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Women at Work Understanding the Wage Gap and its Impact on Montana’s Workforce Barbara Wagner Chief Economist Economic Update Series July 30, 2015.

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Presentation on theme: "Women at Work Understanding the Wage Gap and its Impact on Montana’s Workforce Barbara Wagner Chief Economist Economic Update Series July 30, 2015."— Presentation transcript:

1 Women at Work Understanding the Wage Gap and its Impact on Montana’s Workforce Barbara Wagner Chief Economist Economic Update Series July 30, 2015

2 Montana’s Unemployment Rate Below Normal Levels Source: Local Area Unemployment Statistics for Montana and Current Population Survey for U.S., Bureau of Labor Statistics and MT Dept of Labor and Industry (MT DLI) 5.3% 3.9% U.S. Montana “Normal” Range

3 Montana’s Aging Population Source: Census and Economic Information Center, MT Dept. of Commerce, April 2013 Under 2020 to 64Over 65

4 Montana’s Unemployment Rate Expected to Reach Very Low Levels Source: MT Dept of Labor and Industry (MT DLI) Labor Force Participation Projections U.S. Montana “Normal” Range Projected Unemployment Rates

5 Montana Labor Force Participation Source: ACS 2013 3-Year Estimates, US Census Bureau

6 Part-time Employment by Gender Full-time, Year-round Part-time, year-round Part-year, Part-time Source: Current Population Survey Data 2012 to 2014, U.S. Census Bureau 6

7 Take Away Points Worker shortages are expected due to aging workforce and retirements. Greater labor force participation by women is a necessity. – Caregivers also are good targets for recruitment due to previous experience and training. – More women would participate with greater pay and opportunities.

8 Understanding The Wage Gap Nationally, Women earn 70.6% of men. In Montana, Women earn 67.5% of men. Source: 2013 American Community Survey, 3-Year Estimates

9 Full-Time, Year-Round Wage Gap Women are more likely to work part-time than men. Including only people that work full-time, year-round – Women earn 78% of men nationally, – Women earn 75% of men in Montana.

10 U.S. Median Earnings by Education Category (25 Years and Older with Earnings) 10 Source: 2013 American Community Survey 3-Year estimates, U.S. Census Bureau 68.3% $10,250 68.0% $13,050 67.8% $19,550 Women Men 67.1% $27,150

11 U.S. Median Earnings by Race and Gender (Full-time, Year-Round Workers) 11 Source: ACS 2013 3-year estimates, U.S. Census Bureau Women Men 90% $3,100 86% $5,050 90% $3,950 78% $11,200 80% $11,200

12 U.S. Median Wage by Gender and Class of Worker Source: ACS 2011, 3-year estimates Women Men 12 80.2% $9,250 76.2% $11,500 81.2% 7,700 68.5% 11,850

13 Source: American Community Survey, 2012. Map prepared by Forbes.com. Casserly, Meghan, “The Geography of the Gender Pay Gap: Women’s Earnings by State” http://www.forbes.com/sites/meghancasserly/2013/09/19/the-geography-of-the-gender-pay-gap-womens- earnings-by-state.http://www.forbes.com/sites/meghancasserly/2013/09/19/the-geography-of-the-gender-pay-gap-womens- earnings-by-state

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15 Take Away Points Gender Wage Gap Exists across – Most occupations (there are a few where pay is equal) – All industries – Private, public, and nonprofit – All education groups – All age groups – All states, with Montana on the bottom half Gap has improved over time, but improvement is slow. 15

16 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) 16 Some of these factors may be influenced by discrimination.

17 U.S. Occupations where Women Work 17 Source: ACS, 2013 3-Year Estimates. Some small occupations removed for simplicity. Less Money

18 U.S. Industries Where Women Work 18 Source: ACS, 2013 3-Year Estimates. Some small industries removed for simplicity. More Money Less Money

19 Choice is Good, But There are Caveats Even within each industry / occupation, there is a wage gap. Men are more likely to be promoted to management positions. – Only 39% of U.S. managers are female. – Only 26% of U.S. chief executives are female. Men are more likely to be hired than women, with the bias towards men increasing in higher-paid jobs. – For a low-wage job, females are 9% less likely to get the job. – At the top of the wage distribution, females are 50% less likely to get the job. Source: 2013 ACS 3-Year estimates, Census. 2014 Current Population Data, BLS. Gobillon, Meurs, Roux in Journal of Labor Economics, V33, n2, April 2015 and other studies.

20 Occupation Choice Women choose to work in low-paying occupations 20 Pay Gap Ratio Percent Female Source: ACS, 2013 3-Year Estimates. Some small industries removed for simplicity.

21 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 21

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23 What do studies show? Women have more education and slightly higher grades than men Different college majors plays a role in opportunity – Significant attention to recruiting women into STEM degrees Even among students with the same major and equal school performance, men out-earn women 23

24 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 24

25 Experience and Part-Time Status: Women more likely to Work Fewer Hours 25 Source: 2013 ACS 3-year Estimates

26 Experience and Part-Time Work Women are more likely to care for children and family. Time out of workforce for childbearing. Choose part-time work or relaxed occupations to allow for work and family. Economic theory suggests that the lower-paid partner will take on more home responsibilities. 26

27 Wage Gap Improvements from Women Having Children Later in Life Source: Bureau of Labor Statistics, Median usual weekly earnings of full-time workers. Women’s Usual Weekly Earnings as Percent of Men for Full-Time Workers

28 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

29 Factors Influencing Pay and the Gender Gap Occupation choice Industry choice Education Experience 29 Montana Gap = $0.33 14₵ 9₵ 7₵

30 Conclusions Much of the wage gap can be explained by human capital factors and productivity. There remains a gap. Research suggests cultural stereotypes of greater detriment than overt sexism. Culture changing more slowly than human capital factors. 30

31 EQUAL PAY INFORMATION: WWW.EQUALPAY.MT.GOV WWW.EQUALPAY.MT.GOV DLI WEBSITE: WWW.DLI.MT.GOV ECONOMIC DATA WEBSITE: WWW.LMI.MT.GOV


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