Post on 06-Jul-2018
Understanding the Gender Pay Gap
Presented by
Barbara Wagner, Chief EconomistMontana Department of Labor & Industry
The Basic Gender Pay Gap
2
U.S. women earn 71.1% of the
usual median earnings of men
71.1₵on every dollar
Source: 2016 American Community Survey, 5-Year Estimates, U.S. Census Bureau
Understanding The Wage Gap
Nationally,Women earn 71.1% of men.
In Montana,Women earn 68% of men.
Raw Gap= 𝑚𝑒𝑑𝑖𝑎𝑛 𝑒𝑎𝑟𝑛𝑖𝑛𝑔𝑠 𝑜𝑓 𝑤𝑜𝑚𝑒𝑛
𝑚𝑒𝑑𝑖𝑎𝑛 𝑒𝑎𝑟𝑛𝑖𝑛𝑔𝑠 𝑜𝑓 𝑚𝑒𝑛
Data Source: American Community Survey, 5-
Year Estimates
(2016 used Here)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
19
79
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80
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81
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82
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Women’s Weekly Earnings as a Percent of Men’s Among U.S. Full-Time Workers
4
Source: Bureau of Labor Statistics, Current Population Survey, 2017, Usual weekly median earnings by sex.
Montana won’t close its gender pay gap until 2080.- Institute for Women’s Policy Research
Women’s Median
Earnings are at 81.7% of Men’s Median
Earnings
5
Wage Gap Across States
Source: Map by Business Insider illustrates 2014 American Community Survey 1-Year Estimates.
Source: Map by Time.com using OECD data 2014.
Gender Pay Gap Among Countries
What Causes the Wage Gap?
• It’s not just discrimination• Occupation choice
• Industry choice
• Education
• Experience
• Part-time work/ flexible scheduling
• Time out of workforce for family care
• Union status
• Other factors that influence the size of the wage gap• Race -- Other factors
• Age -- Behavior (i.e. asking for raises)7
These factors may be
influenced by discrimination.
The Basic Gender Pay Gap
8
U.S. women earn 71.1% of the
usual median earnings of men
71.1₵on every dollar
Source: 2016 American Community Survey, 5-Year Estimates, U.S. Census Bureau
55.7%
41.2%
23.7%
30.0%
20.6%
28.7%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Male
Female
Women Work Fewer Hours Than Men
9
• to care for families
• for other reasons
•because they get paid less.
Source: 2016 American Community Survey, 5-Year Estimates, U.S. Census Bureau
Full-Time Year-Round Part-Time and/or Part-Year Did Not Work
Full-Time, Year-Round Workers
10
U.S. women earn 79.6% of the
usual median earnings of men
Including only Full-time, Year-round workers
Differences in Work Hours
Explain about 8₵
Source: 2016 American Community Survey, 5-Year Estimates, U.S. Census Bureau
Diffe
ren
ces in
Wo
rk H
ou
rs
Full-Time, Year-Round Workers
11
Montana FTYR women earn 73.6% of the
usual median earnings of FTYR men
Differences in Work Hours
Explain about 5₵ in Montana
Source: 2016 American Community Survey, 5-Year Estimates, U.S. Census Bureau
Diffe
ren
ces
in W
ork H
ou
rs
- 2.0 4.0 6.0 8.0 10.0
Food preparation and serving related
Personal care and service
Building and grounds cleaning and maintenance
Healthcare support
Office and administrative support
Sales and related
Community and social services
Education, training, and library
Protective service
Healthcare practitioner and technical
Business and financial operations
Life, physical, and social science
Management
Computer and mathematical
Legal
Millions of U.S. Full-Time, Year-Round Workers
Women Tend to Work in Lower Paying Occupations
12
Source: ACS, 2016 5-Year Estimates. Some small occupations removed for simplicity.
Less Money
More Money
U.S. Industries Where Women Work
13
Source: ACS, 2016 5-Year Estimates. Some small industries removed for simplicity.
0 2 4 6 8 10 12 14 16 18
Leisure Activities
Retail
Other services
Admin support
Ag and forestry
Health care
Construction
Education
Wholesale trade
Manufacturing
Transportation
Financial Activities
Public administration
Professional and technical services
Mining
Millions of U.S. Women Workers
More Money
Less Money
Occupational and Industry Choice Explain about Half the Gap
14Source: Blau & Kahn, Academy of Management Perspectives, 2007
10₵
Women Work in Low-Paying Occupations and Industries
Fewe
r Ho
urs W
orke
d
Occupational and Industry Choice Explain about Half the Gap
• Increase women’s participation in STEM fields.• U.S. women comprise only
• 15.4% of engineering occupations at $83,000
• 25.6% of computer and math occupations at $86,170
15
Source: OES, May 2015 and CPS, Bureau of Labor Statistics. www.equalpay.mt.gov
Recent Studies on Women in STEM Occupations
Women Leaving Engineering
Women exit science and engineering jobs more than any other type of
job.
• Not due to family constraints.
• Dissatisfaction with pay and promotion opportunities.
• More likely to report sexual harassment.
Women and Patents
• 7.5% of all patents
• Eliminating the gender gap in patenting would increase GDP per capita by 2.7%
16
Hunt et al, Natural Bureau of Economic Research, WP 17888, 2012.Hunt, Natural Bureau of Economic Research, WP 15853, 2010
Occupational and Industry Choice
Occupations and industry differences explain roughly half of the wage difference between men and women.
17
But is it a choice?
0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0%
Construction and extraction
Transportation
Architecture and engineering
Protective service
Computer and mathematical
Production
Management
Sales and related
Life, physical, and social science
Food preparation and serving related
Legal
Business and financial operations
Community and social services
Education, training, and library
Office and administrative support
Healthcare practitioner and technical
Personal care and service
Healthcare support
Gender Pay Gap Exists in all Occupations
Pay Gap Ratio
Percent Female
Source: ACS, 2016 5-Year Estimates. Some small occupations removed for simplicity.
The Glass Ceiling Effect
19
Study sorted job applicants into groups of
similarly qualified applicants then
Source: Gobillon, Meurs, Roux in Journal of Labor Economics, V33, n2, April 2015 and other studies.
Half Men
Half Women
All Considered Equally Qualified
Education, Years ExperienceQuality of Experience
Past Jobs
“Estimating Gender Differences in Access to Jobs”, Journal of Labor Economics, 2015
tracked them in their job search
The Glass Ceiling Effect
$$$$
$$$
$$
$
$$
$
.7$
$
.7$
$$
20Source: Gobillon, Meurs, Roux in Journal of Labor Economics, V33, n2, April 2015 and other studies.
Women were 9% less likely to get a job than men for low-
wage jobs.
Women were 50% less likely
to get a job than men for high wage jobs.
Occupational and Industry Choice Explain about Half the Gap
21Source: Blau & Kahn, Academy of Management Perspectives, 2007
10₵
Discrimination? Or Not?
Fewe
r Ho
urs W
orke
d
47% of Workforce is Women
22Source: Catalyst, Women in S&P 500 companies, 2015 http://www.catalyst.org/knowledge/women-sp-500-companies BLS
25% of Executive Managers of Fortune 500 Companies
23Source: Catalyst, Women in S&P 500 companies, 2015 http://www.catalyst.org/knowledge/women-sp-500-companies BLS
4% of CEOs of Fortune 500 Companies
24Source: Catalyst, Women in S&P 500 companies, 2015 http://www.catalyst.org/knowledge/women-sp-500-companies BLS
4% of CEOs of Fortune 500 Companies
25Source: Catalyst, Women in S&P 500 companies, 2015 http://www.catalyst.org/knowledge/women-sp-500-companies BLS
CEOs named John
More CEOs named Dave
than CEOs who are Women
Factors Influencing Pay and the Gender Gap
• Occupation choice
• Industry choice
• Education
• Experience
• Part-time work/ flexible scheduling
• Time out of workforce for family care
26
0%
5%
10%
15%
20%
25%
30%
Less than HS diploma HS diploma(equivalency)
Some College Associate's Degree Bachelor's Degree Graduate orProfessional Degree
MaleFemale
Women Slightly More Educated then MenEducational Attainment for Population 25 and Older
Source: ACS, 2016 5-Year Estimates.
More Women
Roughly Equal
Women Becoming More Educated in Recent Generations
0%
5%
10%
15%
20%
25%
30%
35%
40%
25 to 34 years 35 to 44 years 45 to 64 years 65 years and older
Percent of Population with Bachelor's Degree
Source: ACS, 2016 5-Year Estimates.
MaleFemale
Women have Lower Median Earnings at All Education Levels
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
90,000
Less than HS HS Diploma &equivalency
Some college &associate's
Bachelor's Graduate or professional
Me
dia
n E
arn
ings
fo
r P
op
ula
tio
n 2
5 a
nd
Old
er
Source: ACS, 2016 5-Year Estimates.
MaleFemale
Women have Higher Poverty Rates at all Education Levels
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
Less than HS HS Diploma & equivalency Some college & associate's Bachelor's or Higher
Pe
rce
nt
of
Po
pu
lati
on
25
an
d O
lde
r
Poverty Rate by Gender and Education LevelMale
Female
Source: ACS, 2016 5-Year Estimates.
55.7%
41.2%
23.7%
30.0%
20.6%
28.7%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Male
Female
Hours Worked
31Source: 2016 Time Use Survey, Bureau of Labor Statistics, and 2016 5-Year ACS, U.S. Census Bureau
Full-Time Year-Round Part-Time and/or Part-Year Did Not Work
Women8.4 hours
Men9.0 hours
Hours Worked on Days Workedamong Full-Time Workers
Hours Worked Caveats
1. At the median, both men and women work 40 hours per week.1. Research suggests men more likely to over-report work; women over-report
family care.
2. Women work less because they are paid less.
32
Motherhood Penalty
• Men’s earnings increase with children; women’s decrease.
• Long-term unemployed workers (6 months out of the workforce) take 20 years to catch up; mothers never catch up.
Economic Decisions on Parenthood
Lower-paid partner will take on more home responsibilities.
33Source: Angelov, Johnansson, and Lindahl, 2016. Journal of Labor Economics, 2016, v34, n3.
-30%
-25%
-20%
-15%
-10%
-5%
0%
5%
10%
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Wag
e G
ap
Years after First Child Born
Impact on Child Birth on Within-Couple Earnings
Wife’s Wages Relative to Husband’sIn years after birth
Percent of Families where the Wife is the Highest Earner
34
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
19
87
19
88
19
89
19
90
19
91
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92
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95
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20
02
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04
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05
20
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20
08
20
09
20
10
20
11
20
12
20
13
20
14
Source: Bureau of Labor Statistics, Current Population Survey, 2015
37%
Resume Studies Suggest Women’s Experience Discounted
Male and female pseudo-job seekers send similar resumes, but with different names.
1. Male receives more job offers.
2. Male receives higher starting salary offers.
3. Both male and female managers showed similar bias.
Source: Blau and Kahn, 2000
Experience Loss Explains Small Amount of Gap
36Source: Blau & Kahn, Academy of Management Perspectives, 2007
Occu
patio
n an
d In
du
stry
Fewe
r Ho
urs W
orke
d
Experience3₵
And Some Other Stuff
37Source: Blau & Kahn, Academy of Management Perspectives, 2007
Occu
patio
n an
d In
du
stry
Fewe
r Ho
urs W
orke
d
Experien
ce
Race, Union Status, Education, Etc.
What’s Left?
38Source: Blau & Kahn, Academy of Management Perspectives, 2007
Occu
patio
n an
d In
du
stry
Fewe
r Ho
urs W
orke
d
Experien
ce
Unexplained Portion is about 9%, varies from 5% to 15% depending on study
Discrimination?
What’s Left?
• Negotiation (and retaliation for negotiation)
• Competitiveness
• Hiring bias
• Gender Roles
39
Subtle and Subconscious Bias by Both Men and
Women
Developing a Corporate Culture of Equal Pay
• Successful diversity policies include:• Executive involvement
• Sponsorship programs
• Enforcement
• Pay gaps within the same business and same occupations are rare.• Different job titles with similar duties
• Across companies with women at the low end of market
40
Hiring
• Post a wage range to help women apply and negotiate.
• Most people make hiring decisions within 15 seconds of the interview.
41
• Gender balanced interview
• Testing is less biased than interviews
• % women applicants and likelihood of hire
Retention
• Retention rates of men vs. women• Men switch jobs slightly more often than women
• Women leaving often blamed on family, but usually its pay and lack of opportunity
• Compare wage levels to ranges published by Dept. of Labor & Industry
42Source: ICEDR, 2016. HBR, 2016.
Make a Chart(Or Better Yet, a Pay Audit)
43
5
10
15
20
25
30
35
40
20 25 30 35 40 45 50 55 60 65 70
Pay
per
Ho
ur
Age
Women Men
Source: State Employee Pay Data, 2013. Wittenberg-Cox, 2016. “To Understand Your Company’s Gender Imbalance, Make a Graph” Harvard Business Review
Conclusions
• Much of the wage gap can be explained by human capital factors.
There remains a gap.
• Research suggests cultural stereotypes of greater detriment than overt sexism.
• Culture changing more slowly than human capital factors.
44
www.equalpay.mt.gov
45
data and presentations
available at