farming, forestry, and fishing.. 4.2 1.2 3 3
Total
Index of Segregation Men Women 32.6 34.8
Duncan Segregation Index
Aug. Aug.
WHITE 2000 2000 Aggregate Disaggregate
Total, 16 years and over (thousands) 62,649 51,196
Percent. 100 100
Men Women
Managerial and professional specialty 28.6 33.3 4.7
Executive, administrative, and managerial 15.4 15 0.4
Professional specialty 13.2 18.3 5.1
Technical, sales, and administrative support 19.6 40.3 20.7
Technicians and related support 2.8 3.4 0.6
Sales occupations 11.9 13.3 1.4
Administrative support, including clerical 5 23.6 18.6
Service occupations 8.8 16.6 7.8
Private household 0.1 1 0.9
Protective service 2.5 0.7 1.8
Service, except private household and protective 6.2 14.9 8.7
Precision production, craft, and repair 20.1 1.9 18.2 18.2
Operators, fabricators, and laborers 18.4 6.4 12
Machine operators, assemblers, and inspectors 5.7 4.1 1.6
Transportation and material moving occupations 6.7 0.7 6
Handlers, equipment cleaners, helpers, and laborers 6 1.7 4.3
Farming, forestry, and fishing.. 4.5 1.4 3.1 3.1
White
Index of Segregation Men Women 33.25 35.35
Duncan Segregation Index
BLACK
Aug. Aug.
2000 2000 Aggregate Disaggregate
Men Women
Total, 16 years and over (thousands) 7,173 8,095
Percent. 100 100
Managerial and professional specialty 19 25.9 6.9
Executive, administrative, and managerial 8.8 10.6 1.8
Professional specialty 10.2 15.2 5
Technical, sales, and administrative support 18.9 37.7 18.8
Technicians and related support 2.3 4 1.7
Sales occupations 8 10.5 2.5
Administrative support, including clerical 8.6 23.2 14.6
Service occupations 16.1 24.5 8.4
Private household - 1.2 0
Protective service 4.3 1.4 2.9
Service, except private household and protective 11.8 21.8 10
Precision production, craft, and repair 13.3 1.8 11.5 11.5
Operators, fabricators, and laborers 30.5 9.7 20.8
Machine operators, assemblers, and inspectors 8.7 5.8 2.9
Transportation and material moving occupations 12 1.7 10.3
Handlers, equipment cleaners, helpers, and laborers 9.8 2.2 7.6
Farming, forestry, and fishing.. 2.2 0.5 1.7 1.7
Black
Index of Segregation Men Women 34.05 36.25
Duncan Segregation Index
WOMEN Aug. Aug.
2000 2000 Aggregate Disaggregate
Total, 16 years and over (thousands) 62,649 51,196
Percent. 100 100
White Black
Managerial and professional specialty 33.3 25.9 7.4
Executive, administrative, and managerial 15 10.6 4.4
Professional specialty 18.3 15.2 3.1
Technical, sales, and administrative support 40.3 37.7 2.6
Technicians and related support 3.4 4 0.6
Sales occupations 13.3 10.5 2.8
Administrative support, including clerical 23.6 23.2 0.4
Service occupations 16.6 24.5 7.9
Private household 1 1.2 0.2
Protective service 0.7 1.4 0.7
Service, except private household and protective 14.9 21.8 6.9
Precision production, craft, and repair 1.9 1.8 0.1 0.1
Operators, fabricators, and laborers 6.4 9.7 3.3
Machine operators, assemblers, and inspectors 4.1 5.8 1.7
Transportation and material moving occupations 0.7 1.7 1
Handlers, equipment cleaners, helpers, and laborers 1.7 2.2 0.5
Farming, forestry, and fishing.. 1.4 0.5 0.9 0.9
Women
Index of Segregation White Black 11.1 11.65
Duncan Segregation Index
Aug. Aug.
MEN 2000 2000 Aggregate Disaggregate
Total, 16 years and over (thousands) 62,649 51,196
Percent. 100 100
White Black
Managerial and professional specialty 28.6 19 9.6
Executive, administrative, and managerial 15.4 8.8 6.6
Professional specialty 13.2 10.2 3
Technical, sales, and administrative support 19.6 18.9 0.7
Technicians and related support 2.8 2.3 0.5
Sales occupations 11.9 8 3.9
Administrative support, including clerical 5 8.6 3.6
Service occupations 8.8 16.1 7.3
Private household 0.1 - 0
Protective service 2.5 4.3 1.8
Service, except private household and protective 6.2 11.8 5.6
Precision production, craft, and repair 20.1 13.3 6.8 6.8
Operators, fabricators, and laborers 18.4 30.5 12.1
Machine operators, assemblers, and inspectors 5.7 8.7 3
Transportation and material moving occupations 6.7 12 5.3
Handlers, equipment cleaners, helpers, and laborers 6 9.8 3.8
Farming, forestry, and fishing.. 4.5 2.2 2.3 2.3
Men
Index of Segregation White Black 19.4 23.1
Segregation Index
From the previous tables
– What can we say occurs when the
segregation index is based on more
aggregate data as compared to more
disaggregate data?
Segregation Index
There is also a hierarchal component to
job segregation?
Hierarchal Segregation
Percent Female of Faculty in Institutions of
Higher Education by Academic Rank,
1974-75, 1985-86, 1994-95, 1998-1999
Academic 1974-75 1985-85 1994-95 1998-99
Rank
Professor
10.1 11.6 16.2 18.7
Associate
17.3 23.3 31.2 34.6
Professor
Assistant
27.9 35.8 44.7 46.8
Professor
Segregation Index
The segregation is likely to have a large
impact on wages
For instance, jobs that have generally
more women are likely to have lower
wages
– (will discuss this more when we look at
models of discrimination)
HOUSEHOLD DATA HOUSEHOLD DATA
ANNUAL AVERAGES ANNUAL AVERAGES
39. Median weekly earnings of full-time wage and salary workers by detailed occupation and sex
(Numbers in thousands)
2005
Both sexes Men Women
Occupation
Number Median Number Median Number Median
of weekly of weekly of weekly
workers earnings workers earnings workers earnings
Total, 16 years and over............................................... 103,560 $651 58,406 $722 45,154 $585
Management, professional, and related occupations...................... 36,908 937 18,311 1,113 18,597 813
Management, business, and financial operations occupations... ..... 14,977 997 8,195 1,167 6,782 847
Professional and related occupations.......................... .... 21,931 902 10,116 1,058 11,815 792
Service occupations............................................... .... 14,123 413 7,024 478 7,099 379
Sales and office occupations....................................... ... 25,193 575 9,539 690 15,654 520
Sales and related occupations...................................... 10,031 622 5,582 762 4,449 483
Office and administrative support occupations...................... 15,161 550 3,957 605 11,205 533
Natural resources, construction, and maintenance occupations........... 12,086 623 11,569 628 517 486
Farming, fishing, and forestry occupations......................... 755 372 601 388 154 327
Construction and extraction occupations............................ 6,826 604 6,663 606 163 480
Installation, maintenance, and repair occupations.................. 4,504 705 4,305 706 199 691
Production, transportation, and material moving occupations............ 15,251 540 11,963 591 3,288 420
Production occupations.......................................... .. 8,403 538 5,991 608 2,412 423
Transportation and material moving occupations................... . 6,848 543 5,972 574 876 412
Duncan Index Across Years and
Countries
The Duncan Index can also be used to
compare Segregation over time
And Segregation across Countries
GENDER DUNCAN INDEX OF
SEGRAGATION
Duncan Index of Occupational Segregation, Selected Countries (Fig 8.5, p.296)
Belarus
Iran
Poland
Austria
France
Country
Korea
Germany
Hong Kong
Russian Federation
United States
Pakistan
Tahiland
0 10 20 30 40 50 60 70
Duncan Index