INDEX OF SEGREGATION : INDEX OF SEGREGATION Are Jobs Gender, Race, or Ethnically Blind?
REVIEW : 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 : 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 : 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 : 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-Employer Discrimination Past Discriminating Hiring Practices
Followed with Mouth to Mouth Hiring Practices
Current Employer Discrimination : Current Employer Discrimination Prejudice
Consumer Preferences
Other
First Source: Non-Market Discrimination : 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 : U.S. MEDIAN EARNINGS BY GENDER AND RACE/ETHNICITY, YEAR-ROUND FULL-TIME WORKERS, 2001 Table 8.1 p. 277
FEMALE/MALE MEDIAN ANNUAL EARNINGS RATIO, U.S. YEAR-ROUND FULL-TIME WORKERS Figure 8.1, p. 278 : FEMALE/MALE MEDIAN ANNUAL EARNINGS RATIO, U.S. YEAR-ROUND FULL-TIME WORKERS Figure 8.1, p. 278
FEMALE/MALE HOURLY WAGE RATIOSBY AGE GROUP AND YEAR Table 8.2, p. 280 : FEMALE/MALE HOURLY WAGE RATIOSBY AGE GROUP AND YEAR Table 8.2, p. 280
FEMALE/MALE HOURLY WAGE RATIOSBY AGE GROUP AND YEAR Table 8.2, p. 280 : FEMALE/MALE HOURLY WAGE RATIOSBY AGE GROUP AND YEAR Table 8.2, p. 280
FEMALE/MALE MEDIAN ANNUAL EARNINGS RATIO BY EDUCATION LEVEL, 2001 Figure 8.2, p. 282 : FEMALE/MALE MEDIAN ANNUAL EARNINGS RATIO BY EDUCATION LEVEL, 2001 Figure 8.2, p. 282
DISTRIBUTION OF ANNUAL EARNINGS BY GENDER, YEAR-ROUND FULL-TIME WORKERS, U.S., 2001 Figure 8.3, p. 283 : DISTRIBUTION OF ANNUAL EARNINGS BY GENDER, YEAR-ROUND FULL-TIME WORKERS, U.S., 2001 Figure 8.3, p. 283
FEMALE/MALE EARNINGS RATIOS, MEDIAN WEEKLY EARNINGS OF FULL-TIME WORKERS, SELECTED DEVELOPED COUNTRIES, 1979-1998 Table 8.3, p. 284 : FEMALE/MALE EARNINGS RATIOS, MEDIAN WEEKLY EARNINGS OF FULL-TIME WORKERS, SELECTED DEVELOPED COUNTRIES, 1979-1998 Table 8.3, p. 284
FEMALE/MALE EARNINGS RATIOS, MEDIAN WEEKLY EARNINGS OF FULL-TIME WORKERS, SELECTED DEVELOPED COUNTRIES, 1979-1998 Table 8.3, p. 284 : FEMALE/MALE EARNINGS RATIOS, MEDIAN WEEKLY EARNINGS OF FULL-TIME WORKERS, SELECTED DEVELOPED COUNTRIES, 1979-1998 Table 8.3, p. 284
PROPORTION FEMALE FOR SELECTED OCCUPATIONS, UNITED STATES, 2002 Table 8.2 pp. 286-288 : PROPORTION FEMALE FOR SELECTED OCCUPATIONS, UNITED STATES, 2002 Table 8.2 pp. 286-288
PROPORTION FEMALE FOR SELECTED OCCUPATIONS, UNITED STATES, 2002 Table 8.2 pp. 286-288 : PROPORTION FEMALE FOR SELECTED OCCUPATIONS, UNITED STATES, 2002 Table 8.2 pp. 286-288
PROPORTION FEMALE FOR SELECTED OCCUPATIONS, UNITED STATES, 2002 Table 8.2 pp. 286-288 : PROPORTION FEMALE FOR SELECTED OCCUPATIONS, UNITED STATES, 2002 Table 8.2 pp. 286-288
PROPORTION FEMALE FOR SELECTED OCCUPATIONS, UNITED STATES, 2002 Table 8.2 pp. 286-288 : PROPORTION FEMALE FOR SELECTED OCCUPATIONS, UNITED STATES, 2002 Table 8.2 pp. 286-288
PROPORTION FEMALE FOR SELECTED OCCUPATIONS, UNITED STATES, 2002 Table 8.2 pp. 286-288 : PROPORTION FEMALE FOR SELECTED OCCUPATIONS, UNITED STATES, 2002 Table 8.2 pp. 286-288
PROPORTION FEMALE FOR SELECTED OCCUPATIONS, UNITED STATES, 2002 Table 8.2 pp. 286-288 : PROPORTION FEMALE FOR SELECTED OCCUPATIONS, UNITED STATES, 2002 Table 8.2 pp. 286-288
PROPORTION FEMALE FOR SELECTED OCCUPATIONS, UNITED STATES, 2002 Table 8.2 pp. 286-288 : PROPORTION FEMALE FOR SELECTED OCCUPATIONS, UNITED STATES, 2002 Table 8.2 pp. 286-288
PROPORTION FEMALE FOR SELECTED OCCUPATIONS, UNITED STATES, 2002 Table 8.2 pp. 286-288 : PROPORTION FEMALE FOR SELECTED OCCUPATIONS, UNITED STATES, 2002 Table 8.2 pp. 286-288
Segregation Index : 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 : 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 : Duncan Segregation Index We will look at two segregation indexes. The First is known as the Duncan Segregation Index
Duncan Segregation Index : Duncan Segregation Index Where mi and fi represent the percent of males and females working in this job category respectively
Or M and F could represent any other two groups
Duncan Segregation Index : 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 : 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,
Duncan Segregation Index: An Example : Duncan Segregation Index: An Example
Duncan Segregation Index: An Example : Duncan Segregation Index: An Example
Duncan Segregation Index: An Example : Duncan Segregation Index: An Example
Duncan Segregation Index: An Example : 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 : Duncan Segregation Index: An Example
Duncan Segregation Index: An Example : 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 : IP Segregation Index The second segregation index is the IP segregation index.
IP Segregation Index: An Example : IP Segregation Index: An Example
IP Segregation Index: An Example : IP Segregation Index: An Example
Duncan Segregation Index: An Example : Duncan Segregation Index: An Example
Duncan Segregation Index : Duncan Segregation Index
Duncan Segregation Index : Duncan Segregation Index
Duncan Segregation Index : Duncan Segregation Index
Duncan Segregation Index : Duncan Segregation Index
Duncan Segregation Index : Duncan Segregation Index
Segregation Index : 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 : Segregation Index There is also a hierarchal component to job segregation?
Hierarchal Segregation : Hierarchal Segregation
Segregation Index : 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)
Slide56 : 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 : Duncan Index Across Years and Countries The Duncan Index can also be used to compare Segregation over time
And Segregation across Countries
Slide60 : GENDER DUNCAN INDEX OF SEGRAGATION