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
PERCENTAGE OF
MEN’S EARNINGS
WOMEN($)
MEN($)
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
ACROSS COHORT
18-24
25-34
35-44
45-54
WITHIN COHORT
18-24
25-34
35-44
45-54
WAGE RATIO (%)
1978-1988
1988-1998
-
10.6
12.5
9.8
6.6
1.2
2.3
7.4
6.8
-
-2.4
-1.6
5.8
2.9
-9.2
-6.7
2.9
4.5
FEMALE/MALE MEDIAN ANNUAL
EARNINGS RATIO BY EDUCATION
LEVEL, 2001
Figure 8.2, p. 282
DOCTORATE
PROF. DEGREE
MASTER'S DEGREE
BAC. DEGREE
A. DEGREE
HS GRAD
<HS
75.1%
60.3%
72.2%
75.1%
74.9%
73.4%
72.4%
0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0%
DISTRIBUTION OF ANNUAL EARNINGS
BY GENDER, YEAR-ROUND FULL-TIME
WORKERS, U.S., 2001
Figure 8.3, p. 283
>$75,000
$50-74,999
$35-49,999
MEN
WOMEN
$25-34,999
$20-24,999
$10-19,999
<$10,000
0
5
10
15
20
25
FEMALE/MALE EARNINGS RATIOS, MEDIAN
WEEKLY EARNINGS OF FULL-TIME
WORKERS, SELECTED DEVELOPED
COUNTRIES, 1979-1998
Table 8.3, p. 284
1979-1981
1989-1990
1994-1998
PERCENTAGE POINT
CHANGE IN RATION,
1979-1971 TO 1994-1998
AUSTRALIA
80.0%
81.4%
86.8%
6.8
AUSTRIA
64.9%
67.4%
69.2%
4.3
BELGIUM
N.A.
84.0%
90.1%
6.1*
CANADA
63.3%
66.3%
69.8%
6.5
FINLAND
73.4%
76.4%
79.9%
6.5
FRANCE
79.9%
84.7%
89.9%
10.0
GERMANY
(WEST)
71.7%
73.7%
75.5%
3.8
N.A.
N.A.
74.5%
N.A.
COUNTRY
IRELAND
*BASED ON CHANGE BETWEEN 1989-1990 AND 1994-1998.
FEMALE/MALE EARNINGS RATIOS, MEDIAN
WEEKLY EARNINGS OF FULL-TIME
WORKERS, SELECTED DEVELOPED
COUNTRIES, 1979-1998
Table 8.3, p. 284
1979-1981
1989-1990
1994-1998
PERCENTAGE POINT
CHANGE IN RATION,
1979-1971 TO 1994-1998
ITALY
N.A.
80.5%
83.3%
2.8*
JAPAN
58.7%
59.0%
63.6%
4.9
NETHERLANDS
N.A.
75.0%
76.9%
1.9*
NEW ZEALAND
73.4%
75.9%
81.4%
8.0
N.A.
N.A.
71.1%
-
83.8%
78.8%
83.5%
-.3
N.A.
73.6%
75.2%
1.6*
UNITED KINGDOM
62.6%
67.7%
74.9%
12.3
UNITED STATES
62.5%
70.6%
76.3%
13.8
NON-U.S. AVERAGE
71.2%
74.6%
77.8%
6.2
COUNTRY
SPAIN
SWEDEN
SWITZERLAND
*BASED ON CHANGE BETWEEN 1989-1990 AND 1994-1998.
PROPORTION FEMALE FOR SELECTED
OCCUPATIONS, UNITED STATES, 2002
Table 8.2 pp. 286-288
OCUPATION
%FEMALE
AUTOMOBILE MECHANIC
1.2
ROOFERS
1.5
CARPENTER
1.5
PLUMBERS, PIPEFITTERS, ETC.
1.7
ELECTRICIAN
1.9
CONSTRUCTION TRADES
2.1
BRICKMASONS AND STONEMASONS
2.2
FIREFIGHTERS
2.5
AIRPLANE PILOT AND NAVIGATORS
3.0
PROPORTION FEMALE FOR SELECTED
OCCUPATIONS, UNITED STATES, 2002
Table 8.2 pp. 286-288
OCUPATION
%FEMALE
TRUCK DRIVERS
4.3
MECHANICAL ENGINEERS
4.5
MACHINIST
4.8
MECHANICS AND REPAIRERS
4.8
PEST CONTROL
5.6
ELECTRICAL AND ELECTRONIC ENGIREERS
8.8
CIVIL ENGINEERS
9.6
AEROSPACE ENGINEERS
10.7
CLERGY
11.2
PROPORTION FEMALE FOR SELECTED
OCCUPATIONS, UNITED STATES, 2002
Table 8.2 pp. 286-288
OCUPATION
%FEMALE
TAXICAB DRIVERS AND CHAUFFEURS
11.7
CHEMICAL ENGINEERS
12.2
FARMING, FORESTRY, AND FISHING
14.9
BUTCHERS AND MEAT CUTTERS
16.4
POLICE AND DETECTIVES
17.5
ATHLETES
20.0
CORRECTIONAL INSTITUTION OFFICERS
21.5
ARCHITECTS
23.7
COMPUTER PROGRAMMERS
27.2
PROPORTION FEMALE FOR SELECTED
OCCUPATIONS, UNITED STATES, 2002
Table 8.2 pp. 286-288
OCUPATION
%FEMALE
MAIL CARRIERS, POSTAL SERVICE WORKERS
28.8
MATHEMATICAL AND COMPUTER SCIENTISTS
29.2
JANITORS AND CLEANERS
30.3
SECURITIES AND FINANCIAL SERVICES SALES
32.3
PHYSICIANS
32.6
LAWYERS AND JUDGES
33.7
TEACHERS, COLLEGE AND UNIVERSITY
36.7
BUS DRIVERS
41.3
PHARMACISTS
41.8
PROPORTION FEMALE FOR SELECTED
OCCUPATIONS, UNITED STATES, 2002
Table 8.2 pp. 286-288
OCUPATION
%FEMALE
BIOLOGICAL AND LIFE SCIENTISTS
44.5
BAKERS
46.6
BARTENDERS
50.0
REAL ESTATE SALES
51.8
COMPUTER OPERATORS
52.9
INSURANCE SALES
53.1
ECONOMIST
54.2
PHYSICIANS’ ASSISTANT
55.6
TEACHERS, SECONDARY SCHOOL
56.4
PROPORTION FEMALE FOR SELECTED
OCCUPATIONS, UNITED STATES, 2002
Table 8.2 pp. 286-288
OCUPATION
%FEMALE
PSYCHOLOGISTS
57.6
PHYSICAL THERAPISTS
61.3
SALES COUNTER CLERKS
64.5
SOCIAL WORKERS
70.3
WAINTERS AND WAITRESSES
71.0
THERAPISTS
71.1
HOTEL CLERKS
75.0
CASHIERS
77.7
TEACHERS, ELEMENTARY SCHOOL
81.5
PROPORTION FEMALE FOR SELECTED
OCCUPATIONS, UNITED STATES, 2002
Table 8.2 pp. 286-288
OCUPATION
%FEMALE
LIBRARIANS
83.0
LEGAL ASSISTANTS
84.0
DATA-ENTRY KEYERS
84.6
RECORD CLERKS
84.9
DIETICIANS
87.5
NURSING AIDES, ORDELIES AND
ATTENDANTS
BANK TELLERS
89.0
HAIRDRESSERS AND COSMETOLOGISTS
89.3
FINANCIAL RECORDS PROCESSING
90.6
89.1
PROPORTION FEMALE FOR SELECTED
OCCUPATIONS, UNITED STATES, 2002
Table 8.2 pp. 286-288
OCUPATION
%FEMALE
REGISTERES NURSES
91.0
SPEECH THERAPISTS
94.0
LICENSED PRACTICAL NURSES
94.4
CLEANERS AND SERVANTS
95.2
DENTAL ASSISTANTS
97.7
RECEPTIONISTS
97.9
TEACHERS, PRE-KINDERGARTEN AND
KINDERGARTEN
CHILD CARE WORKERS
98.4
SECRETARIES
98.6
98.5
Segregation Index

One way of establishing if jobs are distributed
in a gender, race, and ethnic blind form is by
looking at whether certain jobs are more likely
to have a larger percent of a certain type of
employees.
 In other words, is this job more likely to be a
male or female job
 Or, is this job more likely to be held by a
minority than a non-hispanic white
Segregation Index
This can be measured thru the use of
the Segregation Index
 The index attempts to review whether
there is a “larger” than expected
presence of a certain group in any given
job category

Duncan Segregation Index

We will look at two segregation indexes.
The First is known as the Duncan
Segregation Index
I
n
1
2
M
i 1
i
 Fi
Duncan Segregation Index
Where mi and fi represent the percent of
males and females working in this job
category respectively
mi
fi
Mi 
and Fi 
m
f

Or M and F could represent any other
two groups
Duncan Segregation Index

When I = 0
– That implies that there is no segregation in
any job category. In other words, Mi = Fi

When I = 1
– That implies that there is complete
segregation in all job categories. This can
be seen since when Mi >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
M
i 1
i
1, and
n
 F 1
i 1
i
Duncan Segregation Index: An
Example
Romance
Novelist
74
Hot Dog
Venders
55
Mimes
Women
4
15
81
Men
70
40
7
88
Duncan Segregation Index: An
Example
 3 mi f i 
 3

S  0.5 
   0.5   M i  Fi 
 i 1

 i 1 m f 
 m1
m3
f3 
f1
m2
f2
 0.5 






f
m
f
m
f 
m
 70
4
40
15
7
81 
 0.5 






100 117
100 117
100 
 117
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 1.5004
 .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
Novelist
130 (74)
Hot Dog
Venders
74 (55)
Mimes
13 (88)
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.
I
n
1
T
 (1  a)m
i 1
i
 a fi
m
where T  m  f , and a 
T
IP Segregation Index: An
Example
Romance
Novelist
74
Hot Dog
Venders
55
Mimes
Women
4
15
81
Men
70
40
7
88
IP Segregation Index: An
Example
IP
IP
IP
IP
IP
IP
1 3 
117 
 177 

1 
 Mi  
 Fi

217 i 1 
217 
217


1 3

 .460829 mi  .53917 fi
217 i 1
1
.460829 70  .53917 4  .460829 40  .53917 15  .460829 81  .53917 7 

217
1
30.10138  10.34562   40.447 

217
1
80.89401

217
 .372783
Duncan Segregation Index: An
Example
Romance
Novelist
74
Hot Dog
Venders
55
Mimes
Women
34
25
41
Men
40
30
47
88
Duncan Segregation Index
A-20. Employed persons by occupation, race, and sex
Aug.
2000
Aug.
2000
Aggregate Disaggregate
TOTAL
Total, 16 years and over (thousands)
Percent.
Managerial and professional specialty
Executive, administrative, and managerial
Professional specialty
Technical, sales, and administrative support
Technicians and related support
Sales occupations
Administrative support, including clerical
Service occupations
Private household
Protective service
Service, except private household and protective
Precision production, craft, and repair
Operators, fabricators, and laborers
Machine operators, assemblers, and inspectors
Transportation and material moving occupations
Handlers, equipment cleaners, helpers, and laborers
Farming, forestry, and fishing..
Index of Segregation
Men
Women
73,299
62,302
100
100
28
14.6
13.3
19.6
2.9
11.4
5.4
9.5
0.1
2.6
6.9
19.2
19.5
6.1
7.2
6.3
4.2
Total
Men
32.4
14.3
18.1
39.7
3.6
12.9
23.3
17.6
1
0.8
15.8
2
7.1
4.5
0.8
1.7
1.2
Women
4.4
0.3
4.8
20.1
0.7
1.5
17.9
8.1
17.2
12.4
0.9
1.8
8.9
17.2
3
1.6
6.4
4.6
3
32.6
34.8
Duncan Segregation Index
WHITE
Aug.
2000
Aug.
2000
Total, 16 years and over (thousands)
Percent.
62,649
100
Managerial and professional specialty
Executive, administrative, and managerial
Professional specialty
Technical, sales, and administrative support
Technicians and related support
Sales occupations
Administrative support, including clerical
Service occupations
Private household
Protective service
Service, except private household and protective
Precision production, craft, and repair
Operators, fabricators, and laborers
Machine operators, assemblers, and inspectors
Transportation and material moving occupations
Handlers, equipment cleaners, helpers, and laborers
Farming, forestry, and fishing..
Men
Women
28.6
33.3
15.4
15
13.2
18.3
19.6
40.3
2.8
3.4
11.9
13.3
5
23.6
8.8
16.6
0.1
1
2.5
0.7
6.2
14.9
20.1
1.9
18.4
6.4
5.7
4.1
6.7
0.7
6
1.7
4.5
1.4
Index of Segregation
White
Men
Aggregate Disaggregate
51,196
100
Women
4.7
0.4
5.1
20.7
0.6
1.4
18.6
7.8
18.2
12
0.9
1.8
8.7
18.2
3.1
1.6
6
4.3
3.1
33.25
35.35
Duncan Segregation Index
BLACK
Aug.
2000
Total, 16 years and over (thousands)
Percent.
Managerial and professional specialty
Executive, administrative, and managerial
Professional specialty
Technical, sales, and administrative support
Technicians and related support
Sales occupations
Administrative support, including clerical
Service occupations
Private household
Protective service
Service, except private household and protective
Precision production, craft, and repair
Operators, fabricators, and laborers
Machine operators, assemblers, and inspectors
Transportation and material moving occupations
Handlers, equipment cleaners, helpers, and laborers
Farming, forestry, and fishing..
Index of Segregation
Aug.
2000
Aggregate Disaggregate
Men
Women
7,173
8,095
100
100
19
8.8
10.2
18.9
2.3
8
8.6
16.1
4.3
11.8
13.3
30.5
8.7
12
9.8
2.2
Black
Men
25.9
10.6
15.2
37.7
4
10.5
23.2
24.5
1.2
1.4
21.8
1.8
9.7
5.8
1.7
2.2
0.5
Women
6.9
1.8
5
18.8
1.7
2.5
14.6
8.4
11.5
20.8
0
2.9
10
11.5
1.7
2.9
10.3
7.6
1.7
34.05
36.25
Duncan Segregation Index
WOMEN
Total, 16 years and over (thousands)
Percent.
Managerial and professional specialty
Executive, administrative, and managerial
Professional specialty
Technical, sales, and administrative support
Technicians and related support
Sales occupations
Administrative support, including clerical
Service occupations
Private household
Protective service
Service, except private household and protective
Precision production, craft, and repair
Operators, fabricators, and laborers
Machine operators, assemblers, and inspectors
Transportation and material moving occupations
Handlers, equipment cleaners, helpers, and laborers
Farming, forestry, and fishing..
Index of Segregation
Aug.
2000
Aug.
2000
62,649
100
51,196
100
White
33.3
15
18.3
40.3
3.4
13.3
23.6
16.6
1
0.7
14.9
1.9
6.4
4.1
0.7
1.7
1.4
Black
25.9
10.6
15.2
37.7
4
10.5
23.2
24.5
1.2
1.4
21.8
1.8
9.7
5.8
1.7
2.2
0.5
Women
White
Black
Aggregate Disaggregate
7.4
4.4
3.1
2.6
0.6
2.8
0.4
7.9
0.1
3.3
0.2
0.7
6.9
0.1
0.9
1.7
1
0.5
0.9
11.1
11.65
Duncan Segregation Index
MEN
Total, 16 years and over (thousands)
Percent.
Aug.
2000
Aug.
2000
62,649
100
51,196
100
Managerial and professional specialty
Executive, administrative, and managerial
Professional specialty
Technical, sales, and administrative support
Technicians and related support
Sales occupations
Administrative support, including clerical
Service occupations
Private household
Protective service
Service, except private household and protective
Precision production, craft, and repair
Operators, fabricators, and laborers
Machine operators, assemblers, and inspectors
Transportation and material moving occupations
Handlers, equipment cleaners, helpers, and laborers
Farming, forestry, and fishing..
White
28.6
15.4
13.2
19.6
2.8
11.9
5
8.8
0.1
2.5
6.2
20.1
18.4
5.7
6.7
6
4.5
Black
19
8.8
10.2
18.9
2.3
8
8.6
16.1
4.3
11.8
13.3
30.5
8.7
12
9.8
2.2
Index of Segregation
Men
White
Black
Aggregate Disaggregate
9.6
6.6
3
0.7
0.5
3.9
3.6
7.3
6.8
12.1
0
1.8
5.6
6.8
2.3
3
5.3
3.8
2.3
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
Rank
Professor
Associate
Professor
Assistant
Professor
1974-75
1985-85
1994-95 1998-99
10.1
11.6
16.2
18.7
17.3
23.3
31.2
34.6
27.9
35.8
44.7
46.8
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
ANNUAL AVERAGES
39. Median weekly earnings of full-time wage and salary workers by detailed occupation and sex
HOUSEHOLD DATA
ANNUAL AVERAGES
(Numbers in thousands)
2005
Both sexes
Men
Women
Number
Median
of
weekly
workers earnings
Number
Median
of
weekly
workers earnings
Number
Median
of
weekly
workers earnings
Occupation
Total, 16 years and over............................................... 103,560
Management, professional, and related occupations...................... 36,908
Management, business, and financial operations occupations... ..... 14,977
Professional and related occupations.......................... .... 21,931
Service occupations............................................... .... 14,123
Sales and office occupations....................................... ... 25,193
Sales and related occupations...................................... 10,031
Office and administrative support occupations...................... 15,161
Natural resources, construction, and maintenance occupations........... 12,086
Farming, fishing, and forestry occupations.........................
755
Construction and extraction occupations............................
6,826
Installation, maintenance, and repair occupations..................
4,504
Production, transportation, and material moving occupations............ 15,251
Production occupations.......................................... ..
8,403
Transportation and material moving occupations................... .
6,848
$651
937
997
902
413
575
622
550
623
372
604
705
540
538
543
58,406
18,311
8,195
10,116
7,024
9,539
5,582
3,957
11,569
601
6,663
4,305
11,963
5,991
5,972
$722
1,113
1,167
1,058
478
690
762
605
628
388
606
706
591
608
574
45,154
18,597
6,782
11,815
7,099
15,654
4,449
11,205
517
154
163
199
3,288
2,412
876
$585
813
847
792
379
520
483
533
486
327
480
691
420
423
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
Country
France
Korea
Germany
Hong Kong
Russian Federation
United States
Pakistan
Tahiland
0
10
20
30
40
Duncan Index
50
60
70