GENDER SEGREGATION BY OCCUPATION IN THE U.S.

Paige Hehl, UW Eau ClaireFaculty Mentor: Dr. David Schaffer

Previous Research

Some economic researchers have concluded that gender discrimination in the U.S. is essentially gone. Schaffer’s previous research suggested otherwise. Our research using a different set of statistical techniques and an enormous database supports the idea of continuing discrimination against women in the labor market.

Data

Data was obtained from the Current Population Survey (CPS) for the years 1971-2006. (http://www.census.gov/cps/)

We have approximately 60,000 observations for each year.

Used Stata 10 & 11

0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.000.00

0.03

0.06

0.09

0.12

0.15

0.18

0.21

0.24

0.27

0.30

Distribution of White Males and Females Across Occupation Categories, 2002

female distnmale distncombined distn

Oaxaca Decomposition

Regression of wage rate onto years of schooling and potential experience:

Differential due to Discrimination

Differential due to differences in human capital

Method 1: Extending Oaxaca Decomposing further to obtain

differential due to gender segregation We used three types of occupations

A: Occupations with less than 30% female workers

B: Occupations with 30-70% female workers C: Occupations with more than 70% female

Actual wage gap calculated as A∆= ∑[(NiM/NM)lnWiM – (NiF/NF)lnWiF]

A∆= H+D+S H= differential due to differences in

human capital D= differential due to discrimination S= differential due to gender

segregation

H= ∑ βiM(XiM – XiF) (Ni/N)

D= ∑(βiM-βiF)XiF (Ni/N)

S= ∑ {[(NiM/NM)-(Ni/N)]lnWiM – [(NiF/NF)-(Ni/N)]lnWiF}

Need program for more categories

Results from Decomposing

1971 A∆= 0.546149

(actual logwage gap)

H= 0.017139 D= 0.453878 S= 0.075132 S is about 13.8% of

A∆

2002 A∆= 0.281517

(actual logwage gap)

H= -0.008705 D= 0.225145 S= 0.06507

S is about 23.1% of A∆

Method 2:Regression Analysis with Additional Variables

Regressed certain variables against the natural log of wages

Used years of education, potential experience, fraction-female, average occupation education, and others

Restricted the wages between $2 - $200 (an hour) to eliminate some of the variance

Used weighted averages

Additional Variables 500 occupation categories

determined by the Census Bureau Fraction-female (within each occupation) Average education (within each

occupation)

Fraction-Female Coefficients 2006  Fraction Female Males Females

0-.10 0.000 0.000.11-.20 -0.131 -0.132.21-.30 -0.099 -0.132.31-.40 -0.130 -0.157.41-.50 -0.174 -0.265.51-.60 -0.219 -0.279.61-.70 -0.275 -0.341.71-.80 -0.272 -0.316.81-.90 -0.293 -0.318

.91-1.00 -0.343 -0.322

1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007

-0.35

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

White Males: 7-period wgtd. moving avg.

0.15Linear (0.15)0.25Linear (0.25)0.35Linear (0.35)0.45Linear (0.45)0.55Linear (0.55)0.65Linear (0.65)0.75Linear (0.75)0.85Linear (0.85)0.95Linear (0.95)

1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 2007

-0.35

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

White Females: 7-period wgtd moving avg

0.15Linear (0.15)0.25Linear (0.25)0.35Linear (0.35)0.45Linear (0.45)0.55Linear (0.55)0.65Linear (0.65)0.75Linear (0.75)0.85Linear (0.85)0.95Linear (0.95)

Interpretations Types of Discrimination

Pure Discrimination Gender Segregation Penalty

It has always been the case that wages decrease as you move to a more female job

The size of the wage gap has increased over time

Jobs have become less segregated, but the wage penalty has gotten larger for being in the more female segregated jobs.

Citations

Borjas, George. Labor Economics. 5th. New York, NY: McGraw-Hill/Irwin, 2008. Print.

Fluckiger, Yves, and Jacques Silber. The Measurement of Segregation in the Labor Force. Germany: Physica-Verlag Heidelberg, 1999. Print.